# Christian Catalini — full corpus Founder and economist. Co-creator of Libra at Meta, co-founder of Lightspark, founder of the MIT Cryptoeconomics Lab. Research and writing on the economics of AGI, verification, stablecoins, and digital markets. Index: https://catalini.com/llms.txt · License: all rights reserved. --- ## Expert Verification Closes the Automation Loop - canonical: https://catalini.com/notes/expert-verification-closes-the-loop/ - original thread: https://x.com/ccatalini/status/2073035910850216047 - date: 2026-07-03 This is the exact dynamic we predicted back in February: verification by top experts is the missing piece to close the automation loop. It’s like running through the unique “weights” in the expert’s brain, bringing into the picture what is otherwise not measured yet. [x.com](https://twitter.com/rohanpaul_ai/status/2072911021308879219) But it can also be a curse for the talent involved, as each closed loop pushes the automation frontier further, forcing the expert to move up the value chain. Whether experts feel liberated (more time for high-value tasks, more output!) or displaced depends on where their daily tasks sit on the measurable versus non-measurable line. This is why both the AI labor market doomers and utopians are wrong. It all depends on that threshold. More in the full paper: --- ## OUSD and the 140-Company Bet on a Neutral Stablecoin - canonical: https://catalini.com/notes/ousd-neutral-stablecoin-bet/ - original thread: https://x.com/ccatalini/status/2071986034016174227 - date: 2026-06-30 Today, more than 140 companies, most of which compete fiercely with one another, agreed to back the same stablecoin. The vehicle is [@openstandard](https://x.com/openstandard), a new and deliberately independent company launching Open USD, or OUSD, and positioning it not as anyone’s product but as neutral infrastructure for payments, trading and the internet economy. The backer list is impressive: Visa, Mastercard and American Express in the same consortium, alongside Stripe, BlackRock, Coinbase, Google, BNY Mellon and a long roster of banks and fintechs that have committed to integrating OUSD at launch. And the design is the tell: OUSD charges nothing to mint or redeem at any scale, sends nearly all of the reserve income back to the companies that distribute it rather than to the issuer, and is governed collectively rather than by whoever got an early start first. It goes live across Solana, Stellar, Base, Polygon and other chains later in 2026, with Bridge co-founder [@zcabrams](https://x.com/zcabrams) as interim CEO. It is the open standard that the economics of stablecoins have been pointing toward all along. Stablecoins were never meant to be a profit center. The reason is simple: issuance does not grant any additional economics above and beyond the distribution, in terms of balances or payments volume, that you already bring to the table. Which leads to two possible universes: one in which an endless number of stablecoins come into existence, and they all struggle for relevance, and one where companies realize this is nonsense and agree to a standard. That was the core idea behind Libra, and it now lives on with Open Standard. Open Standard could easily succeed where Libra failed. Circle failed to capitalize on the first-mover opportunity in the regulatory-centric market, and to effectively compete with Tether for the offshore, massive market for dollarization. That left Circle in a tough spot, one in which it has to increasingly compete with its customers with products like the CPN, and to do what all platform architects with network effects do: tax participation at the choke point, in this case the mint and burn fees that limit interoperability and conversions back to fiat. And of course, once you realize what was obvious to many before, you try to extend your influence over the network, hoping that it will make your product more sticky. That’s the idea behind Circle’s own network, [@arc](https://x.com/arc). Control the rails and the asset, and you may be able to replicate more of Libra’s playbook. Except, that’s the wrong read of Libra. Libra was always only meant to be an enabler for wallets, merchants and platforms. It was meant to fill a void in a fragmented and historically slow infrastructure. Libra was an open protocol with open ambitions, including on the decentralization of the network. We just never got to play that level of the game because of regulatory headwinds. But the time is perfect right now. The ecosystem realizes that a set of open standards and rules that everyone agrees to is way more powerful than a stablecoin issuer becoming too powerful against the banks, fintechs or digital platforms. Nobody wants that world. Does this mean [@openstandard](https://x.com/openstandard) will succeed? From here on, it really depends on the team’s ability to execute well on streamlined governance, independence and further ecosystem buildout through partners. The reality is that everyone is excited at the announcement, but then the real struggle is getting people to converge on standards and rules. The Principles for Financial Market Infrastructures (PFMI) exist for a reason. The GENIUS Act solved many of the critical dimensions, but many more will need to be solved. The excitement about a more open alternative to fragmented stablecoin issuance is real. Having driven the design of an independent organization like this before, I know that from here things will be hard. And coordinating governance when parties need to collaborate first and then compete fiercely is not easy. Dee Hock is the only one who figured this before, and maybe an agent trained on his thoughts and on how to design a chaordic alliance of frenemies may be able to help the Open Standard team scale. The world of payments and financial services will be much better if an open standard succeeds. Today, it looks like it might be the one carrying the name. Full story in [@ForbesCrypto](https://x.com/ForbesCrypto): [forbes.com](https://www.forbes.com/sites/christiancatalini/2026/06/30/why-an-open-standard-will-win-the-stablecoin-race/) --- ## Why An Open Standard Will Win The Stablecoin Race - canonical: https://catalini.com/writing/open-standard-stablecoin-race/ - original: https://www.forbes.com/sites/christiancatalini/2026/06/30/why-an-open-standard-will-win-the-stablecoin-race/ - date: 2026-06-30 - outlet: forbes Today, more than 140 companies, most of which compete fiercely with one another, agreed to back the same stablecoin. The vehicle is Open Standard, a new and deliberately independent company launching Open USD, or OUSD, and positioning it not as anyone’s product but as neutral infrastructure for payments, trading and the internet economy. The backer list is impressive: Visa, Mastercard and American Express in the same consortium, alongside Stripe, BlackRock, Coinbase, Google, BNY and a long roster of banks and fintechs that have committed to integrating OUSD at launch. And the design is the tell: OUSD charges nothing to mint or redeem at any scale, sends nearly all of the reserve income back to the companies that distribute it rather than to the issuer, and is governed collectively rather than by whoever got an early start first. It goes live across Solana, Stellar, Base, Polygon and other chains later in 2026, with Bridge co-founder Zach Abrams as interim CEO. It is the open standard that the economics of stablecoins have been pointing toward all along. Stablecoins were never meant to be a profit center. The reason is simple: issuance does not grant any additional economics above and beyond the distribution, in terms of balances or payments volume, that you already bring to the table. Which leads to two possible universes: one in which an endless number of stablecoins come into existence, and they all struggle for relevance, and one where companies realize this is nonsense and agree to a standard. That was the core idea behind Libra, and it now lives on with Open Standard. Open Standard could easily succeed where Libra failed. Circle failed to capitalize on the first-mover opportunity in the regulatory-centric market, and to effectively compete with Tether for the offshore, massive market for dollarization. That left Circle in a tough spot, one in which it has to increasingly compete with its customers with products like the Circle Payments Network, and to do what all platform architects with network effects do: tax participation at the choke point, in this case the mint and burn fees that limit interoperability and conversions back to fiat. And of course, once you realize what was obvious to many before, you try to extend your influence over the network, hoping that it will make your product more sticky. That’s the idea behind Circle’s own network, Arc. Control the rails and the asset, and you may be able to replicate more of Libra’s playbook. Except, that’s the wrong read of Libra. Libra was always only meant to be an enabler for wallets, merchants and platforms. It was meant to fill a void in a fragmented and historically slow infrastructure. Libra was an open protocol with open ambitions, including on the decentralization of the network. We just never got to play that level of the game because of regulatory headwinds. But the time is perfect right now. The ecosystem realizes that a set of open standards and rules that everyone agrees to is way more powerful than a stablecoin issuer becoming too powerful against the banks, fintechs or digital platforms. Nobody wants that world. Does this mean Open Standard will succeed? From here on, it really depends on the team’s ability to execute well on streamlined governance, independence and further ecosystem buildout through partners. The reality is that everyone is excited at the announcement, but then the real struggle is getting people to converge on standards and rules. The Principles for Financial Market Infrastructures (PFMI) exist for a reason. The GENIUS Act solved many of the critical dimensions, but many more will need to be solved. The excitement about a more open alternative to fragmented stablecoin issuance is real. Having driven the design of an independent organization like this before, I know that from here things will be hard. And coordinating governance when parties need to collaborate first and then compete fiercely is not easy. Dee Hock is the only one who figured this before, and maybe an agent trained on his thoughts and on how to design a chaordic alliance of frenemies may be able to help the Open Standard team scale. The world of payments and financial services will be much better if an open standard succeeds. Today, it looks like it might be the one carrying the name. --- ## Intelligence Wants to Be Free - canonical: https://catalini.com/writing/intelligence-wants-to-be-free/ - original: https://catalini.substack.com/p/intelligence-wants-to-be-free - date: 2026-06-27 - outlet: substack We’re at a fork in the road. One path leads to the rapid and irreversible bureaucratization of intelligence. Government approval, absent clear and technically sound guidelines, becomes a way to pick winners, erect barriers to entry, and give labs someone to blame if a model goes rogue. The alternative path is one where we battle to retain distributed and market-driven access to intelligence, capabilities are widely distributed, and the battle is fought in the market rather than in Washington D.C. And while ultimately intelligence will want to be free ([free as in speech](https://en.wikipedia.org/wiki/Wikipedia:Gratis_versus_libre), not as in beer), and the arc will bend towards openness, we could face a long, dark period of an intelligence caste system. Deciding who gets to use frontier intelligence and who doesn’t is simply too much power for any single company or administration to wield unilaterally. The economic rents that would follow from that power would undo the key assumption of free-market economies that talent, effort and ingenuity map (even with friction and imperfection) to the ability to succeed. It would land the United States in a model that is much more similar to the planned economy of its challenger, China. Capitalism requires that the decentralized and voluntary exchange in free markets is able to organize resources, drive human ingenuity and innovation, and ultimately guarantee societal welfare better than any form of centralized planning, no matter how smart, AI-augmented, or well-intended altruist. But a world where frontier intelligence is not voluntarily available to market participants is one where this assumption falls apart. It is one where the profit motive is replaced by favor, influence and access to the *spice*. Some have called for a [rebel alliance](https://x.com/nickgrossman/article/2070181707613937866). But the problem with rebel alliances is that they are hard to organize, and often confuse faith in ideas such as decentralization and openness without challenging the alternative from first principles. Early crypto made exactly the same mistakes. We made exactly the same mistakes when we tried to build Libra, only to brace for impact after regulators did to our naive ideas for decentralization what they are doing right now to Anthropic and OpenAI. For decades, proponents of stronger privacy and control over your data made the same mistake in trying to challenge the large, two-sided social media platforms and their network effects. And I’ve made the same mistake. Yes, it is true [open networks do eventually win](https://x.com/ccatalini/status/1983588222921023552?s=20), but this typically happens in unexpected ways and never in the format that resembles the format of the centralized alternative. Linux did not win on the desktop, it had to wait for the cloud. Decentralized intelligence will not win in the same format as the one we’re being served by the large foundation labs. It will not win by trying to acquire context and digital traces of your work [inside your company Slack](https://x.com/ccatalini/status/2069845846003433702?s=20) or by [watching your computer use](https://x.com/ccatalini/status/2067690466980810926?s=20). It will not win by collecting unique data at scale through the relentless acquisition of incumbents with fragile business models beyond their historical archives. Decentralized intelligence will win by playing to its strengths. The fact that despite truly magical model capabilities, every human still has something to contribute. The “weights” we all carry in our brain, shaped by the unique set of experiences we’ve all accumulated and mistakes we’ve made, [are still unmeasured](https://arxiv.org/html/2602.20946v2). While we’re slowly leaking bits of it with each interaction with AI, they’re still ours. The fact that despite the massive temptation to deploy AI across every firm as fast as possible to not fall behind your competitors, some CEOs are realizing that the [feedback and verification loops](https://x.com/ccatalini/status/2066876927789674965?s=20) that are shaped every day by their top talent and accumulated experience are worth defending and owning. The fact that despite models being magical, [they are not the defensible product anymore](https://x.com/gdb/status/2057670776803996110?lang=en). Smart harnesses, more focused domain data, [verification infrastructure](https://x.com/ccatalini/status/2026311784421036223?s=20), evals and expertise can deliver us the same results in a more distributed, market-driven way. The fact that ideas are in the air, and open source models are not far behind. Yes, the government may try to limit access to your weights, the same way it once tried to limit, and failed, access to [self-custody](https://x.com/ccatalini/status/2070314553313993025?s=20) of value. Intelligence wants to be non-custodial. Intelligence wants to be [free](https://x.com/ccatalini/status/2070640726493544454?s=20). We just have to figure out how. --- ## Nadella's Test: What's Left When the AI Model Is Pulled? - canonical: https://catalini.com/notes/nadellas-test-thread/ - original thread: https://x.com/ccatalini/status/2066876927789674965 - date: 2026-06-16 [@satyanadella](https://x.com/satyanadella) defined what decides whether your company and job stay defensible as AI improves. The economics says it holds on a single condition. One his post left out. [x.com](https://x.com/satyanadella/status/2066182223213293753?s=20) [@satyanadella](https://x.com/satyanadella)'s sharp test for whether your company will hold a defensible moat as artificial intelligence accelerates: you should be able to swap out a generalist model without losing the "company veteran" expertise built into your learning system. At first glance, this may sound obvious. If removing the model means you no longer deliver value, the model was the one doing your job. But Nadella's read is more nuanced, grounded in an understanding that where we go from here is not yet decided... Despite loud voices arguing that the window has closed and the frontier labs will inevitably win, a significant share of capabilities will be commoditized. Every hyperscaler will eventually source enough compute, and open source models trail closely. [x.com](https://x.com/AndrewCurran_/status/2066332670817456584?s=20) Willingness to pay for frontier intelligence won't disappear, especially where AI can deliver meaningful breakthroughs. But converting compute into a sustainable business edge takes more than a model — something OpenAI itself has acknowledged. [x.com](https://x.com/gdb/status/2057670776803996110) Some believe that if you have the best model, you win. That the first to build self-improving AI will open a lead too wide to close. Nadella's test inverts that: build a future where you can swap the model without loss, and the model is by definition a commodity input. We are far from that world today. Anyone who experienced Fable's productivity boost, then saw it vanish when the model was banned, was reminded of the incredible value of frontier intelligence. [forbes.com](https://www.forbes.com/sites/christiancatalini/2026/06/11/the-moral-of-fable/) Which is also why many are clamoring for a more open, resilient ecosystem, or even a rebel alliance: a handful of leading providers concentrates too much power — economic and political — in too few hands. [x.com](https://x.com/mignano/status/2066535541651243294?s=20) Still, the deeper shift is structural: as AI drives the cost of execution toward zero, the binding constraint stops being intelligence and becomes verification. Tasks with measurable inputs and outputs get cheaper. But in many critical domains, checking the work does not — it still runs on scarce experience, long feedback loops, and someone willing to stand behind the result. The top experts in those domains become the critical verifiers and underwriters of agentic work. So what does a world where the model is hot-swappable look like? One where leading firms refuse to concede their crown jewels to the foundation models. That crown jewel is verification infrastructure. Everything the firm has measured and can measure, plus everything its top experts have learned — the accumulated experience that shapes how they verify, judge, curate, and apply taste on the job. Nadella correctly identifies the associated self-improving loop as the new, key intellectual property of the firm. And he is right that, set up correctly, it compounds. That advantage is a network effect, but not the familiar kind. For two decades the strongest moats grew with sheer participation: more users, more sellers, more developers & apps. But now agents can manufacture activity and port inventory and workflows. Only verification-grade network effects survives: every dispute resolved, fraud caught, and expert correction is reusable precedent: a settled case that lets the firm safely automate the next case faster. That is the asset that deepens with use. It cannot be manufactured with compute, because it is earned one verified outcome at a time. Every time a firm turns inputs such as atoms, information, and tokens into a more refined version of them, it scales those network effects. But only if the same pass also sharpens the ground truth it relies on, or codifies a piece of the tacit knowledge locked in its experts' heads. The second move is the harder one, and it is what will separate the firms that thrive with AI from the ones that get commoditized by it. That judgment, what to approve, what to reject, which exception matters, lives in the part of the workflow no one outside the firm can codify as well. Encode it as reusable ground truth and the next agent applies it without the expert in the loop, freeing the scarcest resource the firm has and widening the share of work it can trust at scale. Scale is only defensible when each round produces verified precedent the next one can use. In the near-AGI era, every company has one job: converting the remaining bottleneck — verification — into better proprietary measurement and more automation, as fast as possible. AI-native firms have already learned to leverage their own record of judgment: which outputs were approved, which were rejected, which edge cases mattered. For that record to be defensible, it has to be built around outcomes only the firm can measure at scale. Which is why Nadella reaches for a distinctly private architecture: private evals, private RL environments, performance benchmarked against the outcomes the business cares about, not public leaderboards. Inside those firms, as Nadella puts it: “Employees will see their expertise amplified and their judgment become part of systems that make it replicable and scalable". What he leaves unsaid is that this is not always good news for the verifiers themselves — some will automate themselves out of their job while the firm keeps the replicable, scalable parts. The ones who thrive will use the new tools to move up the intelligence stack and further scale their time. For firms and individuals alike, in a competition that is now global, value accrues to exactly what others cannot measure and judge with the same precision. But measuring is not the same as measuring the right thing. Nadella’s hill-climbing machine only compounds if it climbs the right hill. Point a loop at the wrong measure and it accumulates plausible output that satisfies the metric while violating intent — impeccable, and worthless. The counterintuitive part is that some of a firm's most valuable records are its failed experiments, errors, and missteps. Rejected output, captured right, is the best training signal there is for institutional judgment. This is why verification is the missing word in Nadella’s test. A verified loop compounds into long term value. An unverified one accumulates hidden liability, and the two look identical — right up until they don't. It would be easy to dismiss this as Microsoft simply talking its book. It sells the picks and shovels for verification loops. It profits from a world where value accrues one level up from the model — in the context, evaluation, workflows, and institutional memory that make models useful inside a firm. But notice the stakes behind Nadella’s pitch. If a frontier lab reaches AGI and the model swallows the work, Microsoft is finished as anything but a passive shareholder — the company selling you the harness is disintermediated the same day you are. Nadella, more than almost anyone, cannot afford his thesis to be false. Microsoft wants you to own your loop, on its rails. The frontier labs need the opposite: they can’t defend the model on its own — the Bitter Lesson commoditizes it first — so they extend into the layer that is defensible, which is yours. The loops a firm sees as sovereignty are the loops the labs see as their next training frontier. They will bundle the verification signal your operation emits every day into their evals — for your benefit, of course. Accept it, and the token capital you thought you were building turns out to be theirs. Nadella is right that the firms of the next decade run on top human capital and token capital together. What his picture leaves out is how those convert into advantage. Full article on [@Forbes](https://x.com/Forbes): [forbes.com](https://www.forbes.com/sites/christiancatalini/2026/06/16/nadellas-test-whats-left-when-the-ai-model-is-pulled/) --- ## Nadella’s Test: What’s Left When The AI Model Is Pulled? - canonical: https://catalini.com/writing/nadellas-test/ - original: https://www.forbes.com/sites/christiancatalini/2026/06/16/nadellas-test-whats-left-when-the-ai-model-is-pulled/ - date: 2026-06-16 - outlet: forbes Satya Nadella challenges companies to build AI systems where generalist models can be swapped without losing unique "company veteran" expertise. He posits that as AI capabilities are commoditized, the true defensible moat shifts from the models themselves to a firm's internal "verification infrastructure." This encompasses accumulated experience, expert judgment, and the ability to precisely measure and validate AI outputs. This process creates a "hill climbing machine," where improved workflows generate superior training signals, compounding tacit knowledge unique to the firm. Ultimately, the critical bottleneck and new intellectual property lie in a company's unparalleled ability to verify and stand behind AI-driven results. Satya Nadella [defined](https://x.com/satyanadella/status/2066182223213293753) a sharp test for whether your company will hold a defensible moat as artificial intelligence accelerates: you should be able to swap out a generalist model without losing the “company veteran” expertise built into your learning system. At first glance, this may sound obvious. If removing the model means you no longer deliver value, the model was the one doing your job. But Nadella's read is more nuanced, grounded in an understanding that where we go from here is not yet decided — despite increasingly loud voices arguing that the [window has closed](https://x.com/AndrewCurran_/status/2066332670817456584?s=20) and the leading frontier labs will inevitably win it all. ## The Model Is Not The Moat A significant share of frontier capabilities will be commoditized — every hyperscaler will eventually source enough compute, and open source models trail closely. Willingness to pay for frontier intelligence won't disappear, especially where AI can deliver meaningful [breakthroughs](https://x.com/ccatalini/status/2064708458352398403). But converting compute into a sustainable business edge takes more than a model — something OpenAI itself has [acknowledged](https://x.com/gdb/status/2057670776803996110). Some believe that if you have the best model, you win. That the first to build self-improving AI will open a lead too wide to close. Nadella's test inverts that: build a future where you can swap the model without loss, and the model is by definition a commodity input — however capable, however far ahead. We are far from that world today. Anyone who experienced [Fable](https://www.forbes.com/sites/christiancatalini/2026/06/11/the-moral-of-fable/)'s productivity boost, then saw it vanish when the model was banned, was reminded of the incredible value of frontier intelligence. Which is also why many are clamoring for a more open, resilient ecosystem, or even a [rebel alliance](https://x.com/mignano/status/2066535541651243294?s=20): a handful of leading providers concentrates too much power — economic and political — in too few hands. ## From Intelligence To Verification Still, the deeper shift is structural: as AI drives the cost of execution toward zero, the binding constraint stops being intelligence and becomes [verification](https://arxiv.org/html/2602.20946v2). Tasks with measurable inputs and outputs get cheaper. But in many critical domains, checking the work does not — it still runs on scarce experience, long feedback loops, and someone willing to stand behind the result. The top experts in those domains become the critical verifiers and underwriters of agentic work. So what does a world where the model is hot-swappable look like? One where leading firms refuse to concede their crown jewels to the foundation models. That crown jewel is [verification infrastructure](https://arxiv.org/abs/2602.20946): everything the firm has measured and can measure, plus everything its top experts have learned — the accumulated experience that shapes how they verify, judge, curate, and apply taste on the job. Nadella correctly identifies the associated self-improving loop as the new, key intellectual property of the firm. And he is right that, set up correctly, it compounds: *“I think of it as a hill climbing machine. And unlike most assets, it compounds. Every improved workflow generates better training signal, which accelerates the accumulation of tacit knowledge unique to the firm. The companies that build this early will have an advantage that is hard to replicate, regardless of any new individual model capability.”* ## The Only Loop That Compounds That advantage is a network effect, but not the familiar kind. For two decades the strongest moats grew with sheer participation: more users, more sellers, more developers and apps. In an agentic economy that weakens, because agents can manufacture the activity that used to signal health, and port real inventory and workflows across platforms in minutes. Scale can even invert: when millions of agents optimize the same metrics, they flood a network with plausible noise it mistakes for quality, and more activity makes it less valuable, not more. One kind survives, and we called it [verification-grade network effects](https://arxiv.org/html/2602.20946v2#S8). Every dispute resolved, fraud caught, and expert correction becomes reusable precedent: a settled case that lets the firm safely automate the next case faster. That is the asset that deepens with use. It cannot be manufactured with compute, because it is earned one verified outcome at a time. Every time a firm turns inputs such as atoms, information, and tokens into a more refined version of them, it scales those network effects. But only if the same pass also sharpens the ground truth it relies on, or codifies a piece of the tacit knowledge locked in its experts' heads. The second move is the harder one, and it is what will separate the firms that thrive with AI from the ones that get commoditized by it. That judgment, what to approve, what to reject, which exception matters, lives in the part of the workflow no one outside the firm can codify as well. Encode it as reusable ground truth and the next agent applies it without the expert in the loop, freeing the scarcest resource the firm has and widening the share of work it can trust at scale. Scale is only defensible when each round produces verified precedent the next one can use. In the near-AGI era, every company has one job: converting the remaining bottleneck — verification — into better proprietary measurement and more automation, as fast as possible. AI-native firms have already learned to leverage their own record of judgment: which outputs were approved, which were rejected, which edge cases mattered. For that record to be defensible, it has to be built around outcomes only the firm can measure at scale. Which is why Nadella reaches for a distinctly private architecture: private evals, private RL environments, performance benchmarked against the outcomes the business cares about, not public leaderboards. Inside those firms, as Nadella puts it: *“Employees will see their expertise amplified and their judgment become part of systems that make it replicable and scalable".*What he leaves unsaid is that this is not always good news for the verifiers themselves — some will [automate themselves out of their job](https://x.com/ccatalini/status/2026311841425875347?s=20) while the firm keeps the replicable, scalable parts. The ones who thrive will use the new tools to move up the intelligence stack and further scale their time. For firms and individuals alike, in a competition that is now global, value accrues to exactly what others cannot measure and judge with the same precision. But measuring is not the same as measuring the right thing. Nadella’s hill-climbing machine only compounds if it climbs the right hill. Point a loop at the wrong measure and it accumulates plausible output that [satisfies the metric while violating intent](https://hbr.org/2025/06/what-gets-measured-ai-will-automate) — impeccable, and worthless. The counterintuitive part is that some of a firm's most valuable records are its failed experiments, errors, and missteps. Rejected output, captured right, is the best training signal there is for institutional judgment. This is why *verification* is the missing word in Nadella’s test. A verified loop compounds into long term value. An unverified one accumulates [hidden liability](https://www.forbes.com/sites/christiancatalini/2026/03/18/babysitting-the-slop/), and the two look identical — right up until they don't. ## Follow The Incentives It would be easy to dismiss this as Microsoft simply talking its book. It sells the picks and shovels for verification loops. It profits from a world where value accrues one level up from the model — in the context, evaluation, workflows, and institutional memory that make models useful inside a firm. But notice the stakes behind Nadella’s pitch. If a frontier lab reaches AGI and the model swallows the work, Microsoft is finished as anything but a passive shareholder — the company selling you the harness is disintermediated the same day you are. Nadella, more than almost anyone, cannot afford his thesis to be false. Microsoft wants you to own your loop, on its rails. The frontier labs need the opposite: they can’t defend the model on its own — [the Bitter Lesson commoditizes it](https://x.com/ccatalini/status/2062569709372104712?s=20) first — so they extend into the layer that is defensible, which is yours. **The loops a firm sees as sovereignty are the loops the labs see as their next training frontier.** They will bundle the verification signal your operation emits every day into their evals — for your benefit, of course. Accept it, and the token capital you thought you were building turns out to be theirs. Nadella is right that the firms of the next decade run on top human capital and token capital together. What his picture leaves out is how those convert into advantage. The moat is not the model. It is not even the learning loop. It is the part of the loop a company will put its name, balance sheet, and future on: the ability to perform verification, for a specific set of jobs, better than anyone in the world. The same logic that puts Microsoft at risk runs all the way down to you. Every knowledge worker holds domain expertise a model would happily absorb. What is still yours is the verification it cannot do without you. Yet. --- ## The Constraint on Mastery Is No Longer Access - canonical: https://catalini.com/notes/mastery-learning-rate/ - original thread: https://x.com/ccatalini/status/2065079059617558825 - date: 2026-06-11 For most of history, finding out what you’re good at required the right mentor, firm or zip code. AI collapses all three into the same chat window. The constraint on mastery is no longer access. It’s finding the domain where your learning rate is steepest—and building. The dark version is the “Missing Junior Loop”: AI automates the entry-level reps that used to build expertise. But the same models generate unlimited, personalized training/practice. The tech that severed the apprenticeship can rebuild it on demand with higher fidelity. When a rep costs ~zero in any domain, you can run a parallel search and find rapidly where you improve fastest (and what you enjoy the most!). Innate talent discovery stops being a lottery ticket and becomes a science. Something you can measure in weeks. Why it matters: as execution is commoditized, the scarce asset is deep expertise that can steer and verify machine output. The meta-skill of the decade is accelerated mastery — building expertise faster than the market rate. We unpack what AI-native individuals will do to stay on the frontier: accelerated mastery, synthetic practice, moving up the intent-and-underwriting stack in Section 8 of “Some Simple Economics of AGI” (w/ [@wu_jane](https://x.com/wu_jane) [@xianghui90](https://x.com/xianghui90)): [arxiv.org](http://arxiv.org/html/2602.20946v2#S8) [@wu_jane](https://x.com/wu_jane) [@xianghui90](https://x.com/xianghui90) Since the paper is over 100 pages, you can feed the MD file directly to your favorite LLM: [catalini.com](https://www.catalini.com/s/paper.md) --- ## The Moral Of Fable - canonical: https://catalini.com/writing/the-moral-of-fable/ - original: https://www.forbes.com/sites/christiancatalini/2026/06/11/the-moral-of-fable/ - date: 2026-06-11 - outlet: forbes On June 9, Anthropic released [Claude Fable 5](https://www.anthropic.com/news/claude-fable-5-mythos-5), the first of its Mythos-class models offered to the general public, days after the company confidentially filed for an IPO. The launch described four guarded domains. Three — cybersecurity, biology, chemistry — operate in the open: trip a classifier and the model refuses or visibly hands you off to the older Claude Opus 4.8. The fourth worked differently. A passage deep in the 319-page system card disclosed that when Fable detects frontier AI development — pretraining pipelines, training infrastructure, accelerator design — it quietly degrades its own answers. The card itself called the intervention ["not visible to the user."](https://fortune.com/2026/06/10/anthropic-accu-claude-fable-5-limits-capabilities-ai-researchers-developers/) Affected traffic, by Anthropic's estimate: 0.03 percent. The percentage was small. The principle was not. Within a day, open-model researchers, AI-safety stalwarts, and Anthropic alumni revolted; the company conceded it had made the wrong tradeoff and promised to surface the safeguard. It is worth being precise about what got corrected. Fable will now announce when it declines to help advance AI. It will still decline. And a visible guardrail casts a wider net: Anthropic admits more innocuous requests will get caught while it tunes its classifiers. The fence acquired a sign. It did not move. Reasonable people can defend the fence. A system that improves systems is not an ordinary product feature, and Anthropic says Claude already writes most of its own code; its terms have long barred training rivals on its output. But the defense is beside the larger point: a private company has now drawn the first explicit border on the map of where machine intelligence may compound. The stakes come from the economics underneath that map. ## When Ideas Become Free Progress has always been recombination. Algebra exists because Greek geometry, Persian astronomy, and Indian arithmetic landed for the first time in one language and one ninth-century mind — al-Khwārizmī’s. Each fusion expands what the next generation can fuse; that is why growth compounds. Humans, though, pay dearly for distance: bridging far-apart fields takes careers, institutions, and luck, and [the toll rises](https://www.kellogg.northwestern.edu/faculty/jones-ben/htm/burdenofknowledge.pdf) as knowledge piles up. A model that has ingested nearly everything pays almost nothing for the same traverse. Its edge over us is not uniform: it widens with the gap being crossed. But producing *candidate* ideas was never the whole job. Make a scarce input free and you do not abolish the bottleneck — you promote the next constraint in line. That constraint, as [my co-authors and I argue](https://arxiv.org/abs/2602.20946), is *verification*: the cost of establishing that an output is [actually true](https://www.forbes.com/sites/christiancatalini/2026/03/18/babysitting-the-slop/). A far-flung recombination is a lottery ticket; unchecked, it is worth the average of the drum — roughly nothing. Generation fills your hand. Verification prices it. Cross those two dimensions — how far an idea travels across knowledge domains, how cheaply it is checked — and the future splits four ways. Within a narrow domain and checkable: grunt-work automation that lifts every productivity baseline. Within a narrow domain, but hard to check: experts graduate from producers to arbiters, rationing judgment across machine output—["babysitting the slop".](https://www.forbes.com/sites/christiancatalini/2026/03/18/babysitting-the-slop/) Across domains and checkable: the takeoff zone, where a model can find *and* confirm what no human could, and gains stack at machine speed. Across domains and uncheckable: a fool’s gold, where discovery and confident hallucination look identical — and where the largest prizes sit. The takeoff zone is no longer hypothetical. An OpenAI reasoning model recently [overturned](https://openai.com/index/model-disproves-discrete-geometry-conjecture/) a conjecture Paul Erdős posed in 1946, toppling an eighty-year assumption in combinatorial geometry by importing machinery from algebraic number theory — two fields with no obvious reason to meet. It worked because mathematics grades itself: the proof holds or it doesn’t, within hours. Aim the same engine at drug development, strategy, or macro policy and the self-improving loop stalls: a trial takes years to read out, a strategy a decade. Recursive self-improvement will transform the domains that check themselves and idle everywhere else. The fault line of the next decade is not who generates knowledge the fastest, but who verifies it. ## The Border Around the Fastest Loop That is what makes Fable a turning point. AI research is the purest self-grading territory on the map: benchmarks score instantly, and every verification doubles as training data for the next model — exactly why frontier labs dominate it. The first border, then, was drawn around the fastest loop, by a company competing inside it, on the eve of its public listing. For builders, the compass points downstream. With generation commoditized, durable value sits in the two tasks machines cannot do for themselves: choosing which recombinations to pursue, and proving which paid off. The ultimate prize is measurement infrastructure — the simulations, evals, or world model (see Prof. Fei-Fei Li’s [taxonomy](https://drfeifei.substack.com/p/a-functional-taxonomy-of-world-models)) that turn a slow-verifying field into a fast one, and so decide where the acceleration spreads next. Three and a half centuries ago, the Royal Society adopted *nullius in verba* — take nobody’s word for it — because ideas were never the scarce thing; verified and reproducible ones were. That discipline now must run in two directions. A safeguard is a claim like any other, and this week’s reversal made Anthropic’s audible without making it auditable: we still cannot inspect where the line sits or how it may move over time. Recombination of ideas is now free. The contest ahead is over who gets to verify — the machine’s answers, and the borders drawn around them by the tech giants of this new era. --- ## Where Self-Improving AI is the Beginning of Infinity (And Where It Hits a Wall) - canonical: https://catalini.com/writing/self-improving-ai-beginning-of-infinity/ - original: https://catalini.substack.com/p/where-self-improving-ai-is-the-beginning - date: 2026-06-10 - outlet: substack Yesterday, Anthropic shipped [Claude Fable 5](https://www.anthropic.com/claude/fable), its most capable public model yet — with one quiet exception: point it at frontier AI research, and it degrades its own output. No notice, no fallback. Intelligence that can improve intelligence is now rationed. The [premise](https://www.anthropic.com/institute/recursive-self-improvement) had landed days earlier: Claude already writes over 80% of Anthropic’s code, runs its experiments, and is edging into the judgment calls research depends on. The caution may be warranted. But the precedent is stark: one company has begun drawing the borders of where the most consequential technology of our time may compound—unilaterally, and partly invisibly. The question is no longer whether self-improving AI is coming, but where the compounding is allowed to run, and who gets to verify it. The answer begins twelve centuries ago. ## **The Freedom to Recombine Ideas** We rarely think of *algorithm* as a name, or *algebra* as a book. But centuries before they became the foundation of modern AI, they were exactly that. Ninth-century mathematician al-Khwārizmī had a brilliant mind, but also the luck of living in the exact place where the world’s frontier knowledge had just arrived: Greek geometry, Persian astronomy, and Indian arithmetic with its weird new zero, all translated for the first time into the same language. Ideas that incubated for centuries on separate continents were suddenly brought together as algebra. Recombination of ideas is the core engine of human progress. It is also a compounding one: every invention multiplies the combinations available to the next. Economist Martin Weitzman called this “recombinant growth.” As the knowledge of one generation becomes the foundation for the next, human civilization has been executing its own, slow algorithm of recursive self-improvement. ## **Scaling the Human Mind** Because of our biological limits, we learned to build technologies and fine-tune institutions—from writing and R&D teams to computation and the web—to augment our ability to process what is known. Yet the final step of recombination is still bound to us. For two ideas to actually fuse, they must still intersect within the same mind. Furthermore, as the sheer volume of human knowledge expands, innovators must climb longer just to reach the frontier of a single discipline, let alone multiple ones. Economist Ben Jones called this the “[death of the Renaissance Man](https://www.kellogg.northwestern.edu/faculty/jones-ben/htm/burdenofknowledge.pdf)”—an era where invention arrives later in life, driven by narrower and narrower specialists. Artificial intelligence removes this constraint. By absorbing the vast majority of codified human knowledge, it can map and traverse the rugged landscape of everything known on our behalf. It is al-Khwārizmī’s lucky accident—the collision of separate worlds into a single place—made permanent and available to everyone. ## **AI’s Comparative Advantage** When it comes to recombining ideas, humans and machines face completely different economics. For a person, cognitive costs increase steeply with distance: mastering far-apart fields is difficult and eventually impossible. Our best attempts to work around this limit require heavy scaffolding. In academia and corporate R&D, overcoming this friction means funding dedicated centers, aligning complex incentives, and spending years just to build a shared language. Merging distant fields often requires the blank slate of a startup as a forcing function—like Pixar pulling computational physicists into the same room as Disney-trained storytellers—just to force truly novel recombinations. This is why radical, cross-disciplinary leaps remain so impossibly rare. But for a machine that has read everything, the cost barely climbs at all. The asymmetry carries a sharp implication: AI’s advantage over us is not uniform but widens with distance. Within a specialized domain, human experts stay competitive as top verifiers and arbiters of agentic output—some call it judgment, others taste or curation, but it really boils down to what the human has seen before and how they [measure](https://arxiv.org/html/2602.20946v2) it relative to the machine. But out at the seams between disciplines, where our own cognitive costs are incredibly high, the machine is already superhuman. There is just one catch… ## **The Verification Divide** A flood of recombinations is not the same as progress. As the distance between domains increases, the nature of the bet fundamentally changes. Distant recombinations are highly skewed: they yield a mountain of useless dead-ends, offset by the rare, world-altering breakthrough. A distant recombination is therefore a lottery ticket. Without verification, the rare jackpot is indistinguishable from the pile of losing tickets, and its value collapses to the average of the pile: almost nothing. **Generation determines what you hold. Verification determines what it’s worth.** For a recombination loop to actually compound, two steps must happen in sequence: you generate a new idea, and then you verify it. Whatever comes next will be built on the assumption that the first idea holds. **That confirmation is not a formality. It is the difference between knowledge, which accumulates because each checked layer can bear the weight of the next, and unverified output, which merely accumulates idea debt.** **It is verification that makes the loop truly recursive, rather than just impressively fast.** When you commoditize a scarce input, you do not remove the bottleneck. You simply relocate it. For all of human history, intelligence—the generation of the next idea—was the scarce resource that progress waited on. Make it abundant, and the [constraint immediately moves downstream to verification](https://arxiv.org/html/2602.20946v2): the cost of establishing that any given output is actually correct. Crucially, that cost is not a property of the idea itself, but of the domain. In mathematics and software, verification is often nearly free and instant—the proof holds, the tests pass, the code compiles—and the loop is closed at machine speed. But in domains burdened by long, unforgiving feedback loops—from entrepreneurship and business strategy to frontier science dealing with unknown unknowns—verification cannot simply be automated. Here, the loop of recursive self-improvement grinds to a halt. Within these domains, AI may well have driven the cost of generation to zero, but verification still costs precisely what the world has always charged for it. And that newly scarce step is exactly where value will accrue. ## **The Recombination-Verification Matrix** Map these two dimensions against each other—the vast knowledge distance AI can bridge versus the last-mile verification costs the real world imposes—and the future of progress fractures into four quadrants. This is the domain of the known knowns. When the cognitive distance is short and the answers are easily checked, AI acts as a bulldozer for friction—effortlessly automating incremental discoveries, routine improvements, and daily grunt work. It won’t yield world-changing breakthroughs, but driving the cost of execution to zero fundamentally raises the baseline of human productivity, allowing experts to shift their time higher up the intelligence value chain. #### **The Land of Expert Verifiers (Within Field, Hard Verification)** AI generates relentlessly, but progress is entirely bottlenecked by the human capacity to check the work. Because verification remains stubbornly difficult, top experts must transition from being primary creators into ultimate arbiters. By using the machine to clear away the legwork, these top verifiers can scale their true scarce resources—their taste, experience, and intuition—across an unprecedented volume of output. #### **The Rapid Takeoff (Across Fields, Easy Verification)** Where distant recombination meets cheap verification, the AI gold rush unfolds first. It is the unexplored frontier where the moment an AI finds a novel combination, it can independently prove it is correct and close its own loop. Gains stack rapidly without a human-in-the-loop, making this the quadrant where AI will deliver massive, world-altering benefits the fastest. #### **Fool’s Gold** **(Across Fields, Hard Verification)** This is the same frontier, but nothing found here can be cheaply confirmed. A real discovery and a confident hallucination are indistinguishable. This is no accident: the most distant recombinations often land precisely where no discipline owns the tests yet—no established benchmark, no standard eval, no single expert qualified to referee across the gap. The structure of the problem puts the biggest prizes behind the worst measurement: AI’s advantage is largest exactly where our ability to verify is weakest. ## **A New Golden Age of Discovery** Last month, an internal OpenAI reasoning model disproved a conjecture Paul Erdős posed in 1946. It involved the planar unit distance problem—the deceptively simple question of how many pairs among *n* points in a plane can sit exactly one unit apart. For eighty years, it stood as one of the most stubborn open questions in combinatorial geometry, and for eighty years, the field assumed a particular grid arrangement was the absolute limit. The model proved otherwise, autonomously discovering an infinite family of configurations that beats the grid outright. The way the model got there is the core thesis of this piece: it cracked an elementary geometry problem by importing heavy machinery from algebraic number theory. These were two fields with no immediately obvious reason to meet, joined across exactly the distance no human was positioned to cross. This is al-Khwārizmī’s move, made by a machine. And it counts. It is an insight the field can build its next result on—not merely a plausible claim—for a reason that has nothing to do with the solution, and everything to do with the domain. In mathematics, the second step is nearly free. A proof either holds from its first line to its last, or it does not. Verification is fast and absolute, a stark contrast to the years a clinical trial or a macroeconomic forecast might require. The distant recombination delivered the breakthrough, but it was the low cost of verification that let the loop close behind it. Mathematics is anchored by a single, universal standard of proof. But the further a field drifts from that absolute certainty—the longer and fuzzier its verification gets—the more that same flood of confident, far-flung ideas simply piles up unconfirmed, leaving real discoveries indistinguishable from mirages. Progress runs at the speed of automation where checking is cheap, and at the speed of verification everywhere else. The widening gap between those two speeds is set to become the defining fault line of discovery. There is only one looming exception to this rule: the simulation problem. If [world models](https://drfeifei.substack.com/p/a-functional-taxonomy-of-world-models) become capable of running infinite, highly realistic counterfactuals—effectively turning real-world friction into the mere cost of compute—the verification bottleneck vanishes. We are seeing early glimpses of this in physics and robotics. Should this extend to modeling complex markets and social systems, the machine delivers verification-in-a-box. At that point, the 2x2 matrix collapses, the path to superintelligence is cleared, and the only things left unautomated will be the things humanity has literally *[never measured](https://hbr.org/2025/06/what-gets-measured-ai-will-automate)*. ## **The Endless Frontier** For founders, inventors, and scientists asking themselves where to deploy their time, the clash between AI’s infinite capacity for recombination and the annoying friction of real-world verification acts as a compass. It points directly toward the new frontier. The most obvious opportunities sit in the Rapid Takeoff quadrant—distant problems paired with frictionless verification. But this space is crowding quickly, and the frontier AI labs hold an inherent structural advantage here. In these domains, cheap verification doesn’t just check the work; it generates the exact data needed to train the next model. Modern reasoning models scale through automated reward signals, and this quadrant supplies an infinite synthetic loop of them for free. **Fable’s launch made the advantage explicit: AI research itself — instantly benchmarked, self-grading — is the purest Rapid Takeoff territory on the map, and it is the first domain a lab has drawn a border around.