Welcome to Edition 14 of The Reading List — your fortnightly antidote to the noise. Every two weeks, I share my favourite reads across crypto, finance, technology, culture, and beyond. I also share what I’m watching and reading.

What I’m Watching and Reading

I spent the past two weeks prepping for moving cities. So cardboard boxes and last-minute checklists got all my attention. I haven’t read nearly as much over the past month as I usually do. But I did make one trip to the cinema (cannot miss that for sure).

I watched The Odyssey a little over a week ago and gave it 4.5.

Christopher Nolan’s storytelling is top-notch and the single biggest reason to watch it in theatres. Matt Damon and the rest of the cast are breathtaking in places, carrying the emotional weight of a journey whose scale could easily have overwhelmed its characters.

I found dialogue delivery and visuals slightly lacking by Christopher Nolan’s standards. Some stretches appeared dull and too monochromatic for a film built around one of literature’s most expansive journeys.

Ludwig Göransson compensates for much of that. He does with the music what only he seems capable of doing. Even when the film seems to be lost in the dullness of the visuals, Ludwig keeps the film alive and moving.

Between watching The Odyssey, packing up one home and attempting to make another feel like one, I have had a relatively quiet month of reading. But I promise to be back with some interesting reads over the coming fortnight.

Despite my thin reading list, the macro events kept the calendar full

Got any recommendations for nice watches or reads? Write to me?

The Fortnight That Was

In the final two weeks of July, US inflation cooled marginally (at least for now), while the US–Iran conflict refused to reach a durable conclusion.

US consumer prices rose 3.5% in the year to June. The Federal Reserve’s preferred Personal Consumption Expenditures index subsequently eased from 4.1% in May to 3.7% in June. Overall, inflation is slowing, but it remains too high for the Fed to feel comfortable.

US real GDP expanded at an annualised rate of 1.5% in Q2, slowing from 2.1% in the first quarter. Consumer spending, investment and exports increased, but lower government spending dragged on the headline figure.

Despite slower growth and inflation still above target, the Fed kept interest rates unchanged at 3.5%–3.75%. The 9–3 vote was divided, with a trio voting in the opposite direction for the first time since 2019. Economic activity is holding up, but the war-induced energy shock has made the path back to 2% inflation more difficult.

By the end of July, the pause in the US-Iran war looks less like a settlement and more like another interval between escalations. Iran said it had stopped or turned back vessels attempting to cross the Strait of Hormuz, while attacks on shipping and US-linked facilities revived fears of a wider regional conflict. Brent crude ended July roughly 22% higher.

The markets reflected all this uncertainty.

Bitcoin was the only major asset in the chart to end the fortnight meaningfully lower (-1.6%). Ether outperformed BTC with 1.3% gains in the fortnight. However, both ETH and BTC ended July in the green with 18.6% and 7.3% gains.

Underneath these price movements, we kept observing and writing about the same structural change across crypto, AI, fintech and capital markets.

Creating a financial asset, issuing a token or building a model is becoming easier. The more valuable layer is increasingly the one that provides product distribution, financing, liquidity, and a place inside the wider economy.

That was also the thread running through the stories we published at Token Dispatch over the past fortnight.

What We Wrote Last Fortnight

With Is Crypto VC Dying?, Vaidik examined why specialist investors such as Paradigm and Framework Ventures are broadening their mandates into AI, robotics and aerospace. The shift does not necessarily mean crypto has failed. It may instead signal the maturity of the technology, meaning the informational advantage once held by crypto-only investors matters less. Crypto founders must now compete for capital and attention inside portfolios increasingly dominated by AI.

In Equity Learns to Borrow, I explored why raising corporate debt is routine while issuing equity remains a ceremony involving bankers, roadshows and substantial fees. Tokenised issuance could widen the geographic pool of buyers and allow companies to distribute shares more continuously, making equity issuance behave a little more like tapping a debt programme.

That drove me to write further about the thesis of crypto transforming into fintech. DTCC, SWIFT, Visa and other financial infrastructure operators are beginning to use blockchains to move securities, deposits and collateral. Crypto’s biggest impact may come from becoming the infrastructure they use behind the scenes. Crypto companies that once hoped to defeat Wall Street are increasingly invoicing the traditional financial companies by offering them tailor-made crypto infra solutions.

Vaidik then challenged one of the industry’s favourite interpretations in Is Crypto Money Fleeing Crypto?. The growth of tokenised real-world assets is usually presented as evidence that traditional institutions are arriving on-chain. Yet much of the identifiable demand comes from crypto protocols and DAO treasuries converting volatile reserves into tokenised Treasuries and dollar yield. The RWA boom may currently be more about crypto dollarising itself.

Finally, in Robinhood’s Bigger Baskets, I looked at how Robinhood is increasing the amount each existing customer does within its ecosystem. Funded customers grew 7% year-on-year in the second quarter, but average revenue per user climbed 24%. Robinhood Chain and its forthcoming social feed may matter less as standalone businesses than as connective layers that encourage the same customer to trade, borrow, save and invest across more products without leaving the platform.

Across a majority of our stories, we focused on one recurring theme: crypto is making issuance easier. Distribution, financing and integration are becoming the moat.

We have plenty more coming over the next two weeks. Before we get there, here is some literature that should keep you in good company.

Some of these could be behind a paywall. Sorry!

Regulation & Policy

• Republicans Are Stuck in 2020. Maybe We All Are.: An argument that pandemic politics, election denial and anti-science grievance fused in 2020 into a coalition that continues to define the American right.

• Resist the Technocrats: A critique of international institutions that disguise political choices as neutral expertise, and a case for restoring democratic disagreement without rejecting knowledge itself.

Crypto & Tech

• The Machiavellian Case for Decentralized Networks: Omid Malekan argues that decentralisation matters not because distributed systems are flawless, but because they constrain how much power any single institution can accumulate.

• One Human, Once: A deep dive into proof-of-personhood systems, comparing centralised biometric databases with identity systems built around passport chips and zero-knowledge proofs.

• Onboarding the Next Generation: Binance Research examines how younger users are entering crypto, what they use it for and which products could turn early experimentation into durable adoption.

• Lending Markets Are the New Kingmakers: As issuing stablecoins and tokenised assets becomes easier, lending protocols may decide which versions matter by setting collateral caps, LTVs, liquidity, and borrowing utility.

• The Broken Link Between Protocol Revenues and Token Value: A useful reminder that a successful company or protocol does not automatically make its associated token a good investment, as Ripple’s equity and XRP increasingly demonstrate.

• I Believed…: A reflection on crypto’s retreat from its 2021 utopian promises and its maturation into a more regulated industry built around stablecoins, tokenisation, perps and prediction markets.

• The Changing Shape of Onchain Ownership: Noelle Acheson explains how BNY’s onchain transfer-agent service could make tokenised funds more useful by allowing legal ownership to move alongside the token itself.

Finance & Economy

• In Defense of Markets That Sometimes Close: A case for nights and weekends as natural circuit breakers that give institutions time to negotiate rescues, reorganise risk and stop financial stress from compounding continuously.

• An SPV of an SPV of an SPV: A map of the hidden fees, ownership ambiguity and exit risks inside layered private-market SPVs, followed by a plea for boring but enforceable investor protections.

• Singapore’s Average Wealth Is Climbing, but There’s a Catch: Singapore ranks far higher in average wealth than median wealth, exposing how gains from financial assets disproportionately accrue to richer households.

• What Would It Look Like If the AI Bubble Popped?: Matt Stoller traces how an AI bust could travel through retirement funds, universities, utilities, private equity and public budgets without necessarily resembling the 2008 crisis.

• Information Timing and Release: The Gaming of Guidance: Aswath Damodaran connects corporate reporting with central-bank guidance and argues that more frequent information is not necessarily more useful information.

• The Situation Deteriorated: Matt Levine uses the unwinding of Situational Awareness’s leveraged AI trades to show how a long-term thesis can be right while its short-term funding structure still destroys the trade.

• Elevators Won’t Repair Themselves: A look at independent sponsors and search funds through a basic private-equity question: does value come from financing the acquisition or operating the company afterwards?

AI & Innovation

• Why Compute Might Get 10x More Expensive: Dwarkesh Patel argues that increasingly valuable AI output could make demand for compute grow faster than supply, concentrating frontier intelligence and pricing out lower-value uses.

• Inference Market—and Micro—Structure: A framework that treats AI-inference providers like market makers competing through quotes, latency, compute inventory and token-level economics.

Culture & Beyond

• The Writing Habit That Saved My Brain—and My Future: Dan Koe presents writing as a system for thinking clearly, learning faster and gradually building a body of work that compounds into opportunity.

• Overthinking Hates a Moving Target: George Mack recommends walking, sketching and speaking thoughts aloud as practical ways to make vague worries concrete and interrupt rumination.

• Streamlining Addiction: An essay on how mobile gambling and prediction markets remove the physical and social friction that once limited addiction, repackaging vice as seamless trading.

• Extreme Heat Is Costing Us Hours of Lost Sleep: Three charts show how hotter nights are reducing sleep worldwide, with the heaviest burden falling on people living in warmer and lower-income regions.

• Humanity’s Golden Age of Language May Have Occurred 2,000 Years Ago: New modelling suggests humans may once have spoken many times more languages before empires and large states accelerated linguistic homogenisation.

• How Art Invented Humanity: A philosophical argument that art was not merely produced by an already formed human mind, but helped create human self-awareness and cognition.

• Propaganda I’m Not Falling For: 21 short provocations rejecting familiar scripts around careers, hustle, retirement, constant news consumption, passion, talent, legacy and luck.

• How the Creator Economy Took Over Media: Scott Galloway examines a barbelled media economy where a handful of creators capture enormous value while most struggle to convert attention into a sustainable livelihood.

• Why Talented People Outside the US Keep Losing Roles They Should Win: An essay on how proximity bias, self-promotion and cultural discomfort with workplace politics can make capable remote and international workers invisible to the institutions evaluating them.

That’s all for this fortnight. Catch you in the next edition.

Until then, happy reading!
Prathik

P.S.: Want to recommend interesting literature? Write to me, and I shall include them in the next edition 👇🏾

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. If you want to reach out to 170,000+ subscriber community of the Token Dispatch, you can explore the partnership opportunities with us 🙌

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Disclaimer: This newsletter contains analysis and opinions of the author. Content is for informational purposes only, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

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The first job is enormous and expensive. It built the credit bureaus, the scoring companies, the underwriting departments, the collections agencies, and the courts that enforce a judgment. A default follows you for years. Trillions of dollars of infrastructure exists so that a bank can hand money to a stranger and have a decent idea whether it is coming back.

