Founder · Economist · Writer
I study what happens to money, markets, and institutions as AI drives the cost of intelligence toward zero — and as open networks rewire how value moves. Founder of the MIT Cryptoeconomics Lab, co-founder of Lightspark, and co-creator of Libra.
§ 01 What I’m thinking about now
The economics of AI
AI is driving the marginal cost of execution toward zero — so the scarce resource migrates. The new bottleneck is our biologically bounded capacity to audit, underwrite, and take responsibility for machine decisions.
The economics of stablecoins
The next platform war is over the rails of the global economy itself: closed, vertically integrated “CorpChains” versus open networks that unbundle the asset from the rails. Cooperate on the platform, compete on products.
The GENIUS Act
Issuance is becoming a commodity; the advantage is distribution. With the GENIUS Act setting reserve and redemption guardrails, the open question shifts to infrastructure for AI agents: portable identity, programmable payments, verifiable trust.
When intelligence is cheap, the scarce resource becomes trust — and trust gets built on open networks.
§ 02 Latest thinking
Stablecoins aren’t a profit center. So the future belongs not to a dominant issuer but to 140 rivals who agree on one neutral standard, and share the upside.
Decentralized intelligence will not win in the same format as the one we're being served by the large foundation labs.
Nadella 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.
Anthropic quietly rationed the one domain where AI compounds fastest. Its fix made the fence visible, but didn't move it.
The moral of the Fable: verification sets the speed, and the labs draw the borders.
§ 03 Record
Co-creator · 2018–2022
Chief Economist of the Diem Association and Head Economist of Meta’s FinTech division; engaged regulators from the Fed and U.S. Treasury to the ECB, Bank of England, and MAS.
Co-founder · 2022–2026
As Chief Strategy Officer, led the Finance, AI and Data Science, Business Development and Sales, Corporate Development, and Strategic Partnerships teams. Now Advisor to the CEO.
Founder · 2017–
Research on the economics of AI and AGI, digital assets, stablecoins, and cryptocurrencies. Designed the 2014 MIT Digital Currency Research Study, which gave every MIT undergraduate access to Bitcoin.
§ 04 Heard on
CoinDesk Podcast Network — What Libra’s arc teaches about Open Standard’s OUSD and collectively governed stablecoin rails.
Beyond the Prompt — Anything AI can measure, it will automate — the dividing line for every job and firm.
Beyond The Prompt - How to use AI in your company — The unexpected economics of AGI: why measurability decides what gets automated, and trust decides what gets deployed.
§ 05 Signal
1/ Today, more than 140 companies, most of which compete fiercely with one another, agreed to back the same stablecoin. The vehicle is @openstandard, a new and deliberately independent company launching Open USD, or OUSD, and positioning it not as anyone's product but as neutral infrastructure.
1/ Nadella's Test: What's Left When The AI Model Is Pulled? @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.
AI hits the slop ceiling: over the next months, systems we rely on will quietly break. Not from bad AI. From AI output that was cheap to produce, plausible enough to pass, and never verified by anyone with the expertise to catch it. All the shovels are on the verification side.
"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!
1/ 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.
1/ Skill-biased technical change is dead. @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.
§ 06 Advisory
§ 07 Contact
The routed contact form (Board & executive / Speaking & press / Advisory / Research) ships in P3.