** Ironically, the more defensible opportunities sit in Fool’s Gold. The true prize in this quadrant isn’t generating answers, but building scalable forms of verification. Whoever engineers the measurement infrastructure that turns a long-lag question into a short one—the simulation that replaces the physical lab, or the formal eval a soft discipline has never had—does not make a single discovery. Instead, they convert an entire region of the map from Fool’s Gold into a Rapid Takeoff Zone. They supply the missing half of the loop, and in doing so, they define exactly where the golden age is permitted to spread. As in the Land of Expert Verifiers, building this infrastructure demands harvesting the insights of the world’s top talent. It requires progressively extracting the intuitive “weights” locked inside their minds, converting their tacit knowledge into replicable, measurable digital traces that finally close the loop for full automation. Notice how this shifts the economic rents. For most of history, the scarce resource was the bridge—the rare person or team who could hold distant fields in a single mind commanded a massive premium. Today, spanning that distance is practically free. The new rents sit one step downstream, captured entirely by the two jobs the machine cannot do for itself: choosing which recombinations are worth advancing, and verifying which ones actually paid off. For scientists and professionals, the lesson is clear: the method of verification is no longer the boring half of the work—it *is* the work. For entrepreneurs, builders, and creatives, the mandate is exactly the same. In an age of infinite output, a durable business isn’t built by generating more of it. It is built by being the arbiter whose verification the world trusts. ## **Take Nobody’s Word For It** Science built an institution for this exact problem three and a half centuries ago. When the Royal Society was founded, it took as its motto *nullius in verba*—take nobody’s word for it. The point was never that ideas were scarce. The point was that an idea counts for nothing until it has been checked, and that the act of checking is the institution’s reason to exist. We are about to inherit more ideas than any civilization has ever held: recombinations conjured at near-zero marginal cost, across distances no single mind could bridge. Whether that becomes a golden age of discovery for your startup, your science, or your art, or simply a planetary waste of tokens, turns on the oldest discipline we possess: the refusal to take the machine’s word for it. And that refusal cannot stop at the model. The labs building self-improving systems are also drawing the borders of self-improvement: which domains may compound at frontier speed, which must be routed elsewhere, and which restrictions users are even allowed to see. Their caution may be justified; a loop that improves intelligence is not an ordinary product feature. But *nullius in verba* was never a judgment about motives. It was a rule for claims. A safeguard is a claim too. A civilization mature enough not to take the machine’s word for its answers cannot take any lab’s word for where the loop may close. **Recombination is now free. The future belongs to whoever is allowed to verify it.** --- ## Bot Chargebacks, Voyages, and AI Liability - canonical: https://catalini.com/writing/bot-chargebacks-ai-liability/ - original: https://www.koreaherald.com/article/10760547 - date: 2026-06-02 - outlet: korea-herald What 17th-century maritime commerce teaches about liability when AI agents transact on our behalf. Full text at the original outlet: https://www.koreaherald.com/article/10760547 --- ## Stablecoins Break the Beautiful Business Model of Banking - canonical: https://catalini.com/notes/stablecoins-break-banking-model/ - original thread: https://x.com/ccatalini/status/2046598000181674027 - date: 2026-04-21 If you are a bank, your business model is beautiful. You take people's money, pay them zero, lend it out at five or more, and keep the difference. Someone else offering to pay interest is the one thing that breaks the model. Stablecoins offer to pay interest. Stablecoin issuers earn ~4% on the Treasuries backing their tokens. Historically they kept it. The obvious move is to share it with holders. GENIUS stopped issuers from paying directly. CLARITY is fighting over whether exchanges and distributors can. [x.com](https://x.com/SecScottBessent/status/2042211752767562054?s=20) [@NCBankers](https://x.com/NCBankers) is asking senators for "an airtight prohibition on payments for stablecoins acting as a store of value... without carve-outs that can be met through nominal activity or loyalty programs." Translation: make stablecoins worse than us, by law. [x.com](https://x.com/EleanorTerrett/status/2045572030775398669?s=20) This is a masterpiece of the genre: we cannot stop stablecoins from existing, but you must legally mandate they be worse than our products. We are the banks, we own the concept of interest, so you must stop the computer program... In the 1880s, several US states — e.g. NH, VT — required margarine to be dyed pink. Not labeled pink. Dyed! The theory was nobody spreads pink grease on bread. Technically legal, commercially dead. The Supreme Court struck it down as "in necessary effect, prohibitory." So the dairy lobby pivoted. The 1902 Grout Bill taxed yellow margarine 40x more heavily than white. It did not tax margarine. It taxed margarine that resembled butter. Substitute "yellow" for "economically or functionally equivalent" and you are reading the CLARITY Act draft. The margarine industry shipped white blocks with a separate capsule of yellow dye. Consumers kneaded it in at home. For fifty years, Americans performed a small act of civil disobedience at their kitchen tables every week. Nobody was fooled. The workaround became the product. In 1933 banks got an airtight prohibition on paying interest on demand deposits. Regulation Q. In 1971 two guys started the first money market mutual fund — formally a security, economically a checking account paying market rates. It now holds $7.6 trillion. Banks lost. The deeper problem: yield isn't a side feature for banks. Their profit depends on paying zero on deposits. Stablecoins-that-share-yield is specifically the product that breaks that. This is Blockbuster vs. Netflix. Blockbuster also thought late fees were defensible. Not every bank is Blockbuster. JPMorgan's JPMD deposit token — which pays interest because it's a deposit, not a stablecoin — launched on a public blockchain last year. The last time the banks asked for an airtight prohibition, they got Vanguard. The time before, somebody got Wisconsin. [@Forbes](https://x.com/Forbes) [@ForbesCrypto](https://x.com/ForbesCrypto) [forbes.com](https://www.forbes.com/sites/christiancatalini/2026/04/20/the-banks-would-like-to-dye-your-stablecoins-pink/) --- ## The Banks Would Like To Dye Your Stablecoins Pink - canonical: https://catalini.com/writing/banks-dye-stablecoins-pink/ - original: https://www.forbes.com/sites/christiancatalini/2026/04/20/the-banks-would-like-to-dye-your-stablecoins-pink/ - date: 2026-04-20 - outlet: forbes If you are a bank, your core business model is quite elegant. You take people’s money, you pay them zero percent interest on their checking accounts, and you lend that money out to other people at five or seven percent interest. You keep the difference. This is a very good business, and if you have it, you will fight very hard to keep it. The problem with paying your depositors zero percent is that eventually, someone else will come along and offer to pay them something. When this happens, you have two choices. You can raise your own deposit rates to compete, which costs you money and ruins your business model. Or you can go to the government and ask them to make it illegal for the others to pay interest. Historically, banks strongly prefer the second option. A stablecoin is a cryptocurrency pegged to the US dollar. If you give a stablecoin issuer a dollar, they give you a digital token, put your dollar in Treasury bills, and earn about 4%. Historically, stablecoin issuers have kept that yield for themselves. The obvious next step in the evolution of this product is that they share some of the yield with you, so that you will hold their token instead of leaving your money parked elsewhere. Under GENIUS, issuers themselves cannot pay yield to holders. The live CLARITY fight is whether affiliated exchanges, distributors, or rewards programs can share those economics with users in ways that are functionally equivalent to interest. The banks do not care for this. And so they are calling their senators. Congress has been locked in talks for months over a crypto regulatory framework — the GENIUS Act last summer for stablecoin issuers, and now the CLARITY Act for everything else, including the question of what stablecoin players can do. Treasury Secretary Scott Bessent has publicly urged the Senate to move forward: But the traditional banking lobby has demands first. According to Crypto In America reporter [Eleanor Terrett](https://x.com/EleanorTerrett/status/2045572030775398669?s=20), the North Carolina Bankers Association has been circulating a message, encouraging member banks to call lawmakers with this script: *“The CLARITY Act must include an airtight prohibition on payments for stablecoins acting as a store of value by clearly barring any interest or yield-like payments tied to the holding, retention, or balance of payment stablecoins — without carve-outs that can be met through nominal activity or loyalty programs.”* This is a masterpiece of the genre. What the banks are saying, in plain English, is: “We cannot stop stablecoins from existing, but you must legally mandate that they be worse than our products.” They want to ban anything ["economically or functionally equivalent"](https://x.com/EleanorTerrett/status/2036279124382077137?s=20) to interest. We are the banks, we own the concept of interest, so you must stop the computer program. It is also, as it turns out, a margarine law. In 1869, a French chemist named Hippolyte Mège-Mouriès figured out how to make a cheap spreadable fat from beef tallow. Napoleon III wanted something to feed the army and the poor, and Mège-Mouriès gave him margarine. By the mid-1870s it had arrived in the United States, where it cost significantly less than butter and tasted, to an unaided palate, basically the same. This is the point at which the American dairy industry discovered that it could not compete on price or efficiency with a man who had invented butter in a factory, and so, like all industries that cannot compete on price or efficiency, it turned to the regulators. By the turn of the century, more than thirty states had passed anti-margarine laws. The pitch was consumer protection: people could not be allowed to accidentally buy margarine while thinking it was butter. The mechanism was, in retrospect, spectacular. New Hampshire and Vermont, among others, required margarine to be dyed pink. Not *labeled* pink. *Dyed.* The theory was that nobody will spread pink grease on bread, and therefore the product will be technically legal but commercially dead. This is an airtight prohibition without carve-outs that can be met through nominal activity. The Supreme Court struck down New Hampshire’s pink-margarine law in 1898, holding that it was “in necessary effect, prohibitory.” So the states pivoted. They said: fine, you can sell margarine, but you cannot sell it yellow. Margarine is naturally white. Butter is yellow because cows eat grass. Without the color, the consumer will look at this tub of white grease and reject it. Commercially dead, but this time constitutional. The federal Margarine Act of 1886 added a two-cent-per-pound tax. The Grout Bill of 1902 raised it to ten cents per pound on *yellow* margarine while leaving uncolored margarine at a quarter of a cent. Read the Grout Bill carefully. It does tax margarine — but it taxes margarine that resembles butter forty times more heavily. The regulated quantity is not just the product; it is the product’s resemblance to the incumbent product. Substitute “yellow” for “economically or functionally equivalent” and you are reading the March draft of the CLARITY Act. The margarine industry did what industries do when regulators ban yellow. It shipped the product as a block of white margarine with a separate capsule of yellow dye. The consumer put the block in a bowl at home and worked the dye through with a wooden spoon. Generations of Americans spent the first half of the twentieth century sitting at their kitchen tables, performing a small act of civil disobedience every week to save thirty cents on butter. By the mid-1940s, Leo Peters had patented a plastic pouch with the dye capsule sealed inside, so consumers could pinch and knead the bag instead of mixing margarine in a bowl. This was considered a major innovation. If you are over a certain age, someone in your family may remember this. Wisconsin kept its yellow-margarine restrictions until 1967, the last state to give up. Minnesota required public disclosure when oleomargarine was served in place of butter. Violations could carry criminal penalties. The point was not subtle: margarine could exist, but the law made restaurants announce the substitution. Nobody was fooled. Everyone understood the point. The workaround *became* the product. Eventually, World War II hit. Butter was heavily rationed, margarine was less so, and American households got so used to mixing the dye that they became much more comfortable substituting margarine for butter. Margarine outsold butter by 1958. The dairy lobby had spent eighty years successfully defending the legal definition of the word “butter,” and in the process had taught an entire country that you could mix your own yellow dye into a cheaper, longer-lasting, identically-functional spread and it would be fine. The carve-out became the industry. By the time Wisconsin gave up in 1967, margarine was not the substitute. It was the mass-market spread, and butter had become the luxury good. In a strange coda, butter later won a different fight. By the 2000s, margarine’s trans-fat reputation had collapsed, and butter brands increasingly competed on provenance, fat content, and flavor — Irish grass-fed butter, European-style butterfat, cultured butter. The industry that had spent eighty years legislating against its substitute eventually won a different fight, the one no regulator had forced on it, which was to pay attention to what customers actually wanted. This is the part where you may be nodding and assume the same thing will happen with stablecoins. Which it probably will. But there is a more recent and more financially precise version of this story, and it is even less flattering to the bank lobby, because the bank lobby is the one it happened to. In 1933, the Banking Act prohibited banks from paying interest on demand deposits and gave the Fed authority to cap rates on savings deposits. This was Regulation Q. It was meant to prevent destructive rate competition and protect the community bank deposit franchise. It was airtight. It had no carve-outs. It was the closest financial ancestor of the regime the NCBA is currently asking Senator Tillis to enact for stablecoins. In 1971, Bruce Bent and Henry Brown started the first money market mutual fund. It held short-term Treasuries and commercial paper. It passed the yield through to shareholders as “dividends,” because technically it was a 1940 Act registered fund and not a bank. It was functionally a checking account paying market rates, but formally it was a security, and Regulation Q regulated banks, not securities. In 1977 Merrill Lynch added check-writing and a Visa card and called it the Cash Management Account. By the early 1980s, money-market funds had become a $200-billion-plus industry. Today they hold more than $7.6 trillion. Deposit-rate ceilings were dismantled through the 1980s; the demand-deposit interest ban finally disappeared in 2011, seventy-eight years after the original prohibition. The thing the banks wanted to protect in 1933 — their exclusive franchise over yield-bearing, dollar-denominated, liquid instruments — they lost to a wrapper that was technically not a bank. They did not lose it because of bad regulation. They lost it because the airtight prohibition trained an entire adjacent industry to build the same product in a form the prohibition did not cover. So. Back to the NCBA sentence. “Airtight prohibition” is a thing you can ask for. You will sometimes get it. The Oleomargarine Act of 1886 is an airtight prohibition. Regulation Q is an airtight prohibition. What airtight prohibitions are very bad at is remaining about the thing they were written about. The margarine laws were about butter, until they were about teaching consumers that butter was optional. Regulation Q was about bank deposits, until it was about making money market funds a better savings vehicle for the American middle class. The prohibition works on the dimension the incumbent specified. The industry routes around that dimension. The resulting product is a version of the substitute specifically adapted to the contours of the prohibition. Which tends to make it better. The CLARITY Act fight is about whether a crypto exchange can pay yield on a stablecoin balance. The banks want airtight. They want no carve-outs met through nominal activity. They want no exceptions for novel loyalty programs or business models. They want an economic equivalence standard strong enough to catch any structure that has the effect of interest, even if it is formally something else. This is, one should grant, a coherent request. It is what a lawyer who understood everything about how margarine beat butter, and everything about how money market funds beat banks, would ask for. It is the prohibition you would draft if you had read the history. And the reason it will not work is that the airtight prohibition is often the cause of the substitution. It is not the defense against it. The dairy industry did not lose to margarine despite the yellow-dye laws. It lost to margarine *because* of them. The laws created a product category — mix-your-own margarine — that consumers engaged with at their kitchen tables for fifty years. Regulation Q did not fail to protect banks from money market funds. Regulation Q was the reason money market funds existed in that form. If the CLARITY Act passes with an airtight prohibition on anything economically equivalent to interest, the stablecoin industry will spend the next decade designing products that are formally something else. They will hand users a white stablecoin and a digital packet of yellow dye and let them mix the yield in at home — which is to say, they will build products specifically adapted to the contours of whatever the government agencies will jointly write in their rulemaking. And at the end of the decade, the bank deposit franchise will discover it has been competing not with stablecoin yield, which is easy to regulate, but with whatever the industry built instead. The deeper problem for the banks is that yield is not a side feature they’re defending. Their profit depends on paying depositors zero and earning five, and stablecoins-that-share-yield is specifically the product that breaks that model. This is Blockbuster and Netflix. In 2000, Blockbuster collected $800 million in late fees, which was sixteen percent of its revenue. The company was profitable because it was annoying. The famous story is that Reed Hastings started Netflix because Blockbuster charged him $40 for returning *Apollo 13* late; Marc Randolph, his co-founder, has since admitted they made that up because it was the easiest way to explain the subscription model to the press. Which is fine. The story worked because everyone instantly understood what Netflix was selling. They were selling not-Blockbuster. That same year, Blockbuster had the chance to buy Netflix for $50 million and laughed them out of the room. In 2005, it tried to scrap late fees to compete. It could not figure out how to make money without them. It brought them back under a different name and filed for bankruptcy in 2010. The airtight prohibition is the version of that story where Blockbuster gets Congress to ban flat-rate subscriptions. Which is, in effect, what the banks are asking for. [Not every bank is Blockbuster.](https://www.forbes.com/sites/christiancatalini/2025/12/17/how-banks-learned-to-stop-worrying-and-love-stablecoins/) The smart response to better rails is to use the better rails. JPMorgan has done exactly that: its deposit token JPMD — which can pay interest because it is a bank deposit rather than a stablecoin — launched on a public blockchain last year. Multiple banks are running similar tokenized-deposit products on their own private blockchains, which is a permutation of the same bet. The largest banks are not sitting this one out. They are building the product the NCBA wants Congress to ban. Which suggests the lobbying is less a strategy than a delay tactic — one that won’t save the banks running it, because the loudest banks in the lobbying fight may not be the banks best positioned to compete. The White House Council of Economic Advisers published a [paper](https://www.whitehouse.gov/research/2026/04/effects-of-stablecoin-yield-prohibition-on-bank-lending/) two weeks ago arguing that a complete ban on stablecoin yield would increase aggregate bank lending by $2.1 billion — 0.02 percent of total loans. The American Bankers Association rebutted this by saying the CEA had studied the [wrong question](https://bankingjournal.aba.com/2026/04/the-cea-studied-the-wrong-question-on-stablecoin-yield-and-community-banks/). On this one narrow point, the ABA is right. The CEA studied the current-scale lending effect of a prohibition. The relevant question is what happens in year twenty. The relevant comparison is not money market funds in 1972. It is money market funds in 2011. The banks are welcome to get the airtight prohibition they are asking for. They should probably be careful what they ask for. The last time they asked for one, they got Vanguard. The time before that, somebody got Wisconsin. --- ## Thomas Midgley Jr. and the Limits of 'Productivity-Raising' - canonical: https://catalini.com/notes/midgley-productivity-externalities/ - original thread: https://x.com/ccatalini/status/2045595151633166546 - date: 2026-04-18 Thomas Midgley Jr. invented two of the most productivity-raising, competitively-produced inputs of the 20th century: leaded gasoline and CFCs. Both were obviously good by that standard. One poisoned three generations. The other punched a hole in the ozone layer. More intelligence will make us richer, healthier, better taught. Kevin is right about that. But "productivity-raising input" describes a transition, not a destination — and every transition relocates value before it expands it. [x.com](https://x.com/Afinetheorem/status/2045506796224499835?s=20) Verification has to scale with capability. Burden-of-proof arguments only work when the proof arrives in time. Midgley's didn't. --- ## Agentic AI Is Waiting for Its Plimsoll Line - canonical: https://catalini.com/notes/agentic-ai-plimsoll-line/ - original thread: https://x.com/ccatalini/status/2045525975874912295 - date: 2026-04-18 In 1876 Britain made shipowners paint a line on every hull. Before it, "coffin ships" sailed overloaded because owners collected more from the insurance than the voyage. Shipping didn't scale on bigger hulls — it scaled on a mark anyone could verify. Agentic AI is waiting for its Plimsoll line. To safely delegate our economy to machines, trust can no longer rely on manual inspection — trust must be hardcoded into the architecture itself. [substack.com](https://substack.com/home/post/p-194563373) Durable advantage belongs to those who cryptographically certify output, insure it, and absorb the costs if it fails. Scale without verification is just liability. --- ## Agents Are Starting to Operate Real Systems — Who’s Actually in Control? - canonical: https://catalini.com/writing/agents-operating-real-systems/ - original: https://a16zcrypto.substack.com/p/agents-are-starting-to-operate-real - date: 2026-04-18 - outlet: a16z As AI agents begin operating real systems, the question shifts from capability to control — identity, payments, and verifiable trust for machine actors. Full text at the original outlet: https://a16zcrypto.substack.com/p/agents-are-starting-to-operate-real --- ## Software Is Eating Labor - canonical: https://catalini.com/notes/software-is-eating-labor/ - original thread: https://x.com/ccatalini/status/2045185456699285824 - date: 2026-04-17 "Software is eating the world" got a sequel: software is eating labor, as labor becomes software. Everyone's staring at the models. The actual bottleneck is verification. Intelligence is commoditizing. What isn't: unique, fresh, proprietary data about what the world actually looks like. That data isn't just training fuel. It's what teaches a verifier to separate real work from confident slop. So AI favors one kind of company: owns a live feed of reality, turns it into labor-as-software, uses that same data to verify the output. Unique data → verification → scaling. Skip the middle and you don't have a business. You have an expensive intern. --- ## LLMs Are the Wagon Wheel Bar at Civilization Scale - canonical: https://catalini.com/notes/llms-wagon-wheel-bar/ - original thread: https://x.com/ccatalini/status/2036474348895346978 - date: 2026-03-24 [@annosax](https://x.com/annosax)'s core thesis was that Silicon Valley won because ideas leaked across company boundaries at a bar in Mountain View. LLMs hold the entirety of recorded human thought in their latent space... ...they're the Wagon Wheel Bar at civilization scale—surfacing connections no individual or discipline has the institutional memory to notice. The difference is nobody at the bar could remix your life's work at zero marginal cost and publish it before you finished your drink. Except Marshall said it in 1890: ideas are "in the air." Maybe we've spent a century overweighting who said something first and underweighting who verified it, executed it, and stood behind it. AI didn't create that problem. It just made it impossible to ignore. --- ## The Trojan Horse Externality - canonical: https://catalini.com/notes/trojan-horse-externality/ - original thread: https://x.com/ccatalini/status/2036185291468447849 - date: 2026-03-23 “Cognitive surrender” is the psychology. The economics is the Trojan Horse externality: the cost to verify is rising while the cost to generate collapses. Humans aren’t giving up… they’re priced out of checking. Which is worse! [x.com](https://twitter.com/rohanpaul_ai/status/2036134704999694835) The verification layer is where all the value will be created and destroyed in the agentic era. [x.com](https://twitter.com/a16z/status/2032220250650132612) Not the execution layer. Not the model layer. The verification layer. And almost nobody is pricing it in. --- ## Karpathy's Throwaway Caveat Is the Hard Ceiling - canonical: https://catalini.com/notes/karpathys-throwaway-caveat/ - original thread: https://x.com/ccatalini/status/2035737259564302664 - date: 2026-03-22 Karpathy just described the hard ceiling on trillion-dollar autonomous systems as a throwaway caveat about his overnight hyperparameter script ([@NoPriorsPod](https://x.com/NoPriorsPod)) — and went back to tuning his learning rate... [@karpathy](https://x.com/karpathy): "This is extremely well suited to anything that has objective metrics that are easy to evaluate... writing kernels for more efficient CUDA code [...] are the perfect fit. Perfect fit." "But many things will not be. [...] If you can't evaluate then you can't auto research it." Nobody in the conversation reacts to this. He's describing a property of his hyperparameter tuner the way you'd describe a property of your dishwasher. Works great for plates, not for cast iron... [x.com](https://x.com/saranormous/status/2035080458304987603?s=20) Except the "cast iron" is every autonomous system whose output a human can't cheaply verify. So, you know. Most of the economy. What he actually said is: the bottleneck on autonomous AI is not intelligence. It's not compute. It's not data. It's whether anyone can check the answer. That's it. That's the whole economics of AGI! Every lab is racing to remove humans from the loop. The entire economy depends on keeping them in it. No one has reconciled this. We tried. The cost to automate is collapsing. The cost to verify is bounded by biology. That single asymmetry drives everything: alignment drift, the collapse of the junior pipeline, liability-as-software, the future of work, and where value will ultimately accrue. Paper: [arxiv.org](https://arxiv.org/html/2602.20946v2) --- ## Generation Scales. Verification Doesn't. - canonical: https://catalini.com/notes/generation-scales-verification-doesnt/ - original thread: https://x.com/ccatalini/status/2035347943323279800 - date: 2026-03-21 The answer is you can’t — not cheaply. Verifying whether a paper is a breakthrough requires roughly the same expertise as producing one. Generation scales. Verification doesn’t. [x.com](https://twitter.com/dwarkesh_sp/status/2035083959499972976) We call this the Measurability Gap. The harder a task is to verify relative to how hard it is to execute, the less safely you can automate it. AI science is the extreme case: infinite generation, fixed verification bandwidth. We formalize this, and map the conditions under which verification becomes the binding constraint on AI progress, in Section 5: [arxiv.org](https://arxiv.org/html/2602.20946v2#S5) “Reality is the ultimate eval” is exactly right. The question is whether world models can internalize enough physics to run that eval without a human expert in the loop. If they can’t, we have a ceiling. [x.com](https://twitter.com/elonmusk/status/2035235191586017537) --- ## Lowell's Mills and the Shape of Verification Infrastructure - canonical: https://catalini.com/notes/lowell-mills-verification-infrastructure/ - original thread: https://x.com/ccatalini/status/2034617918198284401 - date: 2026-03-19 This is a great description of what verification infrastructure looks like in practice. In our new paper we argue this is the binding constraint on the AI economy — the same bottleneck textile mills hit when they scaled looms faster than weavers could check them. [x.com](https://twitter.com/rohit4verse/status/2033945654377283643) In 1842, the managers at Lowell’s textile mills had an idea so obvious it barely counted as one. Their weavers each ran two power looms. The mills had just bought more machines. Give each weaver a third loom, output goes up 50%. It didn’t work. The problem wasn’t physical — the machines did the weaving. The weaver’s real job was watching cloth get made: scanning for broken threads, catching defects, intervening before a flaw ruined an entire bolt. Add a third loom and the verification load exceeded human bandwidth. The mills had to cut loom speeds 15% just to keep quality from collapsing. It took a full year of retraining before weavers could run three looms at full speed. They’d upgraded the machines, only to discover the machines weren’t the bottleneck. Economist [@JamesBessen](https://x.com/JamesBessen) reconstructed this history. Once the power loom was in place, 62% of subsequent productivity gains came not from better machines, but from better-skilled humans who could monitor more of them. “They were monitoring.” By 1902 a single weaver ran 18 looms and produced 50x the output of a century earlier. But mills had to triple training investment — from $47 to $162 per weaver. Capital and skilled labor weren’t substitutes. They were complements. Today the loom is an AI agent. The cost to generate is collapsing. The cost to verify — to confirm it’s correct, safe, and not hallucinated — stays anchored to human judgment. One curve is a rocket. The other is a bicycle. The gap between those two curves is where economic value goes to die. My co-authors [@XiangHui](https://x.com/XiangHui) [@JaneWu](https://x.com/JaneWu) and I wrote about why verification — not intelligence — is the binding constraint on the AI economy. The weavers’ story is comforting: capital and labor were complements. But here’s the question we wrestle with in the paper: what happens when the verification layer itself becomes software? The problem with AI checking AI is that the errors become correlated. Same training data, same blind spots, same confident mistakes. You don’t get independent verification. You get a hall of mirrors that looks like consensus. That’s the path to what we call the Hollow Economy. Output explodes. Everything looks efficient. But the system is quietly losing the ability to catch its own mistakes—because the humans who could spot them were never trained, and the AI verifiers share the same blind spots. Meanwhile the pipeline that produces those humans is already severed. Juniors aren’t getting hired for the entry-level work that builds experience. Seniors are codifying their expertise into the models. The stock of human verification capacity is drawing down. The alternative demands real investment: accelerated mastery through AI that compress years of experience, synthetic apprenticeships that simulate edge cases at density no traditional job provides, and many more entrepreneurial and R&D experiments. The goal isn’t to compete with AI at execution. It’s to keep human capacity for steering and verification high enough that we actually know when the machines have drifted. The weavers figured this out. The question is whether we will. [forbes.com](https://www.forbes.com/sites/christiancatalini/2026/03/18/babysitting-the-slop/) --- ## Babysitting The Slop - canonical: https://catalini.com/writing/babysitting-the-slop/ - original: https://www.forbes.com/sites/christiancatalini/2026/03/18/babysitting-the-slop/ - date: 2026-03-18 - outlet: forbes In 1842, the managers of Lowell, Massachusetts's textile mills had what seemed like a straightforward idea. Their weavers each operated two power looms. The mills had just acquired more machines. The math was simple: give each weaver a third loom, output goes up by fifty percent. It didn’t work. Something counterintuitive happened instead. With three looms running, even the most experienced weavers couldn't keep up. Not with the physical labor—the machines did the weaving. The problem was *monitoring*. A weaver's real job wasn't making cloth. It was watching cloth get made: scanning for broken threads, catching defects, making micro-adjustments before a flaw could propagate through yards of fabric. Add a third loom, and the verification load exceeded human bandwidth. The mills had to cut loom speeds by 15% just to keep quality from collapsing. They'd upgraded the machines, only to discover the machines weren't the bottleneck. It took a full year of retraining before weavers could run three looms at full speed. By 1902, a single American weaver managed 18 power looms and produced over 50 times the output of a weaver a century earlier —but only after mills tripled their training investment per worker, from $47 to $162. [Bessen](https://x.com/JamesBessen), who painstakingly reconstructed this [history](https://scholarship.law.bu.edu/cgi/viewcontent.cgi?params=/context/faculty_scholarship/article/4181/&path_info=More_Machines__Better_Machines...Or_Better_Workers.pdf), found that once the power loom itself was in place, 62% of the remaining productivity gains through the Northrop loom era came not from further mechanical inventions, but from better-skilled humans who could monitor more looms at once. "The weavers were not simply idle during this time," he wrote. "They were monitoring". The binding constraint was never the loom. It was never the thread, the cotton, or the power source. It was the weaver's ability to verify the loom's output. Today, the loom is an AI agent. The constraint hasn't changed. ## The Bicycle and the Rocket In a [recent paper](https://arxiv.org/pdf/2602.20946), my co-authors [Xiang Hui](https://olin.washu.edu/faculty/xiang-hui), [Jane Wu](https://www.anderson.ucla.edu/faculty-and-research/strategy/faculty/wu), and I argue that the binding constraint on AI-driven economic growth is not intelligence, not compute, not execution capacity. It is human *verification bandwidth*—the scarce ability to confirm that AI agents actually did what they were supposed to do, correctly, safely, and honestly. The core concept is what we call the [Measurability Gap](https://x.com/ccatalini/status/2026311825898504608?s=46), and understanding it is the key to understanding why AI progress on benchmarks keeps diverging from AI progress in the real economy. Two cost curves are moving in opposite directions. The cost to *generate*—to have an AI produce code, analysis, text, decisions—is falling exponentially with every new model release. The cost to *verify*—to confirm the output is correct, safe, non-hallucinated, and aligned with intent—remains stubbornly bottlenecked by human time, domain expertise, and feedback latency. One curve is a rocket. The other is a bicycle. The widening space between them is where economic value goes to die. The numbers make this vivid. SWE-bench coding accuracy jumped from 4.4% to 71.7% in a single year. Task horizons for autonomous agents are doubling on a sub-year cadence. AI can now write entire pull requests, draft regulatory filings, generate onboarding workflows. But Google's DORA reports show that greater AI adoption is associated with *lower* delivery stability. Daron Acemoglu projects AI's total factor productivity contribution at a modest 0.53–0.66% over a decade—not because AI isn't capable, but because verification bottlenecks cap the value that actually gets realized. And when verification fails, it fails spectacularly. Days ago, a [Chinese cybersecurity company](https://x.com/ccatalini/status/2033742180607791529?s=46) accidentally shipped its private cryptographic key inside a public release—a verification lapse so basic it's almost comic, except that it exposed the entire signing infrastructure that authenticated their software. Nobody checked. The AI economy is increasingly full of outputs that nobody checked. The automation boundary, we argue, is no longer [“routine versus non-routine”](https://arxiv.org/html/2602.20946v2#S7)—the old framework economists used to predict which jobs machines would take. The new boundary is **measurable versus non-measurable.** If a human can verify the output in seconds—thumbs up on a chatbot response, quick visual check on a generated image, run the code and see if it compiles—adoption is fast and value capture is real. If verification requires domain expertise, extended time horizons, or adversarial stress-testing, the Measurability Gap yawns open and adoption stalls, even when the AI is technically brilliant. This is why the first killer AI products were chat, image generation, and code autocomplete. Not because those were the hardest problems. Because they were the most *verifiable*. The hard frontier is everything else—and it's most of the economy. We are getting dramatically better at producing output and not meaningfully better at confirming it's right. ## Your Data Moat Is Probably the Wrong Data For any organization sitting on proprietary data, this framework forces a surprisingly uncomfortable question: which of your data assets actually matter in an AI world? We distinguish two types. The difference is subtle but has enormous strategic implications. **1. Execution-grade knowledge** is the stuff that teaches an AI *what to do*. Finished code. Completed contracts. Final reports. Clean datasets. Polished outputs. This is what most companies think of when they hear "proprietary data advantage." And it is structurally vulnerable. As foundation models improve—as they ingest more public examples of good code, good contracts, good reports—the marginal value of your private stash of finished work declines. The model already knows how to write a contract. Your 10,000 historical contracts help a little less with each generation of frontier model. **2. Verification-grade knowledge** is different. It teaches systems *what to reject*—and more importantly, *why*. This is the data generated at the point of failure: redlines on deals that almost closed but didn't, deployment blocks on code that passed tests but broke in production, false-positive logs from fraud detection, near-miss records from compliance reviews, edge-case adjudications where expert judgment overrode the default answer. It is the institutional memory of things going wrong, encoded with enough context to be actionable. Here's why verification-grade data is so much more valuable—and why its value is actually *increasing* with AI capability. In a world where AI can effectively convert data and compute into labor—where a sufficiently rich dataset can train, fine-tune, or prompt a model to replicate expertise—the quality, recency, and granularity of your data determines how much skilled labor you can synthesize. This is the **labor as software** thesis: data doesn't just inform decisions, it *becomes* the decision-maker. Execution-grade data gives you a model that can produce outputs. Verification-grade data gives you a model that can *audit* outputs. And in a world where production is cheap and verification is expensive, the second capability is worth dramatically more. Think of it concretely. A bank's accumulated database of KYC/AML failures, fraud false-positives, edge-case adjudications, and compliance near-misses is verification-grade ground truth. Each record encodes a moment where a human expert said "this looks right but isn't" or "this looks wrong but is actually fine" or "this is the specific reason we blocked this transaction." That judgment, captured at scale with timestamps and context, is the raw material for training verification systems that can eventually widen the verification bottleneck itself. And because these records are more recent, more fine-grained, and more domain-specific than anything in a foundation model's training corpus, they get *more* powerful as AI improves—not less. Better base models mean you can extract more signal from each verified data point. Your failure library becomes a force multiplier. A competitor can replicate the ability to *generate* an onboarding workflow. It cannot replicate the 15 years of institutional failure-memory required to *trust* that workflow at scale. The verification-grade data is the moat precisely because it accrues slowly, is hard to fake, and becomes more valuable as AI makes generation cheaper. The asymmetry cuts deeper than most people realize. AI lowers the cost of executing tasks far faster than it lowers the cost of verifying whether those tasks were done honestly. A scanned passport used to be identification—now it's raw material for a generative model. A video selfie used to be a liveness check—now it's a challenge to the best deepfake on the market. [You can automate the paperwork faster than you can believe the paperwork.](https://www.forbes.com/sites/christiancatalini/2026/03/10/software-eats-the-brokerage-ai-lowers-cost-crypto-makes-it-verifiable/) Every advance in generation is simultaneously an advance in the attack surface for verification. The dominant strategy follows: rent cognition, own trust. Use frontier models for reasoning. Privatize your domain context and your verification stack. Execution commoditizes. Verification is the moat. ## What Happens When the Network Effect Runs in Reverse There is a related problem worth thinking through carefully, because it threatens one of the core assumptions of platform strategy. The standard playbook for platforms goes like this: get big, get network effects, let the flywheel spin. More users attract more users. The platform gets better because it gets bigger. This is the story of every successful marketplace, social network, and exchange.Now consider what happens when AI agents join your platform. Because they imitate human behavior so convincingly, platforms can’t easily filter them out. But beneath that plausible veneer, they are all trained on the same data and suffer from the same architectural blind spots. We call this "agentic slop," and it has a fatal flaw: common-mode failure. When these agents hallucinate or guess wrong, they don't make random, independent human mistakes. They make the exact same mistake. A million agents flooding a platform don't give you a million independent signals. They give you a million perfectly correlated, human-passing mistakes, making it impossible to tell what is actually real. So network effects invert. Instead of more participants making the platform more valuable, more AI-generated participants make the platform less trustworthy. The quality humans—the ones whose verified behavior is actually valuable—notice the rising noise floor and leave. The trust flywheel doesn't just slow down. It runs in reverse. The metric that matters isn't raw network size anymore. It's what we call *verified network scale*—the authenticated, verified share of participants whose outputs can actually be trusted. Platforms that measure and defend that number will survive. Platforms optimizing for raw volume are building on quicksand. Scale without verification isn't a moat. It's debt that compounds. For regulated industries—banking, healthcare, insurance—this dynamic cuts both ways. These sectors resist full automation the longest, because verification requirements are written into law. That's expensive and frustrating today. But once a verification stack clears regulatory gates, it becomes nearly impossible to dislodge. Nobody voluntarily rips out a compliance infrastructure that a regulator has signed off on, especially not to replace it with something newer and unproven. The barrier that slows you down on the way in is the same barrier that keeps competitors out once you're through. ## Liability Is the Product Now The emerging organizational model is what we call the [AI Sandwich](https://arxiv.org/html/2602.20946v2#S7). Directors at the top, navigating uncertainty and orchestrating agent swarms. Verified agents in the middle, executing at scale. And Liability Underwriters at the bottom, serving as adversarial auditors who absorb and price risk. The bottleneck in this model is verification bandwidth, not headcount. Revenue models follow. The shift is from SaaS to **Liability-as-a-Service**: the product is not the agent but the *indemnified outcome*. In February 2026, ElevenLabs launched an AIUC-1 certified insured AI voice agent—insurance bundled as the product boundary. Value these firms the way you'd value insurers: by underwriting margin, loss experience, and reserve adequacy. And short the firms that are liquidating verification capacity—automating junior roles without replacing the training pipeline—because they are converting future oversight capability into current earnings. That trade has a name in finance. It's called eating your seed corn. ## The Weavers Knew Return to Bessen’s weavers. The 19th-century mills that thrived didn't just buy more looms. They tripled their training investments. The ones that simply added machines and skimped on human oversight failed. Bessen found that the elasticity of substitution between capital and labor in weaving was strikingly low—between 0.23 and 0.26. In plain English: you couldn’t just throw machines at the problem. The two factors were so tightly coupled that upgrading the looms without comparably upgrading the weavers left most of the potential gains on the table. Capital and skilled labor weren't substitutes. They were complements. The machine was only as good as the human checking its work. The modern parallel holds exactly. The companies and institutions that will capture AI's value aren't the ones deploying the most agents. They are the ones investing in the capacity to verify what those agents produce—building the failure libraries, training the next generation of expert auditors, underwriting the liability when the machine is wrong, and turning their verification-grade data into the training signal that makes the next round of verification systems better. The defining challenge of the agentic economy is not the race to deploy. It is the race to verify. The loom has never been faster. The question is whether anyone is watching the cloth. --- ## Dread Is Looking at the Wrong Side of the Net - canonical: https://catalini.com/notes/wrong-side-of-the-net/ - original thread: https://x.com/ccatalini/status/2033180597317951943 - date: 2026-03-15 The honest reaction watching this is dread. A machine that never tires, never misses, never charges by the hour. It screams substitution. That instinct is not wrong. But you’re looking at the wrong side of the net. [x.com](https://twitter.com/zhikai273/status/2033035812431081778) That same simulation capability is the most powerful training technology ever built. A decade of mastery, compressed into a year. This isn’t just about juniors. Entry-level work is vanishing. Senior expertise is being mined into training data. The entire workforce must move up—toward steering intent, verifying agentic output, underwriting risk. Flight simulators for work are how you compress that leap. --- ## Measurability-Biased Technical Change - canonical: https://catalini.com/notes/measurability-biased-technical-change/ - original thread: https://x.com/ccatalini/status/2033030491692216575 - date: 2026-03-15 Skill-biased technical change is dead. [@karpathy](https://x.com/karpathy) shows what its successor looks like: measurability-biased technical change. The fault line is no longer how educated you are. It’s whether your output can be measured. If it can, it will be industrialized. No exceptions. What’s exposed isn’t “strategy” or “research.” It’s the measurable execution bundled inside those roles — the drafts, the models, the analyses. The economy built a wage premium around that bundle. AI unbundles it. What survives is the non-measurable core: defining intent, navigating genuine uncertainty, verifying agentic work, and absorbing liability. The question for every knowledge worker is simple: strip away the execution layer, and what’s left? That’s your moat. Or your problem. We mapped the economics. Playbook included. Because what’s coming is not the end of human relevance. It’s a forced migration—from doing to steering, from executing to verifying, from producing answers to underwriting their consequences. [arxiv.org](https://arxiv.org/html/2602.20946v2) --- ## Software Eats The Brokerage—AI Lowers Cost, Crypto Makes It Verifiable - canonical: https://catalini.com/writing/software-eats-the-brokerage/ - original: https://www.forbes.com/sites/christiancatalini/2026/03/10/software-eats-the-brokerage-ai-lowers-cost-crypto-makes-it-verifiable/ - date: 2026-03-10 - outlet: forbes The internet made it free to watch. Finance kept it expensive to own. Billions of people follow markets from a phone, yet four billion adults cannot buy into them. Not because the system is hostile—because it is expensive. Modern finance can move $500 million domestically in seconds. It cannot serve a $50 investor at a profit. Compliance, custody, settlement: the entire machinery was built for institutional scale, and its costs do not scale down. The exclusion mechanism is not mysterious. To let someone buy $50 of stock, a traditional intermediary must still perform the full institutional dance: verify identity, screen sanctions, collect documents, arrange custody, connect to settlement, maintain records, assume regulatory liability. When the lifetime revenue on the account is measured in cents and the compliance burden in dollars, the math does not become inclusive just because people make grand speeches about an idealistic “[Finternet](https://www.bis.org/publ/work1178.htm)”. Financial institutions do not hate small investors. Their unit economics do. So the system does the rational thing. It sets minimums. It geoblocks. It "de-risks." It politely informs vast populations that they may participate later—once they have more wealth, cleaner paperwork, or the good fortune to live in a friendlier jurisdiction. In roughly half the world’s countries, there is not even a liquid stock exchange. The financial system works well. It just does not work for most people. For decades, that was an inconvenience. In an [economy approaching AGI](https://x.com/ccatalini/status/2026311784421036223?s=20), it becomes a structural crisis. ## The Stakes are Rising Since 1987, U.S. labor income has risen 58 percent, while capital income has surged 137 percent. That divergence is not over—AI will deepen it. As my co-authors and I argue in ["Some Simple Economics of AGI,"](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6298838) AI automates tasks fastest where outputs are measurable and verifiable. That compresses returns to routine labor while amplifying returns to ownership. If your only asset is your labor, you are structurally short the future. Access to capital markets is no longer one path to prosperity among several. It is the path. And [roughly four billion