The second job takes a set of scales, and that’s it

The securities lenders, the margin clerks, they price the object, and sleep well. It is the oldest lending there is, and it works perfectly. It has never grown into anything, because a system where you must already own something to borrow something mostly serves people who do not need it.

Crypto lending does the second job when it comes to lending, safely. People think of crypto, they freak out, they just remember the bad things and Sam Bankman-Fried first. So, pick a safer option, good for us.

In crypto, to borrow a thousand dollars, you first have to have fifteen hundred dollars.

The product is available only to people who already have capital. It works fine for a trader who wants leverage without selling a position, and that is a real business. For the rest of the world, the offer is to prove you do not need this, and we will give it to you. Fair enough.

In the traditional financial system, credit drives economic growth. A bank will lend a baker money to buy an oven based on the baker’s future ability to sell bread. The bank trusts the borrower, and new economic value is created. Works because the people who need a loan are, by definition, people who are short.

Today I want to show you who is trying to do the first job on-chain, and what happens to them.

In the US, that market runs to $5.14 trillion. Crypto has approximately zero of it. Few things block the way:

Identity. Unfortunately, a wallet is not a person. I can make ten thousand of them now for the price of the gas. If a lender cannot tell that the address asking for money today is the same human who walked away from a loan last year, the reputation system built on top collapses on the first day someone bothers to attack it.

Pricing. Even with identity solved, a lender needs a way to charge one borrower 9% and another 29%. That takes history, and which requires a bureau. On-chain data shows what a wallet did in DeFi. But you have no way of knowing whether that person kept a job or paid the previous loans on time.

Recourse. When a borrower stops paying in the normal world, a chain of consequences starts. Collections call. The default lands on a credit file. A court can garnish wages. When a wallet stops paying, what can you do? The wallet costs nothing to abandon. The lender has no name to sue, or address to send a letter, and nothing to seize.

The fourth is the law. Every enforcement tool I just listed requires a license. A collections agency operates under a licence and follows federal rules on how often it may call and what it may say. The rate a lender charges is subject to a usury cap that varies by state and product. Consumer lending is one of the most heavily supervised activities in finance, and a protocol doing it without permission is simply breaking the law.

Watch where that pushes everyone. Straight to the graveyard we go.

Goldfinch launched in 2021 with a16z and Coinbase Ventures behind it, and they skipped on-chain identity entirely. They lent to real businesses in emerging markets through professional underwriters who know those markets, and let crypto supply the capital. Goldfinch has motorcycle taxi financiers in Kenya, lenders in Nigeria and Southeast Asia, and borrowers across eighteen countries.

Tugende Kenya took $5 million in October 2021 to expand its book of financing bikes for taxi drivers. Goldfinch later found that $1.9 million had been moved to Tugende’s struggling Ugandan parent, which the loan terms did not allow. Tugende defaulted in June 2023.

Another borrower, Stratos, left $7 million unpaid on a credit line, while a third, Lend East, defaulted on nearly $6 million. Altogether, the protocol watched more than $18 million vanish into the very real-world risks they wanted to solve. Goldfinch wound down in June this year, after originating around $100 million. Its token is down 99.8%.

You think about it, every one of those failures was an ordinary credit failure. Fuel prices rose, drivers could not pay, covenants broke, a borrower moved money they should not have moved. The blockchain worked well. It just had absolutely no way of knowing if that money was ever coming back.

Maple is the more instructive artefact, because Maple was the biggest unsecured lender crypto ever built and it did not die. But to survive, it had to completely abandon its original mission. It realised that doing unsecured lending based on trust and identity was too dangerous in crypto.

On 5 December 2022, Orthogonal Trading defaulted on eight loans totalling $36 million. That was roughly 30% of all active loans on the protocol. Orthogonal had told its underwriter through November that its FTX exposure was about $2.5 million. On 3 December it admitted the actual number was far larger. The deception instantly erased 80% of the capital in the most exposed pool (M11 USDC pool, which held about $31 million), and Maple conceded they would likely recover only $2.5 million of the $36 million total.

Sid Powell said afterwards that undercollateralised lending needed harder due diligence, and that Maple might move to partial collateral.

It moved all the way. Maple today runs loans at collateral ratios above 140%, reports no losses since 2023, and has grown past $2.2 billion in deposits doing it. Safer option worked well enough.

Which brings us to who is trying now, because plenty of people are, and they have sorted themselves neatly by which blocker they attack.

Divine Research goes after the identity blocker. It has issued around 30,000 loans since December 2024, mostly under $1,000, in USDC, to teachers and fruit vendors and anyone with an internet connection. Borrowers verify with a World ID iris scan, which stops one person from opening a second account after walking away from the first. Interest runs 20% to 30%. The first-loan default rate is about 40% according to Financial Times.

3Jane goes at pricing blocker. It pulls a borrower’s bank data through Plaid and their VantageScore from Credit Karma, wraps both in zero-knowledge proofs so nothing sensitive moves on-chain. They issue a credit line off the result. Paradigm led its seed round. It holds roughly $62 million and is the largest uncollateralised lender on-chain today.

Wildcat goes at recourse, without underwriting anyone. It publishes a template master loan agreement that borrower and lender sign, and then it gets out of the way. Its own documentation says it does not assess creditworthiness and cannot interfere with a market once deployed.

Huma took a different route and stopped lending to people at all. Huma Finance is considered the first PayFi network. They have partnered with Qiro Finance, which serves as a strategic underwriting and risk-monitoring partner for Huma’s PayFi network.

Huma finances invoices and cross-border payment flows, where a known institution owes a known amount on a known date. It has originated $2.3 billion that way.

Not one of these enforces anything on-chain. Divine excludes you from the future, which is the weakest sanction on the list and which its 40% default rate tells you the borrowers have already priced. 3Jane hands the file to a US collections agency, which works because its borrowers are Americans with legal identities and credit reports that a default will damage. Wildcat goes straight to court.

Without over-collateralization to seize, every workable mechanism here is forced back into the old system. When things go wrong, in most cases something with a lawyer in it made people pay.

And notice where the successful ones drifted. 3Jane’s site now describes it as a credit-backed yieldcoin for fintech originators, offering warehouse lines of $5 million to $200 million. It bought $8.5 million of small business credit receivables from a company called Slope. Huma finances B2B payment flows. If a payment defaults, Huma relies on real-world factoring agreements and sends lawyers to enforce the contract. Both protocols pivoted to institutional lending because it anchors the debt in the old world. With a signed agreement and a jurisdiction to enforce it.

Which is why the market’s next attempt is deduction at source.

If your salary lands on-chain, a lender can be paid before you are. That is the first mechanism crypto has ever had that touches a consumer’s actual money where it spawns. The infrastructure went live this year. Deel processes $22 billion in payroll and started offering stablecoin salary payouts through MoonPay in March, across roughly 40,000 businesses in the UK and EU. Rise has run stablecoin payroll natively for years. Toku built a private version with Aleo and Paxos for companies that cannot have salaries visible on a public chain. Because these companies are officially processing salaries in stablecoins, the infrastructure is finally there to do “deduction at source”.

Read: The Glorified Babysitters - by Thejaswini M A

But there’s still a problem. Deel pays into non-custodial wallets - The worker’s wallet, the worker’s keys. Once the money lands there, a lender has no more claim on it than it had before, and no way to reach in. Interception must happen upstream in the Web2 payroll file. But if a provider like Deel allowed a crypto protocol to hook into their system, they would suddenly be acting as a debt collector or credit servicer.

As we pointed out in the blockers, “the law,” wage garnishment and salary deductions are heavily regulated. Right now, no payroll provider, including Rise, Bitwage, or Deel, natively offers automated loan deductions or wage garnishment to Web3 lending protocols.

Crypto can move money to anyone on earth in seconds. Because the system guarantees irreversible settlement, it inherently cannot force that money to return. Every time somebody solves the coming-back part, they solve it with traditional instruments like court, a collections agency, a credit bureau, or a boss.

Now, deduction at source is not a new invention.

Nineteenth-century British and American employers paid wages in company scrip, redeemable at the company store, at prices the company set. The worker’s pay never became money they controlled. Parliament passed the Truck Acts specifically to stop it, requiring wages in coin of the realm. The mechanism there was the employer controlling both the pay and where it could go.

Deduction at source is also how a 401k works. Also how student loan garnishment works, and child support, and every payroll savings scheme ever run. These are hardly called exploitative.

Brazil has run deduction at source for twenty years as consignado, deducting instalments directly from paychecks. Average payroll loan rates are 28%, while unsecured loan rates are 146%. But it works entirely through strict legal frameworks like employer contracts, wage caps, and labour courts. Crypto wants this system, but blockchains cannot natively read or enforce the traditional legal machinery required to run it.

The FTC wrote its Credit Practices Rule in 1984, and one of the six things it banned was the wage assignment. A creditor can no longer put a clause in a consumer loan contract that sends the borrower’s pay straight to the lender. A creditor may use a payroll deduction plan in which the consumer authorises a series of deductions as a way of making each payment. What a creditor cannot have is an assignment the borrower is unable to revoke.

So, deduction as a way of paying is allowed, but deduction as a way of collecting is not.

The FTC wrote down its reasoning. It found that wage assignments pushed people into giving up legitimate defences, because a borrower would rather pay a debt they disputed than have a creditor ring their employer about it. Some feared losing their job over the call. Without legal enforcement, crypto payroll deduction relies on voluntary borrower consent, solving nothing, since defaulting borrowers can simply revoke it.

Brazil’s model works because the law locks in the deduction and caps the wage hit, removing the borrower’s ability to cancel.

This is why protocols pick their jurisdictions strategically. Divine Research operates offshore, while 3Jane relies on American courts and credit bureaus. Each anchors itself in whatever real-world jurisdiction provides the legal leverage they need to make the money come back.

What would have to be true for crypto to have consumer credit, then?

A lender would need to know that multiple wallets belong to the same person, which biometrics can solve if everyone agrees to be scanned. It would need a legally regulated credit bureau to track a person’s repayment history across different protocols. It also requires a way to force you to keep paying even after you decide you want to cancel. Consumer protection laws simply won’t let anonymous software have that much control over your real-life income.

Aave has been running for six years and has never learned the name of a single person who used it. Blockchain can’t go to the lawyers and the courts. And therefore we wait.

—Thejaswini

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. If you want to reach out to 200,000+ subscriber community of the Token Dispatch, you can explore the partnership opportunities with us 🙌

📩 Fill out this form to submit your details and book a meeting with us directly.

Disclaimer: This newsletter contains analysis and opinions of the author. Content is for informational purposes only, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

A few weeks ago, I called Robinhood a financial supermarket because of the single roof that caters to every financial need of an American. In Building a Financial Supermarket, I wrote how its newly launched chain doesn’t have to earn significant revenue on its own as long as it can connect its more than dozen businesses and cross-sell its various products to its 28+ million funded users.