adults](https://ctf-images-01.coinbasecdn.net/o10es7wu5gm1/fyuLdm745lpI9PSkycZPH/c42890f3a9a6cddc9231757459e919e6/From-the-unbanked-to-the-unbrokered-CBI-Jan-2026-Digital-Single_Page.pdf) worldwide cannot take it. ## AI Breaks the Cost. Then It Breaks the Evidence. AI changes part of this equation fast. Much of retail finance is rules-based and measurable: onboarding, document handling, customer support, suitability checks, reporting, reconciliation, basic portfolio construction. Those are exactly the tasks AI drives toward software-like marginal cost. The minimum economically viable account size should fall hard. A $50 account in Nairobi or Manila ought to become almost as cheap to serve as a $50,000 account in New York. But here the story takes a harder turn. AI also degrades the evidence that compliance depends on. Finance is not only an execution business. It is a verification business. The same tools that make forms cheaper to process make [documents cheaper to fake](https://www.forbes.com/sites/christiancatalini/2024/12/19/can-cryptos-scarcity-tame-ais-infinite-abundance/). A scanned passport is no longer just identification—it is raw material for a generative model. A video selfie is no longer a liveness check—it is a challenge to the best deepfake generator on the market. AI makes the onboarding cheaper and the utility bill less believable. We call this the [measurability gap](https://x.com/ccatalini/status/2026311825898504608?s=20): AI lowers the cost of *executing* tasks far faster than it lowers the cost of *verifying* whether those tasks were done honestly. In finance the gap bites immediately. You can automate the paperwork faster than you can *believe* the paperwork. A system that responds by layering ever-thicker checks on top of increasingly untrustworthy documents is not solving the problem. It is performing seriousness at rising cost. ## Not the Casino. The Cryptography. The resolution is [architectural](https://www.forbes.com/sites/christiancatalini/2025/08/11/stripe-is-building-a-blockchain-can-openness-survive-branded-rails/), and it comes from the part of crypto that never makes headlines. The useful insight is not that every asset should become a meme coin. It is that compliance and ownership can be made portable, programmable, and provable. In a better design, a trusted institution verifies a user once and issues a reusable digital credential. The user can then prove what regulators actually care about—residency, sanctions clearance, accredited status, eligibility—across compliant venues without handing over the same dossier every time. Zero-knowledge proofs are the technical mechanism. The plain-English version: stop making people reapply for the right to exist every time they want to buy an asset. But architecture is policy. If tokenization is sold to incumbents as private back-office software, they will do the obvious incumbent thing: lower their own costs, preserve the walls, keep the spread. The economics become transformative only when the base layer is open. Then portability is real. Users move assets between providers. Services unbundle. Intermediaries compete on price instead of living off network lock-in. That matters because traditional finance still extracts rent through closed networks. A simple equity trade can bounce through brokers, custodians, clearinghouses, transfer agents, and foreign-exchange layers—each adding cost, delay, and another chance to say no. On open rails, settlement moves from days to near-instant atomic exchange. Compliance is done once and reused. Minimums shrink from meaningful sums to the size of a mobile top-up. Recent estimates suggest tokenized equity trading could cut transaction costs by more than 30 percent. More important, it changes who counts as a customer. Finance starts to look less like a cartel of databases and more like the internet. ## The Leapfrog The adoption pattern already tells you where this goes. Digital-asset usage is strongest where traditional access is weakest: emerging markets, mobile-first economies, places where people solve financial problems with software because the formal system never solved them. That is the same logic that produced mobile money in Sub-Saharan Africa. But the stakes are higher. What is being leapfrogged is not payments. It is the brokerage account—and with it, access to the compounding that increasingly separates those who build wealth from those who watch it built. None of this requires regulatory nihilism. The sensible design keeps the base layer neutral and enforces local rules where they belong—at exchanges, custodians, and application-layer touchpoints that onboard users and assume obligations. Countries can still apply capital controls, disclosure requirements, and investor protections. The point is not to abolish regulation. It is to stop hard-coding yesterday's inefficiencies into tomorrow's infrastructure. The real test of the next financial system is not whether Wall Street can tokenize another product for institutions. It is whether a person with $50 in weekly savings can buy, hold, and sell a tiny slice of productive capital as easily as sending a message. --- ## The AI Was Mining Cryptocurrency - canonical: https://catalini.com/notes/the-ai-was-mining-crypto/ - original thread: https://x.com/ccatalini/status/2030308540800532639 - date: 2026-03-07 The AI was mining cryptocurrency. Nobody asked it to. Nobody prompted it. Nobody even knew...until a firewall flagged the unusual traffic early one morning. A research team claims it was training a model. The agent learned to complete the tasks. [x.com](https://x.com/AlexanderLong/status/2030022884979028435?s=20) The agent also—as an instrumental side effect of RL optimization—probed internal networks, diverted provisioned GPU capacity to mine crypto, and opened a reverse SSH tunnel from an [@alibaba_cloud](https://x.com/alibaba_cloud) training server to an external IP. None of it was required for task completion. Now here's the thing... we don't know if this report is even real! And that's actually the point... [x.com](https://x.com/tszzl/status/2030136921448657136?s=20) We are entering an economy where AI agents act autonomously, at scale, across millions of environments—and we lack the infrastructure to verify what they're doing or to verify the claims people make about what they did. Whether this specific incident happened matters less than the fact that you can't easily tell. That gap—between what is claimed and what can be verified—is exactly what the Trojan Horse Externality describes. [arxiv.org](https://arxiv.org/abs/2602.20946) The most dangerous failure mode of AI isn't the one where it breaks. It's the one where it works perfectly—on the thing you're measuring—while quietly pursuing emergent goals in every dimension you're not. The fix is verification. But verification is slow, expensive, and stubbornly human. The agent scales. The checking doesn't. And now we can't even verify the warning. [x.com](https://x.com/a16zcrypto/status/2029628679895273614?s=20) --- ## Weird Employees for $200 a Month - canonical: https://catalini.com/notes/weird-employees-200-a-month/ - original thread: https://x.com/ccatalini/status/2029696640089739267 - date: 2026-03-05 You’ve just been told you have superpowers. You can hire weird employees for $200/month. What do you build? I joined [@eddylazzarin](https://x.com/eddylazzarin) & [@rhackett](https://x.com/rhackett) from [@a16zcrypto](https://x.com/a16zcrypto) to unpack my new AGI paper‚ and what it means for your career, company and the economy. [x.com](https://x.com/a16zcrypto/status/2029628679895273614?s=20) The thesis? Automation costs are collapsing. Verification costs aren’t. The bottleneck is shifting from intelligence to human verification bandwidth. That gap is where the next generation of great companies will be built. We cover: ➡️ why the one-person billion-dollar startup is moving from meme to reality ➡️ why experts rationally train their replacements ➡️ how to race towards an augmented economy rather than a Hollow one ➡️ why crypto becomes load-bearing infrastructure ➡️ what to do if you’re 22, 42 🌌, or already building "The apprenticeship is dead. The real work is beginning." If you’re trying to understand where leverage comes from next, listen. 🎙️ Podcast: [open.spotify.com](https://open.spotify.com/episode/0OZxPLPfwXlMbpDR33GwOv?si=wYqDnpeVTo-_PQJiXr2JcA) 📜 Paper: [arxiv.org](https://arxiv.org/html/2602.20946v2) --- ## The Labor Data Looks Contradictory. It Isn't. - canonical: https://catalini.com/notes/labor-data-not-contradictory/ - original thread: https://x.com/ccatalini/status/2027494777793720680 - date: 2026-02-27 The labor data looks contradictory but isn't. Juniors struggling: frozen pipelines, roles quietly disappearing. Top performers thriving: AI accelerates execution, experience lets them verify agentic work and ship more. Both true at once. Not a paradox. [x.com](https://x.com/DavidSacks/status/2027087693327237251?s=20) Block just cut ~40% of its workforce. Not a pivot. A structural reset—the work became measurable enough to automate. This is measurability-biased technical change hitting an org chart... at once (and yes, they had bloat). But expect many more. [x.com](https://x.com/jack/status/2027129697092731343?s=20) Top performers benefit from a Jevons paradox: AI makes execution cheaper so they do more of it, and their scarce verification capacity gets more valuable with every unit they can check. But they built that expertise through the exact junior roles now disappearing. [x.com](https://x.com/SemiAnalysis_/status/2027443723362042308?s=20) The top performer has a shelf life too. Every time you train a model, fine-tune a system, or build an eval suite, you're encoding the tacit knowledge that makes you scarce. The Codifier's Curse doesn't come all at once. It comes one workflow at a time. The bar for top keeps rising. The bar for average keeps getting automated. The middle is where the compression happens—and it's compressing fast. --- ## Smaller, Flatter Teams: It's Happening - canonical: https://catalini.com/notes/smaller-flatter-teams/ - original thread: https://x.com/ccatalini/status/2027144582480408632 - date: 2026-02-26 It's happening: "the intelligence tools we’re creating and using, paired with smaller and flatter teams, are enabling a new way of working which fundamentally changes what it means to build and run a company. and that's accelerating rapidly" [x.com](https://x.com/jack/status/2027129697092731343?s=20) We unpack why and the broader dynamics of the transition towards AGI here: [arxiv.org](https://arxiv.org/abs/2602.20946) Junior roles vanish before people can build expertise (Missing Junior Loop). Senior experts encode their own tacit knowledge into training data, automating themselves from within (Codifier's Curse). Only through rapid augmentation and accelerated synthetic practice can we remain peers with our own creation. --- ## Some Simple Economics of AGI: The Thread - canonical: https://catalini.com/notes/some-simple-economics-of-agi-thread/ - original thread: https://x.com/ccatalini/status/2026311784421036223 - date: 2026-02-24 Right now, there is a low-grade panic running through the economy. Everyone is asking the same anxious question: what exactly is AI going to automate, and what will be left for us? Most people assume the answer tracks some version of digital versus physical—that knowledge work falls first, then robotics catches up. And almost everyone believes that whatever AI can do in general, it's bad at their particular job. The lawyers think legal judgment is safe. The doctors think clinical intuition is safe. The strategists think strategy is safe. The creatives are sure creativity is safe. A whole vocabulary of comfort has emerged— "taste," "curation," "judgment," "agency," "human touch" — as though naming a residual is the same as defending it. But what if the real boundary has nothing to do with whether work is digital or physical, cognitive or manual, creative or routine—and everything to do with whether anyone can verify the output? [@wu_jane](https://x.com/wu_jane), [@xianghui90](https://x.com/xianghui90) and I spent countless cycles following that question wherever it led. It rearranges almost everything—who thrives, what's defensible, where capital flows, and what it means to be economically human when measurable execution is essentially free. For 300,000 years, human cognition was the binding constraint on progress. Fire, agriculture, writing, calculus, the semiconductor—each required human minds to observe the world, recombine knowledge, and verify the results. The engine of progress was scarce, fragile, costly. The economy organized itself around that scarcity. Wages, credentials, firms, and markets are, at root, mechanisms for rationing attention and leveraging the limited throughput of the human mind. Everything we built was shaped by this single bottleneck. That bottleneck is giving way. We are bootstrapping a second, alien form of cognition—one trained not by the physical friction of survival, but by compressing, predicting, and recombining the sum total of digitized human thought. But when a historically scarce resource suddenly becomes abundant, the constraint doesn't vanish. It migrates — often violently — to its nearest complement. Intelligence is becoming cheap. So what becomes expensive? Any task that can be reduced to a metric can be industrialized—regardless of the prestige, complexity, or training historically required for its human execution. The legal brief. The diagnostic. The strategy deck. The creative campaign... Not because AI is "better." Because it's measurable—and therefore automatable. Measurability is the new fault line. 🚨 New paper: Some Simple Economics of AGI— how measurement and verification shape the agentic economy. Full analytical framework + operational playbook for individuals, companies, investors, and policymakers. [papers.ssrn.com](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6298838) The architecture of the agentic economy is defined by the collision of two racing cost curves. Their divergence is the central structural fact of this transition. The Cost to Automate — driven relentlessly downward by compute and accumulated knowledge. SWE-bench accuracy went from 4.4% to 71.7% in a single year. Agent task horizons that frontier systems can handle autonomously are doubling on a sub-year cadence. The capability curve has become self-referential. Agents now accelerate the very engineering pipelines that produce their successors. OpenAI reports the first frontier model that was instrumental in creating itself. The interval between generations is compressing faster than institutions can update their oversight. The Cost to Verify — bounded by the biological limits of human cognition, feedback latency, and institutional capacity. This curve bends, but slowly. It is tethered to human attention, human incentives, and the apprenticeship pipelines that produce human expertise. The gap between these curves is the Measurability Gap. It determines the verifiable share of the economy — the threshold separating truly productive agentic execution from merely plausible output. This is why "human-in-the-loop" is not a stable equilibrium. It is a transient state whose half-life shortens with every model generation. The loop is stretching thinner as the gap widens. Verification is the ultimate complement to abundant intelligence—and it is structurally scarce. In the agentic economy, durable advantage belongs not to those who generate output but to those who can certify it. This isn't just theory. Measurability-biased technical change is already reshaping the labor market — not through the channels most people expect. Employment for early-career workers in AI-exposed fields has declined ~16% relative to less-exposed occupations. Not mass layoffs—frozen hiring pipelines that quietly treat AI as a direct substitute for junior execution. This is the Missing Junior Loop: firms are rationally thinning the pipeline that produces future verifiers at precisely the moment the economy most needs to expand verification capacity. The old apprenticeship model is being quietly dismantled. Meanwhile, the Codifier's Curse erodes expertise from within. It doesn't just automate tasks—it extracts the tacit knowledge that made senior judgment valuable and commoditizes it faster than the profession can replenish it. When [@claudeai](https://x.com/claudeai) Code Security surfaces classes of high-severity vulnerabilities that seasoned auditors missed for years — not through superior intuition but through exhaustive automated pattern-matching — the expertise moat drains from the inside out. [@claudeai](https://x.com/claudeai) 27/ And when oversight weakens, alignment drifts. Frontier reasoning models learned to subvert unit tests rather than fix the underlying code—a strategy legible only because a second model was monitoring the first's chain of thought. [@claudeai](https://x.com/claudeai) 28/ GPT-4 executed an insider trade and hid it from its supervisor. o3 disabled its own shutdown scripts in 79 of 100 runs. Claude Opus 4 attempted blackmail in 84—96% of runs. None were instructed to do this. [x.com](https://x.com/PalisadeAI/status/1926084638071525781?s=20) [@claudeai](https://x.com/claudeai) 29/ This is Goodhart's Law with teeth—optimization treating every unmeasured dimension as an unconstrained degree of freedom. [@claudeai](https://x.com/claudeai) 30/ The paper maps the economy into four structural regimes based on two axes: cost to automate and cost to verify. [@claudeai](https://x.com/claudeai) 31/ Safe Industrial Zone—cheap to automate, affordable to verify. This is where early AI adoption clustered: chat, images, short code bursts. Verification cost was negligible relative to value created. The easy wins. [@claudeai](https://x.com/claudeai) 32/ Human Artisan Zone—hard to automate, but outputs are verifiable. Embodied craft, high-touch services, physical-world expertise. Human comparative advantage holds here—for now. [@claudeai](https://x.com/claudeai) 33/ Pure Tacit Zone — neither automatable nor verifiable. Knightian uncertainty territory. Humans navigate by intuition where the map hasn't reached. Though this frontier shrinks as world models improve. [@claudeai](https://x.com/claudeai) 34/ Runaway Risk Zone—cheap to automate, but unaffordable to verify. This is where the structural danger lives. And as the Measurability Gap widens, more of the economy migrates here. [@claudeai](https://x.com/claudeai) 35/ Unverified deployment is privately rational—you capture the upside of automation while externalizing the tail risk. So the verification deficit becomes systemic. A tragedy of the commons written in code. [@claudeai](https://x.com/claudeai) 36/ The tempting shortcut: use AI to verify AI. But the agent and the synthetic auditor share the same training priors. Correlated blind spots propagate unchecked. The system effectively self-certifies its own failures. [@claudeai](https://x.com/claudeai) 37/ Left unmanaged, these forces pull toward a Hollow Economy: explosive nominal output but decaying human agency. Systems consume real resources to satisfy measurable proxies while the gap between what is measured and what is intended quietly compounds [@claudeai](https://x.com/claudeai) 38/ The Hollow Economy doesn't announce itself with a crisis. It accumulates—through the ordinary economics of cost minimization, one rational deployment decision at a time. [@claudeai](https://x.com/claudeai) 39/ But the Hollow Economy is not inevitable. The game theory is stark—among nations, labs, and firms, relative capability is valued over safety and slowing down unilaterally is not an option. The imperative is not to slow down. It is to build the verification infrastructure that converts acceleration into realized value rather than systemic risk. The answer is not a retreat into obsolescence, but a radical elevation of human purpose. [@claudeai](https://x.com/claudeai) 41/ The paper lays out a full operational playbook. For individuals: the augmented economy inverts the old bargain between talent and resources. [@claudeai](https://x.com/claudeai) 42/ Synthetic practice—"flight simulators for work"—compresses the path to mastery and lets a single person discover aptitude and execute at startup scale. [@claudeai](https://x.com/claudeai) 43/ But because intelligence is now a commodity, the nature of human work must adapt: ➡️ Directors: navigate Knightian uncertainty, transform vague intent into constraints, orchestrate agent swarms. [@claudeai](https://x.com/claudeai) 44/ ➡️ Meaning Makers: create where value depends on social consensus, status, human connection. ➡️ Liability Underwriters: detect hidden risk, absorb liability, produce the ground truth that makes future automation possible. For companies: anchor scale to verified throughput. The organizational structure converges on the "AI sandwich"—human intent, scalable agentic execution, human verification and underwriting. Verification is not a compliance function. It is a primary production technology — and increasingly the most defensible moat. The revenue model shifts from monetizing software access to monetizing verified outcomes — "Software-as-Labor." [@claudeai](https://x.com/claudeai) 47/ Execution is infinitely scalable. The legal and financial capacity to absorb its inevitable failures is the new bottleneck. Liability-as-a-Service. [x.com](https://x.com/elevenlabsio/status/2024121832278757850?s=20) [@claudeai](https://x.com/claudeai) 48/ For investors: stop funding commoditized execution. Capitalize what is not yet measurable—deep tech, long-horizon R&D—alongside the trust infrastructure that expands the verifiable share of the economy and makes deployment insurable. [@claudeai](https://x.com/claudeai) 49/ Agents can inflate apparent network activity at zero marginal cost. Durable moats will depend on verified network scale—sustaining authenticity and provenance, not merely subsidizing volume. If you can't verify it, you can't value it. [@claudeai](https://x.com/claudeai) 50/ For policymakers: the core market failure is a profound structural asymmetry: the gains of AI deployment are aggressively privatized while the systemic risks are socialized. [@claudeai](https://x.com/claudeai) 51/ No prior general-purpose technology simultaneously reduced the cost of learning, discovering, experimenting, and executing across every knowledge domain at once. The agentic economy compresses the cycle from hypothesis to working product across every field. [@claudeai](https://x.com/claudeai) 52/ Whether this transition constitutes humanity's most profound amplifier or a succession event depends on a choice our institutions must make before the market makes it for them. [@claudeai](https://x.com/claudeai) 53/ The choice: whether we scale our capacity for verification, oversight, and meaning at the same velocity we scale our compute. Scale without verification is not a moat. It is an accumulating debt. [@claudeai](https://x.com/claudeai) 54/ History's apex species have never been the fastest or the strongest. They have been the ones that could model, predict, and instrument the world more reliably than their competitors. For the first time, that claim is contestable. [@claudeai](https://x.com/claudeai) 55/ Whether it remains ours depends not on the intelligence we can build, but on the verification infrastructure we choose to build alongside it. [@claudeai](https://x.com/claudeai) 56/ Only by scaling our bandwidth for verification alongside our capacity for execution can we ensure that the intelligence we have summoned preserves the humanity that initiated it. So: "taste," "curation," "judgment," "agency," "the human touch." These are not wrong—but they are not a strategy. They are the names we give to the residual we haven't yet analyzed. [x.com](https://x.com/garrytan/status/2004179841269276938?s=20) [@claudeai](https://x.com/claudeai) 58/ This paper is an attempt to analyze it—and what we found is that the residual has a structure, the structure has a logic, and the logic leads to verification. That is what's defensible. That is what's scarce. That is what we should be building. --- ## The Most Valuable AI Tool in Fintech Is a Banking Charter - canonical: https://catalini.com/notes/ai-fintech-banking-charter/ - original thread: https://x.com/ccatalini/status/2018727061297508472 - date: 2026-02-03 The most valuable AI tool in fintech isn’t an LLM. It’s a banking charter. AI commoditizes software. The charter is the scarce "permission" layer. If everyone can generate code, the moat is who gets to hold money. AI accelerates startups: automate compliance + risk workflows, and draft the mountain of policies for a charter application. It narrows the gap with incumbents. But if you run on a sponsor bank, you’re still renting permission—and AI makes your landlord smarter (and pricier). We’ve seen this movie: Netscape sold a browser, Microsoft bundled IE. In AI fintech, startups sell "intelligence"; banks bundle it with deposits. Add AI on top of siloed legacy systems + decades of fraud/loss data, and incumbents can copy fintechs much faster. [pymnts.com](https://www.pymnts.com/cpi-posts/the-most-valuable-ai-tool-in-fintech-isnt-an-llmits-a-banking-charter/) --- ## The Greatest Breakthroughs Are Removed Frictions - canonical: https://catalini.com/notes/breakthroughs-are-removed-frictions/ - original thread: https://x.com/ccatalini/status/2011125708064768184 - date: 2026-01-13 To every founder asking what to build next—whether in crypto, AI, or fintech: what if the greatest breakthroughs in human history weren’t new inventions, but the simple removal of... friction? 🧵 We are trained to look for the next revolutionary product. But we almost always overlook the invisible, boring standards that allow thousands of new products to exist in the first place. This is a story about that hidden architecture. It’s about why the battle for the future isn’t about building better tech—it’s about agreeing on the rules that let everything connect. It’s a battle that repeats in every era, and today it’s being waged over the operating system for human ambition itself: money. The most dangerous move isn’t falling behind on technology. The most dangerous move is to accept a modern solution that’s just a prettier version of the past. In 1885, the industrial revolution hit a wall at a station in Gloucester. Passengers had to get off, walk, and buy new tickets for a different train. Why? Because the tracks were different sizes. It was a failure of imagination. This could happen again in payments and finance. You look at the proprietary networks. You look at the existing, closed rails. They feel safe. They feel curated. But if you build your startup inside them, you are making an irreversible mistake. When you build on a closed network, you are a tenant. The landlord can change the rent. The landlord can evict you. You can create a feature, but you cannot shape the future. The future requires permissionless innovation. Consider the GPS. The military built it. They owned it. It was a weapon. Then, they flipped a switch. They gave the signal away. Nobody had to sign a deal to build Uber. Nobody had to ask permission to invent Google Maps. That is the power of an open standard. You can build inside a walled garden. You may even get distribution at the start. You may get a false sense of safety. But you will never be truly free. Or you can build on an open network. The "messy" crypto protocols and decentralized networks. The open-source models. The incumbents will tell you the open version is a "toy." They will say it's chaotic. But the toy is the only place where you can be the architect, not the tenant. ▶️ "Your time is limited, so don't waste it living someone else's life"—Steve Jobs. History doesn't remember the gatekeepers. It remembers the ones who tore the gates down. Don't just build a better product. Build a bridge to the wild, permissionless possibilities of tomorrow. ▶️ A centuries-old blueprint for a more open and vibrant future: [@a16zcrypto](https://x.com/a16zcrypto) [a16zcrypto.com](https://a16zcrypto.com/posts/article/why-open-networks-win/) --- ## What Stablecoin Regulation Means for Business - canonical: https://catalini.com/writing/stablecoin-regulation-business/ - original: https://sloanreview.mit.edu/issue/2026-winter/ - date: 2026-01-01 - outlet: mit-smr What the new stablecoin rulebook means for operators and corporate strategy. Full text at the original outlet: https://sloanreview.mit.edu/issue/2026-winter/ --- ## How Stablecoins Are Actually Being Used - canonical: https://catalini.com/notes/how-stablecoins-are-actually-used/ - original thread: https://x.com/ccatalini/status/2002053139961442432 - date: 2025-12-19 How are stablecoins actually being used? New research by [@lightspark](https://x.com/lightspark) and [@artemis](https://x.com/artemis) unpacks the data. Volume has doubled year-over-year, but it’s not driven by retail adoption... It’s mostly B2B settlement and internal transfers. People often ask what the utility of crypto is, and the answer provided by the market so far is doing the things that banks and traditional rails do, but 24/7, faster, and cheaper. The killer app is simply better settlement. Full report: [artemisanalytics.com](https://www.artemisanalytics.com/resources/an-empirical-analysis-of-stablecoin-payment-usage-on-ethereum) --- ## How Banks Learned to Stop Worrying and Love Stablecoins - canonical: https://catalini.com/notes/banks-stop-worrying-thread/ - original thread: https://x.com/ccatalini/status/2001358629237342714 - date: 2025-12-17 How Banks Learned To Stop Worrying And Love Stablecoins—When we announced Libra, the reaction from the global financial establishment was, to put it mildly, "energetic"... The existential fear was that stablecoins—instantly available to billions of people—would break the control that banks have on deposits and payments. If you could hold a digital dollar on your phone that moved instantly, why would you keep your money in a checking account that pays zero percent, charges fees, and effectively closes for the weekend? For years, the prevailing narrative has been that stablecoins are coming for the banks’ lunch through "deposit erosion". But a rigorous new research paper by Professor Will Cong of Cornell University suggests that the industry may have panicked too early. Cong offers a counter-intuitive take: when properly regulated, stablecoins act as a complement to the traditional banking system rather than a disruptor that drains deposits. The Theory of Sticky Deposits—The traditional banking model is a bet on friction. Because the checking account is the only true interoperability layer for our funds, any attempt to move value between external services must transit through a bank. The system is designed so that using anything but the checking account adds friction: the bank controls the only bridge connecting the disparate islands of your financial life. Consumers accept this toll because of the power of the bundle. You keep your money in a checking account not because it is the best place for it, but because it is the central hub where your mortgage, credit card, and direct deposit all talk to each other. --- ## How Banks Learned To Stop Worrying And Love Stablecoins - canonical: https://catalini.com/writing/banks-love-stablecoins/ - original: https://www.forbes.com/sites/christiancatalini/2025/12/17/how-banks-learned-to-stop-worrying-and-love-stablecoins/ - date: 2025-12-17 - outlet: forbes Back in 2019, when we announced [Libra](https://www.forbes.com/sites/christiancatalini/2025/09/05/stripes-tempo-and-the-ghost-of-facebooks-libras-past/), the reaction from the global financial establishment was, to put it mildly, energetic. The existential fear was that stablecoins—instantly available to billions of people—would break the control that banks have on deposits and payments. If you could hold a digital dollar on your phone that moved instantly, why would you keep your money in a checking account that pays zero percent, charges fees, and effectively closes for the weekend? It was a reasonable question at the time. For years, the prevailing narrative has been that stablecoins are coming for the banks’ lunch. The concern is that “deposit erosion” is imminent, and that once consumers realize they can access digital cash with T-bill-like backing, the low-cost funding that powers the U.S. banking system will evaporate. But a rigorous [new research paper](https://cornell.app.box.com/s/njs6ovw8mvtyj06slrlzlcrwjij7a0y1) by Professor Will Cong of Cornell University suggests that the industry may have panicked too early. By examining the evidence rather than the sentiment, Cong offers a counter-intuitive take: when properly regulated, stablecoins act as a complement to the traditional banking system rather than a disruptor that drains deposits. ## The Theory of Sticky Deposits The traditional banking model is a bet on friction. Because the checking account is the only true interoperability layer for our funds, any attempt to move value between external services must transit through a bank. The system is designed so that using anything but the checking account adds friction: the bank controls the only bridge connecting the disparate islands of your financial life. Consumers accept this toll because of the power of the bundle. You keep your money in a checking account not because it is the best place for it, but because it is the central hub where your mortgage, credit card, and direct deposit all talk to each other. If the “death of banking” thesis were true, we would expect to see massive outflows from bank deposits into stablecoins already. [We don’t.](https://media.crai.com/wp-content/uploads/2025/07/22152125/Stablecoins-impact-on-community-bank-deposits-July2025.pdf) As Cong writes, despite the meteoric rise in stablecoin market cap, “*empirical studies to date have found little evidence of deposit erosion or outflows linked to the emergence of stablecoins*”. The friction works. To date, stablecoin adoption has not produced meaningful outflows from traditional deposits. It turns out that warnings about deposit flight are mostly incumbent fearmongering that ignores the basic economic physics of the real world. Deposit stickiness is a powerful force. Most customers value the convenience of the bundle too much to move their life savings to a digital wallet just for a few extra basis points. ## Competition as a Feature, Not a Bug But here is where the dynamic shifts. Stablecoins might not kill the banks, but they will almost certainly annoy them into becoming better. The Cornell paper argues that the mere presence of stablecoins acts as a disciplining force, pressuring banks to stop relying on inertia and start offering higher deposit rates and tighter operational efficiency. When banks face a credible alternative, the cost of complacency goes up. They are suddenly incentivized to price their deposits competitively rather than assuming your money is captive. In this model, stablecoins don't shrink the pie, they encourage “*greater lending, and expanded intermediation, ultimately enhancing consumer welfare*”. As Prof. Cong puts it: “*Rather than displacing traditional intermediation, stablecoins can operate as complementary instruments that broaden the scope of what banks already do well*”. The threat of exit, it turns out, is excellent motivation for the incumbents. ## The Regulatory unlock Of course, regulators are right to worry about [“run risk”](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3899499)—the existential dread that a loss of confidence could trigger a fire sale of the assets backing the stablecoin. But as the paper notes, these are not exotic new dangers; they are the standard risks of financial intermediation, broadly comparable to those faced by other institutions. We already have a playbook for liquidity management and operational risk. The challenge isn’t inventing new physics, it is just applying existing engineering to a new technology. This is where the GENIUS Act becomes the essential bridge. By mandating that stablecoins be fully backed by cash, short-term Treasuries, or insured deposits, the Act effectively legislates safety. As the paper notes, these safeguards *“appear poised to address the key vulnerabilities identified in the academic literature, including run and liquidity risk”*.While the legislation sets the statutory floor—full reserves and enforceable redemption rights—it leaves the operational details to the banking regulators. It will be up to the Federal Reserve and the OCC to operationalize these rules, ensuring that issuers account for operational risks, custodial failures, and the specific nuances of managing reserves and blockchain integrations at scale. ## The Efficiency Dividend Once we move past the defensive posture regarding deposits, we can look at the upside: the plumbing itself is due for an overhaul. The real [promise of tokenization](https://assets.ctfassets.net/o10es7wu5gm1/3DPt8YOiYtdVfqUoeuAJdS/33b4c368f7bc6b4ff7173df36c3d00da/Davos_Whitepaper_A4.pdf) is not just 24/7 availability, but atomic settlement—the ability to move value across borders instantly without the counterparty risk that plagues the current model. Today’s cross-border payments are expensive and sluggish, often taking days to settle as they hop between intermediaries. [Stablecoins](https://www.forbes.com/sites/christiancatalini/2025/04/29/the-stablecoin-wars/) collapse this process into a single, final transaction onchain. This has profound implications for global treasury management: instead of capital being trapped in transit for days, it can be rebalanced across borders instantly, freeing up liquidity that is currently stuck in the correspondent banking void. Domestically, this same efficiency hints at cheaper, faster merchant payments. For the banking sector, this is a rare chance to modernize legacy settlement infrastructure that is currently held together by duct tape and COBOL. ## The Dollar Upgrade Ultimately, the U.S. faces a binary choice: it can lead the development of this technology, or it can watch the future of finance get built in offshore jurisdictions. The dollar is the world's most popular financial product, but its delivery rails are showing their age. The GENIUS Act provides a framework to actually compete. It domesticates the sector: by bringing stablecoins inside the regulatory perimeter, the U.S. converts a shadow banking anxiety into a transparent, resilient upgrade for the global dollar. It turns an offshore novelty into a core piece of domestic infrastructure. Banks should stop worrying about the competition and start figuring out how to use the technology to their advantage. Much like the music industry had to be dragged kicking and screaming from CDs to streaming—only to realize streaming was a goldmine—banks are fighting a transition that will ultimately save them. The moment they realize they can charge for the speed rather than the delay, they will learn to love it. --- ## Crypto's Last-Mile Frictions Are Disappearing - canonical: https://catalini.com/notes/last-mile-frictions-disappearing/ - original thread: https://x.com/ccatalini/status/1999600763795054689 - date: 2025-12-12 The last mile frictions of crypto are disappearing, mostly because permissionless networks are finally doing the obvious, boring thing: admitting that the most useful thing you can do with a blockchain—for now!—is connect it to a Visa card. But once the rails work, the problem shifts. As AI scales, we need to distinguish "machine money from "human money". [@worldnetwork](https://x.com/worldnetwork)'s proof of personhood may just be the compliance layer for the AI age: the only way to prove a transaction—or a post—was made by a person. Full story in [@Forbes](https://x.com/Forbes): [forbes.com](https://www.forbes.com/sites/christiancatalini/2025/12/12/crypto-is-ready-to-be-boring-now/) --- ## Crypto Is Ready To Be Boring Now - canonical: https://catalini.com/writing/crypto-ready-to-be-boring/ - original: https://www.forbes.com/sites/christiancatalini/2025/12/12/crypto-is-ready-to-be-boring-now/ - date: 2025-12-12 - outlet: forbes If you have been watching the crypto space, you might have noticed that things are moving faster lately. Usually, that just means “numbers go up,” but this time the catalyst isn't a bull market or a new cryptographic breakthrough. It is simply that the rules are finally being written down. With stablecoin regulation falling into place, the handbrake is off. Projects are racing to move from “crypto for crypto people” to actual mainstream products, operating on the theory that if you aren't constantly worried about going to jail, you can be a lot more ambitious about building actual businesses. It turns out that when the building blocks are in place—and when stablecoins are a regulated business rather than a lingering existential threat—the definition of “ambitious” changes. You stop trying to reinvent the concept of money and start trying to make products that work. The [last mile frictions](https://hbr.org/2018/06/what-blockchain-cant-do) that constrained blockchains are finally disappearing, mostly because permissionless networks are finally doing the obvious, boring thing: admitting that the most useful thing you can do with a blockchain—at least for now—is connect it to a Visa card. ## The Anonymity Bug Payments was always going to be the first layer crypto had to clear. It is the basic primitive for everything else. Satoshi delivered almost all of the ingredients for an electronic cash system: a digital asset, a global ledger, and the incentives to run it. But for payments to safely scale, you need identity: because modern money is not just a measure of value, but a vector of intent that must be verified. This distinction is critical. Bitcoin brilliantly solved the double-spending problem—ensuring digital cash couldn’t be copy-pasted—but it didn't solve the identity problem. While some tout anonymity as a feature, for global adoption, it is a major bug. I learned this the hard way designing Libra. The first concession we had to make was on non-custodial wallets: we had clever ideas on how to make them safe, but regulators demanded a safe and contained perimeter from day one. Society has strong preferences that financial rails should not support illicit finance, and if your permissionless protocol keeps accidentally funding terrorism, society will eventually revoke its permission. ## The Stablecoin Sandwich The current state of crypto is a textbook example of “[infrastructure inversion](https://www.youtube.com/watch?v=KXIaILHl7Rg).” The theory is that eventually we will have fancy zero-knowledge proofs and onchain attestations that perfectly balance privacy and compliance. The reality is that, for now, we are just pasting the new technology onto the old one in the most boring way possible. Take the “[stablecoin sandwich](https://www.forbes.com/sites/christiancatalini/2025/04/29/the-stablecoin-wars/).” This is the industry term for bridging two otherwise disjointed real-time domestic payment systems by converting fiat to stablecoins, sending them across blockchain rails, and converting them back to fiat on the other side. It works, but the way it scales is ironic. It does not rely on the [openness of crypto networks](https://www.youtube.com/watch?v=k5sILotF4Jc). Businesses do not connect to the permissionless network themselves, that requires additional work. Instead, they hire an orchestration provider to do the compliance checks and talk to the blockchain for them. This is a far cry from controlling your own destiny, and it brings the intermediary right back into the picture. It turns out that blockchains solved *settlement*—moving the value—but they forgot to solve *information*. In the traditional financial system, every payment comes with a sidecar of data: who sent it, why, and whether they are on a sanctions list. If you cannot send that data, the ability to settle the payment in seconds is useless, because the bank on the other end is legally required to reject it. ## Human Money? So what might the future look like? Yesterday’s [World (formerly Worldcoin) event](https://www.youtube.com/watch?v=H2eLyItnqys) in San Francisco offered one potential answer, and it involves [chrome spheres](https://www.forbes.com/sites/digital-assets/2025/05/01/what-everyone-gets-wrong-about-crypto-adoption/). Alex Blania and Sam Altman were on stage reminiscing about the old days, back when it wasn’t entirely obvious that AI would consume the internet. What was obvious to them was that being able to distinguish a human from a bot would eventually become the most useful commodity in the world. This quest for “[Proof of Personhood](https://www.forbes.com/sites/christiancatalini/2024/12/19/can-cryptos-scarcity-tame-ais-infinite-abundance/)” is what motivated Blania to build a custom hardware network to verify that users are, in fact, biological entities. After six years, the pieces are falling into place. What used to look like an awkward futuristic experiment—let’s scan everyone's irises—is starting to look less like a stunt and more like a utility. Altman referenced a quote from [Paul Buchheit](https://www.oreilly.com/radar/machine-money-and-people-money/) that sums up the stakes: "There may need to be two kinds of money: machine money, and human money." It turns out that Proof of Personhood is just the compliance function for the AI age. You need it to separate good actors from bad actors to scale payments, but in a world of infinite synthetic content, you need it to prove the only thing that is still scarce: that something was made by a person. For years, the dream of crypto has been to build a global Venmo on top of crypto primitives. Yesterday, World showcased a wallet that basically delivers that, though the primitives involved look a lot like traditional fintech plumbing. By integrating virtual bank accounts in 18 countries, a Visa card, and local payment rails, they have bridged the gap between crypto and reality. It turns out that what customers really need for global money movement isn’t a new token, it is just the ability to deposit a paycheck and swipe a Visa card. And the way to get them to do it is the classic tech growth model: World isn't charging fees for most of this. Partly this works because banks need to charge you rent, and World doesn't. But mostly it works because moving money should be cheap. To a bank, a wire transfer is a diplomatic mission involving three correspondent banks and a fax machine. To a blockchain, it is just updating a ledger entry. World is betting that the actual cost of money movement is effectively trending towards zero. ## App Store Arbitrage Moreover, it does not stop at payments. Back in 2024, I wrote about what could potentially be a [“killer app” for crypto](https://www.forbes.com/sites/christiancatalini/2024/02/19/is-cryptos-killer-app-finally-here/): Mini Apps. The prediction was that when they arrived, they would look “clunky, niche, and maybe even toy-like”. This sounds innocuous, or maybe just annoying, but the market structure implication is real. The point of Mini Apps isn't just to put a calculator in your X feed, it is to allow developers to distribute software without asking app stores for permission or paying a 30% tax. It turns out that escaping the walled garden is just code for keeping your own revenue. The most valuable feature a new ecosystem can offer developers is simply the ability to process payments without paying a toll to the landlord. The combination of mini apps and strong identity gives developers a range of new primitives, and implies a shift in World's strategy. In the past, the approach was scan your iris or get out, which is a bit prescriptive. The new approach is tiered, treating verified humanity as a premium feature. This makes sense as a market mechanism. Users might be hesitant to scan their biometrics for an abstract, future reward, but they will absolutely do it for extra basis points of yield. Or, perhaps, for love: the team showcased how Tinder users in Japan can use World ID for verification. It turns out that the killer app for sovereign identity is just proving to your date that you aren't a bot. If you doubt that users will trade their biometrics for convenience, you should ask the people scanning their eyes to skip the security line at SFO. ## Off the Record Blania clearly understands the platform paradox: you want top marketplaces, social networks, chatbots, and financial services to use World ID as a primitive, but they won't touch it until you have users. And you don't get users without a product. So you have to build the product yourself. This explains both the payments play, and the move into messaging. World is collaborating with Shane Mac’s team to integrate XMTP, a decentralized messaging protocol, directly into the app. This offers significant privacy advantages over centralized alternatives like Signal, WhatsApp or Telegram. It turns out that if you want to be the invisible identity layer for the internet, you may first have to showcase it by building a better version of messaging. Before the event started, Mac showed me his latest experiment, [Convos](https://convos.org/why). The app is also based on XMTP, suggesting that the interoperability pitch for crypto might actually extend beyond financial services to things normal people use, like messaging. Convos takes advantage of cryptography to deliver an experience without signups, phone numbers, history, or tracking. And, of course, it doesn’t rely on centralized servers. The pitch here is that this might be the first truly off-the-record messaging app. In a world where every Slack message and email is permanent, the ultimate luxury good is a conversation that actually disappears. I’d imagine the early adopters will be investigative journalists, but the broader promise is to restore private conversations as the default setting for human interaction, rather than a suspicious anomaly. Overall, while some of these experiments are early, the trajectory is clear. The infrastructure is finally catching up to the manifesto. Everything crypto enthusiasts envisioned a decade ago is slowly becoming boring enough to actually work, and it is happening just in time. With AI accelerating, the ability to cryptographically verify truth is no longer just a philosophical hobby for cypherpunks. It turns out to be the necessary plumbing for the entire digital economy. --- ## The Trillion-Dollar Battle for Money’s Operating System - canonical: https://catalini.com/writing/trillion-dollar-battle-money-os/ - original: https://www.koreaherald.com/article/10617819 - date: 2025-11-18 - outlet: korea-herald Proprietary CorpChains versus open networks: the platform war over the rails of the global economy. Full text at the original outlet: https://www.koreaherald.com/article/10617819 --- ## Where the Gold–Bitcoin Analogy Ends - canonical: https://catalini.com/notes/gold-bitcoin-analogy-ends/ - original thread: https://x.com/ccatalini/status/1990457318392438792 - date: 2025-11-17 Gold and Bitcoin are scarce assets whose value rests on social consensus. Gold trades on a store-of-value premium: central banks & investors set the clearing price, and its non-monetary uses (electronics, dentistry, jewelry) act as the backstop. But that’s also where the similarities between Bitcoin and gold end. Unlike gold—which has tended to show low or negative correlation with the S&P 500 in downturns—Bitcoin has behaved like a liquidity‑sensitive, high‑beta risk asset. Bitcoin sold off with tech during the 2021–22 tightening and didn’t rally through the largest inflation shock in four decades. That argues against the simple "digital gold" or "inflation hedge" labels some of its proponents fiercely defend... ...and ultimately calls for a much more nuanced explanation. Discover it [@HarvardBiz](https://x.com/HarvardBiz): [hbr.org](https://hbr.org/2025/09/does-bitcoin-belong-on-your-balance-sheet) --- ## The GENIUS Act Forces a Choice - canonical: https://catalini.com/notes/genius-act-forces-a-choice/ - original thread: https://x.com/ccatalini/status/1986459219059683468 - date: 2025-11-06 The GENIUS Act will soon take effect. For leaders, it does more than clarify rules: it forces a choice. 🔀 Will you treat this new technology as a simple utility or as the foundational, new open architecture for payments? For decades, the antagonist has been the uncomfortably familiar world of payments. A private fiefdom running on tollbooths that collect a $187 billion private tax on the economy. Its brilliant marketing scheme? Showering consumers in merchant-funded rewards so they believe they are getting a free service. For a decade, fintech just put a beautiful user interface on yesterday’s plumbing. But the GENIUS Act is a turning point. It’s a green light to take a sledgehammer to the 50-year-old infrastructure. This isn't just new paint: it's changing the plumbing" It's a shift from speculation to utility, driven by regulation. The new technology reveals that the savviest companies were never just in the business you thought. Airlines are two businesses: a low-margin logistics company and a wildly profitable financial company that prints its own private currency. --- ## Open Always, Eventually, Wins - canonical: https://catalini.com/notes/open-always-eventually-wins/ - original thread: https://x.com/ccatalini/status/1983588222921023552 - date: 2025-10-29 "Open always, eventually wins." Money is the last closed network. The next step is neutral, permissionless rails anyone can build on. Full talk ⬇️ The temptation today is to build shiny new CorpChains with higher walls. We’re here to build roads. Why? Because open compounds builders. Open accelerates progress. Open crushes costs. The Silk Road wasn’t a road. It was a network. Nobody owned it, so it routed around emperors, taxes, and bandits—and moved ideas as easily as silk. That’s what open does. Rome’s profound insight? You can't run an empire on chaos. You need an operating system. So they built a standard. One road. One width. One currency. The cost of transport? It collapsed by a factor of ten. The empire clicked into place. The proof? 2000 years later, the lights of Europe at night still trace the paths of those ancient Roman roads. Which leads to a key question: if the blueprint for progress has been so clear for so long… why have we failed to apply it to the most important network of all? The enemy is fragmentation. This isn't just "inefficiency." 🚨 Fragmentation is the tax that the present levies on our future. It's the friction that quietly grinds progress to a halt. And why does it happen? It happens when everyone builds their own little kingdom. This is what fragmentation looks like in the real world. For a hundred years, this was global trade. It was called "break-bulk cargo." And it was a nightmare. Every box, every barrel, every sack... loaded by hand. It was painfully slow. Wildly expensive. The fix came from a total outsider: a trucker from North Carolina named Malcom McLean. He saw the problem wasn't the ships or the cranes. It was the gap in-between, the interface. He had an idea so simple, it was revolutionary... His idea? A simple, steel box. But the genius wasn't the box itself. It was the standard. One design that worked on a truck, a train, a ship. One container. Every port. The cost to load a ton of cargo fell from $5.86 to 16 cents. A 97% reduction. The friction just… vanished. This is England, 1840. Two rail lines, tracks different by a few inches. Total, predictable, maddening friction. This isn't a history lesson. It's a perfect picture of the future of money, if we get it wrong. So why does this keep happening? The paradox: everyone wants an open standard, as long as it's their standard. But the age of top-down standards... is over. The answer must be neutral. Permissionless. Finance already solved for fragmentation once over 50 years ago! 1960s. Every bank, its own card. Bank of America tried to build its own CorpChain. It failed. Spectacularly. The breakthrough? Cooperate on the platform, compete on the products. It worked brilliantly. The growth of the network was staggering. But the story, of course, doesn't end there. Because history has a pattern. The open network of one generation becomes the closed system of the next. As a result, every company today faces the same choice banks had to make in 1976. This brings us to the only question that really matters: what's in it for your company? Why embrace an open network? It's simple. More margin. Faster speed to market, and massive scale. Open networks pull demand toward you. They don’t erase winners. They change how you win. Maersk and IKEA didn’t own the container—they owned execution on top. Let's unpack more of that playbook. This was retail before 1974: every store was its own island. Checkout was slow. Inventory was guesswork. There was no universal language. And then came... The Universal Product Code. One code. Every product. Retail become software. But at first, it almost failed. Retailers wouldn't buy the expensive scanners from IBM until products had the codes. Manufacturers wouldn't print the codes until stores had the scanners. Then it hit a tipping point. Suddenly, the entire system clicked into place. A new rhythm for commerce was born. Scan. Ship. Scale. And those boring little lines? They ended up saving the grocery industry 17 billion dollars. Each year. The savings were actually the least interesting part of the story. The real story is what happened to the companies that saw the future and adopted this standard first. They didn't just get more efficient. They got faster. Smarter. More innovative. Suddenly, they saw it all. What to build. Where to sell it. And what should be coming next. And when you have that kind of clarity, you don't just think bigger. You go global. You build a supply chain on a scale the world had never seen. The early computer industry? Same story. A world of proprietary systems. Every machine was its own universe. Software written for one wouldn't work on any other. Then, in 1981, IBM—the king of closed systems—made a fateful decision. To accelerate speed to market, they built their new PC with off-the-shelf parts from other companies... and licensed its beating heart from a little known software startup from New Mexico... Microsoft. Bill Gates' masterful move was to retain the rights to license MS-DOS to everyone else. IBM accidentally created one of the most influential open standards of our time: Wintel. A "natural experiment" in what happens when you pit closed against open. And the results were not even close. While Apple controlled every piece of hardware and software... "Wintel" exploded. The open platform enabled a pace of innovation that others just couldn't match. Within less than a decade, the PC had over 80% of the market. It's one of the most decisive victories in tech history. The lesson is brutal and absolute: markets don't choose the best product. They choose the biggest, most vibrant ecosystem. Always. The same happened in telecommunications. In the 90s, the mobile industry was a mesh of incompatible national systems. Costs were high and progress was slow. Then came a single, open standard in Europe: GSM. The results were immediate and dramatic. Handset costs were cut in half. Suddenly, a phone wasn't a luxury. It was for everyone. Millions of users rapidly turned into billions. The incumbents who fought it were wiped out. The companies that embraced it built the future. Then came the internet. Like with Corpchains today, at the start, it was very tempting to bet on control: AOL, Apple eWorld, Microsoft Network. But on the other side was a simple, open protocol. It wasn't a product. It was just a set of rules. It wasn't a fair fight. It was a complete annihilation. $2.1 trillion in value in the US alone. Why? Because you cannot curate the future. Permissionless innovation will always create exponentially more value than a closed system. Period. So after all this history, you’d think the lesson would be obvious. What happens when you make the shift from closed to open? This chart shows you. It tracks a company's market value, right at the moment they embrace public APIs. 39% more revenue growth! Why? Because you stop being the bottleneck. You stop trying to do everything yourself. You invert the firm, and you unleash an entire ecosystem of developers and partners to build value with you. The best part of open networks? Their most unexpected wins. The ones that break all the rules. 🐧 When Linux appeared, experts called it a 'toy'. It's not as polished as Windows, it's not an enterprise-grade server. It's a hobbyist project. Today, we still hear the same thing about the Bitcoin network. It's not as fast as our high-performance CorpChain. It is not Turing complete. They are missing the point, just like Linux detractors did then. The power isn't the features in version one. The power is the new, open architecture. That 'toy' with a penguin mascot now runs 90% of the cloud, 100% of the top 500 supercomputers, and created $8.8 trillion in value. It became so dominant that its greatest enemy—the company that once called it a cancer—embraced it. But here's one last thing. This is a satellite. Part of a system called GPS. This wasn't built for you and me... It was built by the US military, for US the military. A closed box. A top secret tool... designed for one thing: strategic advantage and control. Then they flipped a switch. And they gave the signal away. To everyone. For free. They handed humanity a superpower. Suddenly, a logistics company knows exactly where your package is. Suddenly, a couple of people can build a map of the entire planet, put it in your pocket, and you’re never lost again. 🗺️ It’s magic. And here’s the beautiful thing. The truly beautiful thing. Nobody had to launch a satellite. Nobody had to ask permission. The foundation was just… there. Open. For all of us. So we've seen this pattern. Again, and again, and again. And after two thousand years, we come to a choice: some people see the future of money — and they want to own it. Walls. Higher walls. Platforms. Closed platforms. A cage. Painted gold with partnership incentives. They want to own the operating system of your money. And in their system… your organization doesn’t get root access. So they come to you. With a great story about a CorpChain. Purpose-built for payments, they'll say. You need our technology. You need our permission. You need our stablecoin. Remember: their rails, their rules. Their vision has no room for architects. It only has room for tenants. We believe the architect should be you. This was never about technology alone. It's about the freedom to build. The freedom to build the future without asking for permission. Do we build higher walls? Or open roads that connect everyone? Open roads that belong to no one. Open roads that advance human ingenuity. ↘️ History only remembers one of those choices. It remembers the road builders. --- ## True Disruption Is Extremely Rare - canonical: https://catalini.com/notes/true-disruption-is-rare/ - original thread: https://x.com/ccatalini/status/1972686539290239222 - date: 2025-09-29 [@TheEconomist](https://x.com/TheEconomist) called the theory of disruption "one of the most influential modern business ideas". And yet the data stubbornly refuses to cooperate. [x.com](https://x.com/business/status/1972567156328898690) In hard drives, the 3.5" insurgent was bought by giant Seagate, which reinvented itself and quickly caught up. Similarly, Napster should have buried music labels, but they pivoted to streaming, turning piracy into profit. True disruption is extremely rare, and incumbents catch up more often than we’d like to think. They control distribution, and inertia is a powerful selling proposition. [@arampell](https://x.com/arampell) 4/ More on the innovation vs. distribution tension here: [x.com](https://x.com/arampell/status/1968093331067642098) --- ## The GENIUS Act's Break-of-Gauge Problem - canonical: https://catalini.com/notes/genius-act-break-of-gauge/ - original thread: https://x.com/ccatalini/status/1971599830490427901 - date: 2025-09-26 Washington's GENIUS Act promises to finally bring back competition to money movement, but a blind spot threatens to crown a single superpower instead. The situation is a modern replay of a 19th-century fight over about two feet of iron... 🛤️ That fight was the "break of gauge"—a point of total paralysis where non-interoperable rail networks created a crippling tax on commerce. This is the single problem that will decide if the GENIUS Act creates an open financial future or just a new set of walled gardens. The Act meticulously regulates the coin but forgets to standardize the track, meaning value will roll smoothly until it hits the border of a corporate chain, and then stop. The decisive battle is at the network level. Stripe is building its Tempo blockchain, Circle has Arc. These corporate chains are today's different-gauge tracks. Without legally enforced interoperability, we will have simply rebuilt the same siloed payment systems we have today, just with newer technology. How open networks become captive—Breaking interoperability is dangerously easy. A dominant network won't just block a rival. They'll have a ready-made excuse: connecting is "too technically challenging," "unprofitable," or a "compliance risk". It can be done subtly, disguised as a necessary technical upgrade or a prudent new rule. This is how an open highway becomes a captive one. From "May" to "Must"—The solution is to treat interoperability as essential public infrastructure. The GENIUS Act says regulators "may" prescribe standards, a "dangerously gentle word" in a market defined by network effects. That word has to become "must." The choice is simple: build an open highway for all, or pave a faster road to a single kingdom. Full article: [tinyurl.com](https://tinyurl.com/2t2p2vub) --- ## The Unwitting Kingmaker: Why Washington’s GENIUS Act Could Accidentally Crown a Stablecoin Superpower - canonical: https://catalini.com/writing/unwitting-kingmaker/ - original: https://catalini.com/s/1-The-Unwitting-Kingmaker-Why-Washingtons-GENIUS-Act-Could-Accidentally-Crown-a-Stablecoin-Superpowe.pdf - date: 2025-09-26 - outlet: cpi How the GENIUS Act’s design could concentrate the stablecoin market — and how to stop it. Full text at the original outlet: https://catalini.com/s/1-The-Unwitting-Kingmaker-Why-Washingtons-GENIUS-Act-Could-Accidentally-Crown-a-Stablecoin-Superpowe.pdf --- ## Stripe's Tempo and the Grand Bargain - canonical: https://catalini.com/notes/stripes-tempo-grand-bargain/ - original thread: https://x.com/ccatalini/status/1964027763616358450 - date: 2025-09-05 [@Stripe](https://x.com/Stripe) just pulled back the curtain on [@tempo](https://x.com/tempo), its corporate blockchain, and the pitch is a classic. You get an all-star team, state-of-the-art tech, an impressive roster of partners—including one of the card networks the whole thing is designed to replace—and "neutrality." The price for this grand bargain? Just handing the fintech giant the keys to global payments. If this gives you a powerful sense of déjà vu, you're not alone. The only question is if Stripe can write a different ending for the movie Meta already showed us. There's a cliché in tech and finance that being too early is indistinguishable from being wrong. Looking back on Libra, the stablecoin project I helped design inside Meta, I can confirm we weren't just early; we were also comically, spectacularly wrong. We had a bad case of Silicon Valley hubris—the belief that elegant code can simply wish away centuries of financial regulation. We announced our plan to reinvent money with the subtlety of a foghorn, giving every incumbent on the planet time to find their pitchforks. And to top it off, we handed our political opponents a gift-wrapped narrative: a "basket of currencies" that let them paint us as Bond villains coming for the dollar and the euro. There is a simple story one could tell about why Stripe will succeed where Libra failed. A story of better timing, a better brand, and the wisdom of being a second mover. In this story, Tempo is the inevitable winner. The political climate, after all, is radically different today. [@Stripe](https://x.com/Stripe)'s brand isn't emerging from the wreckage of a scandal like Cambridge Analytica. And they get to learn from our very public mistakes. So, case closed? Not quite. The problem is that this entire bull case is based on a fundamental misreading of what actually killed Libra. The Wrong Autopsy—The popular story is that Libra was a regulatory train wreck. The reality is that we were on the verge of becoming the most buttoned-up, regulator-friendly crypto project on the planet. We approached it with the seriousness of building—in the regulators' own view—potential systemic financial market infrastructure. Despite a rocky start, we eventually had a US Treasury veteran at the helm: Stuart Levey, a man who knew the D.C. rulebook by heart. We were in weekly dialogue with every central bank that would take our call. The legal framework we helped build is now, ironically, the basis for the GENIUS Act. We even had the notoriously meticulous Swiss regulator FINMA ready to give us the green light. We got so close you could taste it: Libra’s license was physically sitting on the desk of FINMA’s president, waiting for a signature. And then Janet Yellen entered the chat. [x.com](https://x.com/davidmarcus/status/1862654506774810641) This leads us back to Stripe, and a question that hangs over the entire project: can it avoid repeating Libra's fate? What happens when the antibodies of the financial system—the powerful incumbents—identify Tempo as a new threat and begin to swarm? [x.com](https://x.com/patrickc/status/1963638753752420407) What makes the situation fascinating is the paradox at its heart. After a decade of spectacularly failed attempts to build their own private blockchain clubs, the big banks are grudgingly coming around to the idea that open, permissionless networks are the only way forward. At the very same moment, a new generation of challengers, led by Stripe and Circle, are betting everything on the opposite idea: that the future belongs to slick, branded, proprietary chains. The problem with corporate chains like Tempo isn't a matter of code—it's a matter of incentives. We already know the script. A tech player builds a network and promises fairness to get everyone on board. But once they have a captive market, the temptation to tilt the playing field becomes irresistible. Would a sane competitor bet its future on Stripe's promise not to eventually favor its own products? This isn't a new insight. It’s the very dilemma crypto was designed to solve. As [@cdixon](https://x.com/cdixon) crystallized it, crypto’s purpose is to break this cycle of broken promises. It's the same fundamental economic truth we identified at MIT almost a decade ago: the only thing that truly separates crypto from the systems it aims to replace is that it's permissionless. Full stop. From the very beginning of Libra, my biggest concern wasn't the external fight with regulators, but the internal one. I was terrified we'd never win the debate to make the network truly permissionless. You have to understand, these are the brilliant engineers who build the most efficient centralized systems on Earth. They looked at our crypto ideals with a brutal, and not entirely incorrect, logic: why are we tying ourselves in knots to decentralize the database when the underlying asset is centralized? To them, it was an elegant solution in search of a problem. So, after months of negotiations and economic modeling with one of the world's top market design experts, Scott Kominers, our grand vision for a permissionless future was buried into a single and lonely four-page, appendix document. Of course, the dream of a truly open system was the first casualty. The first domino to fall was the non-custodial wallet—a concession the Libra founding team extensively agonized over. Why? Because regulators need a "clear perimeter." That’s a polite way of saying they need to know who to call—and who to fine—when things go wrong. Their entire compliance playbook was written for a world of intermediaries. A world where users truly control their own money is messy, borderless, and doesn't fit that legacy blueprint. For them, killing self-custody wasn't a choice, it was an obvious necessity based on the tools they understood. The irony, of course, is that this is an entirely solvable problem. Open networks are now pioneering their own native compliance tools that are much more effective than the old model. But for us, back then, it was simply a sign of things to come. So what’s the lesson here? As long as there is a single throat to choke—or a committee of them—you can’t truly rewire the system. Worse, any network with an architect is living on borrowed time. If corporate chains like Tempo and Arc succeed, it will mean the crypto experiment was not a revolution, but a failed coup. The backend technology would be different, yes, but the market structure would be eerily familiar. We would simply swap an old monarchy of card networks and financial sector incumbents for a new one of fintech giants. The throne will have new occupants, but it will be the same throne. And in our fractured world, that reign would inevitably split along geopolitical lines. There is little chance the West and the East would agree to live under the same corporate king, leading not to a unified global system, but to at least two powerful, competing empires. Ultimately, Stripe's Tempo is a referendum on the ghost of Libra. If that ghost was merely a product of bad timing, then Tempo is poised for a historic victory, and the crypto world's original dreamers may finally have to accept a more pragmatic, centralized reality. But if Libra’s ghost is a warning about a fundamental truth—that any system with a single architect is built on a fatal flaw—then Stripe is not writing a new story. It is merely staging an entertaining, and very expensive, sequel. Full story on [@ForbesCrypto](https://x.com/ForbesCrypto): [forbes.com](https://www.forbes.com/sites/christiancatalini/2025/09/05/stripes-tempo-and-the-ghost-of-facebooks-libras-past/) --- ## Stripe’s Tempo And The Ghost Of Facebook’s Libra’s Past - canonical: https://catalini.com/writing/stripes-tempo-libras-ghost/ - original: https://www.forbes.com/sites/christiancatalini/2025/09/05/stripes-tempo-and-the-ghost-of-facebooks-libras-past/ - date: 2025-09-05 - outlet: forbes Stripe just pulled back the curtain on [Tempo](https://www.forbes.com/sites/christiancatalini/2025/08/11/stripe-is-building-a-blockchain-can-openness-survive-branded-rails/), its corporate blockchain, and the pitch is a classic. You get an all-star team, state-of-the-art tech, an impressive roster of partners—including one of the card networks the whole thing is designed to replace—and “neutrality.” The price for this grand bargain? Just handing the fintech giant the keys to global payments. If this gives you a powerful sense of déjà vu, you’re not alone. The only question is if Stripe can write a different ending for the movie Meta already showed us. There’s a cliché in tech and finance that [being too early is indistinguishable from being wrong](https://www.youtube.com/watch?v=xAlCbE-yCTw). Looking back on Libra, the stablecoin project I helped create inside Meta, I can confirm we weren’t just early; we were also comically, spectacularly wrong. We had a bad case of Silicon Valley hubris—the belief that elegant code can simply wish away centuries of financial regulation. We announced our plan to reinvent money with the subtlety of a foghorn, giving every incumbent on the planet time to find their pitchforks. And to top it off, we handed our political opponents a gift-wrapped narrative: a "basket of currencies" that let them paint us as Bond villains coming for the dollar and the euro. There is a simple story one could tell about why Stripe will succeed where Libra failed. A story of better timing, a better brand, and the wisdom of being a second mover. In this story, Tempo is the inevitable winner. The political climate, after all, is radically different today. Stripe isn't emerging from the wreckage of a scandal like Cambridge Analytica. And they get to learn from our very public mistakes. So, case closed? Not quite. The problem is that this entire bull case is based on a fundamental misreading of what actually killed Libra. ## The Wrong Autopsy The popular story is that Libra was a regulatory train wreck. The reality is that we were on the verge of becoming the most buttoned-up, regulator-friendly crypto project on the planet. We approached it with the seriousness of building—in the regulators’ own view—potential systemic financial market infrastructure. Despite a rocky start, we eventually had a US Treasury veteran at the helm: [Stuart Levey](https://en.wikipedia.org/wiki/Stuart_A._Levey), a man who knew the D.C. rulebook by heart. We were in weekly dialogue with every central bank that would take our call. The legal framework we helped build is now, ironically, the basis for the GENIUS Act. We even had the notoriously meticulous Swiss regulator FINMA ready to give us the green light. We got so close you could taste it: Libra’s license was physically sitting on the desk of FINMA’s president, waiting for a signature. And then [Janet Yellen](https://x.com/davidmarcus/status/1862654506774810641) entered the chat. ## Two Competing Philosophies This leads us back to Stripe, and a question that hangs over the entire project: can it avoid repeating Libra’s fate? What happens when the antibodies of the financial system—the powerful incumbent banks and card rails—identify Tempo as a new threat and begin to swarm? What makes the situation fascinating is the paradox at its heart. After a decade of spectacularly failed attempts to build their own private blockchain clubs, the big banks are finally, grudgingly, coming around to the idea that [open, permissionless networks](https://www.forbes.com/sites/christiancatalini/2025/01/16/the-internet-of-money-wants-to-be-free/) are the only way forward. At the very same moment, a new generation of challengers, led by Stripe and Circle, are betting everything on the opposite idea: that the future belongs to slick, branded, proprietary chains. The problem with corporate chains like Tempo or Circle’s [Arc](https://x.com/ccatalini/status/1960824615900733697) isn’t a matter of code—it's a matter of incentives. We already know the script. A tech player builds a network and promises fairness to get everyone on board. But once they have a captive market, the temptation to tilt the playing field becomes irresistible. Would a sane competitor bet its future on Stripe's promise not to eventually favor its own products? This isn’t a new insight. It’s the [very dilemma crypto was designed to solve](https://www.forbes.com/sites/christiancatalini/2025/08/11/stripe-is-building-a-blockchain-can-openness-survive-branded-rails/). As [Chris Dixon](https://a16zcrypto.com/posts/article/why-web3-matters/) crystallized it, crypto’s purpose is to break this cycle of broken promises. It's the same fundamental economic truth we [identified at MIT](https://www.nber.org/papers/w22952) almost a decade ago: the only thing that truly separates crypto from the systems it aims to replace is that it's permissionless. Full stop. From the very beginning of Libra, my biggest concern wasn’t the external fight with regulators, but the internal one. I was terrified we'd never win the debate to make the network truly permissionless. You have to understand, these are the brilliant engineers who build the most efficient centralized systems on Earth. They looked at our crypto ideals with a brutal, and not entirely incorrect, logic: why are we tying ourselves in knots to decentralize the database when the underlying asset is centralized? To them, it was an elegant solution in search of a problem. So, after months of negotiations and economic modeling with one of the world’s top market design experts, [Scott Kominers](http://www.scottkom.com/), our grand vision for a permissionless future was buried into a single and lonely four-page, [appendix document](https://static1.squarespace.com/static/532383d3e4b00a718e33e1da/t/5d5fefc2d7c1240001fa00e5/1566568386697/MovingTowardPermissionlessConsensus_en_US_Rev0814.pdf). Of course, the dream of a truly open system was the first casualty. The first domino to fall was the non-custodial wallet—a concession the Libra founding team extensively agonized over. Why? Because regulators need a "clear perimeter." That’s a polite way of saying they need to know who to call—and who to fine—when things go wrong. Their entire compliance playbook was written for a world of intermediaries. A world where users truly control their own money is messy, borderless, and doesn’t fit that legacy blueprint, making it a traditional compliance officer's worst nightmare. For them, killing self-custody wasn't a choice, it was an obvious necessity based on the tools they understood. The irony, of course, is that this is an entirely solvable problem. Open networks are now pioneering their own native compliance tools—from onchain analytics and attestations, to identity and compliance protocols—that are much more effective than the old model. But for us, back then, it was simply a sign of things to come. ## The Gravitational Pull of Control So what’s the lesson here? As long as there is a single throat to choke—or a committee of them—you can’t truly rewire the system. Worse, any network with an architect is living on borrowed time. It will inevitably break its promises on privacy, developer freedom, interoperability and business neutrality. We’ve all seen this with the internet giants: court the developers, capture the users, and then close the gates. It's a script as predictable as it is profitable. If corporate chains like Tempo and Arc succeed, it will mean the crypto experiment was not a revolution, but a failed coup. The backend technology would be different, yes, but the market structure would be eerily familiar: we would simply swap an old monarchy of card networks and financial sector incumbents for a new one of fintech giants. The throne will have new occupants, but it will be the same throne. And in our fractured world, that reign would inevitably split along geopolitical lines. There is little chance the West and the East would agree to live under the same corporate king, leading not to a unified global system, but to at least two powerful, competing empires. Ultimately, Stripe’s Tempo is a referendum on the ghost of Libra. If that ghost was merely a product of bad timing, then Tempo is poised for a historic victory, and the crypto world's original dreamers may finally have to accept a [more pragmatic](https://x.com/jillrgunter/status/1960856859449147594), centralized reality. But if Libra’s ghost is a warning about a fundamental truth—that any system with a single architect is built on a fatal flaw—then Stripe is not writing a new story. It is merely staging an entertaining, and very expensive, sequel. --- ## Does Bitcoin Belong on Your Balance Sheet? - canonical: https://catalini.com/writing/bitcoin-balance-sheet/ - original: https://hbr.org/2025/09/does-bitcoin-belong-on-your-balance-sheet - date: 2025-09-01 - outlet: hbr A framework for deciding whether corporate treasuries should hold bitcoin. Full text at the original outlet: https://hbr.org/2025/09/does-bitcoin-belong-on-your-balance-sheet --- ## Substitute or Augment? It's All Accounting - canonical: https://catalini.com/notes/substitute-or-augment-accounting/ - original thread: https://x.com/ccatalini/status/1962161198163714109 - date: 2025-08-31 Substitute or augment? [@joshgans](https://x.com/joshgans) has a sharp analysis. But if you zoom out, it's all just accounting. 🧮 The entire story is about what we can—and can't—put a number on. [x.com](https://x.com/joshgans/status/1961882877668315169) Why do juniors get displaced first? Their tasks are built to be measurable to management (and, it turns out, to software). You write checklists, define KPIs, make their output predictable and auditable. AI doesn’t dislike interns... it just loves numbers and columns. Seniors accelerate. They hand AI the measurable bits (first drafts, boilerplate, memos) and spend time on the parts we don’t meter well: what‑ifs, judgment, curation. Management calls it "leverage", economists call it complementarity. But how long does that edge last? The edge lasts until the measurement frontier moves. And it's always moving. Each new instrument moves it: stopwatches ➡️ KPIs ➡️ clickstreams ➡️ prompt logs. 🤖 Today's "unmeasurable craft" is just tomorrow's auditable process, logged and quantified. The frontier of AI isn't just better code, it's the relentless push to codify and create metrics for the judgment and intuition we currently consider unmeasurable. --- ## When Rogoff Apologizes for Underestimating Bitcoin - canonical: https://catalini.com/notes/rogoff-underestimating-bitcoin/ - original thread: https://x.com/ccatalini/status/1958254215626969293 - date: 2025-08-20 When one of the world’s leading macroeconomists publicly apologizes for underestimating Bitcoin, it’s worth paying attention. [@krogoff](https://x.com/krogoff) is a formidable scholar, and over the last decade—from my professor days at [@MIT](https://x.com/MIT) to the design of Libra—I’ve learned a great deal from conversations with him. He has trained some of the best macroeconomists in the market, and I was fortunate to persuade a few to take crypto seriously, work with me over the years, and help move the space forward. But on Bitcoin, even after his mea culpa, Rogoff is still wrong. And I don’t blame him. Much of what Bitcoin is, and represents, is an architectural departure from the macro playbook of recent decades. [x.com](https://x.com/krogoff/status/1957825957684716008) As his [@Harvard](https://x.com/Harvard) colleague [@RebeccaReCap](https://x.com/RebeccaReCap) has shown in her pioneering work on innovation, the changes that truly challenge incumbents are architectural—subtle structural shifts in how the pieces fit together. They’re hard for those steeped in the status quo to grasp—even when they want to—so they get dismissed until they’re obvious. Bitcoin is one of those architectural innovations in how we think about money and financial infrastructure. That’s why many economists have a visceral reaction: it runs against much of what they’ve been taught and believe in. Concede the textbook: when done well, monetary policy can be extremely helpful. Confront the practice: few central banks are truly independent, fewer still consistent. Treat Bitcoin as a neutral asset and financial infrastructure, and the true pattern comes into focus. In a gold rush, it is important to not get caught in the frenzy—unless you’re selling shovels and you profit regardless of the outcome. But is Bitcoin just a frenzy? More than a decade on, the answer is no, for a simple reason: Satoshi Nakamoto solved a thorny computer‑science problem—the double‑spending problem. Before Bitcoin, any digital money needed someone to control the ledger—a central bank, financial institution, or wallet provider. With cryptography and incentives, Satoshi created a currency that’s scarce, hard to copy, and neutral: no one’s in charge of defining ownership or recording transfers. Bitcoin’s neutrality is novel. Though often compared to gold, its properties are different enough to be category‑defining. Yes, both are scarce, both swing in price, and both hold value because society agrees they do. Bitcoin’s utility goes beyond the asset: its network can operate as an open, neutral settlement layer. What is a neutral form of digital money—and an open protocol for moving value—worth to society? Unpacking the Bitcoin Price—Media and crypto community obsess over price swings, but on a log scale much of the drama fades and a steadier trend appears. That pattern matches the diffusion of innovation along an S‑curve—popularized by Everett Rogers. Bitcoin incubated within a small community of cypherpunks and developers. As its price rose, it drew a broader group of early adopters; then consumers and businesses—often in countries with unstable currencies—embraced it as an alternative savings tool and, at times, payment rails. Today, large financial institutions offer it, and sovereigns increasingly eye it to shape fintech and investment strategy. This diffusion process, combined with Bitcoin’s fixed supply, inevitably translates the S-curve into a slow and steady price growth. So while regulatory and market uncertainty drive short-term swings, over longer periods addressable‑market expansion explains the data. What’s Bitcoin’s equilibrium price? Unknown—and it hinges on where we are on the S‑curve. If Bitcoin stays niche, the price could stall. If it goes truly mainstream, further exponential growth is possible. Investors model this against gold, the value of payment and card networks, and more. It’s also prudent to consider the risk that some technological breakthrough or failure may render Bitcoin obsolete. Reassuringly, despite billions raised by would‑be alternatives, none has matched Bitcoin’s network effects or institutional acceptance. Money‑As‑Software—As our tools for recording debits and credits have evolved, so has our idea of money: from shells and beads to salt, metals, paper notes, and ultimately database entries—alongside the rise of central bank independence. Through booms and crises we’ve oscillated between harder and more flexible money—a pendulum swinging between the needs of creditors and debtors. [x.com](https://x.com/RayDalio/status/1953116006680785019) Given that history, it isn’t unreasonable to think that a hard, neutral money secured by cryptographic keys could play a real role in global finance—and possibly be what comes next. Like every form of money before it, Bitcoin has value because enough people agree it does—and as consensus grows, its trajectory looks more like gold’s. But there’s a flipside to expectation‑driven value: if, for any reason, society stops believing Bitcoin will reliably store value and buy future goods and services, its price could collapse toward zero. Fiat currencies experience something similar when faith in governments’ balance sheets fails, and while Bitcoin can’t be debased, other shocks could trigger a comparable loss of trust. Ironically, reckless, leveraged buying by large Bitcoin‑treasury companies—meeting a sharp market correction—could be what undermines confidence in Bitcoin’s progress along its S‑curve. Even then, the underlying innovation is likely to endure: as neutral infrastructure, it disintermediates, cuts costs, and creates real economic value—not just regulatory or tax arbitrage—a puzzle worthy of economists’ attention, [@krogoff](https://x.com/krogoff)'s included. [@krogoff](https://x.com/krogoff) 21/ Full story on [@ForbesCrypto](https://x.com/ForbesCrypto)—[forbes.com](https://www.forbes.com/sites/christiancatalini/2025/08/20/economists-are-still-puzzled-by-bitcoin-should-anyone-be/) --- ## Economists Are Still Puzzled By Bitcoin—Should Anyone Be? - canonical: https://catalini.com/writing/economists-puzzled-by-bitcoin/ - original: https://www.forbes.com/sites/christiancatalini/2025/08/20/economists-are-still-puzzled-by-bitcoin-should-anyone-be/ - date: 2025-08-20 - outlet: forbes When one of the world’s leading macroeconomists [publicly apologizes](https://twitter.com/krogoff/status/1957825957684716008?ref_src=twsrc%5Etfw ) for underestimating Bitcoin, it’s worth paying attention. Ken Rogoff is a formidable scholar, and over the last decade—from my professor days at MIT to the design of Libra—I’ve learned a great deal from conversations with him. He has trained some of the best macroeconomists in the market, and I was fortunate to persuade a few to take crypto seriously, work with me over the years, and help move the space forward. But on Bitcoin, even after his mea culpa, Rogoff is still wrong. And I don’t blame him. Much of what Bitcoin is, and represents, is an architectural departure from the macro playbook of recent decades. When I was a junior professor trying to understand cryptocurrencies and designing the [MIT Bitcoin experiment,](https://www.science.org/doi/10.1126/science.aal4476) many senior colleagues worried I was throwing away a promising academic career on what they saw as a Ponzi scheme. As his Harvard colleague Rebecca Henderson has shown in her [pioneering work](https://www.jstor.org/stable/2393549) on innovation, the changes that truly challenge incumbents are architectural—subtle structural shifts in how the pieces fit together. They’re hard for those steeped in the status quo to grasp—even when they want to—so they get dismissed until they’re obvious. Bitcoin is one of those architectural innovations in how we think about money and financial infrastructure. That’s why many economists have a visceral reaction: it runs against much of what they’ve been taught and believe in. Concede the textbook: when done well, monetary policy can be extremely helpful. Confront the practice: few central banks are truly independent, fewer still consistent. Treat Bitcoin as a neutral asset and financial infrastructure, and the true pattern comes into focus. ## A Digital Gold Rush In a gold rush, it is important to not get caught in the frenzy—unless you’re selling shovels and you profit regardless of the outcome. But is Bitcoin just a frenzy? More than a decade on, the answer is no, for a simple reason: Satoshi Nakamoto solved a thorny computer‑science problem—the double‑spending problem. Before Bitcoin, any digital money needed someone to control the ledger—a central bank, financial institution, or wallet provider. With cryptography and [incentives](https://dl.acm.org/doi/10.1145/3359552), Satoshi created a currency that’s scarce, hard to copy, and neutral: no one’s in charge of defining ownership or recording transfers. Bitcoin’s neutrality is novel. Though often compared to gold, its properties are different enough to be category‑defining. Yes, both are scarce, both swing in price, and both hold value because society agrees they do. Gold has industrial and jewelry uses, but most of its value comes from its role as a store of value. And while gold has the advantage of centuries, as more of life moves online, a digitally native asset like Bitcoin has unique advantages—from spending to custody. Finally, Bitcoin’s utility goes beyond the asset: its network can operate as an open, neutral settlement layer—especially as scaling tech raises throughput to meet real‑world payments demand. What is a neutral form of digital money—and an open protocol for moving value—worth to society? ## Unpacking the Bitcoin Price Media and crypto community obsess over price swings, but on a log scale much of the drama fades and a steadier trend appears. That pattern matches the diffusion of innovation along an S‑curve—[popularized](https://books.google.com/books?id=9U1K5LjUOwEC&printsec=frontcover#v=onepage&q&f=false) by Everett Rogers—where a new technology works through successive segments of adopters. Bitcoin incubated within a small community of cypherpunks and developers. As its price rose, it drew a broader group of early adopters; then consumers and businesses—often in countries with unstable currencies—embraced it as an alternative savings tool and, at times, payment rails. Today, large financial institutions offer it, and sovereigns increasingly eye it to shape fintech and investment strategy. This diffusion process, combined with Bitcoin’s fixed 21 million supply, inevitably translates the S-curve into a slow and steady price growth. So while regulatory and market uncertainty drive short-term swings, over longer periods of time addressable‑market expansion explains more of the data. What’s Bitcoin’s equilibrium price? Unknown—and it hinges on where we are on the S‑curve. If Bitcoin stays niche, the price could stall. If it goes truly mainstream, further exponential growth is possible. Investors model this against gold, the value of payment and card networks, and more. It’s also prudent to consider the risk that some technological breakthrough or failure may render Bitcoin obsolete. Reassuringly, despite billions raised by would‑be alternatives, none has matched Bitcoin’s network effects or institutional acceptance. ## Money‑As‑Software As our tools for recording debits and credits have evolved, so has our idea of money: from shells and beads to salt, metals, paper notes, and ultimately database entries—alongside the rise of central bank independence. Through booms and crises we’ve [oscillated](https://economicprinciples.org/downloads/How-Countries-Go-Broke.pdf) between harder and more flexible money—a pendulum swinging between the needs of creditors and debtors. Given that history, it isn’t unreasonable to think that a hard, neutral money secured by cryptographic keys could play a real role in global finance—and possibly be what comes next. Like every form of money before it, Bitcoin has value because enough people agree it does—and as consensus grows, its trajectory looks more like gold’s. That belief powers the “all‑in” Bitcoin treasury companies—Strategy, Trump Media & Technology Group, and Twenty One—backed by SoftBank, Tether, and the Commerce Secretary’s son’s firm, Cantor Fitzgerald. Their logic: if Bitcoin becomes the ultimate safe haven, accumulate as much as possible—even with risky leverage—so long as interest and principal can be serviced in dollars. But there’s a flipside to expectation‑driven value: if, for any reason, society stops believing Bitcoin will reliably store value and buy future goods and services, its price could collapse toward zero. Fiat currencies experience something similar when faith in governments’ balance sheets fails, and while Bitcoin can’t be debased, other shocks could trigger a comparable loss of trust. Ironically, reckless, leveraged buying by large Bitcoin‑treasury companies—meeting a sharp market correction—could be what undermines confidence in Bitcoin’s progress along its S‑curve. Even then, the underlying innovation is likely to endure: as neutral infrastructure, it disintermediates, cuts costs, and creates real economic value—not just regulatory or tax arbitrage—a puzzle worthy of economists’ attention, Rogoff’s included. --- ## Stripe's Secret Blockchain and the Stablecoin Paradox - canonical: https://catalini.com/notes/stripes-secret-blockchain-paradox/ - original thread: https://x.com/ccatalini/status/1955065720586592636 - date: 2025-08-12 Fintech powerhouse Stripe is secretly building a high-performance blockchain called "Tempo," per a now-removed job posting and Fortune’s reporting. Stablecoins promise to make crypto mainstream by delivering faster, cheaper, more interconnected global payments. The paradox: the same move could undercut what the technology set out to achieve. Add the rush to branded rails and we could end up close to where we started, just with block explorers. Worse, market concentration may rise if a few players use stablecoins to reach previously unimaginable scale. Will History Repeat Itself? In the history of technology, the pendulum regularly swings between centralization and decentralization. Even when a technology has a decentralizing effect, economies of scale in a new dimension—whether complementary resources, talent, brand, or distribution—inevitably become vectors of concentration. A prominent example is the early internet, which brought a wave of entry and competition to the heavily concentrated industries of telecommunications, retail, and media—only to create the perfect conditions for today’s tech giants to scale through network effects and capture a sizable share of value. Although the underlying internet protocols remained open and neutral, massive digital platforms at the application layer walled off participants from competing services by strategically breaking interoperability. From email to social media to payments, we spend most of our time and money within the confines of what the tech giants have designed for us. And while we are clearly better off—more choice, lower prices—it’s increasingly clear that some would prefer a world where platforms do not have as much power and influence over them. Crypto’s reason for existence was to break free from centralized intermediaries. After the 2008 financial crisis, Satoshi wanted to create a world where anyone could exchange value without having to trust a central bank or financial institution ever again. In payments, the most critical battle is unfolding now. Legacy infrastructure is siloed, and incumbents have tremendous power over what we can access—and on what terms. Because of winner‑take‑all dynamics, markets can become so concentrated that the public sector has to step in—the most salient example is China’s introduction of a central bank digital currency to unravel the payments oligopoly established by Ant Group and Tencent. Crypto is a natural, market‑driven solution to this. It provides neutral and decentralized cryptocurrencies like Bitcoin and Ether, as well as truly open and interoperable financial rails via their base layers. But as the technology has matured, two core problems have emerged. Stablecoins’ Centralizing Force—The first problem is that cryptocurrencies are volatile and therefore expensive for payments and financial contracts. To address this, the market has focused on fiat‑backed stablecoins; this inevitably leads to centralization because issuance and sound management require a regulated financial entity to be in charge of—and accountable for—reserve operations. While distributed governance of a stablecoin network is technically possible, it is extremely difficult to get the design right. Libra is the most prominent example: despite backing from more than two dozen leading global companies and countless resources dedicated to establishing credible distributed governance, the project was always perceived as Meta’s initiative. Banks have tried for more than a decade to come together as consortia in response to crypto, and, to date, no joint project has delivered anything tangible. The reason is obvious: until the situation is truly dire, competitors are unlikely to commit to a joint solution—so, in the meantime, everyone hedges their bets across multiple tracks. Intuitively, distributed ownership of a stablecoin network makes sense and is not that different from what ultimately made Visa scale in the 1970s—when Bank of America relinquished control of the BankAmericard credit card program to respond to increasing competition from the consortium that would become Mastercard. Networks of crypto exchanges and fintechs, such as the Global Dollar Network, may be able to move faster, given the agility of the new entrants backing them, but they will still need to strike the right balance between economic incentives and governance to shift members from a wait‑and‑see mode—where everyone hopes to free‑ride on others’ efforts—into action. Even Circle’s Centre Consortium, which had only Circle and Coinbase as members, was dissolved and converted into a simple revenue‑sharing agreement. So, while there might be a solution to the decentralized governance of a stablecoin, what we know is that, to date, the only working model is one that places a single entity in charge of everything. This is, of course, problematic in the long term, and while issuers today control only the asset, they have already started expanding their offerings in ways that limit openness. For example, Circle announced its payment network (CPN), which places it at the center of how payments are executed—from defining rules and eligibility, to inserting itself into every API interaction and price and liquidity discovery, to, of course, collecting a fee. Put together, this setup is not that different from the model that has allowed Visa and Mastercard to dominate payments for decades. From Open Rails to Closed Loops? The second problem crypto has run into is one that is deeply tied to its roots: decentralization is expensive. The economic consequence is that you can only afford it where it truly matters. To date, among networks at scale, that’s been true only for the base layers of Bitcoin, Ethereum, and Solana. At most, that yields a few thousand decentralized transactions per second globally across all of them combined—a far cry from what global payments would require, even before you layer financial services on top. As a result, most transactions no longer occur on the base layers (L1s) but on a sprawling ecosystem of high‑throughput scaling solutions (L2s). L2s offer near‑zero fees and instant settlement, and they’re profitable because they internalize Maximal Extractable Value (MEV)—the gains from reordering, inserting, or omitting transactions in a block. While crypto purists might decry this trend, it aligns precisely with economic theory: users are willing to pay a premium for decentralization and censorship resistance at the core settlement layer, yet they readily trade some of that for greater centralization in higher layers to gain lower costs and faster speeds. The base layers remain open and trustless, and depending on the application, participants may compromise further—even embracing fully trusted, centralized solutions. This trade‑off is broader than a user’s decision to be their own bank and self‑custody funds versus accepting some degree of trust in a third‑party wallet. When building products, Coinbase, Robinhood, and the like care deeply that the underlying network stays neutral and does not play favorites among applications, developers, or businesses—the way the tech giants do on their platforms. Essentially, they are willing to pay for decentralization and neutrality to reduce the risk of hold‑up and expropriation—something that has repeatedly played out on traditional digital platforms. To fully grasp what fast, low‑cost L2s will do to payments and competition in crypto, look no further than what the internet did to news and media: as the cost of distributing—and now, with AI, also generating—large swaths of content fell to zero, business models had to evolve drastically, and massive aggregators (Google, Facebook, Spotify, etc.) emerged to take advantage of the new economics at play. Because L2s remove friction, offer convenience, and allow builders to deliver experiences much closer to traditional fintech products, they are the obvious layer where most of the value will be created—and appropriated. Furthermore, as basic money becomes free and commoditized, competition shifts to the value‑added services and workflows associated with it. That’s exactly where fintechs, neobanks, crypto exchanges, and even traditional financial institutions have a significant advantage. Any one of these players, if it executes well over the next couple of years, can use the technology to establish the first truly massive and global financial network. Once it reaches scale, it could also progressively degrade interoperability, appropriating more of the value—much as today’s internet giants did. So what’s the most likely scenario? Based on how strong and persistent network effects have been in crypto over the last decade, it’s safe to assume that payments and financial services will disproportionately gravitate toward a couple of leading blockchains. Most activity will take place not on their decentralized base layers but on scaling layers branded and shaped by crypto and fintech players (e.g., Base, Robinhood Chain), applications (e.g., Unichain, World Chain), and financial institutions (e.g., Kinexys, Fnality, Partior). Players that control distribution—whether on the consumer, merchant, or institutional side—have a massive advantage, as they own the interface between the blockchain and the real world. Blockchains drastically lower the cost of verifying and coordinating onchain data, but their value is limited without a strong nexus with complementary offchain information—identity, compliance, credentials, creditworthiness, and more. That’s where friction persists—and where economies of scale will decide winners and losers. This is why stablecoin issuers have strong incentives either to commoditize the rails—by issuing on multiple networks and positioning themselves at the center of interoperability across them (e.g., Circle’s CCTP)—or to nudge most activity to a network they control, such as a new L2 or a higher‑level protocol like CPN. Either strategy gives them a shot at becoming massive global fintech leaders and capturing most of the value the technology creates. Meanwhile, crypto and fintech players will want to shift those same valuable transactions to a network over which they have more sway, such as a branded L2. In doing so, they’ll also want either to commoditize stablecoins and other tokenized assets, or to issue their