I still think that thesis is directionally right, but falls short in terms of magnitude.

When I watched Robinhood’s Q2 earnings call sitting halfway across the globe this morning, it made me feel that the ‘financial supermarket’ framing undersells what could follow for the company. A supermarket thrives by getting more people to walk through the door. Robinhood’s second quarter shows it is thriving by getting the same people who came to buy A on the Robinhood app to buy more of A, buy it more often, and increasingly get them interested in buying products B, C and D on Robinhood, too.

And because the company is able to pull this off, it is thriving lately without even making significantly more people walk through its door for the first time.

In today’s piece, I will tell you about the machine underneath Robinhood’s supermarket that turns each customer into a denser revenue node over time, and why the two least profitable things Robinhood launched (or will launch) this year — its chain and its social feed — could become the most important pieces of it.

On to the story…

The Rubric

In just five years since its public listing and 11 years since the app launch, Robinhood has crossed $5 billion in annualised revenue. It took the brokerage giant Charles Schwab almost 30 years since it opened its doors in 1971 to cross $5 billion in annual revenue. One of the biggest drivers of Robinhood’s revenue has been its vast distribution of 30 million funded accounts. It has the entire breadth of product line-up, from memecoin trading to gold and retirement accounts, catering to every demographic. For most businesses, these metrics scream of distribution might. Yet, the company doesn’t want to judge its own progress using these metrics.

Early in the earnings call, Robinhood CFO Shiv Verma told investors to judge the company on three metrics: net deposits, the Rule of 40, and the count of business lines doing $100 million or more in annualised revenue rate (ARR).

In Q2 2026, Legend - Robinhood’s desktop trading and analysis platform - and Credit Card became the latest business lines to join the $100-million ARR club. It now has 13 business lines on that list.

But let’s set aside those metrics and look at something more granular.

At the end of Q2 2026, Robinhood’s funded customers grew 7% year-on-year, from 26.5 million to 28.4 million. Over the same period, average revenue per user (ARPU) climbed 24%, from $151 to $187.

Revenue per customer grew more than three times faster than the customer base.

The trading data also reflects this. Robinhood’s Q2 trading volume on a per-customer basis shows that the equity notional volume per trader rose 56% year-over-year, while Options contracts per trader rose 43%. Yet the number of customers placing equity trades grew just 13%, and those trading options grew 3%.

Robinhood’s event contracts business, which didn’t exist 15 months ago, did $156 million in revenue, up 50% quarter-on-quarter. None of this required Robinhood to acquire a new set of users.

In May this year, I wrote how Robinhood’s ability to package equity, options, and perps trading along with event contracts allows it to offer a much better information-pricing platform than its competitors.

Read: Why Robinhood Might Eat Kalshi’s Lunch

All these suggest that the accurate rubric to assess a company like Robinhood is to look at how much more the financial supermarket sells per basket. That is the growth in its ARPU.

The Gold Ignition

Although Robinhood has more than a dozen businesses, one of the most crucial drivers of its engine is its gold membership subscription. In just the last two years, Robinhood Gold subscription adoption rate has almost doubled from 8.2% to 17% of the total funded customer base.

In Q2 2026, the Gold subscription business generated $216 million in annualised subscription revenue. That’s just about 4% of the total revenue. But there’s a bigger benefit from what every Gold subscriber adds to the overall business. Compared to the average funded customer, a Gold member carries about 4.2x the assets under custody and adopts retirement products at roughly 3.1x the rate.

On the earnings call, CFO Verma noted that 40 to 50% of Robinhood’s new customers sign up for Gold regardless of which product first brought them in.

This shows the cross-selling moat Robinhood has. Even if a customer arrives for commission-free equities, a prediction market on the World Cup, or a 3% cash-back credit card, 1 in 2 of those customers convert to Gold. Once they purchase the $5 per month subscription, they join an exclusive community of 4.8 million members who get access to cheaper options contracts, a 3% IRA match from your employer, 3.5% APY on banking cash, the credit card and more.

The cross-adoption is measurable. Verma pointed out that a prediction-markets customer is more likely to also hold a retirement account with Robinhood. So a person betting on a football match through Robinhood’s prediction markets is also using Robinhood’s retirement accounts to compound their IRA.

Robinhood’s supermarket of financial products doesn’t segment its customers into “gamblers” and “serious investors”. It sells its products to the same customer, and every product the customer uses raises the probability of them using another one.

Despite all this distribution moat, I feel Robinhood is yet to make its most exciting move.

The Two Catalysts

In Building a Financial Supermarket, I argued the chain barely makes money and doesn’t need to. I instead framed Robinhood Chain as a connective layer that makes the other businesses stickier. Having watched Q2 earnings, I would slightly modify the outlook for Robinhood. Its chain and, soon, Robinhood Social, will become two of the biggest catalysts that cut horizontally across its entire suite of products and drive cross-selling across more than a dozen of its businesses.

Consider what the chain enables. A customer buys a tokenised stock. That token becomes collateral on a lending market. The loan funds a perpetual futures position. One dollar has now been used across three products in a single session without ever leaving the app. In the old, fragmented brokerage ecosystem, those three actions happened in three disconnected places. Each of those places had its onboarding frictions and required customers to make a fresh decision. Composability removes that friction.

The chain wires cross-selling into the infrastructure so that the customer can cross-sell themselves across products with minimal or no friction.

Robinhood CEO Vlad Tenev said that the company is set to make its Social feed available for the general audience by the end of Q3. Tenev expects the internal feed to add more credibility to the trade ideas by backing content with verifiable portfolios on the Robinhood trading platform in the same universe. Typically, trade ideas currently come from different worlds. A trader may consume content about prospective trades from Twitter, a podcast, or a friend. The customer would then form intent and arrive at Robinhood only to execute. Robinhood Social could pull that step inside its walls.

This is the most underrated aspect of its social feed. The trust it could add for its 30 million funded users will be unmatched by screenshots or podcasts from any other external platform. When the feed goes live for the masses, Robinhood’s last externally-sourced step in the funnel where the intent to trade is born will also move in-house.

Read: Culturally Crypto, Practically TradFi

I don’t see Robinhood Chain and Social as separate business lines for the company. Instead, I count them as catalysts that drive activity across all its other businesses. A community of 30 million people talking about the latest event contract, the kind of life they built using discipline via the Retirement Accounts and the latest Stock Tokens giving them pre-IPO exposure to Anthropic will drive more aspiration among other users than any user-acquisition marketing campaign.

The Loyalty Playbook

Robinhood’s value-capturing strategy is similar to what we saw with Costco. Most of the third-largest retailer’s margin came entirely from the membership, while their shopping aisles ran near cost to keep members walking in. The neutral layer is not where the profit sits. But often these neutral layers generate adjacent capacities where value accrues. Just as Costco’s aisles and inventory collection made people shop its subscriptions.

Robinhood Chain and Social are akin to such neutral layers that create value-accruing layers. Both of them give reasons to investors or traders to shop for Robinhood’s Gold subscription and shop multiple products across the aisles of the financial supermarket.

Over the years, one of the biggest question marks for Robinhood was the problem of cyclicality. Even as Robinhood registered record equity and options trading volumes in Q2, its crypto trading volume has slipped for three straight quarters. Even on Robinhood Chain, more than 80% of the volume is still driven by memecoin speculation.

A sceptic might see a problem in all this. But I beg to differ.

Robinhood’s diverse and deep ($100 million ARR) business lines ensure that the consolidated business is no longer at the mercy of market cycles. When trading volumes fall, interest-earning assets don’t necessarily fall. The margin book grew 127% YoY to $21.6 billion.

Prediction markets that were primarily driven by sports and elections take a different shape inside a platform like Robinhood. The Rothera joint venture with Susquehanna International Group gives Robinhood a CFTC-regulated prediction markets exchange licence, letting it create its own event contracts. This allows the company to eliminate cyclicality in seasonal categories like sports and elections and offer year-round event contracts tied to macroeconomic and S&P 500-related announcements.

Gold subscription revenue is a flat monthly income that doesn’t care how the markets are performing each month. Robinhood has spent five years assembling businesses whose revenues peak at different times, making the whole company far less cyclical than any single line inside it.

This is reflected in the ARPU number. It climbed 24% because the average customer is now plugged into more businesses at once, and a customer wired into five uncorrelated revenue streams is a fundamentally more durable asset than one wired into a single volatile one.

The more products each customer touches, the more consistent Robinhood’s own revenue curve becomes. Each trough in one business line gets filled by the peak of another, often driven by the same person’s account.

Coinbase reshuffles crypto capital that already exists across consumers and institutions. The legacy brokers hold assets but can’t manufacture engagement. Robinhood stands at a unique position to turn a single customer relationship into a compounding, self-diversifying revenue node across traditional and crypto businesses, both of which can be connected and amplified by its native blockchain.

That’s it for today. I will be back with the next one.

Until next time, stay curious,
Prathik

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Tokenised real-world assets (RWAs) have grown 179% this year. Hyperliquid now does more volume in stocks and commodities than in crypto tokens. And the story everyone is concluding with is that traditional finance is finally coming on-chain.

But when you trace back to who’s actually buying these RWAs, you will find that it looks nothing like institutional adoption, because most of the capital is coming from inside crypto itself. Protocols and DAO treasuries are loading up and converting their own reserves into tokenised treasuries.

Today I’ll dig into how the RWA boom looks more like crypto’s dollarisation event than any institutional arrival, and what it means when crypto’s own protocols become the largest buyers of these tokenised Treasuries.

Who’s actually buying the RWAs

Let me take you back a few years: if you were paying attention to DeFi in 2020 and 2021, you would have seen yields that were absolutely bonkers. Lending pools were advertising 15%-20% annual returns on dollar deposits, sometimes up to 40%. Billions of dollars flooded in, but few questioned where this money was actually coming from.

Because it was coming from token emissions, protocols would mint their own governance token, give it to depositors as a “reward,” and count that subsidy as yield. It was the ultimate gimmick to attract investors and boost TVL, but it only worked as long as the price of those tokens kept rising. Later, when the markets crashed and governance tokens lost 80-90% of their value, DeFi’s actual organic yield was just 2-3%.

That was less than what US Treasury bills offered, with far more risk. And it revealed that the financial system crypto had spent years building could never generate competitive returns from its own economic activity because those yields were coming from new entrants buying governance tokens, and not from any productive use of the capital itself. Once this stream of new money slowed, the whole model collapsed back into what it always was.

So now you had protocols sitting on treasuries worth hundreds of millions of dollars, denominated in their own governance tokens, with no way to earn a competitive return in crypto. And then in 2023, many tokenised versions of US Treasuries and dollar credit products began launching on-chain; for the first time, a protocol could park its reserves in something that earns real dollar yield without ever leaving the ecosystem.