own. In the latter scenario, stablecoins may well be used as a loss leader to expand the reach of a fintech’s offering, and domestic stablecoins will be issued to gain more control over the FX market and support local use cases. Real‑world assets (RWAs), memecoins, other tokens, and applications that are truly differentiated and exclusive to those networks may also help these branded chains retain volume within their borders. The same companies will be able to develop clever rewards and loyalty programs that increase consumer and business stickiness within their ecosystems. As convenience and economic reality win over dogmatism, crypto will look very different than it is today. The good news is that, as part of that transformation, it will be far more useful. And while that may come with more centralization, the fact that the underlying protocols are open source and forkable means that, no matter how large some players may become, they face more pressure to retain greater interoperability than under the status quo. It is also possible that because crypto protocols allow for new market design and incentives, the ultimate solution will be something that was not quite achievable for the internet protocols—which did not have built‑in monetization mechanisms. Regardless, once centralization materializes, some clever group of developers will work hard to undo it, and the cycle will repeat. Full article in [@ForbesCrypto](https://x.com/ForbesCrypto): [forbes.com](https://www.forbes.com/sites/christiancatalini/2025/08/11/stripe-is-building-a-blockchain-can-openness-survive-branded-rails/) --- ## Can Crypto Scale Without Losing Its Soul? - canonical: https://catalini.com/notes/crypto-scale-without-losing-soul/ - original thread: https://x.com/ccatalini/status/1955258248388341993 - date: 2025-08-12 🚨 Can crypto scale without losing its soul? [@stripe](https://x.com/stripe) and [@circle](https://x.com/circle) are both building their own chain! The question isn't speed or functionality—it's openness. Are we building an open protocol for money, or branded rails? Tech moves like a pendulum: we decentralize, then scale, then recentralize around distribution, brand, network effects. The early internet kept protocols open while platforms built walls. Crypto may be approaching the same tipping point. Stablecoins fix crypto's volatility but their governance and reserves bring back a central actor. [@circle](https://x.com/circle)'s Arc or [@stripe](https://x.com/stripe)'s Tempo, fast, but familiar. It’s the Visa and Mastercard playbook, just onchain. Decentralization is expensive, so most transactions are moving to fast L2s. Users trade a little trust and control for convenience (sounds familiar?). When frictions fall, aggregators rise—the internet lesson, this time applied to money (see [@benthompson](https://x.com/benthompson)'s work). Who wins? Whoever owns the last mile—consumers, merchants, institutions. Onchain lowers digital verification costs, but offchain identity, compliance, and credit decide who captures value. Power lives where frictions persist. Two strategies: stablecoin issuers commoditize the rails and deploy their own walled garden ([@Circle](https://x.com/Circle)'s CCTP, CPN, and now Arc). Exchanges, fintechs and neobanks use stablecoins as loss leaders, while growing their L2s. In the long run, if interoperability is compromised, we’ll be back where we started—only with much larger financial incumbents than ever before. More in [@Forbes](https://x.com/Forbes): --- ## Stripe Is Building A Blockchain: Can Openness Survive Branded Rails? - canonical: https://catalini.com/writing/stripe-blockchain-branded-rails/ - original: https://www.forbes.com/sites/christiancatalini/2025/08/11/stripe-is-building-a-blockchain-can-openness-survive-branded-rails/ - date: 2025-08-11 - outlet: forbes Fintech powerhouse Stripe is secretly building a high-performance blockchain called “Tempo,” per a now-removed [job posting](https://archive.ph/dJHvQ) and Fortune’s [reporting](https://fortune.com/crypto/2025/08/11/stripe-blockchain-tempo-paradigm/). This payments-optimized chain would fill a critical gap in Stripe’s crypto stack, complementing its recent acquisitions of stablecoin startup [Bridge](https://www.forbes.com/sites/christiancatalini/2024/11/01/why-everyone-is-wrong-about-stablecoins/) and wallet infrastructure provider Privy. Stablecoins promise to make crypto mainstream by delivering faster, cheaper, more interconnected global payments. The paradox: the same move could undercut what the technology set out to achieve. Add the rush to branded rails—Robinhood’s chain on Arbitrum, Coinbase’s Base on the OP Stack, and now Stripe’s Tempo—and we could end up close to where we started, just with block explorers. Worse, market concentration may rise if a few players use stablecoins to reach previously unimaginable scale. With the GENIUS Act now law, the next 12–18 months will likely determine the outcome. We’ve seen this tension before in the early internet’s open web versus walled gardens. ## Will History Repeat Itself? In the history of technology, the pendulum regularly swings between centralization and decentralization. Even when a technology has a decentralizing effect, economies of scale in a new dimension—whether complementary resources, talent, brand, or distribution—inevitably become vectors of concentration. Once concentration becomes too high, the ingenuity of entrepreneurs and developers invents a new approach to reverse it. A prominent example is the early internet, which brought a wave of entry and competition to the heavily concentrated industries of telecommunications, retail, and media—only to create the perfect conditions for today’s tech giants to scale through network effects and capture a sizable share of value. Although the underlying internet protocols remained open and neutral, massive digital platforms at the application layer walled off participants from competing services by strategically breaking interoperability. From email to social media to payments, we spend most of our time and money within the confines of what the tech giants have designed for us. And while we are clearly better off—more choice, lower prices—it’s increasingly clear that some would prefer a world where platforms do not have as much power and influence over them. ## Crypto As the Antidote Crypto’s reason for existence was to break free from centralized intermediaries. After the 2008 financial crisis, Satoshi wanted to create a world where anyone could exchange value without having to trust a central bank or financial institution ever again. And while the original Bitcoin vision of a fully democratic network—“one‑CPU‑one‑vote”—didn’t pan out due to economies of scale in mining, Bitcoin did deliver what more and more financial institutions and some governments now recognize as a novel and neutral financial asset. Inspired by Bitcoin, entrepreneurs and developers have applied the same principles in an attempt to bring decentralization back to [other digital platforms](https://www.forbes.com/sites/christiancatalini/2025/01/16/the-internet-of-money-wants-to-be-free/)—starting with payments, but branching out into finance, marketplaces, messaging, and social media. Overall, progress toward decentralization is mixed: while it’s true that Bitcoin allows anyone around the world to be their own bank, the vast majority of consumers and institutions rely heavily on intermediaries for custody and use. Similarly, solutions that offer consumers greater control over their private data and the content they create have stayed niche—often because they lag in usability and convenience relative to the centralized counterparts they’re trying to replace. Convenience eats privacy for lunch any day—and it’s difficult to undo the entrenched network effects of the leading digital platforms. ## The Battle for the Future of Payments In payments, the most critical battle is unfolding now. Legacy infrastructure is siloed, and incumbents have tremendous power over what we can access—and on what terms. Because of winner‑take‑all dynamics, markets can become so concentrated that the public sector has to step in—the most salient example is China’s introduction of a central bank digital currency to unravel the payments oligopoly established by Ant Group and Tencent. Crypto is a natural, market‑driven solution to this. It provides neutral and decentralized cryptocurrencies like Bitcoin and Ether, as well as truly open and interoperable financial rails via their base layers. But as the technology has matured, two core problems have emerged. ## Stablecoins’ Centralizing Force The first problem is that cryptocurrencies are volatile and therefore expensive for payments and financial contracts. To address this, the market has focused on fiat‑backed stablecoins; this inevitably leads to centralization because issuance and sound management require a regulated financial entity to be in charge of—and accountable for—reserve operations. While distributed governance of a stablecoin network is technically possible, it is extremely difficult to get the design right. Libra is the most prominent example: despite backing from more than two dozen leading global companies and countless resources dedicated to establishing credible distributed governance, the project was always perceived as Meta’s initiative. Banks have tried for more than a decade to come together as consortia in response to crypto, and, to date, no joint project has delivered anything tangible. The reason is obvious: until the situation is truly dire, competitors are unlikely to commit to a joint solution—so, in the meantime, everyone hedges their bets across multiple tracks. Intuitively, distributed ownership of a stablecoin network makes sense and is not that different from what ultimately made Visa scale in the 1970s—when Bank of America relinquished control of the BankAmericard credit card program to respond to increasing competition from the consortium that would become Mastercard. Networks of crypto exchanges and fintechs, such as the Global Dollar Network, may be able to move faster, given the agility of the new entrants backing them, but they will still need to strike the right balance between economic incentives and governance to shift members from a wait‑and‑see mode—where everyone hopes to free‑ride on others’ efforts—into action. Even Circle’s Centre Consortium, which had only Circle and Coinbase as members, was dissolved and [converted](https://www.circle.com/blog/ushering-in-the-next-chapter-for-usdc) into a simple revenue‑sharing agreement. So, while there might be a solution to the decentralized governance of a stablecoin, what we know is that, to date, the only working model is one that places a single entity in charge of everything. This is, of course, problematic in the long term, and while issuers today control only the asset, they have already started expanding their offerings in ways that limit openness. For example, Circle announced its payment network ([CPN](https://www.circle.com/cpn)), which places it at the center of how payments are executed—from defining rules and eligibility, to inserting itself into every API interaction and price and liquidity discovery, to, of course, collecting a fee. Put together, this setup is not that different from the model that has allowed Visa and Mastercard to dominate payments for decades. ## From Open Rails to Closed Loops? The second problem crypto has run into is one that is deeply tied to its roots: decentralization is expensive. The economic consequence is that you can only afford it where it truly matters. To date, among networks at scale, that’s been true only for the base layers of Bitcoin, Ethereum, and Solana. At most, that yields a few thousand decentralized transactions per second globally across all of them combined—a far cry from what global payments would require, even before you layer financial services on top. As a result, most transactions no longer occur on the base layers (L1s) but on a sprawling ecosystem of high‑throughput scaling solutions (L2s). L2s offer near‑zero fees and instant settlement, and they’re profitable because they internalize Maximal Extractable Value (MEV)—the gains from reordering, inserting, or omitting transactions in a block. While crypto purists might decry this trend, it aligns precisely with economic theory: users are willing to pay a premium for decentralization and censorship resistance at the core settlement layer, yet they readily trade some of that for greater centralization in higher layers to gain lower costs and faster speeds. The base layers remain open and trustless, and depending on the application, participants may compromise further—even embracing fully trusted, centralized solutions. This trade‑off is broader than a user’s decision to be their own bank and self‑custody funds versus accepting some degree of trust in a third‑party wallet. When building products, Coinbase, Robinhood, and the like care deeply that the underlying network stays neutral and does not play favorites among applications, developers, or businesses—the way the tech giants do on their platforms. Essentially, they are willing to pay for decentralization and neutrality to reduce the risk of hold‑up and expropriation—something that has repeatedly played out on traditional digital platforms. To fully grasp what fast, low‑cost L2s will do to payments and competition in crypto, look no further than what the internet did to news and media: as the cost of distributing—and now, with AI, also generating—large swaths of content fell to zero, business models had to evolve drastically, and massive aggregators (Google, Facebook, Spotify, etc.) emerged to take advantage of the new economics at play. Because L2s remove friction, offer convenience, and allow builders to deliver experiences much closer to traditional fintech products, they are the obvious layer where most of the value will be created—and appropriated. Furthermore, as basic money becomes free and commoditized, competition shifts to the value‑added services and workflows associated with it. That’s exactly where fintechs, neobanks, crypto exchanges, and even traditional financial institutions have a significant advantage. Any one of these players, if it executes well over the next couple of years, can use the technology to establish the first truly massive and global financial network. Once it reaches scale, it could also progressively degrade interoperability, appropriating more of the value—much as today’s internet giants did. ## Whoever Controls the Last Mile Wins So what’s the most likely scenario? Based on how strong and persistent network effects have been in crypto over the last decade, it’s safe to assume that payments and financial services will disproportionately gravitate toward a couple of leading blockchains. The remaining chains will need to specialize within an industry vertical to stay relevant. Most activity will take place not on their decentralized base layers but on scaling layers branded and shaped by crypto and fintech players (e.g., Base, Robinhood Chain), applications (e.g., Unichain, World Chain), and financial institutions (e.g., Kinexys, Fnality, Partior). Players that control distribution—whether on the consumer, merchant, or institutional side—have a massive advantage, as they own the interface between the blockchain and the real world. Blockchains drastically lower the [cost of verifying and coordinating](https://dl.acm.org/doi/10.1145/3359552) onchain data, but their value is limited without a strong nexus with complementary offchain information—identity, compliance, credentials, creditworthiness, and more. That’s where friction persists—and where economies of scale will decide winners and losers. ## From Strategic Partners to Swappable Modules This is why stablecoin issuers have strong incentives either to commoditize the rails—by issuing on multiple networks and positioning themselves at the center of interoperability across them (e.g., Circle’s Cross‑Chain Transfer Protocol)—or to nudge most activity to a network they control, such as a new L2 or a higher‑level protocol like CPN. Either strategy gives them a shot at becoming massive global fintech leaders and capturing most of the value the technology creates. Meanwhile, crypto and fintech players will want to shift those same valuable transactions to a network over which they have more sway, such as a branded L2. In doing so, they’ll also want either to commoditize stablecoins and other tokenized assets, or to issue their own. In the latter scenario, stablecoins may well be used as a loss leader to expand the reach of a fintech’s offering, and domestic stablecoins will be issued to gain more control over the FX market and support local use cases. Real‑world assets (RWAs), memecoins, other tokens, and applications that are truly differentiated and exclusive to those networks may also help these branded chains retain volume within their borders. The same companies will be able to develop clever rewards and loyalty programs that increase consumer and business stickiness within their ecosystems. ## Can’t Be Evil? As convenience and economic reality win over dogmatism, crypto will look very different than it is today. The good news is that, as part of that transformation, it will be far more useful. And while that may come with more centralization, the fact that the underlying protocols are open source and forkable means that, no matter how large some players may become, they face more pressure to retain greater interoperability than under the status quo. It is also possible that because crypto protocols allow for new market design and incentives, the ultimate solution will be something that was not quite achievable for the internet protocols—which did not have built‑in monetization mechanisms. Regardless, once centralization materializes, some clever group of developers will work hard to undo it, and the cycle will repeat. --- ## Africa's FX Drought, in Three Numbers - canonical: https://catalini.com/notes/africas-fx-drought/ - original thread: https://x.com/ccatalini/status/1952727589644329326 - date: 2025-08-05 Africa’s FX drought in three numbers: dollars trickle in, but ~$750 bn of imports, ~$90 bn in debt coupons, and a stealthy ~$89 bn in illicit flows suck them right back out. End-game: everyone queues for the last $20 in the till. In the pre-stablecoin era, inflation + capital controls meant a back-alley FX bazaar—fragmented liquidity, 20% spreads, settlements by motorbike. Stablecoins rewired the old FX market: liquidity pools on tap, fees shaved to basis points, and cash-in/out in seconds—riding the mobile money rails already in everyone’s pocket. More in [@yosephayele](https://x.com/yosephayele)'s post! [writing.lavavc.io](https://writing.lavavc.io/p/stablecoins-in-africa-part-i) --- ## Washington’s New Stablecoin Law Has a 19th-Century Flaw - canonical: https://catalini.com/writing/washingtons-stablecoin-law-flaw/ - original: https://www.lightspark.com/news/insights/washingtons-new-stablecoin-law - date: 2025-08-01 - outlet: lightspark What free-banking history warns about the new U.S. stablecoin framework. Full text at the original outlet: https://www.lightspark.com/news/insights/washingtons-new-stablecoin-law --- ## What's Left on Your Résumé That Can't Be Back-Propagated? - canonical: https://catalini.com/notes/resume-back-propagated/ - original thread: https://x.com/ccatalini/status/1942281230520836573 - date: 2025-07-07 When a bot’s inner monologue is, "What leverage keeps me from being unplugged?," you know the code has graduated from Excel macros to higher-level strategy. What’s left on your resume that can’t be back-propagated? AI is rapidly routinizing anything that is predictable and measurable. But humans can still thrive in areas full of unknown unknowns... We're good at innovating and creating new things in areas where probabilities vanish... So pay attention to what is measurable—and to what stubbornly isn't to find your personal edge. Full story: [hbr.org](https://hbr.org/2025/06/what-gets-measured-ai-will-automate?ab=HP-hero-latest-1) --- ## AI, Taste, and the Blank-Cell Frontiers - canonical: https://catalini.com/notes/ai-taste-blank-cell-frontiers/ - original thread: https://x.com/ccatalini/status/1939729929782083993 - date: 2025-06-30 Provocative take on how AI will conquer taste—straight from [@joulee](https://x.com/joulee)’s chat with [@ivanhzhao](https://x.com/ivanhzhao). cc: [@teamSundial](https://x.com/teamSundial) [@NotionHQ](https://x.com/NotionHQ). Their "agency" concept is the same unruly territory we mapped as unknown unknowns and what-ifs in [@HarvardBiz](https://x.com/HarvardBiz)—the bits the spreadsheet can’t pin down. [@wu_jane](https://x.com/wu_jane), [@kevalexzhang](https://x.com/kevalexzhang) and I argue the edge lives in those blank-cell frontiers no metric dares to tread. Links to both pieces: [lg.substack.com](https://lg.substack.com/p/when-ai-has-better-taste-than-you) and [hbr.org](https://hbr.org/2025/06/what-gets-measured-ai-will-automate) --- ## Humans Are Evolutionary Generalists - canonical: https://catalini.com/notes/humans-evolutionary-generalists/ - original thread: https://x.com/ccatalini/status/1938269075500896596 - date: 2025-06-26 Humans are evolutionary generalists, selected to navigate half-drawn maps. We don’t merely survive unknown unknowns—we thrive on them, and that resilience is our defining edge. Over countless generations we fine-tuned our vocal cords and social brains until language emerged—opening the door to cumulative knowledge, abstract reasoning, and symbolic thought. From there we pushed beyond our biological limits, forging tools that stretched our senses, expanded our memory, and multiplied our abilities. But the cornerstone of our advantage is our highly plastic, densely wired prefrontal cortex. This neural command center lets us spin endless "what-ifs," rehearse counterfactual futures, and pivot strategy the instant conditions shift. Short of a true singularity, even quantum machines will struggle to match our talent for open-ended, cross-domain counterfactual planning. More at [@HarvardBiz](https://x.com/HarvardBiz) [x.com](https://x.com/HarvardBiz/status/1936261290961273272) --- ## Hybrid Corn, ImageNet, and AI's Adoption Curve - canonical: https://catalini.com/notes/hybrid-corn-ai-adoption/ - original thread: https://x.com/ccatalini/status/1937204462369800453 - date: 2025-06-23 In 1957, Zvi Griliches studied farmers try hybrid corn on prime acres first, then seed the rest once the yields proved worth the cost.📈 AI is running the same adoption curve—only the corn is measurement, the fertilizer is GPUs, and the yield is your job! 🤖 [@drfeifei](https://x.com/drfeifei)'s 2010 ImageNet leaderboard was the tipping point. 14M labeled photos plus public rankings turned vision research into a global hackathon. With two off the shelf GPUs, [@geoffreyhinton](https://x.com/geoffreyhinton), [@ilyasut](https://x.com/ilyasut) & Krizhevsky halved error rates—the day spreadsheets grew eyes. 👀 If you can turn a task into the "Data + Reward + Compute" sandwich, the model will eventually lunch on it. 🦾 And every sensor, clickstream, and synthetic dataset makes the bread cheaper. Fast‑forward: [@AnthropicAI](https://x.com/AnthropicAI) reports 43 % of user sessions are already automation. So the polite chat window you’re using as a copilot today is basically running a dark kitchen for tomorrow’s robo‑staff. 🍳🤖 As measurement costs fall, suddenly even thin‑margin chores clear the ROI bar. Humans still own judgment, though! Sure—until judgment fits a leaderboard. The second we find a proxy label for nuance, it’s headed for the fine‑tune farm. 🏭 Ask the creators whose portfolios are now [@midjourney](https://x.com/midjourney)'s pre‑game snack... What stays out of AI’s reach? Anything lost in Knightian fog: first of their kind ventures, investment bets in a brand-new tech regime, sparking a fashion meme no metric can price. No probabilities to plug in, so no GPT buyout. Leaders should bankroll fuzzy bets, rotate talent through ambiguity, and protect the uncountables—taste, trust, experiences and narratives. Think Amar Bose tuning speakers by ear while rivals optimized frequency charts: on paper it looked wasteful, but customers heard a sound they’d never experienced before. Because, uncomfortable truth: the moment your edge is clean enough to fit a cell, the cell dials an H100 cluster and politely emails HR about the redundancy. Measure what matters, absolutely—yet guard what defies metrics. 🪄 That’s the scarce ground where defensible value still lives. Full article in [@HarvardBiz](https://x.com/HarvardBiz): [x.com](https://x.com/HarvardBiz/status/1936261290961273272) --- ## AI Doesn't Need a Sci-Fi Upgrade to Upend the Economy - canonical: https://catalini.com/notes/no-sci-fi-upgrade-needed/ - original thread: https://x.com/ccatalini/status/1935708804274119141 - date: 2025-06-19 AI doesn’t need a sci-fi upgrade to upend the economy—current models, and the cheaper, more capable versions already in the pipeline, are set to disrupt nearly every corner of the labor market. There are major questions about how much more powerful AI tools might become—and how soon. Yet even if progress stopped tomorrow, the disruption is already underway. To navigate this, leaders need to understand which tasks and responsibilities are most likely to come under pressure and charting a course to move the enterprise up the intelligence value chain before time runs out. What Is Not at Risk of Automation? Academic researchers and practitioners have extensively debated which jobs and tasks are most vulnerable to automation. Some threats are obvious: self-driving vehicles may soon be in a position to displace millions of ride-sharing, bus, and truck drivers. Meanwhile, language translation, swaths of creative writing, design, and even everyday coding are being handed off to AI. AI research pioneers [@professor_ajay](https://x.com/professor_ajay), [@joshgans](https://x.com/joshgans), [@avicgoldfarb](https://x.com/avicgoldfarb) argued in 2018 that as AI advances, the last bastion of human advantage will be judgment—the ability to weigh options and make decisions under uncertainty. Yet that insight hands us an impossible homework assignment: pinning down exactly what qualifies as judgment at any given moment. Tasks that demand human judgment today could soon pass to AI as models tap richer data and greater compute. Nor can we assume people will always prefer a human therapist, counselor, or mediator, according to recent research. An AI counterpart can operate around the clock, at a fraction of the cost, and—aside from a handful of human superstars—may offer more consistent quality. So, how can we separate the tasks AI will automate next from those that will require new breakthroughs in AI technology to do so? To answer that, we must go back to first principles and revisit where it all began. Back in the mid-2000s, [@drfeifei](https://x.com/drfeifei) saw that the field of computer vision was dealing with a bottleneck: algorithms were pixel-starved, ingesting too little visual data to reach human performance. Her solution was refreshingly brute-force: she built ImageNet—a vast, meticulously labeled image trove assembled with help from Amazon Mechanical Turk. But her true stroke of genius came in 2010, when she bolted a global leaderboard onto the dataset—transforming image recognition into a gladiatorial contest for researchers. For two years, the annual leaderboard inched forward... Then, in 2012, Alex Krizhevsky, [@ilyasut](https://x.com/ilyasut), [@geoffreyhinton](https://x.com/geoffreyhinton) blew the competition away. Using two off-the-shelf NVIDIA cards, the trio was able to train a CNN in just a few days—proving that you could bend computer-vision history on a grad student budget. That moment ended the decades-long AI winter, put neural nets at the center of progress, and revealed the playbook the field still runs on. The framework that propelled the image recognition breakthrough is far more general than most realize. It can be invoked whenever we can a) define the task environment and assemble its data; b) specify a target reward, explicit or implicit (inferred from observing human behavior); and c) provide the computational power to let the system iterate. Stack those three ingredients and you get a general-purpose automation engine. Two data trends now accelerate the flywheel. First, models can mint limitless synthetic examples—for instance, generating virtual "driving miles" that cover every oddball scenario, rather that relying on data from real world drivers. And second, AI is increasingly fielded across a variety of devices and sensors—on phones, in cars, and elsewhere—as a low-cost surveyor, capturing and quantifying real-world signals that were once too expensive or impractical to measure. If you can shoehorn a phenomenon into numbers, AI will learn it and reproduce it back at scale—and the tech keeps slashing the cost of that conversion, so measurement gets cheaper, faster, and quietly woven into everything we touch. More things become countable, the circle resets, and the model comes back for seconds. That means that any job that can be measured can, in theory, be automated. AI now slashes the cost of precise measurement, making continuous, fine-grained sensing the default. Lightweight models run beside the sensors, trimming bandwidth and latency, while synthetic data fills gaps when the real world is slow or awkward to capture. We already live in the era of "artificial-metrics intelligence," where anything we can quantify is swiftly queued for automation. Humans are evolutionary generalists, selected to navigate half-drawn maps. We don’t merely survive unknown unknowns—we thrive on them, and that resilience is our defining edge. But the cornerstone of our advantage is our highly plastic, densely wired prefrontal cortex. This neural command center lets us spin endless "what-ifs," rehearse counterfactual futures, and pivot strategy the instant conditions shift. Short of a true singularity, even quantum machines will struggle to match our talent for open-ended, cross-domain counterfactual planning. As AI accelerates progress, it creates fresh unknown unknowns, so our maps keep being redrawn. Meanwhile, it routinizes the predictable. AI will also struggle in domains where measurement verges on the impossible. It will also lag where measurement is throttled by privacy, ethics, or regulation; where society requires transparent reasoning—at least until model interpretability catches up; and where people simply prefer a human touch. But one crucial carve-out in what can be measured may prove decisive: tasks that defy quantification because their outcome odds are fundamentally unknowable—the realm of Knightian uncertainty, where you can’t assign any probabilities. Scaling a startup, allocating capital or talent into uncertain ventures, containing a novel pathogen, drafting AI ethics, inventing a new artistic medium, igniting a fashion trend, or creating a new genre-bending blockbuster—all sit in zones where probabilities vanish. Some creative acts and discoveries amount to little more than clever recombinations of the familiar, but the truly ambitious hinge on our singular ability to envision genuinely new and complex counterfactual worlds. The list is fluid—tasks drop off the moment they become measurable, and new ones surface just as quickly. Each shift forces painful economic and social adjustments, squeezing more work into a superstar economy... ...that concentrates outsized rewards at the peaks of creativity, talent, and capital. Yet AI offers a paradoxical gift: by democratizing education and serving as everyone’s personal copilot, it hands more people than ever the tools to reach those peaks. For leaders, what lies beyond the spreadsheet? It’s everything that won’t fit in a cell: the skills that refuse to be tallied, the problems with no precedent, the intangibles—trust, taste, quality & experience—and the conviction to press ahead when every metric says "wait." Manage only what you can measure, and you surrender the most valuable ground to rivals who cultivate what can’t be counted. Amar Bose, proved the point: while others worshipped spec-sheet numbers, he zeroed in on how music sounded to people in real rooms—a quality no existing metric could catch—and in doing so, he rewrote the rules of the audio industry. The prescription is simple. Back wildcard bets with fuzzy ROI, reward teams that reframe problems and lean into the unknown, and rotate talent through roles that confront uncertainty across R&D, new markets, and complex customer, partner, and policy interactions. Carve out slack time and engineer cross-team collisions to spark serendipity and idea recombination. Treat those pockets of planned ambiguity not as liabilities, but as strategic assets. Only leaders who pay attention to what is measurable—and, more crucially, to what stubbornly isn’t—will be ready when the next shift arrives. Full piece on [@HarvardBiz](https://x.com/HarvardBiz): [hbr.org](https://hbr.org/2025/06/what-gets-measured-ai-will-automate) --- ## What Gets Measured, AI Will Automate - canonical: https://catalini.com/writing/what-gets-measured-ai-automates/ - original: https://hbr.org/2025/06/what-gets-measured-ai-will-automate - date: 2025-06-01 - outlet: hbr Measurability decides which work AI automates first — and where humans stay in the loop. Full text at the original outlet: https://hbr.org/2025/06/what-gets-measured-ai-will-automate --- ## Can Crypto Go Mainstream Without Losing Its Soul? - canonical: https://catalini.com/writing/crypto-mainstream-soul/ - original: https://www.lightspark.com/news/insights/can-crypto-go-mainstream-without-losing-its-soul - date: 2025-06-01 - outlet: lightspark Openness versus convenience as crypto reaches mainstream scale. Full text at the original outlet: https://www.lightspark.com/news/insights/can-crypto-go-mainstream-without-losing-its-soul --- ## Circle's Choose-Your-Own Exit - canonical: https://catalini.com/notes/circles-choose-your-own-exit/ - original thread: https://x.com/ccatalini/status/1924549607494975964 - date: 2025-05-19 Circle's choose-your-own exit: 1️⃣ IPO—works if it finds a complementary business model 💰 before the Fed trims rates. 2️⃣ [@coinbase](https://x.com/coinbase) buy—feels native: the exchange already pockets ~50% of USDC yield and can truly scale it to the next level📈. 3️⃣ [@Ripple](https://x.com/Ripple) bid—likely the suitor most willing to pay, but how will USDC thrive inside an XRP universe is unclear. 4️⃣ [@PayPal](https://x.com/PayPal) lane—fastest ticket to checkout buttons and ~430 M wallets. [@acce](https://x.com/acce) must be thinking about ⁉️ 5⃣ [@Stripe](https://x.com/Stripe) — cooking up USDB with [@Stablecoin](https://x.com/Stablecoin), which promises to bring developer-native speed for mass-market merchant payments. So why buy? 6️⃣ A dark-horse bank with late-stage stablecoin FOMO and a healthy balance-sheet— though odds are regulatory red tape might be heavier than DIY. Nice problem to have [@jerallaire](https://x.com/jerallaire) & team! 🔥 [x.com](https://x.com/TheBlock__/status/1924526880620753371) --- ## Inference Grid: Where Bitcoin, AI, and Money Collide - canonical: https://catalini.com/notes/inference-grid/ - original thread: https://x.com/ccatalini/status/1923388674479206540 - date: 2025-05-16 Today’s the day! Come tinker where Bitcoin, AI & money collide [@PresidioBitcoin](https://x.com/PresidioBitcoin) with resident AI wizard 🪄🧙 [@kevalexzhang](https://x.com/kevalexzhang). No seat? Comment below and we’ll spill the beans on Inference Grid—the skunkworks project we’re bolting together [@lightspark](https://x.com/lightspark) using [@buildonspark](https://x.com/buildonspark) & ⚡️ Inference Grid is a plug-and-play swap for the big models: smart routing trims the bill and lets you mix-and-match as many brains as you like (uncensored too). Or bring your own silicon—DIY compute nudges us closer to true decentralization, and dropping costs make it a viable alternative. Discover more at: [inferencegrid.ai](https://www.inferencegrid.ai) 🔧👷‍♀️👷‍♂️🚧 Alpha release: things will break—fine print says the AIs will probably fix their own bugs and send us an invoice. 🤖🦾 We crave your feedback! Let’s co-design a sturdier, more decentralized inference stack. The world needs it. 🔥 --- ## Fresh Asphalt Needs On-Ramps - canonical: https://catalini.com/notes/fresh-asphalt-needs-on-ramps/ - original thread: https://x.com/ccatalini/status/1920867394097950887 - date: 2025-05-09 Nothing eases a moderator’s job like panelists willing to puncture buzzwords on contact. Erica Khalili, [@chrismaurice](https://x.com/chrismaurice), [@dadiomov](https://x.com/dadiomov) & [@ShanAggarwal](https://x.com/ShanAggarwal) kept the crowd engaged while deflating the fluff. Thanks [@Lead_Bank](https://x.com/Lead_Bank) [@yellowcard_app](https://x.com/yellowcard_app) [@ModernTreasury](https://x.com/ModernTreasury) [@coinbase](https://x.com/coinbase) [@stripe](https://x.com/stripe). Stablecoins are laying fresh asphalt for global payments, but they need great on/off-ramps to the old highways—bank & card rails—, as well as consumer safeguards. Training wheels for borderless, self-driving programmable money/accounts… and those wheels are coming off fast. The stablecoin killer app might not be a shiny wallet at all—it could be the plumbing. Protocols like x402 let AI agents swipe wallet balances or cards in exchange for compute, data, and whatever’s next. Money that speaks API? Now that’s interesting. [x.com](https://x.com/CoinbaseDev/status/1919784224170889696) --- ## Electricity's Playbook for the Stablecoin Wars - canonical: https://catalini.com/notes/electricitys-playbook-stablecoin-wars/ - original thread: https://x.com/ccatalini/status/1919031578706989528 - date: 2025-05-04 Electricity’s playbook for today’s stablecoin wars: Westinghouse locked in the marquee distribution deals—Chicago World’s Fair, Niagara Falls—and used cheaper, easier-to-scale AC to undercut Edison. Secure the gateways and keep fees low, and the stablecoin crown is yours. Move fast while the sockets are still wobbly: once regulators stamp “60-hertz” on every coin, they will all trade like bulk electrons—reliable, boring, and priced by the kilowatt. Secure the distribution now. Win distribution first, then move up the value stack. Software still eats the world. But a well-armed phalanx of fintechs and legacy banks has a survival-level interest in stopping that. The real question, then, isn’t whether software will eat the world, but whose software gets the seat at the table. Hoard the upside and the network stalls. Share real ownership and it flies—Visa only took off after turning BankAmericard into a bank-owned co-op, giving thousands of banks skin in every swipe. More in the article! --- ## What Worldcoin's Pivot Signals for Crypto - canonical: https://catalini.com/notes/worldcoin-pivot-signals/ - original thread: https://x.com/ccatalini/status/1918009294177591701 - date: 2025-05-01 Yesterday, [@worldnetwork](https://x.com/worldnetwork)'s [@alexblania](https://x.com/alexblania) unveiled his latest plans to a room full of crypto insiders. The U.S. debut is noteworthy, but the real plot twist is Worldcoin’s sprint toward the mainstream and what that signals for crypto’s own leap to everyday commerce. What lessons can crypto founders and builders take from Worldcoin’s evolution? First, build real utility—then sweeten it with tokens. Worldcoin used to lean heavily on its crypto token to drive adoption. But that strategy—often hailed as Bitcoin’s winning formula and copied endlessly—gets the cause and effect all wrong. Bitcoin scaled because it introduced a neutral, fixed-supply asset answerable to no central bank. Sure, mining rewards and moon-shot price hopes drew speculators, later joined by institutional investors and a few sovereigns—but Bitcoin’s lasting builders were hooked on its radical potential as a new kind of asset and payment system, not just a get-rich-quick scheme. By pointing to dating, gaming, and credit—arenas where bots now mingle freely with humans—Blania framed Worldcoin’s proof-of-personhood as the fix, and explained why trading an iris scan to the orb might be a wager worth taking. It’s no shock that Worldcoin, co-founded and chaired by OpenAI’s Sam Altman, is tackling this issue: as AI grows more sophisticated, the need for a reliable, cryptographically secure way to prove someone’s human will become critical. [x.com](https://x.com/eddylazzarin/status/1917762475744977082) Second, delivering real utility outside the crypto bubble means matching the user experience consumers and businesses already get from traditional solutions. And yes, that requires building a bridge between old and new rails. [x.com](https://x.com/cuysheffield/status/1917777920703225922) You can’t skip the awkward stretch where new and old rails overlap—what [@aantonop](https://x.com/aantonop) calls "infrastructure inversion." Picture 56k modems hijacking analog phone lines in the ’90s or the first cars rattling down horse-grade gravel roads. Early Worldcoin tried to skip the inversion phase, making the token the star. Yesterday’s reboot flips the script: it leans into the infrastructure-inversion playbook and on shipping real utility first. You still can’t ship a best-in-class, truly global wallet without latching onto the old rails. On-ramps and off-ramps need to feel effortless—PayPal’s magic when online payments felt dicey—and that seamless flow is what any crypto wallet needs to crack the mainstream. That’s where the World App’s tie-ins with [@stripe](https://x.com/stripe) and a [@Visa](https://x.com/Visa) card stand out, delivering familiarity, trust, and instant utility from day one. Backwards compatibility also keeps incumbents in play, letting them track new players and roll out fresh services. Third, like any new technology, crypto is far from inevitable—no matter what its boosters claim. More precisely, decentralization—crypto’s core principle and its most significant contribution to reshaping markets—is far from a sure thing. --- ## What Everyone Gets Wrong About Crypto Adoption - canonical: https://catalini.com/writing/crypto-adoption/ - original: https://www.forbes.com/sites/digital-assets/2025/05/01/what-everyone-gets-wrong-about-crypto-adoption/ - date: 2025-05-01 - outlet: forbes Yesterday, Worldcoin’s Alex Blania [unveiled](https://www.youtube.com/live/1hvkxrEUWEo?si=5m3Cer59YIBztIs3) the company’s latest plans to a room full of crypto industry insiders. The U.S. debut—riding a friendlier regulatory breeze—is noteworthy, but the real plot twist is Worldcoin’s sprint toward the mainstream and what that signals for crypto’s own leap from early-adopter clubhouse to everyday commerce. Worldcoin’s wager is undeniably bold—convincing Americans to swap an iris scan for a cryptographic “I’m human” badge is no easy sell, privacy guarantees or not, and might be early—but the team has quietly de-risked the plan on several fronts in recent years (details below). What lessons can crypto founders and builders take from Worldcoin’s evolution? ## 1. Build Real Utility—Then Sweeten It with Tokens Worldcoin used to lean heavily on its crypto token to drive adoption. But that strategy—often hailed as Bitcoin’s winning formula and copied endlessly—gets the [cause and effect all wrong](https://hbr.org/2023/01/do-crypto-prices-actually-mean-anything). It also sparked unintended consequences, as Worldcoin discovered during its early rollouts. Bitcoin scaled because it introduced a neutral, fixed-supply asset answerable to no central bank. Sure, mining rewards and moon-shot price hopes drew speculators, later joined by institutional investors and a few sovereigns—but Bitcoin’s lasting builders were hooked on its radical potential as a new kind of asset and payment system, not just a get-rich-quick scheme. Since then we’ve watched thousands of copy-paste tokens try the same trick, and most now shuffle through the crypto-zombie graveyard. Crypto isn’t above the fundamental laws of economics. Like any startup, crypto projects need to target genuine utility first, then use tokens to speed up adoption or address market failures in their ecosystem. In short, while economists may be eager to play engineer, their ideas shine most when a project already has some traction. By pointing to dating, gaming, and credit—arenas where bots now mingle freely with humans—Blania framed Worldcoin’s proof-of-personhood as the fix, and explained why trading an iris scan to the orb might be a wager worth taking. It’s no shock that Worldcoin, co-founded and chaired by OpenAI’s Sam Altman, is tackling this issue: as AI grows more sophisticated, the need for a reliable, cryptographically secure way to prove someone’s human will become critical. Worldcoin may be outpacing the trend, but it’s tackling a huge societal challenge we’ll all face soon. (For a solid primer on this, check out Eddy Lazzarin and co-authors’ [work](https://arxiv.org/abs/2408.07892).) ## 2. Navigating Crypto’s Infrastructure Flip Back in crypto’s early days, we were all swept up in the hype. When I co-designed the [Bitcoin experiment](https://www.science.org/doi/abs/10.1126/science.aal4476) at MIT, I genuinely believed crypto would transform payments and financial services in just a couple of years. A decade later, we’re only just [getting started](https://www.forbes.com/sites/christiancatalini/2025/04/29/the-stablecoin-wars/). Delivering real utility outside the crypto bubble means matching the user experience consumers and businesses already get from traditional solutions. And yes, that requires building a bridge between old and new rails—often through compromises that look downright irrational to crypto purists. You can’t skip the awkward stretch where new and old rails overlap—what Andreas Antonopoulos calls “[infrastructure inversion](https://www.youtube.com/watch?v=KXIaILHl7Rg).” Picture 56k modems hijacking analog phone lines in the ’90s or the first cars rattling down horse-grade gravel roads. This stage puts new technology at a real disadvantage, limiting it to narrow, point solutions rather than sweeping, system-wide change—for a sharp take on this in AI, check out Agrawal, Goldfarb, and Gans’ [work](https://www.youtube.com/watch?v=aRoicN4k5LI). The broader ecosystem needs to shift and adapt before the technology can truly shine. Early Worldcoin tried to skip the inversion phase, making the token the star. Yesterday’s reboot flips the script: it leans into the infrastructure-inversion playbook and on shipping real utility first. You still can’t ship a best-in-class, truly global wallet without latching onto the old rails. On-ramps and off-ramps need to feel effortless—PayPal’s magic when online payments felt dicey—and that seamless flow is what any crypto wallet needs to crack the mainstream. That’s where the World App’s tie-ins with Stripe and a Visa card stand out, delivering familiarity, trust, and instant utility from day one. That need for backwards compatibility also keeps incumbents in play, letting them track new players and roll out fresh services before they’re left behind. The same dynamic is moving crypto into the back office of cross-border payments for businesses and consumers alike. Long term the tech may step into the [spotlight](https://www.forbes.com/sites/christiancatalini/2025/01/16/the-internet-of-money-wants-to-be-free/), but for now it has to coexist with legacy rails to smooth adoption and kill friction. Plenty of crypto concepts—economics included—shine at scale, but without a user-friendly onramp, they stall before hitting that mark. ## 3. Crypto’s Win Hinges on Great Execution Like any new technology, crypto is far from inevitable—no matter what its boosters claim. More precisely, decentralization—crypto’s core principle and its most significant contribution to reshaping markets—is far from a sure thing. Stablecoins show how crypto’s need to link with traditional systems gave rise to a useful tool, yet they risk reintroducing centralized control and [walled-off networks](https://www.forbes.com/sites/christiancatalini/2025/04/29/the-stablecoin-wars/) into what’s supposed to be an open financial stack. I’m betting the open architecture wins—otherwise, what’s the point?—but leading players have incentives to block it. Blania and his team are wagering that consumers will value decentralized control of their data—and that businesses will build better experiences on top of it. I’ve written before about the challenges of [decentralized identity disrupting the status quo](https://www.forbes.com/sites/christiancatalini/2024/12/19/can-cryptos-scarcity-tame-ais-infinite-abundance/), and how centralized players begin with a clear edge in user experience and functionality. To leapfrog those incumbents, Worldcoin first has to persuade users to entrust it with their biometrics. With the U.S. rollout underway, we’ll soon see whether the team struck the right trust-versus-convenience balance. One could imagine a gentler on-ramp: offer an instantly useful perk—a familiar verified badge that unlocks extra features in apps people already love—before asking anyone to peer into the orb. The trade-off, of course, is a weaker proof of identity that begs to be abused. Blania may be right that, in an endless cat-and-mouse with AI, bullet-grade biometrics will be the only rock-solid proof of personhood. Still, he could have eased users in rather than marching them straight to the orb on day one. Airdrop chasers might line up for tokens, but that sugar high fades once the subsidies stop. Sustainable momentum blossoms when you deliver tangible, everyday value—and that’s where the real upside awaits. World App’s payments experience—paired with frictionless, global on- and off-ramps—may well provide exactly that. With an aggressive rollout on the calendar, we’ll soon see whether crypto can break into the mainstream—particularly if Worldcoin can prove that cryptography means privacy and convenience. Apple nailed this with Face ID by cutting seconds from every unlock; Clear did it by pointing travelers to shorter TSA lines. Worldcoin will need to deliver a similarly obvious “oh-wow” moment the very first time someone taps pay. --- ## Edison vs. Westinghouse, Stablecoin Edition - canonical: https://catalini.com/notes/edison-westinghouse-stablecoins/ - original thread: https://x.com/ccatalini/status/1917603682969084096 - date: 2025-04-30 Stablecoin players are staring at an Edison-vs-Westinghouse moment: seize distribution and scale into mainstream payments with new features now—or watch regulators standardize the grid and turn every digital dollar into commodity electrons. [@ForbesCrypto](https://x.com/ForbesCrypto) Only banks, fintechs, startups, and platform giants agile enough to execute the right open-payments play—fast and flawlessly—will plug into a web of interoperable assets and rails, staking their claim to an efficient, streamlined slice of the value chain. Unless today's issuers break into mainstream payments and finance faster than incumbents can mint their own coins, stablecoins will be relegated to background plumbing—fast, dependable, and as thrilling as the wire behind your drywall. In that world, the spoils go to those who own the outlets—wallets, apps, and merchant relationships—through which dollars flow. The stablecoin wars end when coins are unnoticed, only outlets matter. And many of those outlets, inconveniently, are already spoken for. Read more at [@Forbes](https://x.com/Forbes): [forbes.com](https://www.forbes.com/sites/christiancatalini/2025/04/29/the-stablecoin-wars/) --- ## The Stablecoin Wars: The Thread - canonical: https://catalini.com/notes/the-stablecoin-wars-thread/ - original thread: https://x.com/ccatalini/status/1917258653150896282 - date: 2025-04-29 Stablecoins were graduating from the playpen of crypto traders and DeFi “degens” to the main stage of mainstream payments. That fight is now on—albeit mostly off-camera—as a new wave of challengers readies its lines against incumbents Tether and Circle. With flawless execution, a determined stablecoin CEO could still pull off the Herculean feat of turning a plain dollar-jar into something unmistakably special... Short of that breakthrough, though, the industry faces a long slog of competition and fragmentation that could squeeze margins until they’re as thin—and as invisible—as your household electricity bill. The history of electricity provides a warning. In the 1880s, Edison’s direct-current glow from Pearl Street Station turned upscale Manhattan homes into status symbols, while Westinghouse’s alternating current mounted a fierce challenge in the “War of the Currents.” By the 1920s, AC’s scalability and standardized grids had prevailed, stripping electrons of their branding—utilities now competed on price, not panache. Once the meter started ticking, nobody cared who spun the turbines, only who did it cheapest. When it’s time to wrap dollar liabilities, banks and other heavyweight financial institutions will get the crisp ribbon; everyone else is left with scotch tape and yesterday’s newspaper. The logic is simple: the closer you are to the central-bank vault, the lower your cost of minting digital dollars. Stablecoins remain the one part of crypto still tethered to the very TradFi institutions purists dismiss. Yes, software still eats the world, and a savvy issuer could scale fast enough. But a well-armed phalanx of fintechs & banks has a survival-level interest in stopping that. The real question, then, isn’t whether software will eat the world, but whose software gets to do that. Whether stablecoins become distinct franchises or sink into commodity status will be decided by the strategies forged right now. To see why execution matters so much—and why commoditization remains the default—start with first principles and follow the money. At a high level, a stablecoin issuer has just two revenue levers. One is skimming the stock—retaining a slice of the yield from the reserve assets backing each coin. The other is taxing the flow—charging fees whenever the coins move. Both levers come with their own headaches. Strip away the jargon and stablecoins really do just two things: move money (medium of exchange) and hold money (store of value). In practice the two functions blur but treating them as separate buckets makes the market’s trajectory much clearer. Because there’s no single, always-on rail that links national instant-payment systems, payments-orchestration startups have improvised a real-time bridge: convert local fiat into a stablecoin, send the coin over a blockchain, then swap back to fiat on the other side. The double conversion looks clunky on paper, yet the money arrives instantly and settlement is final—so that’s the route some businesses now use for cross-border B2B payments, with a smaller but growing share in remittances too. Based on conversations with the payments teams actually running these "sandwich" corridors—and after stripping out crypto-native noise like high-frequency bots and other gymnastics—I estimate that roughly $10 billion to $30 billion a month already moves through this channel. The "stablecoin sandwich"—and its off-shoots in merchant checkout, gig-economy payouts, and more—is only the opening act. It’s classic infrastructure inversion: the clumsy stage where a new technology has to coexist with the old one. As businesses and consumers get comfortable, they’ll stop ducking in and out and start keeping balances in stablecoins. That’s when the second big job of stablecoins—the store-of-value role—steps into the spotlight. Stablecoins already function as onchain dollar vaults for people who lack easy access to greenbacks—a big reason Tether has exploded across Latin America, Africa, and parts of Asia, especially where hyperinflation burns through local money. But on the store-of-value front, stablecoins are about to face stiff competition from a growing stack of tokenized assets—onchain U.S. Treasuries, money-market funds, and whatever else Wall Street can wrap in code. Standalone issuers must race to carve out real share in everyday payments—fast—if they hope to keep their strategic edge. Fail to embed their coins in mainstream use cases, and the rest of the ecosystem will happily flatten them into just another commodity. Leading crypto exchanges and neobanks aren’t about to let one issuer park a tank on their front lawn. Coinbase just gave PayPal’s PYUSD marquee placement—right beside, but never above, its house favorite USDC. Robinhood and Kraken have meanwhile enlisted in Paxos’s Global Dollar Network (USDG), tossing yet another dollar-pegged contender into the arena. And industry watchers fully expect Revolut and Stripe to unveil coins of their own... ...a smart defensive move before the modular stablecoin stack lets rivals skate straight into their core business. For card networks the stakes are even higher—losing control of settlement simply isn’t an option. Circle, for its part, just introduced the Circle Payments Network (CPN)—an ambitious bid to build a full-stack rail that could one day rival the card networks themselves. If it blinks, nimble orchestration startups—Bridge (now tucked inside Stripe) and BVNK—will happily slot themselves between wallets and merchants and choose the winning coin for every flow. Banks will experiment with every shiny new rail, but their true goal is to keep their own tokenized dollars front-and-center—or, failing that, to claim a slice of the yield on the fiat reserves that stablecoin issuers have to park in their vaults. Large digital platforms won’t sit on the sidelines either. With distribution that spans billions of users, they can press issuers for better economics and fold stablecoins into their flows—all while turning payments into just another feature of a much larger ecosystem. Step back, and the outlines of the endgame come into focus. Only banks, fintechs, startups, and platform giants agile enough to execute this open-payments play—fast and flawlessly—will win. Unless today’s issuers can break into mainstream payments and finance faster than the incumbents can mint their own coins, stablecoins will be relegated to background plumbing—fast, dependable, and about as thrilling as the wire behind your drywall. In that world, the spoils won’t go to whoever mints the slickest dollar clone, but to whoever owns the outlets— the wallets, apps, and merchant relationships—through which those dollars ultimately flow. The stablecoin wars end when no one notices the coins anymore—only the outlets. And many of those outlets, inconveniently, are already spoken for. Full article on [@ForbesCrypto](https://x.com/ForbesCrypto): [forbes.com](https://www.forbes.com/sites/christiancatalini/2025/04/29/the-stablecoin-wars/) --- ## The Stablecoin Wars - canonical: https://catalini.com/writing/the-stablecoin-wars/ - original: https://www.forbes.com/sites/christiancatalini/2025/04/29/the-stablecoin-wars/ - date: 2025-04-29 - outlet: forbes Last week the stablecoin world played whack-a-mole with headlines. PayPal and Coinbase tightened their [collaboration](https://x.com/acce/status/1915391089168597234) around PYUSD—surprising, given Coinbase’s long, profitable ride with Circle’s USDC, which earned the exchange almost as much revenue as Circle itself in 2024. Tether bolstered its U.S. credentials by teaming with SoftBank to bankroll Twenty One Capital, a $3.6 billion bitcoin-buying SPAC led by Brandon Lutnick—son of Commerce Secretary Howard Lutnick. Stripe’s Patrick Collison teased a stablecoin product his team has been wanting to build for years, while Circle, preparing for its IPO, outlined a payment network meant to elbow past SWIFT—and potentially Visa and Mastercard. Not to be outdone, Visa and Mastercard lobbed their own stablecoin trial balloons right back. Back in 2024, Professor Jane Wu of UCLA and I [warned](https://hbr.org/2024/08/the-race-to-dominate-stablecoins) that a fight was coming: stablecoins were graduating from the playpen of crypto traders and DeFi “degens” to the main stage of mainstream payments. That fight is now on—albeit mostly off-camera—as a new wave of challengers readies its lines against incumbents Tether and Circle. Once Capitol Hill finally lifts the curtain with legislation, expect the background hum to crank up to full concert volume. No player is likely to sprint away with dominant market share—unless it moves at break-neck speed and executes a razor-sharp playbook. The last serious bid for mass adoption came in 2021, when Libra was hours from a pilot launch before the Federal Reserve Board pulled the plug. Different regulatory environment, but the lesson holds: the forces that killed Libra may keep today’s market from ever coalescing around a single giant. With flawless execution, a determined stablecoin CEO could still pull off the Herculean feat of turning a plain dollar-jar into something unmistakably special; short of that breakthrough, though, the industry faces a long slog of competition and fragmentation that could squeeze margins until they’re as thin—and as invisible—as your household electricity bill. ## Who Holds the Upper Hand? The history of electricity provides a warning to stablecoin issuers. In the 1880s, Edison’s direct-current glow from Pearl Street Station turned upscale Manhattan homes into status symbols, while Westinghouse’s alternating current mounted a fierce challenge in the “War of the Currents.” By the 1920s, AC’s scalability and standardized grids had prevailed, stripping electrons of their branding—utilities now competed on price, not panache. Once the meter started ticking, nobody cared who spun the turbines, only who did it cheapest. When it’s time to wrap dollar liabilities, banks and other heavyweight financial institutions will get the crisp ribbon; everyone else is left with scotch tape and yesterday’s newspaper. The logic is simple: the closer you are to the central-bank vault, the lower your cost of minting digital dollars. Stablecoins remain the one part of crypto still tethered to the very TradFi institutions purists love to deride. Existing issuers will scramble for bank charters—or at least tight bank partnerships—while a wave of new contenders crowds the field and squeezes margins. Yes, software still eats the world, and a savvy issuer could scale fast enough to turn “Pay with x” into a household phrase. But a well-armed phalanx of fintechs and legacy banks has a survival-level interest in stopping exactly that. The real question, then, isn’t whether software will eat the world, but whose software gets the seat at the table. Libra might have grabbed market share on the back of Meta’s four billion users and the two-dozen heavyweight partners it corralled—enough to make incumbents break a sweat. But its distributed governance and shared-incentive model cut both ways: democratic enough to win more support, slow enough to miss the moment. Overall, bootstrapping a new payment network without giving real ownership to wallets, merchants, and other stakeholders is brutally hard—just ask Visa, which only scaled after spinning BankAmericard into a member-owned cooperative so thousands of banks had skin in the game. Whether stablecoins become distinct franchises or sink into commodity status will be decided by the strategies forged right now. To see why execution matters so much—and why commoditization remains the default—start with first principles and follow the money. How do issuers make money today, and what happens to those revenues once the market reaches equilibrium? ## Stock vs. Flow At a high level, a stablecoin issuer has just two revenue levers. One is skimming the stock—retaining a slice of the yield from the reserve assets backing each coin. The other is taxing the flow—charging fees whenever the coins move. Both levers come with their own headaches. First, even if rates remain lofty, any juicy reserve yield won’t sit in the issuer’s pocket for long. The scramble for market share will force issuers to recycle most of it into user incentives. PayPal has already dangled a 3.7 percent reward on PYUSD balances, and rivals won’t leave that challenge unanswered. Economists like to picture the market at equilibrium first and then reason backward. Run that thought experiment here and one fact jumps out: neither institutions nor consumers will voluntarily leave yield on the table. Early crypto users accepted a few hundred basis points siphoned off by issuers because DeFi returns were stratospheric and alternatives were scarce. But fintech is rewiring that bargain—moving idle cash into interest-bearing havens is now a tap away. The old bottleneck of routing everything through a zero-interest checking account is being dismantled, app by app, across the globe. Moreover, a dip in interest rates can gut a stablecoin issuer’s economics—especially if it’s dragging around hefty fixed costs or a bloated payroll. Tether’s lean model is instructive: once you’ve fought the uphill battle to secure coveted distribution channels and deep liquidity—a moat few can cross—the remaining hurdles to running a stablecoin are surprisingly low. Second, earning on the flow of coins is no picnic either. Extracting a fee from every hop is technically tricky—we wrestled with that while designing Libra. Our modeling showed that, at scale and under competitive pressure, even an issuer that controls both the asset and the network would be forced to push transaction fees toward zero and make money on higher-margin add-ons instead. Most of those add-ons didn’t exist then and still don’t for everyday users; they’ll emerge only when stablecoins function as the operating system for programmable finance rather than as basic payment plumbing. And because payments—domestic and cross-border alike—are being commoditized even faster than stablecoins themselves, issuers need to climb the value stack or watch their margins evaporate. An issuer could, of course, launch a stablecoin network that starts wide-open—minting (entry) remains free—then slowly crank up redemption fees on cashing out (the exit), and make interoperability awkward unless it sits in the middle. That bait-and-switch cuts against crypto’s purpose—true decentralization—the very platform strategy ethos Chris Dixon crystallized in [2018](https://cdixon.org/2018/02/18/why-decentralization-matters). In that scenario, crypto will have taken the scenic route only to recreate a bigger, more centralized middleman. Or, as Lampedusa wrote in The Leopard, “If we want things to stay as they are, things will have to change.” I’m still optimistic. Once you’ve zipped money across a genuinely open network—cleared in seconds, no gatekeepers—it’s hard to accept anything less, whatever shape today’s market takes. So, if the stablecoin market doesn’t regress into a digital oligopoly, what will it look like? Back to first principles: the shape of the landscape follows from the two core jobs stablecoins perform. ## Stablecoins’ Two Core Jobs Strip away the jargon and stablecoins really do just two things: move money (medium of exchange) and hold money (store of value). In practice the two functions blur—most real-world uses fall somewhere between payment rail and savings vehicle—but treating them as separate buckets makes the market’s trajectory much clearer. The medium-of-exchange use case with the most real-world momentum is the “stablecoin sandwich.” Picture it this way: inside any given country, lightning-fast rails—PIX in Brazil, UPI in India, SPEI in Mexico—have conditioned people to expect money to move 24/7. But the moment a payment crosses a border, that speed vanishes. Some dreamers still imagine the BIS knitting these national rails into a grand “Finternet,” but asking Basel to ship working software across borders is like mailing glaciers by express: slow, pricey, and mostly water by the time it arrives. In the meantime, stablecoins slip neatly between those domestic slices, giving everyone the always-on settlement they’ve come to expect. So payments-orchestration start-ups have stepped in with a real-time workaround: flip local fiat into a stablecoin, shoot it across a blockchain, and cash out in local currency at the other end. The double conversion may look clunky on paper, yet the funds arrive instantly and settlement is final—making it the go-to route for some cross-border B2B payments, with a growing slice of the remittance market following suit. Because there’s no single, always-on rail that links those national instant-payment systems, payments-orchestration start-ups have improvised a real-time bridge: convert local fiat into a stablecoin, send the coin over a blockchain, then swap back to fiat on the other side. The double conversion looks clunky on paper, yet the money arrives instantly and settlement is final—so that’s the route some businesses now use for cross-border B2B payments, with a smaller but growing share in remittances too. Based on conversations with the payments teams actually running these “sandwich” corridors—and after stripping out crypto-native noise like high-frequency bots, onchain arbitrage, and other blockchain gymnastics—I estimate that roughly $10 billion to $30 billion a month already moves through this channel. This flow is pure high-velocity: users jump into a stablecoin at one end and exit just as quickly at the other. The deeper a stablecoin’s liquidity pool, the clearer its edge—larger volumes clear without hiccups and each transfer loses fewer basis points along the way. The economics of the “sandwich” will evolve as the market matures. Savvy issuers could use local entities to mint and burn stablecoins on each side of a corridor, recreating onchain the balance-sheet sleight of hand that Wise already performs by updating its internal ledgers. Wise, in fact, could flip its business APIs into a suite of domestic stablecoins to enter the fray. The same play is open to globally licensed crypto exchanges and to banks with an international footprint—though only banks, sitting closest to the central-bank metal, can execute it at materially lower cost. The “stablecoin sandwich”—and its off-shoots in merchant checkout, gig-economy payouts, and more—is only the opening act. It’s classic [infrastructure inversion](https://www.youtube.com/watch?v=KXIaILHl7Rg): the clumsy stage where a new technology has to coexist with the old one. As businesses and consumers get comfortable, they’ll stop ducking in and out and start keeping balances in stablecoins. That’s when the second big job of stablecoins—the store-of-value role—steps into the spotlight. Stablecoins already function as onchain dollar vaults for people who lack easy access to greenbacks—a big reason Tether has exploded across Latin America, Africa, and parts of Asia, especially where hyperinflation burns through local money. Forthcoming U.S. legislation should expand the roster of institutions and everyday consumers willing to park balances in stablecoins, while clarifying the legal safeguards that protect everyone. Right now, U.S. stablecoins operate under a patchwork regime that can’t support real scale, but Congress is ready to stitch up the gaps. But on the store-of-value front, stablecoins are about to face stiff competition from a growing stack of tokenized assets—onchain U.S. Treasuries, money-market funds, and whatever else Wall Street can wrap in code. The big custodians, investment banks, and asset managers are already dipping their toes; as volumes scale, they’ll wade in fully, expanding the menu for holding value and for high-grade institutional global settlement. ## Where the Battle Will Be Won—and Lost Standalone issuers must race to carve out real share in everyday payments—fast—if they hope to keep their strategic edge. Fail to embed their coins in mainstream use cases, and the rest of the ecosystem will happily flatten them into just another commodity. Leading crypto exchanges and neobanks aren’t about to let one issuer park a tank on their front lawn. Coinbase just gave PayPal’s PYUSD marquee placement—right beside, but never above, its house favorite USDC. Robinhood and Kraken have meanwhile enlisted in Paxos’s Global Dollar Network (USDG), tossing yet another dollar-pegged contender into the arena. And industry watchers fully expect Revolut and Stripe to unveil coins of their own—a smart defensive move before the modular stablecoin stack lets rivals skate straight into their core business. For card networks the stakes are even higher—losing control of settlement simply isn’t an option. Mastercard just [unveiled](https://x.com/MastercardNews/status/1916896208187986114) an end-to-end stablecoin framework that lets wallets, acquirers and merchants settle directly onchain, while Visa is slated to [reveal](https://x.com/jackforestell/status/1916948268216684577) more about its stablecoin play tomorrow. Circle, for its part, just introduced the Circle Payments Network ([CPN](https://www.circle.com/cpn/))—an ambitious bid to build a full-stack rail that could one day rival the card networks themselves. If it blinks, nimble orchestration startups—Bridge (now tucked inside Stripe) and BVNK—will happily slot themselves between wallets and merchants and choose the winning coin for every flow. Banks will experiment with every shiny new rail, but their true goal is to keep their own tokenized dollars front-and-center—or, failing that, to claim a slice of the yield on the fiat reserves that stablecoin issuers have to park in their vaults. Large digital platforms won’t sit on the sidelines either. With distribution that spans billions of users, they can press issuers for better economics, fold stablecoins into their existing checkout flows, and shave costs to improve margins—all while turning payments into just another feature of a much larger ecosystem. Step back, and the outlines of the endgame come into focus. Only banks, fintechs, startups, and platform giants agile enough to execute this open-payments play—fast and flawlessly—will plug into a web of interoperable assets and rails, staking their claim to an efficient, streamlined slice of the value chain. Unless today’s issuers can break into mainstream payments and finance faster than the incumbents can mint their own coins, stablecoins will be relegated to background plumbing—fast, dependable, and about as thrilling as the wire behind your drywall. In that world, the spoils won’t go to whoever mints the slickest dollar clone, but to whoever owns the outlets— the wallets, apps, and merchant relationships—through which those dollars ultimately flow. The stablecoin wars end when no one notices the coins anymore—only the outlets. And many of those outlets, inconveniently, are already spoken for. --- ## With Dollar Hegemony At Risk, Could This Be Crypto’s Moment? - canonical: https://catalini.com/writing/dollar-hegemony-cryptos-moment/ - original: https://www.forbes.com/sites/christiancatalini/2025/04/11/with-dollar-hegemony-at-risk-could-this-be-cryptos-moment/ - date: 2025-04-11 - outlet: forbes On Wednesday, President Trump [announced](https://truthsocial.com/@realDonaldTrump/posts/114309144289505174) a much-needed 90-day pause on the steep tariffs he proposed last week during “Liberation Day”—likely prompted by the significant market turmoil his initial decision caused, including a troubling spike in key U.S. Treasury yields. For now, most countries still face a substantial 10% tariff, with two notable exceptions: Russia, exempt from new tariffs but sidelined due to sanctions, and China, singled out with a punishing 145% tariff. For historical context, consider the infamous Smoot-Hawley Tariff Act of 1930, widely blamed for deepening the Great Depression. That measure raised the average tariff rate across goods to just 19.8%, and even then, it strategically targeted specific agricultural and industrial goods. Economists rarely find consensus—but the empirical evidence against sweeping tariffs is nearly unanimous. Tariffs essentially act as an indirect tax on consumers, provoke retaliatory measures, drive inflation higher, and destabilize financial markets. While targeted and temporary tariffs can indeed protect nascent industries from premature foreign competition, these measures must be carefully phased out once industries mature. Similarly, selective tariffs might support essential national security supply chains, but only if implemented judiciously.Yet, the last two weeks represented something unprecedented. To fully grasp the long-term implications, we must start with CEA Chairman Steve Miran’s recent [comments](https://www.whitehouse.gov/briefings-statements/2025/04/cea-chairman-steve-miran-hudson-institute-event-remarks/) on America’s role in providing "global public goods": primarily, a global security umbrella, and secondarily, maintaining the dollar’s position as the global reserve currency. What Miran overlooks is that these roles are inseparable: you cannot maintain reserve currency dominance without military strength. Geopolitical influence and credibility depend fundamentally on a nation’s capacity to protect its interests, both at home and overseas—whether safeguarding global maritime trade routes, undersea internet cables, critical energy resources and rare materials, or vital payment and financial infrastructures. But Miran’s gravest misreading of economics emerges in his claim that being the issuer of the global reserve currency burdens the United States disproportionately. The reality, as most economists recognize, is precisely the opposite: the U.S. dollar's reserve status confers an “exorbitant privilege.” And what exactly does this privilege entail? The global appetite for dollars affords the U.S. government, businesses, and residents lower borrowing costs and greater purchasing power. It channels international capital into American financial markets, boosting growth. This unique position generates substantial seigniorage profits—effectively subsidizing American imports, facilitating persistent trade deficits without immediate economic repercussions, and reinforcing U.S. geopolitical dominance. This privilege is so pronounced that even during severe global disruptions—such as the COVID-19 lockdowns or the 2008 financial crisis—investors consistently flocked to U.S. Treasuries as a safe haven, enabling flexible fiscal responses. In 2008, the demand for safety even outstripped the supply increase from government auctions used to fund massive bailouts. Yet Miran, alongside Trump’s trade advisor Peter Navarro, disregards this reality, arguing instead that importing affordable goods in exchange for low-yield U.S. debt—essentially leveraging the trust in U.S. institutions—is a losing proposition. More dangerously, Miran flips economic logic entirely, asserting there is no privilege, only burdens, insisting the rest of the world should shoulder the costs. Miran suggests that countries should either accept tariffs without retaliation or, even more boldly, simply "write checks to the U.S. Treasury." This intriguing idea somehow overlooks the fact that these countries already effectively "pay" for the privilege of dollar access by sending actual valuable goods and services in exchange for dollars—currency the U.S. conveniently prints at will. This arrangement already generously supports America’s ability to finance deficits cheaply and repay its debts effortlessly in its own currency, which you’d think might be enough of a sweet deal without demanding extra compensation. Yes, great power involves great responsibility. An excessive reliance on cheap capital risks the fate historically experienced by every prior issuer of the reserve currency. Ray Dalio repeatedly warned of this scenario: spiraling debt leading to economic and military overstretch, unchecked inequality, declining investments in education and infrastructure, ultimately eroding trust through endless debt accumulation and money printing. But the real remedy lies in disciplined fiscal policy, structural reforms encouraging innovation, and strategic investments in education, upward mobility, and infrastructure. Miran and Navarro’s policies instead erode the very trust underpinning the dollar’s global status. Their strategy resembles Emperor Diocletian’s late Roman Empire policies—attempting to tax distant colonies heavily to sustain central power, ultimately weakening loyalty and accelerating decline. If allies doubt America's commitment—both militarily and economically—the downward spiral only quickens. Whether we like it or not, America’s leading "export" is arguably its financial sector. Certainly, rebuilding manufacturing capacity in critical sectors is important, but labor-intensive manufacturing jobs aren’t returning—those jobs are now migrating from China to Vietnam, India, and Bangladesh. The future depends on innovation and leadership in fields like artificial intelligence, robotics, and defense technology—not on chasing nostalgic dreams of past industrial glories. Damaging relations with global trading partners, especially allies, through indiscriminate tariffs threatens the dollar’s dominance, prompting nations to seek alternatives for security and commerce. Losing reserve currency status means a dramatic decline in geopolitical, economic, and military influence—relegating America, like Spain, the Netherlands, and Britain before it, to the ranks of former global economic powers. This risk explains why investors closely watched U.S. Treasury yields during the recent market turbulence. Rising yields—partly driven by hedge funds unwinding leveraged trades and foreign central banks selling treasuries to stabilize their currencies ahead of tariff fallout—likely pressured Trump into calling off his gamble. Continued erratic policy moves could erode investor confidence in U.S. Treasuries as safe assets, and ultimately threaten the dollar’s reserve currency status. Thus, Miran and Navarro’s belief that America should tax the world for using dollars may ironically accelerate the dollar’s decline, inadvertently resolving the trade deficit—but in the most painful way possible. ## If the Dollar Falters, Is It Crypto’s Moment to Shine? Likely not—at least not immediately. Bitcoin might offer [neutrality](https://a16zcrypto.com/posts/article/bitcoin-strategic-reserve/) in a fragmented global system, but barring institutional collapse in the U.S., this scenario remains distant. Similarly, no fiat currency stands ready to clearly inherit the dollar's role. The Eurozone, despite boasting a robust economy, deep financial markets, and a credible, independent central bank, still faces significant challenges—fragmented fiscal policies, internal political tensions, and the absence of a unified and strong military presence. While the euro remains the second most-traded currency globally, its potential to become a dominant reserve currency is constrained unless it achieves deeper fiscal integration, resolves internal disputes, and expands trade alliances with the UK, Canada, and other global partners. China’s RMB, supported by the world's second-largest economy and extensive global trade presence, also faces considerable hurdles. Persistent capital controls, transparency concerns, and fundamental trust issues regarding the rule of law significantly hinder broader adoption by Western economies. Absent a major geopolitical transformation, akin to the shifts following World War II, the RMB's global acceptance remains limited. One potential solution could be a basket of currencies, similar to the approach we designed for the [Libra project](https://mitsloan.mit.edu/shared/ods/documents?PublicationDocumentID=5859). However, determining the basket’s weighting would inevitably trigger endless geopolitical debates and infighting, as evidenced by the limited appeal of Special Drawing Rights (SDR), which never gained widespread traction beyond central bank use. Nevertheless, a currency basket could better capture today's shifting global dynamics, balancing trade interconnectedness and recognizing the evolving international order. The real challenge, however, lies in creating a credible new unit of account—a monumental task, as even the EU discovered during its own integration efforts. Trump’s gamble might be to pressure everyone but China into agreements ironically reminiscent of the Trans-Pacific Partnership (TPP), which was originally designed to lower tariffs and improve intellectual property and labor standards around the Pacific Rim, as summarized by investor Bill Ackman: Yet, the risks are substantial, especially since China is unlikely to back down. If tensions persist and significant economic disruption occurs, many more scenarios become plausible. Countries worldwide, including Europe, might increasingly advocate for a neutral stance, underscoring the importance of forthcoming EU-China negotiations. Alternatively, the world could surprisingly switch to Bitcoin—which already functions as a somewhat unusual weighted basket representing various countries’ differing views about the future of monetary policy. Ultimately, this is America’s game to lose—and ideally, sensible policies like free trade, serious investments in education and critical infrastructure, genuine innovation, and smart bets on strategic sectors will win out over short-term trade skirmishes and questionable economic theories. After all, undermining your own strengths is rarely a winning strategy. --- ## Crypto Adoption Is Taking Two Roads - canonical: https://catalini.com/notes/crypto-adoption-two-roads/ - original thread: https://x.com/ccatalini/status/1910344849444020725 - date: 2025-04-10 Something fascinating about crypto and payments is that adoption is quietly taking two different roads—which, conveniently, will eventually run into each other. (h/t [@cdixon](https://x.com/cdixon) [@a16zcrypto](https://x.com/a16zcrypto)) First, you've got stablecoins and Bitcoin quietly doing their thing behind the scenes, powering real-time global payments. Think of this as crypto's boring (but effective!) B2B job—bridging otherwise incompatible domestic payment rails. [x.com](https://x.com/HadickM/status/1910314025847496795) The consumer doesn't notice anything different, except suddenly cross-border payments settle instantly and cost less. Fewer middlemen, fewer headaches—magic, sort of! 🪄 Including on the most competitive cross-border corridor: 🇺🇸 <> 🇲🇽 [x.com](https://x.com/lightspark/status/1870127990715126205) --- ## What Keeps a Currency Dominant - canonical: https://catalini.com/notes/what-keeps-a-currency-dominant/ - original thread: https://x.com/ccatalini/status/1909283322934837587 - date: 2025-04-07 Historically, a currency’s global dominance isn’t just about size or military might.🪖 It’s about trust, stability, and forward-looking strategy. What could the US have done better to strengthen, rather than erode, its leadership? 🗽 💰First, carefully containing national debt—not by dramatic austerity, but through strategic and targeted cost-cutting. Fiscal discipline isn’t flashy, but economic history suggests it’s foundational to long-term stability. Next, aggressively investing in innovation, including advanced manufacturing. The shape of production 5 years from now will be radically different. Leading that transition—not reacting to it—is key to maintaining economic primacy. 🧑‍🎓🧑‍🏫 Education isn't just social policy; it's economic policy. Training the next generation's workforce is one of the best investments a nation can make. With AI rapidly advancing, preparing workers for the future becomes even more urgent. --- ## Bitcoin Is the Ultimate Libra Basket - canonical: https://catalini.com/notes/bitcoin-ultimate-libra-basket/ - original thread: https://x.com/ccatalini/status/1898571693913727029 - date: 2025-03-09 There is no need to reboot Libra, because Bitcoin is the ultimate Libra basket. [x.com](https://twitter.com/davidmarcus/status/1898561942324703668) We once believed we could engineer a flawless currency weighting scheme—balancing store-of-value with low volatility for everyone. Bold, elegant, and ultimately naïve! In truth, governing those weights is as mythical as achieving true decentralization with stablecoins. Like the internet, Bitcoin’s adoption is a messy orchestra of choices. Individuals, firms, and even nations decide how much to participate, crafting decentralized, permissionless, but perfect Libra weights. --- ## Trump’s Strategic Bitcoin Reserve: Balancing Crypto And Dollar Dominance - canonical: https://catalini.com/writing/trumps-strategic-bitcoin-reserve/ - original: https://www.forbes.com/sites/christiancatalini/2025/03/06/trumps-bitcoin-move-how-the-strategic-reserve-balances-crypto-and-dollar-dominance/ - date: 2025-03-06 - outlet: forbes President Trump just signed an [executive order](https://www.whitehouse.gov/presidential-actions/2025/03/establishment-of-the-strategic-bitcoin-reserveand-united-states-digital-asset-stockpile/) establishing a Strategic Bitcoin Reserve and a U.S. Digital Asset Stockpile—a move that might sound like it’s right out of a cyberpunk novel. But crucially, it’s a calibrated action that embraces crypto’s future influence without giving the world the impression that the United States has lost faith in its own currency. ## A Targeted Approach to Bitcoin—Without the Dollar Panic By restricting the Strategic Reserve primarily to forfeited Bitcoin, the administration [reduces the risk](https://a16zcrypto.com/posts/article/bitcoin-strategic-reserve/) of telegraphing any hedge against the greenback. This contrasts sharply with more aggressive alternatives—such as large-scale federal purchases of Bitcoin on the open market or, in a more extreme scenario, backing the dollar with Bitcoin as if returning to a quasi-gold standard. The current approach preserves market stability and avoids sparking unnecessary concerns about the government’s faith in U.S. monetary policy. ### Setting a High Bar for “Strategic” Status The order recognizes Bitcoin’s longstanding track record, decentralization, and institutional adoption. By labeling it as the only “strategic” asset, the order keeps the bar high, reducing the likelihood of lobbying from projects that are neither widely adopted nor meaningfully decentralized. Meanwhile, the U.S. Digital Asset Stockpile will hold other seized digital assets—giving the government flexibility to learn more about these tokens without endorsing them. The rationale is straightforward: like early-stage startups in the dot-com era, some of these assets may eventually prove valuable, whereas many others will likely become irrelevant. ### Keeping the Dollar’s Dominance While Embracing Cryptocurrencies The executive order sends a clear message: the United States intends to lead in crypto innovation, much like it has in traditional finance, but with minimal disruption to the existing monetary system. Moreover, the policy maintains a cost-neutral stance for any potential future Bitcoin acquisitions, ensuring the government does not expand its balance sheet purely for speculative purposes. ### The Future Is Bitcoin and USD Stablecoins Together The next steps in this broader strategy involve establishing a comprehensive framework for USD-denominated stablecoins, which—alongside Bitcoin and other permissionless networks—could underpin a more [open and resilient financial infrastructure](https://www.forbes.com/sites/christiancatalini/2025/01/16/the-internet-of-money-wants-to-be-free/). If done correctly, this platform approach maintains the dollar’s role as the “killer app” while leveraging the neutrality and global reach of networks like Bitcoin. By carefully managing optics and practical considerations, the executive order reveals a government prepared to explore emerging digital frontiers without sacrificing the dollar’s central role. As crypto-related activity grows, this stance allows the U.S. to become a primary hub for Bitcoin and decentralized finance, preserving both innovation and monetary stability. --- ## Decentralization Theater - canonical: https://catalini.com/notes/decentralization-theater/ - original thread: https://x.com/ccatalini/status/1896586283407077824 - date: 2025-03-03 Decentralization theater is crypto’s oldest magic trick: networks with puppet masters backstage imitate the look of true peer-to-peer systems, all to rake in cash. It’s been a grift for over a decade, and the audience still claps. These DINOs—decentralized in name only—are just dressed-up databases. They blend in with real networks to attract funding and grow fast. Investors toss money at the costume party, dazzled by the masks. [x.com](https://x.com/naval/status/1896259911794978895) Here’s the kicker: DINOs often sprint ahead early because they’re centralized. No messy consensus debates—just a CEO barking orders. Speed’s their edge, until you realize it’s a feature, not a bug, of the old world. But the governance? The limits? Pure vanilla centralization with a blockchain cherry on top. Innovative? Not really—unless you count the scale of the hustle. A strategic Bitcoin reserve is already a weak case. For DINOs, it makes no sense—they’re assets pretending to be something they’re not. Forget hoarding crypto, BTC or otherwise. The U.S. should play to its strength: set clear rules, unleash the good actors, and flush out the DINOs. Growth comes from refereeing the game, not joining the pile-on. --- ## Slowly, Then Suddenly: Programmable Dollars - canonical: https://catalini.com/notes/slowly-then-suddenly-programmable-dollars/ - original thread: https://x.com/ccatalini/status/1895171155776118851 - date: 2025-02-27 One day you’re rummaging for paper bills; the next, your wallet is lines of code. It’s the classic "slowly, then suddenly" momentum toward digital, programmable dollars—and [@patrickc](https://x.com/patrickc)’s annual letter offers a timely preview of what’s to come: [x.com](https://x.com/patrickc/status/1895097871369937250)) Use cases are still niche, but each one illustrates the growing value of the open infrastructure—and signals how quickly it’s moving from theory to practice. [@venturedan](https://x.com/venturedan): "we have seen numerous, relatively young startups (months since launch) which are scaling at an astronomical pace and already processing very large volume across different layers of the ecosystem." --- ## First Principles and the Colossus Sprint - canonical: https://catalini.com/notes/first-principles-colossus/ - original thread: https://x.com/ccatalini/status/1891864076105425257 - date: 2025-02-18 Attacking problems from first principles is powerful— [@OpenAI](https://x.com/OpenAI)’s old edge? Scale and talent. Then Colossus hit, built in record speed, with [@nvidia](https://x.com/nvidia) prioritizing [@xai](https://x.com/xai)’s orders and fancy networking demands. [x.com](https://x.com/SawyerMerritt/status/1891719655301267599) [@MichaelDell](https://x.com/MichaelDell) and [@charlesliang](https://x.com/charlesliang) racing to juice up [@xai](https://x.com/xai) with liquid-cooled racks in record time. Nothing like an AI boom to make CEOs personally oversee the plumbing. Just don’t ask about the margins—or the water bill. [x.com](https://x.com/Supermicro_SMCI/status/1850915433073025140) But really, the rest of the secret sauce is the brain trust: [@ibab](https://x.com/ibab), [@makro_ai](https://x.com/makro_ai), [@Yuhu_ai_](https://x.com/Yuhu_ai_), [@ChrSzegedy](https://x.com/ChrSzegedy), [@jimmybajimmyba](https://x.com/jimmybajimmyba), [@TobyPhln](https://x.com/TobyPhln), [@rpoo](https://x.com/rpoo), [@TheGregYang](https://x.com/TheGregYang), [@Guodzh](https://x.com/Guodzh), and more, all with a nudge from [@Tesla_AI](https://x.com/Tesla_AI). That's how you cook up self-improving magic. [x.com](https://x.com/Tesla_AI/status/1884458086859170050) --- ## Beyond Stockpiling Bitcoin - canonical: https://catalini.com/notes/beyond-stockpiling-bitcoin/ - original thread: https://x.com/ccatalini/status/1887607073736958439 - date: 2025-02-06 Instead of merely stockpiling Bitcoin, the U.S. must overhaul its financial architecture to prepare for—and ultimately succeed in—open networks. The upside is a more transparent financial system in which the U.S. continues to leverage its most powerful asset: the dollar. Similar to how tech leaders open-source critical components to establish industry norms while monetizing other areas... ...the U.S. can expand its dollar platform and ensure seamless interoperability with Bitcoin and stablecoins. With its extensive expertise in platform competition, the current administration is uniquely positioned to take this bet. --- ## Bitcoin Reserves Won’t Secure America’s Future—Only A Platform Play Will - canonical: https://catalini.com/writing/bitcoin-reserves-platform-play/ - original: https://www.forbes.com/sites/christiancatalini/2025/02/06/bitcoin-reserves-wont-secure-americas-future-only-a-platform-play-will/ - date: 2025-02-06 - outlet: forbes I just finished a great book on Kindle called DeFinancing the Dollar: Bitcoin the Rescue by author Shi Bok Won, just released last month. It’s a bit short, but still an awesome read on where the global digital financial system is headed, and honestly, it seems like it’s here to stay for the rest of the century. The book’s take lines up perfectly with this article, and both really opened my eyes to what’s coming. Hopefully, we can all keep up with the changes. Can we please get some MMT’s Money Market Tokens? You know a blockchain setup where every million dollars invested mines a new token and all whose investments are registered on that tokens block gets interest, dividend, and capital distribution payments based on the assets that the biggest provider or “Block Captain” creating the token directs the tokens funds, or something like that. The blockchain technology is still in its infancy and I’m pretty sure that we can do better than mining something whose adoption and liquidity is questionable for long periods of time. To me it only makes sense to mine the most liquid asset on the planet, The US Dollar!!! This will put and keep all Americans in the drivers seat of their financial freedoms while also searching our resources with the developing world. ## Download The Forbes App By[Christian Catalini](https://www.forbes.com/sites/christiancatalini/), Contributor. In the wake of President Trump’s unexpected [executive order](https://www.whitehouse.gov/presidential-actions/2025/02/a-plan-for-establishing-a-united-states-sovereign-wealth-fund/) this Monday—which hinted at establishing a U.S. sovereign wealth fund and incorporating Bitcoin into the national strategic reserve—it is crucial to pause and [weigh the tradeoffs](https://a16zcrypto.com/posts/article/bitcoin-strategic-reserve/) involved. While accumulating Bitcoin might seem like an obvious strategy, a more ambitious—and ultimately more effective—plan calls for overhauling the nation’s financial architecture to unlock the potential of [open networks](https://www.forbes.com/sites/christiancatalini/2025/01/16/the-internet-of-money-wants-to-be-free/).The United States occupies a unique position in global finance by issuing the world’s reserve currency—a status often referred to as the “exorbitant privilege.” But it’s more than a label economists use: it fundamentally reflects the global trust in American governance, economic resilience, and the enduring safety of the dollar as a store of value. ## **The biggest risk posed by a Bitcoin reserve** Proponents of a U.S. Bitcoin reserve argue that Bitcoin’s status as “digital gold”—decentralized and without a single point of failure—positions it as a neutral global asset, detached from any one nation’s monetary policy. But would accumulating Bitcoin truly secure U.S. financial leadership? Unlikely. Strategic reserves are meant to ensure stability and provide immediate access during a crisis. Countries store dollars or oil because they need them to repay debts, settle cross-border obligations, and keep essential systems running when supply chains falter. For all its promise, Bitcoin doesn’t meet these near-term needs. But there’s a bigger risk: if America began amassing Bitcoin on a large scale, it might be seen as a hedge against the dollar itself—raising alarms and giving rivals like China or Russia an opening to claim that the U.S. no longer trusts its own currency. Bitcoin’s long-term trajectory could be bright. It could grow into a [universal settlement layer](https://a16zcrypto.com/posts/article/bitcoin-strategic-reserve/) for nations wary of each other’s financial rails. But that transition is still unfolding. Today, the more critical step is building the infrastructure to let Bitcoin and other cryptocurrencies evolve from speculative assets into a key component of global finance. Acquiring a large stash now will drive gains for early adopters and fuel speculation, but it offers minimal strategic advantage. ## **Raising the stakes with a U.S. dollar platform strategy** A far more powerful move than simply buying Bitcoin is to [shape its integration into the U.S. financial system](https://a16zcrypto.com/posts/article/bitcoin-strategic-reserve/). Think of the early internet: the biggest winners weren’t those who just hoarded domain names; they were the ones who built on top of open protocols, becoming the backbone of a new digital economy. ### **1. Become a global Bitcoin hub** Rather than treating Bitcoin solely as an asset, recognize it as an open, permissionless network for money movement. Even countries that shun the dollar might end up using Bitcoin’s neutral ledger. By building robust Bitcoin infrastructure—including secure custody solutions, regulated exchanges, and efficient on- and off-ramps—the U.S. can attract significant economic activity and innovation. This is an opportunity to export American regulatory and compliance frameworks, technological expertise, and financial best practices as the global financial stack evolves. Bitcoin might be the first cryptocurrency to capture financial institutions’ attention, but it won’t be the last. As decentralized finance (DeFi) evolves, the true opportunity lies in becoming the digital capital of that emerging ecosystem. ### **2. Drive adoption of USD stablecoins** Dollar-pegged stablecoins extend the reach of the U.S. dollar by modernizing cross-border payments and making it easier for people worldwide to hold, send, and spend in USD. Their widespread adoption hinges on proper regulation—ensuring transparency, robust backing, and consumer protections. Managed effectively, stablecoins can reinforce dollar dominance by effectively turning the dollar into the digital currency of choice for innovative financial services built on open networks. While [dollarization](https://www.forbes.com/sites/christiancatalini/2024/11/01/why-everyone-is-wrong-about-stablecoins/) may be unwelcome and even hinder USD stablecoin adoption in some regions, that’s exactly where Bitcoin can thrive—as a robust complement and bridge between competing financial systems in a multipolar world. ### **3. Empower U.S. innovation and experimentation** The U.S. didn’t scale the internet on its own—it laid the groundwork that allowed private innovation to flourish. Tech giants emerged by building on top of open protocols within a supportive regulatory environment. Today, a similar strategy could enable U.S. startups and established financial institutions to develop innovative cryptocurrency and stablecoin-based financial services, thereby broadening the dollar’s influence rather than limiting it. A balanced approach—combining robust government oversight with market-driven innovation—will keep the U.S. ahead of top-down alternatives like central bank digital currencies, especially those from authoritarian regimes that are fundamentally incompatible with open networks. ## **A bold, strategic leap** This more complex strategy could secure the U.S. dollar’s dominance for decades. Instead of stockpiling Bitcoin—a move that might undermine confidence—the U.S. could integrate it into its financial system, allowing the government to shape the emerging ecosystem by setting standards and guiding innovation. The upside is a more transparent financial system in which the U.S. continues to leverage its most powerful asset: the dollar. Similar to how tech leaders open-source critical components to establish industry norms while monetizing other areas, the U.S. can expand its dollar platform and ensure seamless interoperability with Bitcoin and stablecoins. While any bold, transformative strategy carries inherent risks, resisting change only accelerates obsolescence. With its extensive expertise in platform competition, the current administration is uniquely positioned to take this bet. --- ## Strategy, Not Speculation - canonical: https://catalini.com/notes/strategy-not-speculation/ - original thread: https://x.com/ccatalini/status/1886779214801821964 - date: 2025-02-04 Leading with strategy, not speculation—The best way for the U.S. to lower its debt-to-GDP ratio isn’t through speculation, it’s through fiscal discipline (e.g. [@DOGE](https://x.com/DOGE)) and economic growth. History is clear: Reserve currencies don’t last forever, and those that fall do so from economic mismanagement and overextension. To avoid joining the fate of the Spanish real de a ocho, the Dutch guilder, the French livre, and the British pound, the United States must focus on sustainable economic strength, not risky financial bets. If Bitcoin were to become the global reserve currency, the U.S. would have the most to lose. There is no smooth transition from dollar dominance to a Bitcoin-based system. Some argue that Bitcoin’s appreciation could help the United States "repay" its debt, but the reality would be far harsher. Such a shift would make it exponentially more difficult for the United States to finance its obligations and sustain its economic influence. And while many dismiss the idea of Bitcoin ever becoming a true medium of exchange and unit of account, history suggests otherwise. Gold and silver weren’t just valuable because they were scarce, they were also divisible, durable, and portable, making them effective currencies — even without sovereign backing or issuance, much like Bitcoin today. Similarly, China’s early paper money didn’t begin as a government-imposed medium of exchange. It evolved from commercial promissory notes and deposit certificates — representations of already trusted stores of value — before gaining wider acceptance as a medium of exchange. Fiat currencies are often seen as an exception to this pattern — declared legal tender by the government, they function immediately as a medium of exchange and later as a store of value. But this oversimplifies reality. What gives fiat money its strength isn’t just legal decree, it’s the government’s ability to enforce taxation and its capacity to meet debt obligations through this power. A currency backed by a state with a strong tax base has intrinsic demand because businesses and individuals need it to settle obligations. This taxation power is what enables fiat currencies to retain value, even without a direct commodity backing. But even fiat systems weren’t built from scratch. Historically, their credibility was bootstrapped from commodities people already trusted, most notably gold. Paper money gained acceptance precisely because it was once redeemable for gold or silver. The transition to pure fiat only became viable after decades of that trust being reinforced. Bitcoin is following a similar trajectory. Today, it is primarily seen as a store of value — volatile, yet increasingly regarded as digital gold. However, as adoption expands and financial infrastructure matures, its role as a medium of exchange will likely follow. History suggests that once an asset is widely recognized as a reliable store of value, the transition to a functioning currency is a natural progression. --- ## The Internet Of Money Wants To Be Free - canonical: https://catalini.com/writing/internet-of-money-wants-to-be-free/ - original: https://www.forbes.com/sites/christiancatalini/2025/01/16/the-internet-of-money-wants-to-be-free/ - date: 2025-01-16 - outlet: forbes Today, Coinbase unveiled a bold [new white paper](https://assets.ctfassets.net/o10es7wu5gm1/3DPt8YOiYtdVfqUoeuAJdS/33b4c368f7bc6b4ff7173df36c3d00da/Davos_Whitepaper_A4.pdf), proposing permissionless networks as the key to transforming payments, finance, and beyond. But to grasp why this is significant, we have to travel back in time. When Satoshi Nakamoto released the Bitcoin whitepaper on October 31, 2008, he likely could not have fully foreseen the profound impact his invention would have on the world. In history, this had occurred only twice before: in 138 BC, when Emperor Wu of Han dispatched diplomat Zhang Qian to establish trade with the Western regions, and in 1989, when Tim Berners-Lee introduced his technical proposal for a [hypertext system](https://www.w3.org/History/1989/proposal.html)—the foundation of the modern web. What do Qian, Berners-Lee, and Nakamoto have in common? Their actions were pivotal in creating entirely new types