Since then, it has become the norm. A recent on-chain buyer study by Arrakis traced $91.3 billion in deposits across more than 10 tokenised dollar-yield products and found that, of the $12.4 billion they could attribute to a named buyer type, two-thirds was attributable purely to crypto protocols and DAO treasury capital. The rest of it was split across crypto-native investors, exchanges, and market makers.

_{Source: Arrakis}

And the amount traced to an institution such as a pension fund, an asset management company, or a bank was zero. In a $36.2 billion market that the industry keeps pushing as institutional adoption, traditional investors are nowhere to be found.

BlackRock launched its BUIDL fund to bring institutional capital onto Ethereum. This was a fully regulated, tokenised treasury fund with risk-free rates, designed specifically so that pension funds could buy it without having to explain crypto to their boards. But today, 98% of the funds are held by crypto-native buyers. Ethena accounts for more than half of the fund’s total value through its USDtb product. The rest of the top 10 holders are protocols like Ondo and Sky’s Spark Sub DAO.

_{Source: Arrakis}

And BUIDL isn’t the only one; across the market, the top five holders of nearly every tokenised RWA product control more than 90% of the supply.

If you want to see what it could look like in the future, the best example is MakerDAO. The protocol held about 17 million DAI in real-world assets in 2021. Today, that number is $4 billion, and more than half of its total collateral base is Treasuries rather than crypto. The entire vision of Maker was that you could run a stable currency backed by crypto-native collateral, overcollateralised enough to absorb ETH’s volatility. That trade-off was always expensive, as you lock up far more value than you mint, but the idea was that decentralisation was worth the capital inefficiency.

What it proved instead was that you can’t, at least not at scale and not without leaning on the very financial system it was trying to replace. After this, the protocol renamed itself and restructured its governance to build dedicated sub-DAOs and manage its Treasury portfolio.

And there’s a reason this keeps happening across the industry, not just at Maker. The problem is no protocol can hold meaningful reserves in its own governance token because the value is circular. The token’s price depends on the protocol’s success, which in turn depends on the treasury’s health, and even that would be related to the token’s price.

Uniswap’s DAO sits on a treasury worth nearly $6 billion, almost entirely in UNI tokens. But last year, its community passed a governance proposal called “Mobilizing the Uniswap Treasury” to diversify out of the native token into stable assets. The protocol’s own voters acknowledged that unless UNI’s price goes up forever, they are better off holding almost anything else. Holding the native token as reserves is like an emerging-market central bank counting its own government bonds as foreign-currency reserves. It only looks solvent as long as you never have to sell.

In international economics, there’s a name for this kind of trap called the “original sin.” It says that only about five currencies in the world can actually sustain borrowing and reserve accumulation in their own denomination. Every other country eventually has to be denominated in dollars, whether its government wants that or not, due to the sheer incumbency of the dollar as the world’s unit of account and because the switching costs are too high and the liquidity is already elsewhere.

Every protocol sitting on a large treasury eventually comes to the same conclusion. The governance token can’t hold value during a downturn, the ecosystem can’t generate enough yield to be sustainable in the long run, and the only rational move is to convert it into something denominated in dollars. It is the same network effects that keep the dollar dominant in global finance that keep stablecoins dominant in DeFi. The move into tokenised Treasuries was actually the final step in dollarisation.

Economics of Dollarisation

The economics literature on dollarisation explains a very precise two-stage process, and crypto has now been through both.

The first stage is asset substitution. People in emerging countries often stop trusting their local currency to hold its value, and so they start saving in dollars instead. They might still be getting paid in the local currency and might still price goods in it, but their savings move into dollar accounts because that’s where purchasing power is more stable.

The second stage is currency substitution. Once enough savings are held in dollars, people start borrowing and lending in dollars too, because it becomes easier to do business in the currency everyone already holds. The two stages feed into each other, and in traditional emerging markets, the whole process typically takes a few years or even decades.

What’s interesting is crypto went through both in about three years. The asset substitution occurred during the bear market, when protocol treasuries began routing their dollar-denominated reserves, such as fee revenue and anything not locked in their governance token, into stable assets rather than redeploying them back into DeFi. The governance token still appears on the balance sheet, but the working capital has now been converted to dollars.

Once those treasuries began holding USDC and USDT, the second stage of currency substitution began almost immediately. Lending markets started to be denominated in stablecoins, and yield products were now being quoted in dollar terms. Trading pairs that had been ETH-denominated also shifted to stablecoin denominations. And now, with all the tokenised Treasuries, the denomination has gone even further: from synthetic dollars to actual US government-issued dollar instruments that earn risk-free yield on-chain.

What took countries like Turkey decades of political crises and currency collapses to reach took crypto only a handful of quarters. Oliver Wyman, in one of its reports earlier this year, said that stablecoins are compressing the traditional timeline of dollarisation from decades to just months. They were talking about emerging markets, but the analysis fits crypto even better because here there is no central bank trying to slow the process down with capital controls or compliance friction. The switching cost on the way in is close to zero.

But that’s also the paradoxical curse of dollarisation: the switching cost on the way out is enormous. Economists call it hysteresis. Once dollarisation takes hold of an economy, it is almost impossible to fully reverse it even if the original conditions that caused it have improved.

Because there is no crypto equivalent of a commodity super-cycle that can suddenly make governance tokens more attractive to hold than dollar yield. And it’s next to impossible for a protocol to impose capital controls or reserve requirements on stablecoin deposits. And unlike a country, crypto doesn’t have an institutional memory of a pre-dollarised era to return to, because for most of DeFi, stablecoins have been the default denomination from the start.

This is a one-way door, and the cost of walking through it is grave. Every time economic activity inside DeFi is denominated in USDC or USDT, the seigniorage or profit that comes from being the issuer of the money flows to Circle and Tether instead of the protocols where the activity is actually taking place. Tether made about $10 billion in profit last year for about 100 employees; Circle did its IPO, and Coinbase took half of USDC’s net interest income just for distributing it.

When Ecuador or El Salvador denominates in dollars, the seigniorage that would have funded their central bank transfers to the Federal Reserve instead. And when DeFi denominates in stablecoins, it accrues to Tether and Circle.

A protocol that denominates in someone else’s currency also loses its ability to manage its own economy because it can’t adjust the supply of its native token to respond to conditions inside its ecosystem, and because the core economic activity is no longer priced in that token. It is the same position as a fully dollarised country that can’t devalue its way through a downturn. The only tools you’re left with in this case are spending cuts, and that is what we’ve seen across DeFi over the past two years. The governance votes to reduce grants, which cuts contributors and slows protocol development, since otherwise the protocols have no other monetary lever left to pull.

There is a protocol called M^0, being built by former MakerDAO and Circle executives, which is described as “a governor of the Eurodollar System”. They are building infrastructure for multiple issuers to mint stablecoins backed by Treasury collateral and are targeting the $20 trillion offshore dollar market. They are not trying to replace the dollar, but instead building better rails for the dollar to run on. And this is what I feel the end state of crypto dollarisation looks like. Where the infrastructure reorganises itself around servicing demand for the dominant currency, and the native tokens become afterthoughts.

Isn’t the original thesis bitcoinisation? Even the most committed maximalists would tell you that it is a multi-decade arc, that it only becomes possible once the dollar itself loses stability. But the interesting thing is, crypto has also built the most efficient dollar distribution network ever. It did not impose its monetary logic on the world; rather, the world ended up imposing its monetary logic on crypto.

The entire industry is running behind to frame the RWA boom as some story about Wall Street discovering the efficiency of blockchains. And of course, the first buyers are crypto-native, but two-thirds of the identifiable capital is going only into tokenised Treasury bills. The safest and vanilla financial product in existence, wrapped in a smart contract.

That’s all for today!

Vaidik

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This way, you can put anything on-chain, but also, you can’t. We are not there yet; the relationship is still complicated.

A tin of tuna in a Lisbon supermarket now carries a code you can scan to see the boat that caught the fish, the date, the ocean, the whole line back to the water. But if the person unloading the boat mislabels the catch, the whole system fails. Tracking only works after the data is entered. The entire process depends on one human making an honest record, and we underfund this critical first step.

Similarly, in the case of blockchain chickens, it worked because it wasn’t a tradeable asset - the whole idea was an immutable provenance record. To prove that it was genuinely premium free-range poultry after years of food safety scandals.

Nobody should be asking whether you can put an asset on-chain. You can. But the ability to verify real-world facts is what tells you what a good and bad tokenisation project.

That’s why we should look at the environmental markets; that’s where I saw identical technology going two ways. One is to record verified truths, and the other to record claims that could be totally fabricated.

Renewable energy certificates work on a blockchain, and carbon credits do not. As the cost of addressing this reason decreases, the financial market for physical assets is opening up.

Start with what a token is, in economic terms, because the industry has spent a decade describing it wrong. A token is a claim. It asserts that some unit exists, and that it belongs to the holder. A blockchain is very good at enforcing the last part. It solves the double-spend problem for the token, so the claim cannot be copied or forged in transit and its ownership is legible to everyone at once. What it cannot do is verify that the underlying thing the claim points to is real, or is what the claim says.

A renewable energy certificate, a REC, says one megawatt-hour of clean electricity went onto the grid. This market is worth around $22-28 billion and grows 14% every year. Why are RECs easy to put on a blockchain?

Because all electricity on the power grid mixes together, it is impossible to separate clean energy from dirty energy once it is flowing through the wires. To solve this, physical meters are placed directly at solar and wind farms to measure the exact amount of clean power they produce before it enters the main grid. When the meter records a specific amount of clean energy being generated, it creates an official document called a REC. Companies use these certificates to prove that a specific amount of clean energy was actually created and added to the system.

This is how the grid works:

The economic significance is that the party certifying the unit is not a human with an incentive to shade the truth. It is a meter, and behind it, the grid, an involuntary third-party verifier with no stake in anyone’s sustainability report. Falsifying its reading would mean corrupting physical infrastructure the seller does not own. In the language of information economics, there is almost no asymmetric information about the core attribute. Buyer and seller face the same hard number, produced by a device neither controls.

When you tokenise a REC, then you are wrapping a unit whose quality has already been established by an independent measurement. The blockchain inherits a fact. And what it contributes is transaction-cost reduction, which is precisely what a liquidity technology is supposed to do.

Power Ledger, an Australian firm that spent years on peer-to-peer solar trading between neighbours, now runs a REC marketplace called TraceX, where generators and corporate buyers trade certificates on-chain instead of through weeks of bilateral paperwork and legal brains. It cleared over 1.2 million RECs in a single month in early 2025, and it plugs into the registries that actually issue the certificates. It connected to M-RETS, one of the largest voluntary REC registries in North America, and in mid-2025 to ERCOT, the Texas grid operator that issued more than 32 million RECs in 2023 alone. Power Ledger says users cut administrative costs by up to 72%.