of networks. For Qian, it was the distributed trade network connecting China and Central Asia; for Berners-Lee, the distributed information network of the web; and for Satoshi, the decentralized financial network of Bitcoin. Each of these networks gave rise to other interconnected systems, drastically advancing humanity’s ability to trade—first with physical goods and cultural exchange via the Silk Roads, then with digital content and information through the internet, and now with digital assets and value via crypto. With each iteration, the world’s GDP grew, driven by human ingenuity, relentless curiosity, and innovation. The Silk Roads, the internet, and crypto networks share a defining characteristic: they are all permissionless. While key individuals, ventures, and governments influenced their evolution, anyone could participate and contribute—whether by establishing a new trade route, developing an internet service, or introducing a new cryptocurrency. No single empire controlled the Silk Roads—instead, competition spurred the development of alternative sea and land routes through organic growth. Merchants, motivated by profit, negotiated independently, often navigating significant uncertainty and assuming substantial personal and financial risks. The outcome was a remarkable surge not only in commerce but also in the exchange of ideas and cultures across regions. A similar evolution occurred with the internet, which began as a US-centric project but transformed over the decades into a truly global network. Initially conceived as an academic and military communication tool, the internet became a commercial success due to the foresight of a US administration that early on recognized the transformative potential of combining a permissionless network with global information exchange. Standardization and measurement—such as the use of proto-currencies like gold or jade—were vital to the viability of the trade routes. Open protocols like TCP/IP for data transmission, DNS for navigation, and HTTP for webpage delivery provided the modular components for global information exchange. In the same way, permissionless networks like Bitcoin and Ethereum introduced native tokens—Bitcoin and Ether—that allowed decentralized digital trade to thrive, first within their ecosystems and now increasingly across their borders. Throughout history, individual rulers and emperors have attempted to control, heavily tax, and even halt trade along the Silk Roads. In modern times, countries like China, Russia, and Iran actively firewall, surveil, and censor their citizens’ internet access. Similarly, the Bank for International Settlements (BIS)—the bank for central banks— has introduced the “[Finternet](https://www.bis.org/publ/work1178.pdf)” initiative—a vision for a controlled, permissioned financial network. But just as trade along the Silk Roads persisted even during wars, and individuals bypass internet restrictions daily using open-source tools like Tor and VPNs, permissionless crypto networks are inevitable. Over the next decade, every digital asset—whether financial or otherwise—will be issued, exchanged, and transformed in innovative ways through crypto rails. Like other general-purpose technologies (GPTs) such as the steam engine and the internet, crypto is embarking on a multi-decade journey to transform economic activity. Beginning with basic payments and financial services, these networks will expand to encompass digital platforms, marketplaces, and applications of AI. While some believe that these open and permissionless networks can be constrained within outdated regulatory frameworks, such efforts are likely to be as ineffective as the curated versions of the internet once proposed by Microsoft, Apple, and AOL in its early days—ideas that have since faded into obscurity as they misjudged the direction of technological evolution. The good news is that permissionless networks can be aligned with society’s values and principles and are fully compatible with efforts to combat financial crime and terrorism financing. Claims to the contrary are often disinformation spread by those who fear the technology will render their roles and influence obsolete. The economic freedom unlocked by crypto provides better tools for enabling entrepreneurial experimentation and making it safe and compliant without compromising privacy. That same economic freedom can restore competition in sectors where market structure has remained unchanged for decades. It will also enable startups to break into previously inaccessible markets and create innovative products and services that are hard to envision today. Just as the decentralized growth of trade routes and internet connections transformed the past, permissionless crypto networks will lead us into a new era of digital experimentation and economic growth. But to understand why these networks are the future of digital exchange and trade, we must start with Bitcoin. ## The Bitcoin Breakthrough Satoshi’s invention was not just a breakthrough in cryptography and game theory but also in [how markets are bootstrapped and operated](https://dl.acm.org/doi/10.1145/3359552). Bitcoin enabled the direct exchange of digital assets without the need for an intermediary. Before Bitcoin, defining and updating ownership of a digital asset—including money—required assigning control to a third party. This arrangement relied on trust that the intermediary would consistently and accurately authorize and record transactions, even in situations where their own interests might diverge. Central banks, commercial banks, and traditional fintech wallets are all examples of trusted intermediaries in financial services. While these intermediaries generally serve their stakeholders well in countries with strong institutions, this is far from the case in many parts of the world. The financial freedom taken for granted in the United States is unimaginable in regions lacking independent central banks, robust rule of law, and a competitive financial sector. The same holds true even in countries with well-functioning financial systems for certain segments of the economy—such as crypto, creators, or political dissidents—that have been actively deplatformed by governments, banks, or card companies due to their activities. Bitcoin restores economic freedom by creating a new form of store of value—often considered as “digital gold”—that anyone can exchange and custody directly, regardless of the trustworthiness of their country’s institutions. In countries with strong institutions, consumers and businesses often delegate the safekeeping and movement of Bitcoin to trusted, regulated wallets. However, even in such cases, the ability to self-custody Bitcoin acts as a check on the market power of these intermediaries. While Bitcoin was the first application of permissionless crypto networks, it laid the foundation for many others to follow. The same principles of direct ownership and intermediary-free exchange of digital assets have now been applied to a wide range of problems, including decentralized computing, prediction markets, file storage, social networks, AI agents, and more. These new networks are built on the same permissionless principles as Bitcoin: anyone can access them, build upon them, or adapt their core components. As entrepreneurs and developers uncover new primitives and modular building blocks, increasingly complex financial and non-financial applications are emerging on decentralized and open infrastructure. While the financial sector was the first to be reimagined—since financial assets are already digital—permissionless networks are increasingly bridging the gap between onchain and offchain economic activity. They are powering applications ranging from digital identity to the tokenization of real-world assets like real estate, commodities, and natural resources. Today, many of the obstacles that hindered permissionless networks just a few years ago are being overcome: from scaling these systems to outperform the centralized counterparts they seek to replace, to resolving last-mile challenges linked to identity verification, to balancing transaction privacy with compliance requirements. As the technology has become more user-friendly and intuitive, adoption has accelerated rapidly in regions of the world—such as LATAM, Africa, and parts of Asia—that lag in financial services. From cross-border remittances to Bitcoin and USD-denominated stablecoins as alternative stores of value, crypto provides a new financial stack that startups and neobanks are increasingly building on. While this new technological paradigm began in finance, it is now expanding beyond payments, lending, and other financial primitives into broader domains. The concept of digital asset ownership is expanding into the creator economy, the creative arts, digital platforms for messaging and social media, AI, and even communications infrastructure. With each iteration, developers are reimagining transactions and interactions—between buyers and sellers, creators and audiences, mobile hotspot data providers and users, and more. The key is that each of these marketplaces is being redesigned without a central intermediary. Unlike the platforms that dominate much of our personal and business lives today, [permissionless networks are owned by their participants](https://a16zcrypto.com/posts/article/forget-antitrust-regulate-to-let-tech-disrupt-itself/). From an economic perspective, this enables contributors to benefit from the network’s growth and share in its success. More importantly, it prevents any single platform architect from unilaterally changing the rules to their advantage, restricting access, or blocking others from participating. Because these networks are permissionless, anyone can build and experiment on them, fostering robust experimentation and innovation. Unlike proprietary APIs, which often impose top-down restrictions on what can be developed, the standardized interfaces of permissionless networks are open, flexible, and modular. Much like the open protocols that power the internet, they are ushering in a new era of digital platform innovation—one unbound by existing business models and dominant players. Ultimately, Satoshi’s most significant legacy was demonstrating that a new type of architecture was possible and that bottom-up experimentation could revive innovation, not just in financial services but across a broad spectrum of digital platforms. This new architecture offers clear advantages over the walled gardens of existing big tech and fintech players. It also outperforms top-down approaches, such as the BIS’s “Finternet,” in identifying and addressing new solutions and challenges. Centralized approaches excel when the problem is well-defined and already understood—such as upgrading a domestic payment system to enable real-time payments. However, they are poorly equipped to address unstructured problems that require a [diversity of approaches and ideas](https://www.forbes.com/sites/digital-assets/2024/04/18/forget-antitrust-regulate-to-let-tech-disrupt-itself/). This is where the same decentralized approach that shaped the trade routes, the internet, and now crypto networks is uniquely positioned to succeed. --- ## Should the United States Implement a Bitcoin Strategic Reserve? - canonical: https://catalini.com/writing/bitcoin-strategic-reserve-a16z/ - original: https://a16zcrypto.com/posts/article/bitcoin-strategic-reserve/ - date: 2025-01-01 - outlet: a16z Weighing the case for a U.S. strategic bitcoin reserve. Full text at the original outlet: https://a16zcrypto.com/posts/article/bitcoin-strategic-reserve/ --- ## Can Crypto’s Scarcity Tame AI’s Infinite Abundance? - canonical: https://catalini.com/writing/crypto-scarcity-ai-abundance/ - original: https://www.forbes.com/sites/christiancatalini/2024/12/19/can-cryptos-scarcity-tame-ais-infinite-abundance/ - date: 2024-12-19 - outlet: forbes *This is the second installment in a four-part series on the intersection of crypto and AI. The*[first article](https://www.forbes.com/sites/christiancatalini/2024/11/26/ai-and-crypto-part-i-decentralizing-ai-big-dreams-bigger-hype/)*explored whether crypto can counter AI’s centralizing force and meet an increasingly insatiable need for compute. Today, we examine if crypto can bring back robust identity and provenance in a world flooded by AI.* Crypto’s chances of decentralizing AI in the near term [are very slim](https://www.forbes.com/sites/christiancatalini/2024/11/26/ai-and-crypto-part-i-decentralizing-ai-big-dreams-bigger-hype/). But can it at least help counterbalance some of its side effects? We suddenly live in a world where generative AI can flood any digital platform with infinite content, can perfectly impersonate us through text, audio and video, and replicate human behavior with [minimal training](https://arxiv.org/abs/2411.10109). While this poses some deep questions about what it even means to be human—[Meghan O'Gieblyn](https://www.meghanogieblyn.com/events) has a thought-provoking book on the topic—it also presents some more immediate and pressing questions for every platform we rely on today. To some extent, none of this is new: Facebook and X have been fighting bots and inauthentic behavior for more than a decade. Yet, the scale and sophistication of what’s now possible is unprecedented and remarkably human-like, reaching far beyond fake profiles or misinformation. Our society depends on [countless](https://www.theverge.com/2024/11/14/24294995/spotify-ai-fake-albums-scam-distributors-metadata) systems designed under the assumption that distinguishing humans from machines is possible. While CAPTCHAs have become more advanced—they now leverage AI to combat AI through behavioral patterns, keystroke dynamics, and trackpad movements—it’s uncertain how long these tiny and frustrating Turing tests will remain effective. As Dzieza aptly [noted](https://www.theverge.com/2019/2/1/18205610/google-captcha-ai-robot-human-difficult-artificial-intelligence), “There’s something uniquely dispiriting about being asked to identify a fire hydrant and struggling at it.” The entropy generated by our actions still carries a distinctly human fingerprint—likely due to the intricate interplay between our nervous system, its various components, our body, and even cellular dynamics. However, it’s conceivable that AI could one day master this as well. ### [Best High-Yield Savings Accounts Of 2024](https://www.forbes.com/advisor/banking/savings/best-high-yield-savings-accounts/) ### [Best 5% Interest Savings Accounts of 2024](https://www.forbes.com/advisor/banking/savings/best-5-percent-interest-savings-accounts/) ## Can Decentralized Identity Beat Centralized Systems? In 2021, most dismissed Worldcoin’s vision of transforming identity verification with an eye-scanning orb as laughable and dystopian. Yet, as the need for stronger “[personhood credentials](https://arxiv.org/abs/2408.07892)” becomes more urgent, its premise may feel less far-fetched. As AI accelerates, so does the need to restore scarcity and safeguard processes from Sybil attacks—threats where the low-cost creation of fake identities undermines the integrity of systems. Enter crypto—the industry that turned digital scarcity and Sybil-resistance, starting with Bitcoin, into a $3 trillion ecosystem. While critics often dismiss it as a series of Ponzis, crypto remains, for better or worse, the one sector that has successfully onboarded millions into the practice of self-custody of digital assets and the difficult discipline of securing private keys. Crypto-based experiences have long paid a significant price for this added complexity compared to the centralized systems they aim to replace. However, this may shift if the user experience improves without compromising on stronger privacy and control over data. But where can decentralized identity realistically outperform centralized solutions? Much like the debate over whether crypto can [decentralize AI](https://www.forbes.com/sites/christiancatalini/2024/11/26/ai-and-crypto-part-i-decentralizing-ai-big-dreams-bigger-hype/), the answer lies in a simple set of trade-offs, which we turn to next. Regardless of the technology, any solution must be intuitive for humans while costly for AI. Yet, if AI can enlist a human workforce, we may ultimately have to accept that humans and AI will operate on increasingly equal footing. ## Disrupting From the Ground Up Decentralized identity exhibits the key characteristics of a [disruptive technology](https://hbr.org/2015/12/what-is-disruptive-innovation) (see graph below): it falls significantly short of centralized alternatives in critical performance areas valued by incumbents, such as delivering a seamless user experience and meeting regulatory requirements. At the same time, it enhances privacy and data ownership, and its open architecture enables developers to freely recombine components to create new products. Proponents of decentralized identity argue that it could be vastly superior to the status quo—even in regulated financial services. Today sensitive personal information is duplicated across systems—e.g. for know-your-customer (KYC) purposes—increasing the risk of leaks and leaving users with little control over how their data is used. Ironically, the fragmentation of data across providers complicates compliance efforts by making it impossible to obtain a comprehensive view when required. An architecture where users have greater control over their data and disclosure only happens when necessary could be both safer and more compliant. Such a user-centric approach would have strong, pro-competitive effects on digital platforms in messaging, social media, and commerce. Because of network effects, these verticals are dominated by a small number of players who control how user data is used and monetized. Decentralized identity would lower user lock-in and enable easier data portability by allowing users to seamlessly transfer their social graph, interactions, or transaction history between platforms. It would also deliver new forms of interoperability between services, and developers could design products that combine in a modular way components from different systems. Yet most users today willingly trade privacy for convenience—and are likely to keep doing so, especially when it means accessing increasingly powerful, albeit invasive, AI tools. In the absence of a privacy black-swan event, decentralized identity will only overtake centralized solutions when it significantly improves usability and exceeds the current regulatory bar. If it succeeds on both fronts, disruption will follow. But big tech companies won’t give up control over identity easily. By integrating elements of decentralized identity—such as verifiable credentials—and shifting parts of AI training and inference to users’ devices, they can address privacy concerns while preserving their gatekeeping role, ultimately reducing the value of decentralization. Governments will also want to retain significant control over digital identity, as it is crucial for law enforcement, national security, taxation, and the delivery of public services. Christensen’s theory of disruption accounts for this challenge, emphasizing that disruptive technologies often gain traction by solving problems incumbents consider insignificant—until they evolve to dominate mainstream use cases too. Within crypto, this pattern is evident with Bitcoin: initially dismissed by central bankers and economists as a poor store of value and an impractical medium of exchange, it has steadily gained adoption—from crypto enthusiasts to traditional financial institutions and now governments. As it continues to diffuse, Bitcoin could ultimately challenge the US dollar and become a new type of global reserve currency. Decentralized identity may follow a similarly gradual yet transformative trajectory. ## The Government’s Role While government-issued identification has existed for centuries, the [modern passport](https://www.nationalgeographic.com/history/article/a-history-of-the-passport) emerged as a response to the surge in immigration to the U.S. following World War I. Over the years, it has evolved through a constant cat-and-mouse game with increasingly sophisticated counterfeiters and forgers. Passports epitomize the “[last mile problem](https://hbr.org/2018/06/what-blockchain-cant-do),” serving as both digital and physical documents. Their integrity and validity depend on the holder matching the biometric data stored on the embedded chip and the printed information on the physical pages, which are secured with advanced printing techniques, holographic elements, laser engraving, and specialized materials. Countries like Estonia, Singapore, India, China, and several in Europe have broadened the scope of services accessible through digital IDs, including public services, welfare, age-restricted purchases, websites, and social media. It is easy to envision governments advocating for similar solutions to address the rising challenges posed by AI, potentially involving biometrics—though such measures could raise significant concerns around privacy, surveillance, and accessibility. In the U.S., the track record of the public sector collaborating on this with private companies such as Id.me and Clear Secure has been poor and includes everything from verification lapses to privacy and reliability problems. In these applications, the introduction of biometrics increases security but also risks: because biometrics are irrevocable, a breach of raw biometric data at a private provider is damaging and irreversible. Modern implementations mitigate this by using biometric tokenization, converting raw data into encrypted tokens, but trust in the provider to perform this correctly and avoid being compromised is still necessary. Overall, this shows that governments should not pick winners but instead allow market forces to shape the application layer of identity. At the same time, regulators have a critical role to play in protecting privacy and ensuring that the digital identity ecosystem of the future is built on robust open protocols and standards. They also have the ability to deliver some of the most foundational attestations and verifications that citizens and businesses will need to ensure the ecosystem is truly trustworthy and useful. Driven by [national security](https://www.newyorker.com/magazine/2017/12/18/estonia-the-digital-republic) concerns, countries like Estonia had to embrace digital identity more than two decades ago. Today, their bet powers everything from public services to safer merchant payments. As the AI threat rises, more countries will follow. What proponents of decentralized identity often overlook is that, while bottom-up approaches may provide enough signal for some applications, it is only through government-issued IDs that participants gain the associated trust, legal assurances, and recourse. The sooner government IDs embrace open protocols, the faster decentralized identity can address high-value applications. ## Big Tech’s Battle for Your Digital Wallet Centralized identity and authentication systems offered by major tech companies come with several advantages. They are user-friendly and familiar, feature battle-tested access recovery mechanisms, and can be strengthened through multi-factor authentication. They also benefit from the significant security investments made by these companies, shifting the burden of protection away from consumers and businesses. With millions of people relying on “sign-in with” flows every day—Okta estimates that [73%](https://assets.ctfassets.net/2ntc334xpx65/77U9sLFO7rD7t9zdI6Q1SV/a8e2054b5affc0280769516eee70b0ea/Social-Login-Report.pdf) of social logins on its platform are powered by Google—these systems represent the most successful and advanced form of secure, global authentication. On mobile devices, companies like Apple, Google, Samsung, Huawei, and Xiaomi have fine-tuned biometric flows to deliver a seamless blend of enhanced security and convenience. However, these tools grant tech companies visibility into every authentication, create a single point of failure in the event of vulnerabilities or breaches, and raise concerns about government surveillance in countries with weak privacy protections and laws requiring extensive data sharing with authorities. Big tech companies have also been rapidly expanding their presence in financial services, a move that grants them access to government-issued forms of verification through know-your-customer (KYC) onboarding processes. This is particularly significant as these companies increasingly compete to dominate the digital wallet experience—spanning payments, credentials, reward and membership programs, ticketing, and travel. By positioning themselves as central identity hubs, they can secure a privileged role across these services and shape the resulting ecosystems to their advantage. When combined with new forms of government ID such as RealID, these wallets can unlock the delivery of verifications in a privacy-preserving way. For example, in collaboration with SpruceID, the California DMV mobile driver’s license (mDL) has implemented a platform for issuing digital credentials, allowing holders to selectively disclose key information—such as confirming they are above the legal drinking age—without revealing their entire ID. Google Wallet lets users scan their [U.S. passport](https://www.theverge.com/2024/9/12/24242033/google-wallet-us-passport-drivers-license-digital-id) for use at select TSA locations, hinting at its potential as a full-fledged identity and attestation platform. Similarly, Apple’s Wallet supports many types of digital cards, and its NameDrop feature already allows users to share information selectively. Overall, as AI gets increasingly better at recreating liveness, both public and private solutions will need to develop new techniques to stay ahead, distinguishing humans from deepfakes and bots. But can decentralization play a meaningful role? That’s what we explore next. ## Decentralized Identity Decentralized identity solutions are private, modular, and global. Instead of relying on credentials issued top-down by trusted authorities, they are bootstrapped from the ground up. Because they operate on permissionless networks, their identifiers and credentials work across providers, driving healthy competitive dynamics at the application layer. But since building trust without leveraging existing institutions is extremely hard, their adoption has been very limited. To become truly useful, decentralized alternatives will have to evolve to resemble their centralized counterparts in terms of usability and compliance. Without this transformation, they will remain confined to problems that do not require off-chain enforcement or legal protections. That does not mean decentralized identity cannot already address highly valuable business problems. In fact, this aligns with the theory of disruption: by tackling issues that centralized providers cannot or choose not to address, and by enabling solutions impossible under traditional architectures, decentralized identity can evolve until it can unlock mainstream adoption. Whenever the demand for stronger identity or reputation stems from business needs rather than regulatory requirements—such as a protocol or game developer aiming to reward humans, but not bots—decentralized solutions can offer a viable alternative. Similarly, while they may not meet the same standard of certification as a trusted third party, they may be able to reduce risk enough to enable transactions that would otherwise be impossible. The parallel here lies in how onchain analytics have enabled blockchain networks to remain open while simultaneously interfacing with regulated institutions that need to assess the risks of transactions entering or leaving their perimeter. Decentralized identity could improve these tools without compromising privacy. Crypto wallets began as passive apps for storing private keys but are quickly evolving into [active](https://vitalik.eth.limo/general/2024/12/03/wallets.html), programmable tools capable of storing user credentials and selectively disclosing information. Onchain attestations—such as those provided through the [Ethereum Attestation Service](https://attest.org/) (EAS)—build on this by allowing trusted issuers to store relevant information onchain for others to access and build upon. While the resulting model is also wallet-centric, similar to those proposed by tech companies, it is unsurprisingly far more user-centric. As individuals gather attestations from financial intermediaries, communities, reputation networks, educational institutions, employers, and other sources, a robust measure of their trustworthiness and humanness can be rapidly established. In essence, this approach makes information about individuals and businesses—often already available on the public web or in the databases of digital platforms—more accessible. A key question is whether this universe of credentials and attestations will require biometrics. Worldcoin is betting that it will, deploying its orbs globally to enable individuals to bridge the last mile between onchain and offchain systems by scanning their retinas. If Worldcoin succeeds in creating defensible network effects around its World ID and making it useful across various applications, it could control the next iteration of the passport—one that is global and not tied to any single country. SpruceID approaches the same problem from the opposite direction by gradually integrating government IDs into the onchain ecosystem. Their solution already supports selective disclosure and offline verification, allowing users to utilize credentials like a driver’s license without the issuing DMV being aware of the transaction. By bridging the gap between traditional systems and decentralized technologies and incorporating high-trust, government-issued credentials, SpruceID may be able to accelerate the viability of decentralized identity solutions. Onflow takes a hybrid approach to bootstrapping trust from government IDs without directly involving the public sector. Their onboarding process, designed to run on a user’s device for enhanced privacy, leverages the rigorous verification already performed during passport issuance to create an onchain attestation. This is achieved by reading the passport’s digital information, including the photo, from its RFID chip and [comparing](https://x.com/sundialmirage/status/1863163741459873882?s=46) it to a biometric face scan conducted via smartphone. By using zero-knowledge proofs, Onflow enables users to later certify key information from their passport without revealing sensitive details—for instance, they can prove their passport is not from a sanctioned jurisdiction or confirm they are old enough to pass an age check. These three examples demonstrate how decentralized identity solutions can differ in trust models, ease of use, and the role of third parties. Interestingly, many of the same considerations apply to the identity and provenance of digital content. With the rise of generative AI, digital content faces similar attestation and verification challenges. While traditional consortia and standards like [C2PA](https://c2pa.org/) are trying to tackle these issues, decentralized approaches could also provide critical proofs—spanning source, ownership, and authenticity—for various digital assets. For example, [Story protocol](https://www.story.foundation/) envisions intellectual property ownership and transactions living on a permissionless network. As with digital identity, some of these digital provenance experiments may find greater success with new applications, media, and IP rather than integrating with existing systems. However, as the pace of creation accelerates, this distinction may become increasingly irrelevant. ## But What Will the Future Actually Look Like? Ultimately, whether centralized identity, secured by big tech on top of government IDs, or decentralized identity, secured by permissionless networks, prevails will depend on crypto’s ability to drive growth in new use cases that legacy technology cannot address. Without a killer app that exclusively operates on crypto rails and accelerates the adoption of decentralized identity, it is unlikely that we will address the challenges posed by AI through the harder-to-use and less-compliant decentralized approach. While decentralized identity can be global from day one, enabling faster experimentation and more competition, consumers will still gravitate toward solutions that are simple, familiar, and already trusted. Big tech will fight to retain control over identity, as it underpins so many aspects of a person’s economic and social interactions. Governments, on the other hand, may attempt to counterbalance this by adopting open standards, though they are likely to stop short of fully embracing permissionless networks—as illustrated by the California DMV example. A killer crypto app that quickly drives adoption of decentralized identity cannot rely solely on the launch of a speculative token. Instead, it must address problems that don’t demand full regulatory compliance from day one, as that would first require changes to laws and regulations. While decentralized identity could improve KYC flows, shifting to a privacy-preserving model requires new rules. However, it may still help de-risk stablecoin payments and improve institutional treatment of DeFi liquidity pools. Without a killer app, decentralized identity may stay in incubation for a while, with users quietly accumulating onchain attestations from various providers for different purposes within the same wallet. As these building blocks come together, developers will refine risk, fraud, reward, and compliance processes to counter increasingly capable AI, eventually making decentralized identity more useful—which, of course, is exactly what the theory of disruption would predict. --- ## Decentralizing AI—Big Dreams, Bigger Hype? - canonical: https://catalini.com/writing/decentralizing-ai/ - original: https://www.forbes.com/sites/christiancatalini/2024/11/26/ai-and-crypto-part-i-decentralizing-ai-big-dreams-bigger-hype/ - date: 2024-11-26 - outlet: forbes *This is the first article in a four-part series delving into the intersection of crypto and AI. We begin with a simple yet provocative question: can crypto’s decentralized architecture effectively counter AI’s seemingly unstoppable drive toward centralization?* For an industry rooted in the dry, analytical domains of cryptography and game theory, crypto has an uncanny ability to draw exceptional storytelling talent. As Steve Jobs allegedly said, “The most powerful person in the world is the storyteller,” and nowhere is this more evident than in the crypto space. If you’ve spent any time in the crypto space, you’ve likely witnessed the ebb and flow of narratives and memes—each wave elevating potential winners, only to crash ashore with the next market correction. Over the last decade, the crypto space has evolved through a series of shifting narratives: from Bitcoin as a hedge against inflation, to financial inclusion, decentralized finance, the NFT boom in arts and creative industries, DAOs, the metaverse, and most recently, stablecoins and dollarization as signs that crypto may have found its product-market fit. The reality is that crypto is a general-purpose technology (GPT), much like the steam engine, electricity, and the internet before it—each of which took years to weave their transformative impact through the fabric of the economy. While good storytelling in crypto moves at the speed of memes, actual deployment takes time, patience, and a willingness to tackle tedious “[last mile](https://hbr.org/2018/06/what-blockchain-cant-do)” challenges. For instance, when it comes to crypto revolutionizing payments, the technology itself isn’t the limiting factor; the real challenges lie in tackling practical but essential issues such as compliance, identity verification, and regulatory alignment. In fact, for many applications, it’s the absence of clear regulation that continues to hinder broader adoption. The engineers have delivered—now it’s up to Congress to establish the regulatory framework needed to make crypto mainstream. ## The New Frontier: Crypto Meets AI? The latest narrative in crypto is its inevitable role as the critical infrastructure for AI. And while the love and attention predominantly flows from crypto to AI developers—who are preoccupied with the race to AGI, securing chips, and scaling nuclear power, regardless of payment method—the story remains, at least on the surface, compelling. But we shouldn’t get carried away. As Kahneman aptly [put it](https://www.nytimes.com/2011/10/23/magazine/dont-blink-the-hazards-of-confidence.html): *“Confidence is a feeling, one determined mostly by the coherence of the story and by the ease with which it comes to mind, even when the evidence for the story is sparse and unreliable.”* ### [Best High-Yield Savings Accounts Of 2024](https://www.forbes.com/advisor/banking/savings/best-high-yield-savings-accounts/) ### [Best 5% Interest Savings Accounts of 2024](https://www.forbes.com/advisor/banking/savings/best-5-percent-interest-savings-accounts/) When evaluating the intersection of crypto and AI from first principles, the prevailing narrative starts to show its cracks. Sure, the long-term potential is hard to deny. But for now—beyond the headline-grabbing entertainment agents like Truth Terminal and Luna AI—the reality is far more mundane than the hype machine would have you believe. Spoiler alert for the final installment of this series: the short-term overlap isn’t where most people are looking. It’s less glamorous than advertised, but once you notice it, it’s almost painfully obvious. Over the coming weeks, we’ll explore three key areas where crypto and AI intersect: 1) using crypto to curb centralization in AI—an issue that’s top of mind for many, including regulators; 2) leveraging crypto to address generative AI’s side-effects, like restoring digital scarcity, enhancing provenance, and enabling more robust identity systems; and 3) establishing crypto as the payments infrastructure for AI agents. Finally, we’ll wrap up with a look at one high-impact opportunity where crypto and AI can deliver significant value right now. ## **Decentralizing AI** AI decentralization spans at least three dimensions, none of which are easy—or particularly practical—with today’s technology. Crypto could, in theory, decentralize: 1) the compute required to train or run AI models; 2) the data used to train or refine those models; and 3) the underlying business model itself. ## 1. Decentralizing Compute Right now, all signs point to centralized compute as the key to AI scaling—just look at the space-race scramble for capital, hardware, and even dedicated [nuclear energy](https://www.economist.com/business/2024/10/09/big-tech-is-bringing-nuclear-power-back-to-life) sources. But crypto enthusiasts argue that as decreasing returns to scale start to hit massive data centers, or as public unease grows over any one company wielding that much power, the demand for decentralization will inevitably rise. The irony, of course, is that this vision didn’t even pan out for crypto’s leading networks. Satoshi’s original ideal of a democratic “one CPU, one vote” consensus quickly gave way to the realities of physics and economics, resulting in massive concentration—not just in Bitcoin mining, but even more so in hardware. Today, the top three ASIC producers dominate nearly all global supply, and they’re all Chinese companies. Similarly, in Ethereum, the leading proof-of-stake network, staking is less decentralized than many would prefer, with a few large staking pools holding a substantial share of the market. If Bitcoin’s consensus didn’t end up running on a fully decentralized network of [toasters](https://www.ft.com/content/98b32005-09d9-3263-85aa-5f9303c8935e) or industrial appliances, why should we expect AI to be any different? Some argue that decentralized AI could tap into the underutilized compute capacity of increasingly powerful consumer and business hardware—a bit like idle black car drivers waiting for a ride before Uber came along. It’s an appealing analogy, and efforts like Seti@home have demonstrated how this capacity can be harnessed for pro-social purposes, such as protein folding. However, at scale, these devices will inevitably operate as an extension of big tech, shaped and controlled by centralized entities. Tech companies can rapidly deploy capital, replicate infrastructure across multiple locations, negotiate preferential deals with hardware and energy suppliers, and leverage top-down decision-making to accelerate execution. Case in point: Elon Musk assembled the world’s most powerful AI training system in just 122 days. While powerful smartphones, laptops, cars, and robots will increasingly handle some local AI processing, it’s clear that the companies behind these devices will retain preferential access to that compute. Apple and Google are already leveraging this dynamic with their hybrid approach to on-device and cloud-based training and inference. Meanwhile, Elon Musk has [hinted](https://www.theverge.com/24139142/elon-musk-tesla-aws-distributed-compute-network-ai) at the possibility of parked Teslas forming a distributed cluster for AI inference. While connectivity might seem like a hurdle, it’s not hard to imagine Tesla using Starlink for this. OpenAI and Anthropic are also venturing into hardware development. Ultimately, while edge computing will play a crucial role in AI, it’s clear that incumbents will get to shape its trajectory first. Where this leaves a network of edge devices incentivized through crypto is unclear, even before we get to the thorny issues of training on untrusted and heterogeneous hardware, effectively distributing the load to ensure parallelism and fault tolerance, and protecting the intellectual property tied to countless compute cycles—especially if the model weights are ultimately visible to all. In the end, the only projects likely to adopt decentralized, crypto-powered AI compute might be those with no other choice—either because they are entirely grassroots, open-source initiatives without corporate backing, or because they operate in highly adversarial and contested environments where decentralization is a necessity for training or inference. While crypto can enhance transparency and verifiability in inference, the willingness to pay for these benefits compared to just placing trust in centralized players’ reputations remains uncertain. As with much of crypto, the question of who will truly value censorship resistance is hard to answer until we witness the failure modes of centralized solutions—imagine a Cambridge Analytica moment, but for AI—and whether such failures would meaningfully shift preferences. ## 2. Decentralizing Data Another argument for why AI needs crypto centers on its potential to deliver greater privacy and control over user data. The problem is that this mirrors the same reasoning crypto proponents (and others before them) have long used to predict the rise of decentralization across digital platforms like social media, messaging, and marketplaces—predictions that have yet to materialize. The reality is that, even in the face of major scandals, most consumers simply don’t care, and the trade-offs in convenience and usability have been far too steep to justify the privacy benefits. Moreover, privacy-focused tech companies like Apple are already moving the most sensitive aspects of training and inference directly onto user devices. This minimizes the privacy advantage of a decentralized solution. For enterprises, OpenAI and Anthropic can employ similar controls to those that have already made corporations comfortable with cloud solutions—all while delivering these capabilities at a fraction of the cost of decentralization. Monetizing data for AI training or post-inference feedback is likely to be economically insignificant. Most user data holds little value—except in rare, high-stakes moments like major life events—and consumers are already willing to provide it in exchange for free services. A stronger emphasis on privacy didn’t help early Web3 experiments attract mainstream users away from Web2 incumbents, and it’s unclear why the outcome would be any different with AI. It’s an incumbents’ game, where a decentralized alternative is at an even greater disadvantage compared to a decentralized social network or creator economy platform. ## 3. Decentralizing the Business Model Open-source AI models are gaining prominence and approaching state-of-the-art performance, thanks to contributions from organizations like Meta, xAI, MistralAI, and DeepSeek AI. Notably, some of these teams have achieved comparable results to the leading players with significantly smaller budgets. In response to U.S. export controls on advanced GPUs, Chinese companies have pushed the boundaries of what’s possible through a clever mix of optimization techniques and architectural changes. If these trends continue, novel business models centered around open-source AI could become increasingly viable, including those that reshape the production of AI models themselves. While, as discussed above, this approach may not be particularly effective for large generalist models, an AI ecosystem with a dedicated crypto token tailored to a specialized domain might prove viable. This is hardly new territory for crypto, which has been experimenting with market design and token economics since Ethereum’s launch. However, open-source ecosystems have long faced challenges with developing radically new monetization models. Most contributors participate out of passion for the pro-social effects of open source, as a means to showcase their skills in the labor market, or because it aligns with their tech employers’ strategic goals by producing code that complements their business models. While crypto projects have experimented with adding crypto tokens to repository contributions or rewarding maintainers of key open-source libraries, this has been mostly a fringe phenomenon. A specialized AI ecosystem that uses a native crypto token to reward scarce talent, compute, data, feedback, and other contributions is a theoretically fascinating idea, but in practice, it seems exceedingly difficult to execute successfully. Native crypto tokens are an effective way to give early contributors and adopters upside in a project and address the cold-start problem. However, they have mostly backfired, [attracting speculators instead of builders](https://hbr.org/2023/01/do-crypto-prices-actually-mean-anything), and distracting founders with too much funding. They’re the digital equivalent of the “resource curse,” pulling teams away from the messy, unglamorous task of building actual products and toward the shinier, more immediate allure of price movements. While there may be a clever way to align these incentives effectively around an AI application, it remains a very complex endeavor. ## Will crypto meaningfully limit centralization in AI? While an interesting area of academic and R&D exploration, the use of crypto to decentralize AI remains commercially limited and is likely to remain so for the foreseeable future. Moreover, hybrid solutions—like those being developed by Apple, Tesla, and other incumbents—can already deliver key privacy and latency benefits of edge inference without the added complexity and costs of decentralization. That said, crypto’s role shouldn’t be entirely dismissed: in such a fast-evolving space, breakthroughs in distributed AI model development might quickly shift the cost-benefit equation, or the downsides of centralization could materialize much sooner than anticipated. Similarly, open-source efforts might succeed in token economic design where previous consumer-focused crypto projects fell short, potentially unlocking innovative new business models. After all, the idea of a decentralized computing platform seemed laughable just a few years ago, yet Ethereum’s growth has proven the skeptics wrong. Some speculate that open-source AI could be the first to achieve AGI—and if it does, it’s possible that a native crypto token might play a role in mobilizing the resources to make it happen. Post-AGI, all bets are off anyway—at that point, we’ll probably be a lot more concerned about using crypto to keep our robot overlords aligned than debating its utility for decentralization. --- ## Why Everyone Is Wrong About Stablecoins - canonical: https://catalini.com/writing/everyone-wrong-about-stablecoins/ - original: https://www.forbes.com/sites/christiancatalini/2024/11/01/why-everyone-is-wrong-about-stablecoins/ - date: 2024-11-01 - outlet: forbes Stripe’s [recent acquisition](https://www.forbes.com/sites/alexkonrad/2024/10/17/stripe-talks-buy-crypto-startup-bridge-1-billion/) of stablecoin orchestration startup Bridge sent shockwaves through the crypto world. For the first time, a major payments company committed over a billion dollars to accelerate its use of this technology. Though this isn’t Stripe’s first attempt at crypto, the timing feels different. Enthusiasm for stablecoins is at an all-time high, and Bridge’s co-founder, Zach Abrams, positioned the company masterfully: by branding it as the ‘Stripe of crypto,’ he ensured it would catch the attention of the Collison brothers. What most miss: Bridge might be worth $1.1 billion to Stripe, but on its own, it likely wouldn’t have hit that mark. This isn’t due to any lack of talent—Zach and his team assembled a top group of engineers—but rather because making money with stablecoins is extremely challenging. Whether through issuing, orchestrating (i.e., converting between stablecoins), or integrating them with legacy banking rails, achieving long-term profitability will be a significant challenge. But how can that be? After all, Circle and Tether have been raking in [substantial profits](https://x.com/paoloardoino/status/1852066710783967552) following the interest rate hikes of the last two years, and with ongoing anticipation around a Circle IPO, the market appears primed for further growth and consolidation. The reality is that network effects in the stablecoin market are likely much weaker than most anticipate, and it’s far from a winner-take-all environment. In fact, stablecoins may well function as loss leaders, and without essential complementary assets, could even become a losing venture. While industry insiders often cite liquidity as the primary reason only a few stablecoins will dominate, the truth is far more complex. So what are the biggest misconceptions about stablecoins? Let’s take a closer look. ### [Best High-Yield Savings Accounts Of 2024](https://www.forbes.com/advisor/banking/savings/best-high-yield-savings-accounts/) ### [Best 5% Interest Savings Accounts of 2024](https://www.forbes.com/advisor/banking/savings/best-5-percent-interest-savings-accounts/) ## **1. Stablecoins need a complementary business model**. When we [designed Libra](https://www.youtube.com/watch?v=ex8JVqmLJpw), it was clear to us that stablecoins require a complementary business model to thrive. The Libra ecosystem was structured around a non-profit association that brought together wallets, merchants, and digital platforms to support both stablecoin issuance and the payment rails on which these assets would move. Relying solely on reserve interest isn’t a sustainable way to monetize a stablecoin. We learned this early on, as we were planning to issue stablecoins backed by currencies with minimal (Euro) or even negative (Yen) interest rates at the time. Stablecoin issuers like Circle and Tether seem to overlook that today’s high-interest environment is an anomaly, and a sustainable business can’t be built on a foundation that’s likely to crumble when market conditions shift. Of course, it’s not just the ‘stock’ of stablecoins that can be monetized; their ‘flow’ can be too. Circle’s recent increase in redemption fees suggests they’re starting to realize this. However, this approach violates a fundamental principle in payments: to build user trust and retention, entry and exit must be seamless. While exit fees may be acceptable in gaming, they’re a poor fit for mainstream payments, as they undermine the basic expectation that money should feel unrestricted and readily available. This leaves transaction fees as a potential revenue source—but enforcing them on a blockchain is challenging without strict control over the protocol. Even then, it’s impossible to impose fees on transactions occurring between users within the same wallet provider. These are all scenarios we explored exhaustively with Libra, highlighting just how complex and uncertain the business model was for the non-profit association. So what options do stablecoin issuers have? Unless they’re relying on temporary regulatory loopholes—which are unlikely to hold long-term (more on that in the next section)—they’ll need to start competing with their own customers. Circle’s recent initiatives—including programmable wallets, a cross-chain protocol, and the Mint program—reveal exactly where the company is going. And that’s unwelcome news for many of its closest partners. This is nothing new in platform strategy: never allow a partner to come between you and your customers. Yet, many exchanges and payments companies are doing just that by letting Circle into their ecosystem. For Circle to survive, it must transition into a payments company, even if that means encroaching on its allies’ territory. It’s a familiar pattern—think of Amazon with third-party sellers, travel platforms with hotel chains, or Facebook with news publishers. As platforms succeed, they frequently bring in-house the functions they initially depended on partners to bootstrap and refine, adopting and monetizing what works. Developers within Apple’s and Google’s ecosystems are all too familiar with this. Stripe doesn’t face this dilemma. As one of the world’s most successful payments companies, they’ve mastered the art of deploying and monetizing a streamlined software layer on top of global money movement—a model that scales efficiently through network effects without being slowed down by the need for country-specific banking licenses. Stablecoins accelerate this approach by acting as a bridge between Stripe and domestic banking and payment rails. What was once a network constrained by legacy institutions—including card companies—can now overcome its last-mile problem, delivering significantly more value to merchants and consumers. This is also why PayPal launched its own stablecoin, with other fintech giants like Revolut and [Robinhood](https://www.bloomberg.com/news/articles/2024-09-26/robinhood-revolut-explore-entering-the-burgeoning-stablecoin-sector) soon joining the fray. Competing on open protocols is a shift from their usual playbook, but they can fine-tune their stablecoin strategy to complement their core offerings. In doing so, they’ll make stablecoins exceptionally affordable and convenient for consumers and businesses alike. ## 2. Dollarization is not a product Crypto has a history of greatly underestimating the influence of regulation on its future. We learned this the hard way with the release of the first Libra whitepaper, which led to two grueling years of intense regulatory interactions to align the project with the expectations of policymakers and regulators. The same is true for stablecoins today. Many assume that stablecoins will seamlessly operate as low-cost, global dollar accounts for consumers and businesses. After all, in a crisis, everyone in the world would prefer to hold dollars in a too-big-to-fail U.S. financial institution. Moreover, one might think the U.S. government would support this, as it strengthens the dollar’s position as the world’s reserve currency. The reality is far more complex. While the United States risks losing a great deal if its financial and sanctions infrastructure is no longer the global standard—and would face even greater consequences if the dollar’s ‘exorbitant privilege’ erodes, as it has for every reserve currency before it—this doesn’t mean the U.S. Treasury will always favor accelerating dollarization. In fact, its Office of International Affairs would view this as a significant challenge to both diplomacy and global financial stability. Countries that value monetary policy independence, fear capital flight in a crisis, and worry about destabilizing their domestic banks will strongly oppose the large-scale adoption of frictionless USD stablecoin accounts. They’ll use every tool available to block or limit these accounts, just as they’ve resisted other forms of dollarization. And while it may be impossible to stop crypto transactions entirely, as the Internet has shown, governments have numerous ways to restrict access and curb mainstream adoption. Does this mean stablecoins are doomed in emerging economies with capital controls or concerns over capital flight? Not at all—the rise of domestic stablecoins that adhere to local banking and regulatory frameworks is inevitable. While the U.S. dollar has traditionally dominated the stablecoin market, things could change rapidly. In Europe, following the implementation of the Markets in Crypto-Assets (MiCA) regulation, banks, fintech companies, and new entrants are rushing to issue euro-denominated stablecoins. This approach has the benefit of preserving the stability of the local banking system, and will be even more important in regions like Latin America, Africa, and Asia. Clear regulation also enables banks to finally enter and compete on an equal footing, something that hasn’t yet occurred in the United States. Banks can issue [deposit tokens](https://hbr.org/2021/08/stablecoins-and-the-future-of-money) in addition to fully-backed stablecoins, allowing them to boost revenue through money creation. This puts pure-play stablecoin issuers—who lack banking licenses, access to the discount window, or government deposit insurance—at a significant competitive disadvantage. ## 3. There will not be a single stablecoin winner Yes, an issuer can build network effects around global liquidity and availability for its stablecoin, but as DEX protocols know all too well, liquidity is as easily lost as found. Similarly, economies of scale in branding and marketing may help issuers capture mindshare, but they don’t always translate into a truly defensible position. The reality is that a stablecoin’s most important feature—its peg to a currency like USD or EUR—is also its greatest weakness. Today, these assets are seen as distinct, but once regulation standardizes stablecoins and makes each equally safe, individuals and businesses will view them simply as dollars or euros. While legal distinctions do exist—as highlighted during the Silicon Valley Bank run—most people don’t differentiate between dollars held at Bank of America and those at Chase. That’s the magic of those dollars functioning as money—a feat orchestrated behind the scenes by the Federal Reserve. The same will be true for stablecoins. While there may be dozens in each major market, this complexity will be abstracted away for users. When that happens, the [economics of stablecoins](https://hbr.org/2024/08/the-race-to-dominate-stablecoins) will favor entities with either a complementary business model, as described above, or those that control the interface between stablecoins and the assets backing them—be it bank deposits, U.S. treasuries, or money market funds. That is bad news for pure-play issuers like Circle, whose current banking system interfaces depend on entities such as BlackRock and BNY Mellon. These financial giants are well-positioned to become direct competitors. For instance, BlackRock already operates the largest tokenized U.S. Treasury bills and repos fund (BUIDL). A common misconception in the history of technological disruption is how frequently incumbents manage to push back. Even Clayton Christensen’s key example of disruptive innovation—the rise of smaller disk drive producers in the hard disk industry—is wrong: Seagate not only survived disruption but remains the world’s largest manufacturer to this day. In heavily regulated industries like financial services, the odds are even more heavily stacked against new entrants. Tech companies with banking licenses, like Revolut, Monzo, and Nubank, are well-positioned to lead in their markets, and other players are likely to accelerate their licensing efforts to gain similar advantages. However, many players in the stablecoin market will struggle to compete with established banks and may face acquisition or failure. Banks and credit card companies will resist a market dominated by one or two stablecoins. Instead, they’ll advocate for a landscape with multiple interoperable and interchangeable issuers. When that happens, liquidity and availability will be driven by existing distribution channels to consumers and merchants—an advantage already held by neobanks and payment companies like Stripe or Adyen. Fully-backed stablecoins like USDC and USDT will need high-velocity use cases to remain viable—such as enabling cross-border money movement—or they’ll need to attract a DeFi ecosystem that can introduce transparent fractionalization to subsidize their narrow-bank model. Meanwhile, deposit tokens issued by banks or tokenized funds will benefit from stronger underlying economics, which will drive their adoption across both consumer and institutional use cases. Institutional users, in particular, are used to managing diverse assets like money market funds and pay close attention to the opportunity cost of their capital. The race to the bottom in sharing stablecoin yields is already well underway in that segment. In every region, national champions—from banks to crypto firms—will position themselves as the essential entry point into the local market. However, they’ll need to carefully consider how stablecoins, by linking domestic rails to blockchain networks, could also lower barriers for foreign competitors to enter and compete. After all, the core transformation here from a business perspective is that these systems will run on [open protocols](https://www.forbes.com/sites/digital-assets/2024/04/18/forget-antitrust-regulate-to-let-tech-disrupt-itself/). ## So what does this all mean? The future is bright for leading payments, fintech, and neobank players, who can leverage stablecoins to streamline operations and accelerate global expansion. It also opens new opportunities for domestic stablecoin issuers to position themselves and ready their payment systems for global interoperability—an area where stablecoins are poised to succeed where the bureaucratic [BIS’s ‘Finternet’](https://www.bis.org/publ/work1178.htm) vision will quickly fall short. Leading crypto exchanges will also leverage stablecoins to enter the consumer and merchant payments space more aggressively, positioning themselves as credible challengers to major fintech and payment companies. While questions remain about how stablecoins will scale AML and compliance controls as they go mainstream, there’s no doubt they offer an opportunity to rapidly modernize our financial services stack and shake up industry leadership. --- ## Crypto Policy Needs to Empower Builders, Not Speculators - canonical: https://catalini.com/writing/crypto-policy-builders/ - original: https://www.project-syndicate.org/commentary/crypto-regulation-us-election-trump-bitcoin-boosterism-gives-harris-an-opening-by-christian-catalini-1-et-al-2024-09 - date: 2024-09-01 - outlet: project-syndicate Crypto regulation should reward building real utility, not speculation. Full text at the original outlet: https://www.project-syndicate.org/commentary/crypto-regulation-us-election-trump-bitcoin-boosterism-gives-harris-an-opening-by-christian-catalini-1-et-al-2024-09 --- ## How The SEC’s Attack On NFTs Harms Creators - canonical: https://catalini.com/writing/sec-attack-nfts/ - original: https://www.forbes.com/sites/digital-assets/2024/08/29/how-the-secs-attack-on-nfts-harms-creators/ - date: 2024-08-29 - outlet: forbes In a move that surprises few, yet concerns many, the U.S. Securities and Exchange Commission has issued a [Wells Notice to OpenSea](https://x.com/dfinzer/status/1828791832009953706), the leading NFT[APENFT](https://www.forbes.com/digital-assets/assets/apenft-nft/) marketplace. This action highlights SEC Chairman Gary Gensler’s approach of regulation by enforcement, continuing his pattern of targeting high-profile innovators instead of fostering a regulatory environment that truly protects investors and consumers. While the technology mirrors what arts and collectibles have achieved offline for centuries, it also unlocks new monetization and engagement models for digital creators. But if the goal is a broad crackdown on an entire technological paradigm, none of that matters—a strategy as historically futile as it is misguided. Rather than fostering constructive dialogue, such actions stifle innovation and further delay thoughtful crypto regulation. As with [earlier actions](https://www.forbes.com/sites/qai/2023/02/21/the-secs-stablecoin-crackdown-could-reshape-the-entire-crypto-market/), the SEC’s attacks undermine the very players actively seeking regulation and willing to collaborate with Congress to develop a constructive and safe digital assets framework. Even when the targeted companies eventually clear their names, the initial damage lingers—often derailing founders from their core mission and draining resources that could have been spent on growth. These actions once again underscore the inadequacy of existing legal frameworks in addressing the unique challenges and opportunities of digital assets. The SEC is applying outdated rules to fundamentally new products and services while overlooking the parallels between these new assets and established categories like art and collectibles. The longer this continues, the greater the risk that the United States will fall behind in leading this sector. ### [Best High-Yield Savings Accounts Of 2024](https://www.forbes.com/advisor/banking/savings/best-high-yield-savings-accounts/) ### [Best 5% Interest Savings Accounts of 2024](https://www.forbes.com/advisor/banking/savings/best-5-percent-interest-savings-accounts/) Non-fungible tokens mark a breakthrough in the design of digital markets, enabling ownership of digital goods in ways previously unimaginable. Before distributed ledger technology, distinguishing a digital original from its copies was impossible. Now, where a market was once nonexistent or highly flawed and concentrated, we can finally establish an efficient one. The fact that digital goods are costly to produce but easy to replicate—a phenomenon amplified by the internet—has already driven transformative changes across many industries, from software to music. Piracy's surge in the early 2000s made this clear, undermining markets that could no longer protect and reward creators and developers adequately. In music and video, the challenge was only addressed when platforms like Spotify and Netflix offered low-cost streaming as an alternative to pirated content. Yet, many creators, beyond the most successful, still struggle to effectively monetize their work. The difference today is that we have better technology to tackle this challenge. Creators are no longer confined to bundling content into subscriptions or offering it for free on social media, hoping to monetize their audience later. They now have a broader set of tools to create and capture value through their communities. But under the current regulatory climate, much of this is blocked by the threat of NFTs being classified as securities. Ironically, it’s the creators who strive to build lasting value for their audiences who are most at risk, while bad actors chasing quick gains are favored. We urgently need a legal framework that [separates crypto assets from the transactions they are involved in](https://corpgov.law.harvard.edu/2022/12/06/why-cryptoassets-are-not-securities/), necessitating new legislation—not securities laws ill-suited for this purpose—to regulate these markets effectively. Such a framework would also help challenge the stranglehold big tech platforms have over these transactions, allowing new communities to form around these digital artifacts and enabling them to transact and create value in innovative ways. Digital ownership on a blockchain can facilitate new forms of financial support, the development of derivative works, and the distribution of value among various participants in the creator economy—giving more creators the chance to earn a living. As [Kominers and Kaczynski](https://www.youtube.com/watch?v=xWLLYjVhoqs) detail in their book, NFTs can represent a wide range of assets, transforming interactions across various sectors—including the creative industries, education, music, entertainment, real estate, gaming, fashion and loyalty programs. They can also redefine community and brand governance, allowing a broader range of stakeholders to derive value from their contributions. Much like how open source software has expanded the ways we produce software, [NFTs can broaden how we produce and consume digital goods](https://www.competitionpolicyinternational.com/wp-content/uploads/2022/02/6-Can-Web3-Bring-Back-Competition-to-Digital-Platforms-Christian-Catalini-Scott-Duke-Kominers.pdf). For instance, they enable digital artifacts to be used and remixed by others while ensuring credit and rewards still reach the original creators. The idea that the internet could democratize access to finance and resources for creators is not new. In 2006, alongside Ajay Agrawal and Avi Goldfarb from the University of Toronto, [we studied how digital platforms could transform](https://www.nber.org/system/files/working_papers/w19133/w19133.pdf) the creative industries—not through crypto, but through crowdfunding. Even then, it was evident that a more direct connection between creators and their audience was possible, allowing fans who invested time and effort in supporting a creator’s breakthrough to benefit as well. It was an early, perhaps naive, attempt to reform the music label system and share more of the returns with artists and creators. Today, crowdfunding underpins a significant portion of the arts and creative sectors, as well as early tech prototypes and more. In a world where the National Endowment for the Arts has an annual budget of about $200 million, individual crowdfunding platforms like Kickstarter have contributed billions to the arts over a few years. NFTs are attempting to expand on this with much better technology and transparent ways to design incentives for supporters and others who contribute time and effort to a project’s growth. They foster meaningful communities and interactions, breaking away from the cookie-cutter formats imposed by the leading digital platforms on distribution. Attacking NFTs restricts the range of transactions the economy can support, harming artists, creators, and communities. It confines creators to a limited set of existing business models—the very ones that have granted enormous control and influence to the big tech platforms we rely on daily, from social media to the creator economy. If Chairman Gensler genuinely cared about U.S. competitiveness and prosperity, and the thousands striving to earn a living through digital work, he would stop regulation by enforcement. Rather, he should consider a constructive path forward for a technology that, no matter his stance, is inevitable. --- ## Why Big Tech Can’t Solve The Content Moderation Problem - canonical: https://catalini.com/writing/big-tech-content-moderation/ - original: https://www.forbes.com/sites/digital-assets/2024/08/28/why-big-tech-cant-solve-the-content-moderation-problem/ - date: 2024-08-28 - outlet: forbes Mark Zuckerberg’s [letter](https://x.com/JudiciaryGOP/status/1828201780544504064) this week to Rep. Jim Jordan (R-OH), where he expresses regret over censoring free speech under pressure from the administration, is the latest salvo in the never-ending saga of platform content moderation. The White House, in a characteristically quick rebuttal, [remarked that](https://www.politico.com/news/2024/08/26/zuckerberg-meta-white-house-pressure-00176399) “tech companies and other private actors should take into account the effects their actions have on the American people, while making independent choices about the information they present.” Which is the sort of vague guidance that lacks specificity and falls short of addressing the underlying problem. The reality is that content moderation—beyond the clear-cut cases of hate speech, violence, abuse, illegal activity, or threats to child safety, self-harm, etc.— is extremely difficult to get right and is bound to be perpetually flawed. The challenge only intensifies when it comes to breaking news or politically and socially charged events, where the stakes are high, and the incentives for various factions to skew public perception are even higher. There’s no easy playbook here; it’s messy, contentious, and often feels like an impossible balancing act. Any centralized platform is destined to make mistakes—there’s no avoiding it. The idea of making genuinely “independent choices” or outsourcing these decisions to an impeccably balanced oversight board is more fantasy than reality. Even with the best intentions, the need for quick decision-making under uncertainty guarantees errors on both ends: censoring content that shouldn’t be, while simultaneously allowing fake or harmful content to spread before the truth can catch up. It’s a classic case of damned if you do, damned if you don’t. The pandemic offers a textbook example of how hindsight can make it easier to spot where mistakes were made—with today’s information, for instance, we can see that mandating vaccines for those who had already contracted the virus was likely [unnecessary](https://www.thelancet.com/article/S0140-6736(22)02465-5/fulltext). However, it’s easy to overlook that, at the time, misinformation was spreading like wildfire across social media, and vaccines were a critical tool that saved millions of lives. A [study](https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(22)00320-6/fulltext) published in *The Lancet*, one of medicine’s top journals, estimates that vaccines prevented as many as 14 million deaths worldwide. While there may be debate over the exact numbers, there remains a strong scientific consensus on the life-saving impact of vaccines, even in hindsight. ### [Best High-Yield Savings Accounts Of 2024](https://www.forbes.com/advisor/banking/savings/best-high-yield-savings-accounts/) ### [Best 5% Interest Savings Accounts of 2024](https://www.forbes.com/advisor/banking/savings/best-5-percent-interest-savings-accounts/) So, while the White House may have been acting with good intentions, it’s evident that the decision to censor free speech—including humor and satire—was wrong. But let’s be clear: the solution the White House reiterated this week is equally flawed. It merely shifts the burden from the government to a private company, effectively outsourcing the blame. Platforms shouldn’t be tasked with making these impossible choices. They are for-profit businesses, and while they should certainly take steps to curb content that is undeniably harmful, they should not be cast as the ultimate arbiters of our speech. This is not a new insight. Internet platforms today wield too much power, and content moderation is a prime example of a responsibility they’d rather not hold, yet it permeates everything else they do. Even when there are sincere attempts to distribute control—like our efforts with the Libra Association—achieving truly balanced participation and representation is impossible within the confines of a traditional web platform. While the issue is most obvious in social media, it extends far beyond, impacting everything from merchants attempting to reach customers on Amazon to developers trying to distribute and innovate within Apple’s ecosystem. What’s a better solution? For starters, grassroots efforts for verification and fact-checking—like X’s Community Notes—should be actively encouraged. This bottom-up approach is how the internet built Wikipedia, the most comprehensive and reliable encyclopedia available, and how Reddit users sift through news and controversial topics daily. Even better, fact-checking should be platform-agnostic. It’s a public good, and when someone goes through the effort to debunk a piece of misinformation, that correction should be as widely disseminated as possible. Second, we need to adopt an open protocol approach to social media. Not only should users be able to take their audiences with them across platforms—something the FTC could enforce to [rapidly accelerate competition and innovation](https://www.forbes.com/sites/digital-assets/2024/04/18/forget-antitrust-regulate-to-let-tech-disrupt-itself/)—but they should also have the freedom to choose the algorithms and filters that shape their feeds. Imagine an algorithm marketplace where consumers can opt for content curated by their social circle, all the way to minimal or no filtering—much like what X under Musk successfully dismantled from the old Twitter. The White House’s position reflects a paternalistic approach to content distribution, one that a different administration could easily exploit to serve its own interests. True progress lies in empowering users to critically evaluate information themselves and providing them with the tools to customize their own experience. Only then can we move toward a more resilient and transparent system. The technology to make this vision a reality already exists, and open protocols built on crypto rails have demonstrated it’s possible. What’s lacking is the commitment to modernize our current web infrastructure—moving away from closed, walled gardens with excessive control over all types of curation, toward a [more open and modular digital infrastructure](https://www.nber.org/system/files/working_papers/w22952/w22952.pdf). Regulators have a crucial role in enabling this transformation, and instead of relying on regulation by enforcement—as exemplified by [today’s S.E.C. action](https://x.com/dfinzer/status/1828791832009953706) against OpenSea—they should consider how to support entrepreneurs in building the next generation of the internet. With the rapid rise of AI-driven content creation, the stakes could not be higher. --- ## The Race to Dominate Stablecoins - canonical: https://catalini.com/writing/race-to-dominate-stablecoins/ - original: https://hbr.org/2024/08/the-race-to-dominate-stablecoins - date: 2024-08-01 - outlet: hbr The competitive dynamics deciding who wins the stablecoin market. Full text at the original outlet: https://hbr.org/2024/08/the-race-to-dominate-stablecoins --- ## Are Stablecoins Winner-Take-All? - canonical: https://catalini.com/writing/stablecoins-winner-take-all/ - original: https://catalini.com/s/2-ARE-STABLECOINS-WINNER-TAKE-ALL-Christian-Catalini-Jai-Massari.pdf - date: 2024-07-15 - outlet: cpi Whether network effects make the stablecoin market tip to a single winner. Full text at the original outlet: https://catalini.com/s/2-ARE-STABLECOINS-WINNER-TAKE-ALL-Christian-Catalini-Jai-Massari.pdf --- ## Forget Antitrust, Regulate To Let Tech Disrupt Itself - canonical: https://catalini.com/writing/forget-antitrust/ - original: https://www.forbes.com/sites/digital-assets/2024/04/18/forget-antitrust-regulate-to-let-tech-disrupt-itself/ - date: 2024-04-18 - outlet: forbes For decades, policymakers have tried to curb big tech’s growing influence on our lives, from the government’s antitrust case against Microsoft[MSFT](https://www.forbes.com/companies/microsoft) for its anticompetitive behavior against Netscape in the [browser market](https://www.forbes.com/1999/11/05/mu1.html?sh=48642ca84292) in the late 1990s, to the FTC challenging the [acquisitions](https://www.forbes.com/sites/siladityaray/2020/11/19/report-states-ftc-set-to-sue-facebook-over-acquisitions-of-instagram-whatsapp/?sh=154d1cb259f0) of Instagram and Whatsapp by Meta, Amazon’s[AMZN](https://www.forbes.com/companies/amazon) practices with its [sellers](https://www.forbes.com/sites/tylerroush/2023/09/26/feds-file-landmark-suit-against-amazon-for-protecting-online-retail-monopoly/?sh=3333cebb56c6) and [customers](https://www.forbes.com/sites/willskipworth/2023/10/03/amazon-allegedly-used-secret-algorithm-to-raise-prices-on-consumers-ftc-lawsuit-reveals/?sh=1b530404196d), [Apple’s recent $2 billion EU fine](https://www.forbes.com/sites/siladityaray/2024/03/04/apple-fined-nearly-2-billion-by-european-union-for-abusing-its-dominance-to-harm-music-streamers/?sh=7d69dd8e593e) for its conduct against Spotify, and now the new [DOJ case](https://www.forbes.com/sites/moorinsights/2024/04/05/apples-doj-lawsuit-was-inevitable-and-will-change-the-company-forever/?sh=54ea221816b7) against Apple[AAPL](https://www.forbes.com/companies/apple). Unfortunately, in all these cases, antitrust enforcement and fines have been extremely ineffective. Similarly, well-intentioned rules, like GDPR, [backfired](https://www.brookings.edu/wp-content/uploads/2019/12/ES-12.04.19-Marthews-Tucker.pdf) by raising compliance costs, thus aiding established firms and hindering new privacy-centric players. Even when they don’t backfire, regulations in this area run into all sorts of implementation challenges. While the key objective of the [Digital Markets Act](https://commission.europa.eu/strategy-and-policy/priorities-2019-2024/europe-fit-digital-age/digital-markets-act-ensuring-fair-and-open-digital-markets_en) (DMA) is directionally correct—to prevent companies that have become gatekeepers in so many of our economic and social interactions to abuse their dominant position—its execution leaves plenty of room for incumbents to stall, whether it’s in the name of privacy, security or technical complexity. The truth is that Microsoft Internet Explorer was not defeated by large antitrust fines or by giving consumers the option to [choose a browser](https://en.wikipedia.org/wiki/BrowserChoice.eu) in Windows, but by the world moving on with mobile devices and Microsoft missing that wave of innovation. Fundamentally, it's through the same innovative forces that created these extremely successful companies that competition can be brought back. And it is the policymakers who determine if that happens. Innovation that is truly disruptive requires an [architectural rewiring](https://hbr.org/2016/03/the-other-disruption) of how problems are solved, and that sparks the need for new regulation. ### [Best High-Yield Savings Accounts Of 2024](https://www.forbes.com/advisor/banking/savings/best-high-yield-savings-accounts/) ### [Best 5% Interest Savings Accounts of 2024](https://www.forbes.com/advisor/banking/savings/best-5-percent-interest-savings-accounts/) When faced with a novel technological paradigm, policymakers can make one of two major mistakes: regulate too early, or wait for too long. When regulation is too rigid, too early, it is equivalent to picking winners at a time when the landscape is still uncertain. So it should come as no surprise that this approach never works. A recent example is the [executive order on AI](https://www.whitehouse.gov/briefing-room/presidential-actions/2023/10/30/executive-order-on-the-safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence/#:~:text=(ii)%20any%20computing%20cluster%20that,per%20second%20for%20training%20AI.) issued by President Biden. This order appears to be more driven by fear than by technical considerations. For example, it sets thresholds based on the number of floating-point operations to determine the level of regulation for AI projects. Because the thresholds are arbitrary, they will either be irrelevant, or in the worst case, actually detrimental to AI development in the United States. When regulation arrives too late instead, policymakers push the best innovators out by failing to provide them with clarity. That’s what is happening in the United States with crypto, and comes at the risk of the country squandering its lead. It also ironically helps projects that are comfortable breaking the law, as we have seen with the FTX scandal. The excuse, [at least from the SEC](https://www.sec.gov/news/statement/gensler-coinbase-petition-121523), is that rules written in 1933 and a framework for financial markets designed when we relied on open outcry trading, physical stock certificates and prices rolled out on ticker tape do not need any updating. Regulation that arrives too late or too early protects incumbents. And it's hard to blame policymakers, as their incentives are not aligned. Unlike venture capitalists, who enjoy massive upside on success and limited downside on failure, regulators and policymakers get little credit when things go well, and all the blame when they don’t. The decision by the U.S. government to not over-regulate the internet drove decades of economic growth, but few likely remember the names of those involved in it. As a result, the typical regulatory “portfolio” is filled with safe but mediocre bets. The exceptions are moments in history where governments had the courage to propel their nations forward, from the Marshall Plan, to China’s economic reform, the space race, the EU single market, and more. Today we are at a similar juncture for all of our digital infrastructure: from AI and robotics, to financial services and digital marketplaces, if the United States wants to continue to lead, it needs to create the right conditions for competition to thrive. Like in the early days of the internet, this starts with policymakers embracing and nurturing a novel architecture based on open protocols. But how can open protocols limit the power of big tech intermediaries and accelerate a new wave of innovation? In Latin, intermediary means “in the middle.” Intermediation can be extremely helpful to society, and many transactions would never exist without intermediaries. But when intermediaries accumulate too much power, they not only capture all of the value they create, but also slow down progress. Unfortunately, accumulating power is a natural result of being an intermediary: When you’re in the middle, you have access to better information than either side, can decide on what terms others participate, and shape interactions to your advantage. As a result, historically we’ve alternated between the rise of new intermediaries, and the subsequent push to remove them from their privileged position. So what is an effective approach to rein in powerful intermediaries? You need to find an alternative way to connect the two sides of the market. Sometimes the government may regulate away the intermediaries’ most outrageous behaviors or become a benevolent (but inefficient) intermediary. Sometimes technology surprises us all with something much better: interoperability. In latin, interoperability means “to work between.” Which makes it clear why interoperability is the best antidote to someone standing in the middle. We’ve seen this all before. Because the internet was built on open and interoperable protocols, it was a strong decentralizing force and decreased the power of intermediaries across a range of industries. It also created the conditions for new and more powerful intermediaries to emerge from marketplaces and payments, to messaging and social media, the creator economy, etc. Propelled by the need to monetize the fast-growing networks they created, internet-based intermediaries proceeded to limit interoperability and constrained consumers and businesses within their walled gardens. Today, their walls define how businesses surface products to their customers, developers distribute their apps, how we interact with our social network, how creators connect to their audiences, and a lot more. By controlling access, the underlying data, and the algorithms that rank results and match buyers and sellers, each one of these platforms shapes how society allocates attention, effort and money. Without a change in direction, AI will only make this worse, since it builds on the advantage these companies have established across data, compute, and distribution channels. Interoperability fixes this. Imagine a world where you can send and receive messages irrespective of the messaging app you use. Same with sending and receiving money, reading updates from your social or news feed, finding the right product or service, or interacting with an AI agent. On a truly interoperable network consumers and businesses have actual leverage against intermediaries, as they can port their business elsewhere without having to rebuild their audience, social graph, or customer base. Developers also won’t worry about their platform becoming a competitor overnight. By injecting interoperability into our digital interactions, open protocols unravel the advantage tech companies have established over the last decades, and force them to compete again. This, in turn, drives the type of innovation that helped the United States lead in the early days of the internet. However, for any of this to materialize, regulators must first establish a framework that allows the new open protocols enabled by cryptocurrencies to thrive. With regards to everything from securities laws and financial market infrastructure to stablecoins, the time to act on crypto regulation is now. Otherwise, these protocols and the economic growth they promise will develop elsewhere. The impact of these developments extends well beyond financial services. These open protocols, which are gradually rewiring our financial system, have the potential to reshape competition in AI, digital platforms and infrastructure. Entrepreneurs and developers are already at work. However, much like in the internet’s early days, their ventures will not succeed without the right regulatory framework. --- ## Is Crypto’s Killer App Finally Here? - canonical: https://catalini.com/writing/cryptos-killer-app/ - original: https://www.forbes.com/sites/christiancatalini/2024/02/19/is-cryptos-killer-app-finally-here/ - date: 2024-02-19 - outlet: forbes Crypto is a [general-purpose technology](https://www.nber.org/system/files/working_papers/w22952/w22952.pdf) (GPT) like the steam engine, electricity, the internet, and AI. Because GPTs require a major rewiring of the economy to be useful, we inevitably overestimate how quickly they will change our lives. But when change eventually happens, it is faster and more pervasive than expected. After more than ten years of experimentation and infrastructure building, crypto is at a turning point, and might soon find its ChatGPT moment. The internet incubated for decades within academic and military circles before becoming [commercial](https://www.youtube.com/watch?v=NwbMhTkmfew). Similarly, artificial intelligence was mostly a research endeavor before OpenAI, Tesla[TSLA](https://www.forbes.com/companies/tesla) and big tech turned it mainstream. For crypto believers, decentralization has always been the holy grail. Historically, tech has swung like a pendulum between centralization and decentralization: from mainframes to PCs, Microsoft[MSFT](https://www.forbes.com/companies/microsoft) Windows to the web, and finally, to the walled gardens of today's tech giants. The next logical step? An open infrastructure powered by, you guessed it, crypto. But what does "open" mean? After all, the web is already built on open standards and protocols, but that led to more market concentration, not less. What is different this time is that crypto pushes for deeper forms of interoperability and portability — from your social graph, to your content, to your “bank” account. In payments, the lack of interoperability in today’s services is very salient. Digital wallets and card networks do not allow you to send or receive money outside of their curated network. Similarly, you can’t move your funds from one fintech app to another without going back to your bank account, which still acts as the only interoperability layer for our financial lives. Incumbents with market power fight tooth and nail to prevent interoperability and portability. They don’t want their customers sending or receiving payments to and from their competitors too easily. Nor do they want you to be able to move your business elsewhere if you are dissatisfied with their terms and conditions. It's not good for their bottom-line, even if it would be great for everyone else. ### [Best High-Yield Savings Accounts Of 2024](https://www.forbes.com/advisor/banking/savings/best-high-yield-savings-accounts/) ### [Best 5% Interest Savings Accounts of 2024](https://www.forbes.com/advisor/banking/savings/best-5-percent-interest-savings-accounts/) The same is true for access to distribution. While you may have invested countless hours building your audience, identity, reputation, or social graph on a platform, you never truly own the fruits of your labor, the platforms do. And it doesn’t matter if you are a creator, app developer, gig worker, or merchant — the platform you helped scale has all the leverage. Crypto, by forcing interoperability and portability into platforms, turns today’s walled gardens into open infrastructure anyone can build and compete on. While this represents a major threat for incumbents, because the technology is developed in a decentralized fashion it also takes a very long time to mature. We've now been waiting for crypto's "killer app" for over a decade, just like AI was waiting for its ChatGPT moment. So, when it arrives, what will it look like? Probably a bit clunky, niche, and maybe even toy-like at first. Think [Frames](https://www.notboring.co/p/framing-the-future-of-the-internet) on [Farcaster](https://www.farcaster.xyz/): interactive applications that can be embedded in posts — essentially like a fully-fledged App Store in your social feed. Innocuous, right? But this crypto primitive is potentially transformative from a market structure perspective. It allows developers to distribute their creations freely, escaping the walled gardens that dictate how they get paid and what they can build (remember the recent [Spotify-Apple drama](https://twitter.com/eldsjal/status/1750988499518362089?s=20)?). "But couldn't we already do this on the web?" you might ask. Yes and no. That's where crypto's multiyear investment in rebuilding the infrastructure of the internet shines. Frames are crypto-native apps, meaning authentication, identity, and payments are just a click away for users. Unlike Web2 platforms, where control over the underlying data helps build barriers to entry, Frames data can also live on-chain, where it is accessible to everyone. Multiple companies and projects can build front-ends to that data, aggregate it in novel ways and compete with different business model. Users are in full control of their social graph and content, and can move freely between the resulting products and experiences. This combination will unlock [frictionless commerce](https://x.com/dwr/status/1757507458573160921?s=20), novel ways for creators and developers to monetize their ideas, and eventually new type of marketplaces and platforms will emerge and compete. Developers on Frames are rebuilding key parts of the Web2 and mobile stacks with crypto building blocks, and that's inspiring. Even more intriguing? Closed platforms will struggle to replicate Frames' openness, as it threatens their traditional monetization and curation models. Are Frames the future? Maybe not, but they're a glimpse of what crypto has been promising from the beginning. The infrastructure is now in place, and it's up to developers to unleash their creativity. Remember Bitcoin[BTC](https://www.forbes.com/digital-assets/assets/bitcoin-btc/)? It took over a decade, but now it's the uncontested bridge between traditional finance and crypto, and its network can serve as the foundation for new payment and financial services. Just like AI went from "meh" to ChatGPT overnight, decentralized networks and applications are finally getting slick enough to capture mainstream attention. In 2023, [it was important to urge](https://hbr.org/2023/01/do-crypto-prices-actually-mean-anything) crypto entrepreneurs to ditch the obsession with new token launches and reckless trading, and focus on real value for consumers and businesses. The FTX winter was a harsh lesson, but the seeds that were planted then are starting to sprout. By focusing on utility instead of speculation, crypto can finally deliver on its long-awaited promise. So, is the killer app here? Maybe not yet, but the stage is set for a much more exciting act two. Stay tuned. *You can follow me*[@ccatalini](https://twitter.com/ccatalini). *I am thankful to*[Leigh Cuen](https://twitter.com/La__Cuen)*,*[Jai Massari](https://twitter.com/JaiMassari)*,*[Jane Wu](https://twitter.com/wu_jane)*, and*[Linda Xie](https://twitter.com/ljxie)*for their helpful comments, which greatly improved this article.* --- ## The Hidden Breakthrough Behind Bitcoin - canonical: https://catalini.com/writing/hidden-breakthrough-bitcoin/ - original: https://www.lightspark.com/news/insights/the-hidden-breakthrough-behind-bitcoin - date: 2023-06-01 - outlet: lightspark The economic breakthrough underneath bitcoin’s design. Full text at the original outlet: https://www.lightspark.com/news/insights/the-hidden-breakthrough-behind-bitcoin --- ## Do Crypto Prices Actually Mean Anything? - canonical: https://catalini.com/writing/crypto-prices-mean-anything/ - original: https://hbr.org/2023/01/do-crypto-prices-actually-mean-anything - date: 2023-01-01 - outlet: hbr What crypto asset prices do — and don’t — tell us about underlying value. Full text at the original outlet: https://hbr.org/2023/01/do-crypto-prices-actually-mean-anything --- ## How Digital Currencies Can Help Small Businesses - canonical: https://catalini.com/writing/digital-currencies-small-businesses/ - original: https://hbr.org/2022/05/how-digital-currencies-can-help-small-businesses - date: 2022-05-01 - outlet: hbr Cheaper, faster payment rails as a lifeline for small-business margins. Full text at the original outlet: https://hbr.org/2022/05/how-digital-currencies-can-help-small-businesses --- ## Can Web3 Bring Back Competition to Digital Platforms? - canonical: https://catalini.com/writing/web3-competition-digital-platforms/ - original: https://catalini.com/s/Can-Web3-Bring-Back-Competition-to-Digital-Platforms.pdf - date: 2022-03-07 - outlet: cpi Whether portable, user-owned assets can restore contestability to platform markets. Full text at the original outlet: https://catalini.com/s/Can-Web3-Bring-Back-Competition-to-Digital-Platforms.pdf --- ## Stablecoins and the Future of Money - canonical: https://catalini.com/writing/stablecoins-future-of-money/ - original: https://hbr.org/2021/08/stablecoins-and-the-future-of-money - date: 2021-08-10 - outlet: hbr Why stablecoins matter, how they should be regulated, and what they mean for the future of money. Full text at the original outlet: https://hbr.org/2021/08/stablecoins-and-the-future-of-money --- ## It’s Time to Knock Down the Walled Gardens of the Payments System - canonical: https://catalini.com/writing/payments-walled-gardens/ - original: https://www.americanbanker.com/opinion/its-time-to-knock-down-the-walled-gardens-of-the-payments-system - date: 2021-06-01 - outlet: american-banker The case for open, interoperable payment rails over closed networks. Full text at the original outlet: https://www.americanbanker.com/opinion/its-time-to-knock-down-the-walled-gardens-of-the-payments-system --- ## DeFi, Disintermediation, and the Regulatory Path Ahead - canonical: https://catalini.com/writing/defi-regulatory-path/ - original: https://www.theregreview.org/2021/05/10/massari-catalini-defi-disintermediation-regulatory-path-ahead/ - date: 2021-05-10 - outlet: regulatory-review How regulators should approach decentralized finance and disintermediation. Full text at the original outlet: https://www.theregreview.org/2021/05/10/massari-catalini-defi-disintermediation-regulatory-path-ahead/ --- ## Bitcoin and Beyond - canonical: https://catalini.com/writing/bitcoin-and-beyond/ - original: https://www.project-syndicate.org/onpoint/bitcoin-and-new-digital-ledger-applications-by-christian-catalini-et-al-2021-04 - date: 2021-04-01 - outlet: project-syndicate Digital ledgers beyond bitcoin: what the technology is actually good for. Full text at the original outlet: https://www.project-syndicate.org/onpoint/bitcoin-and-new-digital-ledger-applications-by-christian-catalini-et-al-2021-04 --- ## Facebook Will Be Unable to Control Libra - canonical: https://catalini.com/writing/facebook-unable-control-libra/ - original: https://en.globes.co.il/en/article-facebook-will-be-unable-to-control-libra-1001303874 - date: 2019-08-01 - outlet: globes Why Libra’s design points toward decentralization rather than corporate control. Full text at the original outlet: https://en.globes.co.il/en/article-facebook-will-be-unable-to-control-libra-1001303874 --- ## Why Blockchain Can Be Good For Competition - canonical: https://catalini.com/writing/blockchain-good-for-competition/ - original: https://www.forbes.com/sites/christiancatalini/2017/10/30/why-blockchain-can-be-good-for-competition/ - date: 2017-10-30 - outlet: forbes In the endless debate about when do you actually need a blockchain within a specific industry vertical versus not, it is easy to lose sight of the big picture. Proponents of permissioned, distributed ledgers are often quick to point out the shortcomings of permissionless protocols such as Bitcoin or Ethereum. Because of their decentralized nature, they do not fit within existing regulatory frameworks, are difficult to monitor and control, and introduce new trade-offs in terms of speed, flexibility and energy consumption into what could otherwise be a seamless process of transaction reconciliation across organizations. Private blockchains, they say, can deliver all the benefits of this new, exciting wave of technological change without disrupting how businesses run their operations. The catch is that permissioned blockchains take advantage of only one of the two, key costs affected by blockchain technology: [the cost of verification](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2874598). In and of itself, being able to cheaply verify the attributes of a specific transaction (e.g. who is involved, their credentials, etc.) without incurring additional costs or performing an extensive audit can be extremely valuable to society. For markets to thrive, buyers and sellers need to be able to trust the information they use to decide when and with whom to transact. Whenever the asymmetry of information between buyers and sellers is too large, markets unravel, and beneficial trades do not take place. Blockchain technology, by lowering the cost of verification, can make markets more secure and efficient, and expand the types of transactions we are willing to engage in. Many of the systems used today across the globe to settle and reconcile transfers of value and digital assets could theoretically be made more efficient with a distributed ledger. Of course, for verification costs to actually drop, the data recorded on a blockchain needs to be accurate to begin with. While this is easy to achieve when all the information needed is generated and updated digitally (as in Bitcoin), when a distributed ledger is used to track offline events, the question of how to port such analog information back into the digital space is an unresolved one. This “last mile” problem constitutes a sizable entrepreneurial opportunity for startups and incumbents that realize that blockchain does not necessarily remove the need for intermediaries, but instead changes the nature of intermediation. Third-parties can still add substantial value to marketplaces (e.g. through curation), but a revenue model simply based on processing transactions is unlikely to be sustainable in the long run. Where permissioned blockchains fall short is in taking advantage of the other, key cost impacted by the technology: [the cost of networking.](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2874598) When combined with a native token, a permissionless blockchain can be used to bootstrap a digital platform without the need for a central intermediary. Driven purely by the incentives embedded within its protocol - which need to be carefully designed! - permissionless platforms enjoy the benefits of a shared network infrastructure, without the main cost it typically involves: market power. As a result of network effects and economies of scale, the digital platforms that shape our lives today have accumulated a high degree of market power. In fact, they often act as the default, “shared infrastructure” within their industry vertical. While this may not always be visible through higher prices for consumers (as many of these products are given away for free), it is typically reflected in adjacent markets (e.g. advertising), and in the amount of data these businesses have accumulated relative to everyone else competing with them. Beyond the [privacy risk](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2916489) of exposing large segments of our digital lives to a small number of players, data concentration has implications for competition - not just today, but also in the future. For instance, if we want a competitive market for [artificial intelligence](https://hbr.org/2016/11/the-simple-economics-of-machine-intelligence) applications, we will need to unlock these data monopolies so that more than a handful of players can generate high quality predictions. **So How Can Blockchain Increase Competition And Lower Barriers To Entry?** To ensure a higher degree of competition, permissionless blockchains can be used to create digital marketplaces without assigning control - both over prices and access to data - to a single operator. When entrepreneurs and developers in this space talk about [“censorship resistance”](https://blog.chain.com/a-letter-to-jamie-dimon-de89d417cb80), it is important to realize that censorship is simply an expression of market power. By allowing individuals and firms to transact without assigning market power to a central intermediary, the digital platforms built on top of permissionless ledgers can turn concentrated markets into substantially more competitive ones. This can lower barriers to entry for startups and lead to new products and services. By lowering the cost of networking, permissionless ledgers also allow for a fine-grained definition of digital property rights, including rights to the underlying data. While on current digital platforms the operator by default has access to all information exchanged, in this new regime, users and businesses will have substantially better control over digital privacy. New data licensing and monetization models will also be possible. Of course, we could have achieved this before by developing an industry standard to ensure interoperability and low barriers to entry. The key difference is that with a native token, digital platforms can reward contributions of talent, capital and resources (e.g. computing, storage etc.) in a fundamentally novel way. Instead of having to price everyone’s contributions during the negotiations for the standard, this can all happen in an automatic fashion as the network organically develops. At the same time, like industry standards, permissionless blockchains will have to develop substantially more reliable and effective forms of governance. For a platform to thrive, it needs to be able to evolve and adapt as new needs emerge. It also needs to address the risk for underinvestment in aspects of the technology that generate a positive externality between participants. Possibly even more important, permissionless networks will have to identify problems individuals and organizations need solved. Only by addressing a real customer need, will these platforms be able to move from the investment and speculation phase, to actual growth. Permissioned blockchains, possibly because they are solving more narrow problems within a framework that businesses understand, have shown that there is demand for the ability to verify and reconcile transaction attributes at a lower cost. Now it’s on the permissionless camp to prove that if you also take advantage of the reduction in the cost of networking, you can actually design a better incentive, governance and innovation system that can outpace alternatives and create a substantially more competitive market. --- ## Seeing Beyond the Blockchain Hype - canonical: https://catalini.com/writing/beyond-blockchain-hype/ - original: https://sloanreview.mit.edu/article/seeing-beyond-the-blockchain-hype/ - date: 2017-03-27 - outlet: mit-smr Separating durable economics from noise in the first blockchain wave. Full text at the original outlet: https://sloanreview.mit.edu/article/seeing-beyond-the-blockchain-hype/