Now the same idea didn’t work when it comes to carbon credits, which look like RECs. Each credit acts as a numbered, tradeable unit for one ton of avoided carbon. Many corporations promise their shareholders and the public that they will become “carbon neutral” or reach “net-zero” emissions. Because they cannot actually stop polluting entirely, they buy credits to mathematically cancel out the pollution they continue to create.

In 2021, a protocol called Toucan built a bridge to haul them on-chain as tokens, and a project called KlimaDAO offered a clever incentive to pour credits into its treasury, buying them up to prop the price and, in theory, make polluting more expensive. Money rushed in, and KLIMA, the token, touched $1 billion marketcap before people looked at what had been bridged.

The core problem with a carbon credit is that it measures a hypothetical scenario, like trees that were supposedly never chopped down. There is no independent hardware to verify this, making the units entirely subjective. Tokenisation could not fix this underlying flaw, but it did make it a bit more dangerous. By pooling these credits together on-chain, protocols like Toucan treated every asset as identical.

It wasn’t that the blockchain itself was bad, but the specific way they pooled these credits together caused a problem.

Then KlimaDAO manufactured demand for that pooled token, buying it up with its own freshly minted KLIMA, at a price propped far above what the junk inside the pool was actually worth. That combination sorted the market. If you held a good credit that fetched a fair price in the normal market, turning it into a pooled token priced at the junk level was a bad trade, so you stayed away. If you held a credit nobody wanted, the pooled token was priced above your credit, so you bridged it and sold. The pool filled with the lowest-quality credits, because those were the only ones the trade made sense for.

A researcher at CarbonPlan in 2022 found that most of the credits bridged to Toucan came from projects already excluded from serious offset markets on quality grounds. Because Verra’s retirements are public, CarbonPlan was able to read exactly which credits went on-chain. It found that 99.9 per cent of them came from projects too old to qualify for the standard aviation offset market, and that 28 per cent came from ‘zombie projects,’ ones that hadn’t sold a credit in years until crypto demand revived them. One hydro project in China logged its first ever retirement only when it bridged on-chain, fifteen years after it started.

A 2024 meta-analysis in Nature Communications looked at nearly a billion tonnes of carbon credits, about a fifth of every credit ever issued, and found that fewer than one in six represented a real emissions cut.

Verra, the largest carbon registry, watched its retired credits get turned into tradeable digital ghosts and, in May 2022, banned the practice outright. KLIMA fell from three thousand six hundred dollars to single digits. KlimaDAO spent over a million dollars of its own treasury retiring the worst of what it held.

Tokenising a broken unit doesn’t repair it, but industrialises it. You take a measurement problem, and you bolt a liquidity engine to it, and now the bad units move faster, price higher, and reach more buyers.

Which gives you a test you can carry to any tokenisation pitch, and it has nothing to do with the token. Is there an independent witness measuring each unit? Can that witness be faked? And, the one people forget, can the borrower own the witness? That’s the tough one.

If you tokenise a barrel of oil in a tank, or a tonne of grain in a warehouse, the whole thing rests on someone attesting the barrel is in the tank and stays there. If the person doing the attesting is the same person borrowing against it, you don’t have collateral.

Commodity trade finance has blown up this way for a century, warehouse receipts written against metal that had already left, or was never there.

Look at livestock, one of the biggest stores of value on earth for people with no access to credit. Banks have always hated lending against it, discounting a cow’s value by as much as 60%, because they had no way to know the animal was healthy, or where it was, or whether it was still breathing. A cow is collateral that can walk away, get sick, or quietly die in a field while the loan sits open. Who is watching the barn?

Three days ago, on a dairy farm in Paraná, Brazil, ten cows became the first livestock formally registered as collateral on the country’s stock exchange.

Each animal wore a smart collar from an agtech company called Cowmed. The collar tracked its health, behaviour and location, hashing that stream into an encrypted identity tied to the loan. The farmer borrowed around twenty thousand dollars against ten cows. The system can even tell if a cow dies, and let the farmer swap in a live one. Cowmed already monitors a hundred thousand animals valued at nearly four hundred million dollars.

If a lot of farmers adopt this, a smart collar tells you a collar is transmitting health and location data. It does not, by itself, tell you the collar is on the cow it’s registered to, that the animal is the one pledged, or that a real cow is on the other end at all. Every failure a farm inspector used to catch is still there. You can strap the collar to the healthiest cow and pledge a sick one. You can move the collar between animals. In principle, you could feed it fake data. So no, it doesn’t end the farm visit on its own. But it can turn one yearly visit into a daily record, so fraud has to be kept up full-time. The same cow now can’t be pledged to three lenders at once, since there’s a record.

A grid meter is placed at a fixed spot the seller can’t move. A cow is mobile, and the collar is only as honest as whoever strapped it on.

A cow with no collar is nearly unverifiable, so banks cut its value by sixty per cent. A cow with a collar isn’t perfectly verifiable either. But, verifiable cheaply enough that a lender takes the bet at a smaller haircut. So, the asset moved up the spectrum. This deal is also three days old, and we don’t have a lot of examples to argue for.

Successful tokenisation relies on a spectrum of measurement reliability. High-quality assets use automated, tamper-proof sensors like power grid meters, satellites, and weighbridges that sellers cannot alter. Low-quality assets depend on hypothetical projections and self-reported math, such as avoidance carbon offsets.

Even the metered end isn’t as settled as it sounds. A meter proves a megawatt-hour existed, but not that it existed near you, or when you needed it. For years, a company in Ohio could buy a certificate from a wind farm in Texas that generated at 3 am and claim to run clean.

So the market is now splitting the unit finer, stamping each certificate with the hour it was made and the grid it was made on. Water credits are following the exact same pattern. A watershed credit is easy to sell and hard to trust, because measuring that a river got cleaner is one thing and proving your project is why it got cleaner is another. The instrument decides how honestly an asset can be tracked. Each time the instrument improves, the market revises what the certificate was really claiming to be.

In a normal market, buyers and sellers will constantly argue over what an asset is worth, causing the price to fluctuate. That is perfectly healthy, but it only works if there is a hard, physical truth anchoring the asset. Like the actual revenue of a company or the physical weight of a barrel of oil. Eventually, the trading price will align with that reality. If you remove that physical proof (like with a subjective carbon credit), the price is completely disconnected from reality. There’s no baseline for the number to fall back on.

Tokenisation is just an accelerator. If the underlying asset is verified, tokenisation builds wealth. If the asset is unverified, it just accelerates a scam. The blockchain cannot check which is which. Crypto projects often defend themselves by pointing to their high liquidity and institutional capital as proof of their legitimacy. Liquidity does not create a true fact. You can build the most efficient, frictionless trading system on earth, but if the physical asset is of no value, the entire market is just a highly optimised fraud.

—Thejaswini

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Every company treasury must regularly decide where to park spare cash overnight. More often than not, the cash goes into money market funds, Treasury bills, commercial paper or overnight repo.

All these instruments are default options for two reasons: the treasurer knows the rate (of interest) and date (of maturity). Certainty is what makes these instruments work. They let a finance team plan knowing how much interest to expect and over what tenure.

On-chain lending has seldom offered certainty. Rates there float by the hour, which is fine for traders and useless for a treasurer. This is why the biggest market in finance, the $60 trillion world of corporate credit that runs on fixed rates and dates, has stayed almost entirely off-chain.

In today’s story, I explore if Morpho’s new Midnight protocol can change that and make DeFi lending attractive for corporate lending and borrowing.

On to the story…

The Need for Fixed Rates

Companies borrowed roughly $13.7 trillion in 2025, the highest annual figure on record, and about $60 trillion of corporate debt sits outstanding today. This machinery funds factories, acquisitions, and payrolls. It runs almost entirely on fixed rates and fixed maturities, because no business can plan around a borrowing cost that changes frequently.

For a decade, a parallel version of this market has been trying to form on public blockchains. It never made a dent in the traditional instruments for this precise reason. Almost all on-chain lending has been built on floating rates. The interest you earn or pay varies continuously with the amount of the shared pool being borrowed at any given moment. That design works well for crypto traders, which is a niche, limited group. It is useless for corporates.

But why is the on-chain credit market not offering fixed-rate lending and borrowing? It had, on many occasions in the past. But all those who offered fixed rates hit the same wall.

Yield Protocol wound down in October 2023 after peaking near $22 million in deposits. Notional Finance’s TVL climbed above $975 million in November 2021 before falling 90% within two years.

To promise a fixed rate for a fixed term, these protocols asked lenders to lock their money to a chosen maturity up front. That capital then was frozen, waiting for a borrower to take the other side. Much worse, that frozen capital was split across pools with different maturity dates, making liquidity thin in each. Thin markets set bad prices, bad prices drive users away, and the market starves to a slow death.

The problem was the steep cost of providing certainty. Each of those protocols was designed to keep every dollar passive until it was deployed.

This is the problem Morpho’s Midnight wants to solve.

Morpho is already one of the largest lending networks in crypto, with more than $11 billion in deposits.

Morpho’s infrastructure powers many consumer products, from Coinbase to Robinhood. Most users of those apps never know it is there, and that is its biggest moat.

On July 21, Morpho launched Midnight, a protocol built specifically for lending at a fixed rate for a fixed term. Instead of a shared pool with a rate set by a formula, Midnight works as a market of offers. A lender posts the rate it wants along with the maturity. A borrower posts what it is willing to pay. When two offers meet, the terms lock. Just as it would happen with a bond or a term loan.

But what happens to the lender’s money while it waits to be matched with a borrower with similar rate and term preferences? While the earlier protocols froze the funds, Midnight is designed to allow those funds to continue earning a floating return on Blue, Morpho’s legacy lending primitive. The capital doesn’t sit idle here.

This is a promising upgrade for every corporate treasurer who wants a known rate, a certain maturity and a defined counterparty. But this works only with scale.

The Time is Ripe

For the first time, an on-chain instrument is designed with a corporate treasury’s preference for a fixed rate and maturity in mind, rather than expecting the treasury to adopt a product centred around crypto traders.

The timing of a few other catalysts makes DeFi lending more practical for corporate treasuries this time.

Firstly, starting in 2024, the FASB Accounting rules let companies mark qualifying digital assets at fair value rather than treating every dip as a permanent writedown. Under the old rule, a treasury had to write down its digital assets each time their prices dipped. But a price recovery wouldn’t let them mark the asset back up. This meant that a bad quarter could permanently dent their balance sheet. This discouraged companies from holding digital assets altogether. The new rule lets the company record fair value to reflect both unrealised gains and losses.

Secondly, new stablecoin legislation has given corporate finance teams a clearer legal footing for holding these instruments.

The distribution Morpho has already put in place helps it gain adoption from the existing institutional networks of those platforms.

Coinbase has originated more than a billion dollars in loans through Morpho’s infrastructure.

Robinhood routes its savings product through Morpho. Société Générale’s digital arm, FORGE, runs lending markets on it. These establish Morpho’s credibility as a reliable integration via on-ramp platforms that corporate treasuries are familiar with.

But the DeFi mechanism isn’t as perfect when you swap the corporate treasury use-case with that of corporate debt.

The Corporate Borrower

The same DeFi lending protocols can even be used by corporates for borrowing on-chain. Except that it has some structural issues to fix before on-chain corporate debt becomes attractive.

Corporate debt is largely unsecured. When a company issues a bond, lenders are betting on its business, which is a function of its cashflows and its ability to pay. The company does not pledge assets worth more than it borrows. That is the entire point of corporate debt. It is raising money precisely because it does not already have that kind of money.

On-chain lending, including Midnight, works the opposite way. It is overcollateralised. No corporate treasurer will want to pledge $100 to raise $70. That resembles a margin loan more than a corporate financing. Corporate bonds work because it is a borrowing secured against the company’s future, not its present. This is what Morpho or any other DeFi lending protocol cannot do yet.

If Morpho Midnight wants corporates to prefer raising debt on-chain over their time-tested traditional channels, then it has to close this gap with unsecured, credit-based lending.

Why the Infrastructure Is Still Promising

Traditional public bonds need scale to make sense. Only when they scale up to at least a few hundred million dollars can they grab the attention of underwriters, rating agencies, lawyers, and roadshows. All-in issuance cost via public bonds can eat several percentage points of the money raised and weeks of time. A market on Midnight can be created by anyone, with protocol fees measured in fractions of a percentage. That removes the gatekeepers who price small and mid-sized companies out of public debt entirely.

Speed and liquidity are the next advantages. A leveraged loan can take twenty days or more to settle, and most corporate bonds are barely tradable once issued. A loan made on Morpho Midnight settles in a single step, and the position becomes a tradable unit instantly. A lender who needs cash early does not need to break the loan or hunt for a bilateral buyer. They can simply sell the units. Similarly, a borrower who wants out can buy units back. Credit that was locked until maturity becomes liquid without a secondary-market desk taking a cut in the middle.

Enforcement is another aspect in which on-chain lending contrasts with off-chain lending. Traditional default is slow and expensive, moving through breach, negotiation, restructuring, and sometimes bankruptcy. On-chain, a position remains healthy as long as its collateral covers its debt; the moment it does not, liquidation occurs automatically. On-chain lending cuts the entire manual procedure.

But faster, automatic liquidation comes with a price. Liquidation can be instant only because the borrower has already posted more than what they took.

Another advantage is composability, a feature traditional credit lacks. An on-chain position is much more valuable than a traditional loan entry on a balance sheet. A tokenised credit position can be moved, sold, or posted as collateral somewhere else. A fixed-rate credit unit can become the raw material for the next product built on top of it. Traditional corporate debt sits still until maturity.

None of this makes Midnight a viable substitute for the corporate bond market today. But it still makes it a prospective candidate that can offer a better set of rails than the one corporate credit currently runs on.

On top of the advantages I mentioned above, the whole thing plugs into the distribution that treasuries already use through Coinbase, Robinhood, and a regulated bank like Société Générale.

The one missing piece is DeFi’s ability to price a borrower’s creditworthiness in addition to its collateral. The infrastructure is ahead of the use case. That’s all the more reason I believe it should be further developed rather than written off.

The Case for Being Optimistic

Many crypto protocols already offer bitcoin-backed loans. But I think the path to making DeFi borrowing and lending credible substitutes to their traditional counterparts runs through tokenised real-world assets as collateral.

A corporate treasury is more likely to deposit a tokenised money market fund, a tokenised pool of receivables, or a tokenised slice of private credit, and borrow against it at a fixed rate than post a volatile crypto token as collateral. This is already happening as you read this. A tokenised version of an Apollo credit fund has been used as collateral inside Morpho’s markets. It’s evidence of a ready infrastructure. Yet the pool of tokenised real-world assets that a treasury could actually pledge is still only a few billion dollars, compared with a $60-trillion debt market. That’s because tokenised collateral is still overcollateralised borrowing. So, the main part of the puzzle to fix remains the overcollateralisation problem.

The closest historical parallel is the Eurobond market, which began in 1963 when borrowers went offshore to raise money faster and with fewer constraints than their home markets allowed. A parallel credit market formed outside the gated incumbent, the same move Morpho Midnight is making now by building credit rails outside the slow, permissioned machinery of traditional debt. But the Eurobond market took decades and an enormous amount of rigid settlement infrastructure to grow into the multi-trillion-dollar system it is today.

On-chain credit is at the same early stage. A corporate treasury can lend on-chain at fixed terms today, and Morpho Midnight can be the biggest beneficiary in enabling that. But for it to become a preferred substitute to off-chain corporate borrowing, it will have to resolve the overcollateralisation problem as a priority.

That’s it for today. I will be back with the next one.

Until next time, stay curious,
Prathik

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The first thing I got reminded of when I read today’s guest essay for the first time was what insurance reveals about human behaviour. Ask most people what insurance they have, and chances are high you might hear phone insurance. Not health cover or a safety net to cover income for dependents. But phone insurance was offered at checkout for a few hundred rupees, and opting for it required the least decision-making.

This reveals how we make decisions around risk. Nobody sat down, listed what could go wrong, ranked it by damage, and decided that their phone screen should be at the top of the list. The risk coverage was offered by default, and the protection got shaped around what was easy to sell. Little did the risk exposure itself matter.

Yet, it works. The claim goes through, the screen gets replaced, and the coverage provides for what it promised.

This brings me to today’s piece.

Lauris works on how states of the world become financial markets — event contracts, derivatives, corporate risk, and the legal and market structure sitting between them.

In today’s piece, Lauris argues that a hedge isn’t a thing to buy at random. It should be a curated relationship built around an exposure you’ve already identified. If you get that order backwards, then you will walk away holding something that pays out on a proposition while your actual problem persists unattended.

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On to Lauris’ story,
Prathik

Anyone can hedge a trade. That does not mean anyone can sell a company “a hedge.”

For a trader, any position that reduces risk elsewhere on the book can reasonably be called a hedge, whether the trader sits on a macro desk, trades crypto, or uses a retail brokerage account.

Buy an election contract against a portfolio exposed to the result and you have hedged the portfolio. The fit may be rough and the protection partial. That still counts as a hedge.

Corporate finance uses the same word for a more demanding relationship. The exposure comes first: a cash flow, liability, or operating risk. The instrument has to match the amount, tenor, and risk factor. Whatever it misses is basis risk. Credit, collateral, documentation, and accounting sit around the trade because the relationship, not merely the payoff, is the product.

A swap, forward, option, or event contract can hedge one account and express a view in another. Its economic function depends on the exposure elsewhere on the holder’s balance sheet. For a company, the relevant questions are which exposure the instrument offsets, in what amount, and for how long.

Both meanings of the word are valid. The category error is treating them as interchangeable.

I have now been in several conversations where experience in a quantitative-trading or market-making seat was assumed to carry over to structuring. The confusion is especially common in tech, where a quant background carries a broad competence halo, often deserved: traders have built excellent exchanges, and many are formidable operators.

But technical horsepower does not make role-specific knowledge portable. Quantitative trading and market making are organised around price, information, and inventory. Structuring a product or a swap that may serve as a hedge is a service operation around a client’s exposure. Not isomorphic.

Prediction markets operators, when thinking about this, make that error frequently. Their natural unit is the contract: list an event, attract liquidity, and find the flow. The same order works poorly for corporate risk transfer, where the exposure comes first. Yet the habit has spread outward from trading and crypto: take the available yes-or-no contracts, map them onto a company’s problems, route the orders to an exchange, and call the portfolio a hedge.

IFRS 9 makes the distinction operational. It asks for a hedged item, a hedging instrument, the risk being hedged, a risk-management objective, and an economic relationship between them [1]. The CFTC starts from the same premise when testing swaps used to hedge physical positions: the risk must arise from an asset, liability, service, or physical commercial activity [2].

What Event Contracts Add

The financial case for prediction markets begins with state-contingent claims. Arrow and Debreu supplied the framework: markets become more complete as they can name, price, and transfer claims on more future states [18]. An event contract can pay if a tariff passes, a merger closes, a drug is approved, or a carbon auction clears above a specified level.

Traditional markets often reach those states only through a proxy, if they price them at all. An event market can create the first observable market price for a state that previously lived inside research notes, scenario models, or bilateral conversations.

For price-threshold claims on the same underlying, the connection to traditional derivatives is exact in the limit: the price of a digital payoff is the negative slope of the call-price curve with respect to strike and can be approximated by an increasingly tight vertical spread [19]. The event contract isolates the terminal state. Before expiry, the options route can carry volatility and mark-to-market exposure, as well as dealer intermediation and replication friction that the buyer did not want.

That identity has limits. “The S&P closes above 7,000” can be mapped onto the S&P option surface. “The Fed cuts in March” or “a tariff passes” remains a legitimate state claim without being the strike derivative of one call curve, and its market price differs from a literal physical probability because it also reflects risk preferences, collateral, liquidity, access, and settlement rules.

The state claim is an input to the company’s cash-flow problem. Prediction markets can manufacture the missing claim, but they cannot manufacture the relationship between that claim and a company’s balance sheet.

Where Event Contracts Matter

Two variables determine where event contracts matter financially:

• Whether a traditional derivative or credible replication already exists.

• Whether a company or investor materially holds the underlying risk.

When material risk already has a derivative, the event contract is a substitute. It has to offer a better fit or a lower all-in cost. The structural cost embedded in the traditional route must exceed the event market’s spread, depth, collateral, and impact costs. This is the replication-cost wedge.

The largest long-run opportunity lies in material risks with no existing derivatives. Here the event contract may be the first instrument, making shutdowns, policy decisions, regulatory milestones, weather outcomes, and corporate events observable and transferable for the first time.

Where a derivative exists but no relevant user materially holds the exposure, there is little unmet risk-transfer demand. Another binary may still be a useful trading product. With neither condition, the market belongs to forecasting, entertainment, or general price discovery rather than corporate hedging infrastructure.

Tradability tells you that a proposition can be priced. Materiality tells you whether anyone has a risk worth transferring.

A contract-first funnel skips the second test: it starts with available listings and searches for companies that can be associated with them.

The Wrong Side of the Desk

A trading mindset starts with a payoff and looks for flow. A structuring mindset starts with a balance sheet and builds the trade.

In fixed income, currencies, and commodities, a corporate client arrives with existing exposures such as floating-rate debt or currency mismatch; fuel bills, inventory, or planned bond issues; and acquisition financing, for an abstract object called a hedge.

It identifies the risk component, chooses the instrument, and sets the amount and tenor. Then it measures the residual basis and fits the result into the client’s documentation, credit arrangements, and accounting policy.

ISDA organises the derivatives market in that order: user, underlying risk, instrument [3]. HSBC’s Autohedge does the same, taking exposures, hedge policy, and risk preferences as inputs before calculating trades [4]. The instrument may be legally separate; economically, the hedge is the relationship around it.

In FICC, a dealer may answer a request for quote with a firm principal-risk price [5]. That is execution: it prices the defined instrument without deciding what exposure the client has or whether the instrument offsets it. Adding a Request-for-Quote (RFQ) to a mismatched contract gives the mismatch a price.

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What Goes Wrong When the Contract Comes First

Consider an importer worried about a possible tariff. Its loss depends on shipment volumes, timing, inventory, pass-through to customers, currency movements, and the company’s ability to find substitute suppliers. An event contract might instead pay one dollar if a public tariff crosses a threshold before a fixed date. The proposition is clean; the fit to the importer’s cash flow is not.

That mismatch is basis risk. A structurer decides which part of the exposure can be transferred and which part the client will retain. An intermediary that starts from the contract does the opposite. It finds a public binary that resembles the client’s problem and treats the resemblance as the hedge. After the trade, the treasurer owns the binary and still owns most of the original risk.

Tailoring the contract creates a second problem. Robert Bartlett and Maureen O’Hara studied 41.6 million Kalshi trades. In their framework, there are no liquidity traders in the Glosten-Milgrom sense because the instrument does not routinely serve the hedging and portfolio-rebalancing role that generates that flow in mature markets [6]. Individuals can still use a contract defensively.

Credit markets show how institutions buy state-contingent risk. In Significant Risk Transfer (SRT), a bank retains its loans and buys first-loss protection through an investor-funded credit-linked note; the BIS counted roughly €800 billion of protected loan pools at the end of 2024 [12]. This is a bank-capital precedent, not a recommendation that corporates buy credit-linked notes. It shows why institutions hold the risk inside a funded instrument with a coupon, documentation, loss allocation, and a mandate line.

The paper also finds higher informed price impact in single-name markets than in broad macro markets [6]. A tariff decision is usually exogenous to an ordinary importer, so its order carries little information. A market maker can welcome the flow, but the public tariff line is only loosely connected to the importer’s loss.

Tighten the contract around a merger, a drug trial, a plant, or another company-specific outcome and the basis improves. The company may now know more than the person quoting it, so the market maker widens, cuts size, or walks away. The welcome trade is the one with the largest basis. The close-fitting trade is the one the market is least willing to warehouse.

A filled contract still leaves the company to explain the objective, ratio, basis, valuation, and financial-statement treatment. A dashboard does not establish that relationship, and an RFQ cannot make an audit committee accept it.

The business model is squeezed from both sides. If the exposure is small and already matches a listed contract, the client can trade it directly. If it is large or bespoke, the client needs structuring and capital. A company that only routes the listed contract adds no capacity. A company that designs the payoff, arranges documentation, and commits or sources capital has become a broker, insurer, or FICC structurer rather than a new category.

The Wrapper Changes the Market

WeatherBill launched a self-serve weather-derivatives platform in 2007. The thesis was that exposed businesses would buy protection. They did not. The company narrowed to farmers, moved onto insurance paper and outbound distribution, and became The Climate Corporation [7].

Event contracts found native demand elsewhere: CME’s FanDuel platform launched in December 2025 and reported 100 million contracts in about eight weeks [8].

Weather went to insurance; sports found retail distribution. The standalone corporate hedge sold through a software funnel remains the missing case.

Where The Risk Sits

Once the exposure is defined, the remaining problem is risk-bearing capacity.

In practice, event risk reaches a balance sheet through three routes. Risk never appears, and has to be transferred somewhere.

1. Trade it directly when the exposure already fits

A Manhattan bar covered a free-drinks-if-the-Knicks-win promotion with roughly $5,000 of event contracts; the liability and contract resolved on the same game [9]. If settlement fits, the same route can handle larger exposures.

A contract tied to a California solar-credit tax rebate reportedly transferred about $600,000 through a displayed, centrally cleared market [10]. Company size is not the dividing line; fit and book capacity are.

I am working with some of the extremely talented folks at @kalshi, especially with @0x_ultra, on providing a showcase for this, as part of the Builder’s Program. It will be released shortly.

2. Fund a pool when the risk is actually poolable

A parimutuel market divides a committed pool among the winners, capping aggregate liability at the capital already present; Goldman Sachs and Deutsche Bank used the mechanism for economic derivatives from 2002, with non-farm-payroll auctions averaging about $9 million before moving to CME in 2005 [11]. The BIS still questioned whether genuine hedging demand would balance sophisticated informed traders [11].

Pooling works only when losses differ, opposite exposures exist, or outside capital is paid to participate. When every participant loses together, the pool simply produces a queue of claimants that someone with capital must stand behind: insurance, reinsurance, or a warehouse again.

I know really smart people like @AadvikVashist are working on this.

3. Put the event inside an instrument institutions already own

In April, Marex issued up to $10 million of a structured note to one Swiss institutional client, paying 7% if Nvidia remains the world’s largest company after a year; the client owns a Marex obligation, and Marex uses event contracts to run the replication [13]. The institution bought a security with an issuer, documentation, and a mandate line, while the event contract stayed on the dealer’s side of the trade. Before the trade reached the client, Marex had turned the event contract into FICC.

Software has a role after the exposure is defined. It can test traditional instruments, identify a coverage gap, and compare an event claim on basis, cost, execution, collateral, law, mandate, accounting, and residual risk. A useful product would encode that process and allow the answer to be no trade.

The Regulatory Blast Radius

A bad corporate-hedging pitch would normally be a problem for its buyers. The damage is wider here because event markets are still fighting over the role they are allowed to play in the financial system. Commercial use does not determine CFTC jurisdiction over an event contract.

The Crypto Council for Innovation grounds that jurisdiction in the Commodity Exchange Act’s swap definition, federal preemption, and the CFTC’s exclusive authority over derivatives markets [14], and an event contract does not stop being federally regulated merely because the person buying it is speculating.

The public-interest case extends beyond corporate hedging. Regulated event markets can name previously unpriced states, produce public prices, and create transparent, collateralised claims with defined settlement rules. Those are serious financial functions even before a treasurer trades one. But hedging remains central to the policy case.

The CFTC describes prediction markets as tools for forecasting, planning, hedging, and speculation. In February 2026, the Commission defended its jurisdiction against state gambling regulators by pointing to business hedging, portfolio management, and information about future outcomes [15]. CCI draws the distinction from gambling through many-to-many execution, transparent pricing, defined settlement benchmarks, surveillance, customer protections, and market integrity [14].

In March, the CFTC reminded prediction-market exchanges of their obligations under the Commodity Exchange Act and Core Principle 3. Its June proposal addresses event-contract design, public-interest review, and responsible innovation [16].

A serious corporate hedge failure would follow a simple pattern. A business is told that a binary position offsets an operating risk, so it posts cash. The contract may expire worthless even though the company loses money, because volumes, timing, or pass-through were never in the payoff; before settlement, its mark may move through earnings while the original exposure remains, leaving the company with a proposition rather than protection.

Regulators have seen the payoff shape before. The CFTC and SEC issued a joint alert after complaints about binary-options platforms refusing withdrawals, identity theft, and software manipulation that generated losses [17]. The regulated event venues discussed here are not those fraudulent brokers: their markets are supervised, transparent, and centrally cleared, but that history raises the cost of mislabeling a trade as protection.

Opponents of federal prediction markets will not write a seminar about basis risk. They will say a company was sold a bet under a derivatives label.

An intermediary that sells a mismatched binary as corporate protection will hand state gambling regulators the industry’s strongest argument against federally-regulated prediction markets.

If you got to the end, truly appreciate you for reading this.

That’s all for today.

Until next time,
Lauris

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References

[1] IFRS Foundation, IFRS 9 Financial Instruments, paragraph 6.4.1 and related hedge-accounting provisions. [PDF]

[2] Commodity Futures Trading Commission, discussion of swaps used to hedge physical positions, 83 FR 7927 (2018). [Final rule]

[3] International Swaps and Derivatives Association, *Evolution of OTC Derivatives Markets Since the Financial Crisis* (January 2021), table 1. [PDF]

[4] HSBC, [Autohedge] and [FX Overlay for Corporate Clients].

[5] Citi, Markets & Banking Execution Policy — FICC. [PDF]

[6] Robert Bartlett and Maureen O’Hara, *Adverse Selection in Prediction Markets: Evidence from Kalshi*, Stanford Law and Economics Olin Working Paper No. 615 (April 16, 2026). [SSRN]

[7] OpinionX, *Deconstructing WeatherBill’s $930M Startup Pivot*. [Article]

[8] FanDuel and CME Group, [FanDuel Predicts launch release]; CME Group, [100 million event contracts announcement].

[9] Catherina Gioino, *This NYC Bar Just Covered Everyone’s Tabs Because the Knicks Won, and Used Kalshi to Hedge Their Bets*, *Fortune* (June 3, 2026). [Article]

[10] John Lothian News, *Kalshi Eyes Institutional Scale as Prediction Markets Prove Fed-Grade Forecasting Value* (July 9, 2026). [Article]

[11] Blaise Gadanecz, Richhild Moessner and Christian Upper, *Economic Derivatives*, BIS Quarterly Review (March 2007). [PDF]

[12] Prashant Babu, Michael Chui and Costas Stephanou, *The Rise and Risks of Synthetic Risk Transfers*, BIS Quarterly Review (March 2026). [Article]

[13] Finance Magnates, *Marex Launches Structured Note Linked to Prediction Market Outcome* (April 2026). [Article]

[14] Crypto Council for Innovation, response to the CFTC prediction-markets advance notice of proposed rulemaking (April 2026). [PDF]

[15] Commodity Futures Trading Commission, [*Understanding Prediction Markets and Event Contracts*] and [press release 9183-26].

[16] Commodity Futures Trading Commission, [prediction-markets advisory] (March 12, 2026) and [*Prediction Markets; Public Interest Determinations*].

[17] Commodity Futures Trading Commission and Securities and Exchange Commission, *Binary Options and Fraud*. [Investor alert]

[18] Kenneth J. Arrow, *The Role of Securities in the Optimal Allocation of Risk-bearing*, *Review of Economic Studies* 31(2) (1964), [DOI]; Gérard Debreu, *Theory of Value: An Axiomatic Analysis of Economic Equilibrium* (1959), [PDF].

[19] Douglas T. Breeden and Robert H. Litzenberger, *Prices of State-Contingent Claims Implicit in Option Prices*, *Journal of Business* 51(4) (1978). [JSTOR]

We will be back with another guest essay soon.

P.S. This piece was originally published here.

We will be featuring good writing and writers we love from time to time. If you have recommendations, send them our way.

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. If you want to reach out to 170,000 subscriber community of the Token Dispatch, you can explore the partnership opportunities with us 🙌

📩 Fill out this form to submit your details and book a meeting with us directly.

Disclaimer: This newsletter contains analysis and opinions of the author. Content is for informational purposes only, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

It was called remote disbursement. To stall a payment, a New Jersey buyer would issue a cheque from an obscure bank thousands of miles away in Montana.

By adding physical distance and extra handoffs between banks, the cheque took days to clear. With interest rates soaring past 10%, keeping that cash in your account for just a few extra days yielded free profit.

There were consultants who did nothing except maintain maps of which small-town banks took the longest to clear. It was the volume that made it work. Americans wrote 8 billion checks in 1970 and 16 billion in 1980. The Federal Reserve float, the money that exists for a moment in two places at once because a cheque has been credited and not yet collected, averaged about $3 billion a day in 1972. It more than doubled between 1975 and 1978.

The Fed was furious. It published a report on remote disbursement in February 1979, then a policy statement telling banks to stop helping. The Monetary Control Act of 1980 called for the practice to be eliminated. Check 21 finished it two decades later. Most cheques now clear in one business day and the Fed processes every one of them in a single building in Atlanta. That was the end of it.

Siemens employs more than 12,000 people across 80-odd countries in a division called Global Business Services, processing invoices and running payroll and reconciling statements. Airbus started one in Lisbon in July 2021 and now has more than 1000 people in Portugal across that centre and its industrial unit. Goldman Sachs, the entire firm, employs 47,400.

Then in September 2024, the same Siemens issued a €300 million bond that settled in minutes with blockchain.

Today I want to show you what connects those two facts. On to the story…

Start with the bond, since it’s the easiest

Siemens issued €60 million on Polygon in February 2023, waiting two days for the trade to settle. 18 months later, it returned with €300 million, swapping a public crypto network for SWIAT. Built by a consortium of European banks, SWIAT is a closed ledger designed specifically to play by institutional rules. That regulatory alignment allowed it to connect to the Bundesbank’s Trigger Solution, settling the entire €300 million automatically, in minutes, in central bank money.

Investors subscribed directly and could see their register entry the moment settlement completed. Peter Rathgeb, the corporate treasurer, ran both issues, and the second one removed nearly all the settlement risk from every party in the deal.

Normally, an institution like Clearstream (a massive Central Securities Depository) has to sit in the middle just to handle the certificate. Nobody’s job at Clearstream is safe or unsafe because of one German bond.

Secondly, the payroll department

Deel runs payroll for more than 40,000 businesses and 1.5 million workers across 150-plus countries, processing over $22 billion a year. Since January 2026, a company can fund its entire global payroll straight from a stablecoin treasury. In June 2026, Deel launched its own dollar-backed digital balance called DLUSD.

What leaves the employer’s side? Trapped liquidity in foreign bank accounts. Emergency troubleshooting for failed wires. Intermediary FX conversion fees. Manual account reconciliations.

What leaves the worker’s side? In Argentina, Turkey and Ukraine, a salary paid in local currency can lose 20 to 40% of its value inside a year. In 2025, 85% of Deel’s Argentine contractors chose to be paid in dollars. In June, the company gave them a dollar balance to hold inside the app they already use, built on Bridge and Privy and Tempo, with rewards on idle funds. In May, it started paying full-time employees in stablecoins on Polygon in the US and Eurozone, at 10 to 25% of net salary after tax.

From a treasury perspective, stablecoin utility is now backed by hard data. According to an EY-Parthenon survey of 350 executives, 13% of firms have already adopted stablecoins. Of those, 41% have realised cost reductions greater than 10% in cross-border B2B payments. This efficiency reclaims $5 million on a $50 million transfer program. This is capital previously lost to fixed operational costs. Looking ahead, 54% of surveyed non-users intend to adopt this infrastructure within a year.

Real end-user stablecoin payments hit roughly $390 billion a year by February 2026, double 2024, and about 60% of it is now B2B rather than trading. Hyundai Card settled a cross-border corporate payment in seven minutes. Visa is running a $7 billion annualised settlement rate across nine chains, up 50% in a quarter. None of these is crypto companies experimenting at the edges.

Businesses are using stablecoins to solve the mechanical problems of slow cross-border settlement and trapped capital discussed earlier.

Third one, the biggest, least discussed - Collateral

JPMorgan’s Kinexys runs about $5 billion a day and has cleared $3 trillion in total, with its intraday repo alone passing $1.75 trillion. BlackRock has posted tokenised money market funds to Barclays as derivatives collateral. Broadridge moves $354 billion a day. CME is building the same thing with Google Cloud, aimed at a $15 trillion collateral market.

I want to explain why collateral is the one to watch if you’re building.

A hedge fund holds a position it doesn’t want to sell and wants to borrow against it. Neither side trusts the other, so the collateral goes to a triparty agent who sits in the middle and holds it. Somebody negotiates the agent’s contract first. Then the asset travels for days, and fees stack.

Semi Liquid secures the collateral in place and changes what the borrower can do with it. Freeze in place, adjust the spending conditions, skip the transfer. Just like Kinexys, it’s going at the same $15 trillion. Look now at the jobs that survive the introduction of software; the logistical aspect of moving the collateral disappears, and what remains are only the difficult human judgments involved in assessing the value of the asset and making the late-night default calls. Which is the line I’d hand to anyone deciding where to point a budget.

Which means technology is not eliminating the cost of misjudging a counterparty. This explains why some of these projects lived and the rest died.

Between 2018 and 2020, big companies including HSBC, Maersk, and BNP Paribas launched four trade-finance blockchain networks. None survived past 2023.

• June 2022 - we.trade went bankrupt.

• November 2022 - Maersk and IBM shut down TradeLens.

• Early 2023 - Marco Polo shut down, $4.6 million in debt.

• November 2023 - Contour closed after averaging only 60 to 70 trades a month (later acquired by XDC Network).

Faster digital letters of credit improved document speed, leaving the core cost of credit underwriting untouched.

Komgo is the only survivor of the group. It got there by dropping the blockchain. Launched in 2018 by major banks, it originally offered both a digital letter of credit and a document workflow tool. The credit product died; the paperwork product continued. While competitors collapsed trying to digitise trust, Komgo survived by pivoting strictly to mechanical plumbing.

Tether proves what happens when a financial company refuses to judge counterparties. By operating strictly as a mechanical conduit, taking dollars, holding Treasuries, and issuing tokens while exchanges handle the actual customers, it removes the operational cost of human trust. This perfectly automated asset-moving model allowed a 300-person team to clear $10.09 billion in profit in 2025. Generating $33.6 million per employee, Tether massively outperforms traditional risk-managing banks like JPMorgan and Goldman Sachs.

Then it stepped into credit. Its secured loans went from $14.60 billion on September 30 to $17.04 billion on December 31, almost $7 billion added in six months. Protected by a $6.34 billion safety net, though the borrowers are kept secret.

The second Tether started lending money, it had to hire humans to evaluate collateral and make late-night margin calls.

Two details heavily distort Tether’s profitability. First, nearly half of its profit came simply from the surging prices of its massive gold and Bitcoin reserves. Second, it pays zero interest on the billions of dollars of tokens it has issued. If a traditional bank held that much customer cash, it would owe billions in interest payouts every single year.

Circle shows the same boundary from the other side. It booked $1.4 billion in distribution costs tied to Coinbase in 2025, up from $924.5 million, per its 10-K. That’s 51% of its $2.7 billion revenue going to a company that neither issues USDC nor manages the reserves. Coinbase runs the onboarding, the KYC queue, the fraud team. Verifying a customer’s identity still requires human judgment. Circle keeps its headcount low by outsourcing this process entirely, turning what should be an internal payroll expense into an external contract line.

So, where to build.

Enterprise blockchain and stablecoin technology solve three operational problems. It automates the movement of cash, collateral, and certificates. It frees up idle capital trapped in payroll floats and escrows. And it removes cross-border friction in Latin America, Africa, and Southeast Asia, the exact use case driving the 10% cost reductions reported by executives.

Corporate issuance, which almost nobody is working on. Germany’s eWpG made Siemens possible. Total eWpG digital securities issuance was around €236 million by June 2024, with KfW adding €150 million across two deals. That’s nothing against the European corporate bond market.

Treasurers used to profit from delayed settlements. When the float died, they shifted to managing pre-funded accounts. Now, tokenisation has vaporised that too.

—Thejaswini

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. If you want to reach out to 200,000+ subscriber community of the Token Dispatch, you can explore the partnership opportunities with us 🙌

📩 Fill out this form to submit your details and book a meeting with us directly.

Disclaimer: This newsletter contains analysis and opinions of the author. Content is for informational purposes only, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

Last year, a single company settled about $4.7 quadrillion in securities transactions. That’s more than 35 times the global GDP. This month, that company - the Depository Trust & Clearing Corporation (DTCC) - began using blockchain to process these transactions.

One of the biggest upgrades happening in global finance right now involves an infrastructure swap. The clearing house isn’t the only one. Messaging cooperatives that connect more than 10,000 banks globally and card networks that reach 200 million merchants are all rebuilding the infrastructure that moves assets with blockchains as the central part of this upgrade.

Crypto’s rails are being adopted faster by some of those very industries that spent a long time dismissing them.

In today’s story, I explain why they are warming up to using crypto as their backend and the role crypto companies are playing in this upgrade.

On to the story…

The Cost Problem

A share of Microsoft you pay for today on the New York Stock Exchange (NYSE) will still take a full day to legally be handed in your name. That’s because the infrastructure that moves share ownership was designed for an era involving paper certificates. Humans have spent over 60 years dematerialising shares and speeding up everything in a stock market. Yet, the part where money and assets change hands is still designed around the infrastructure that existed from the paper era.

It’d be naive to presume that this is just a convenience problem. Delays in processing asset and cash movements always incur a financial cost.

Consider a cross-border bank payment. Most global banks pre-fund accounts in different countries and currencies so that payments can clear in other time zones. They use local deposits and central bank reserves to settle cross-border transactions without waiting for real-time funding during different local business hours.

Even when stock market traders post collateral, that money sits idle and earns nothing. Settlement stops on Friday evening and resumes on Monday, following office hours, even when humans function and live their lives on weekends. Although none of this was initially intended to be an inconvenience, we all continue to pay a tax for using this infrastructure, even as faster and cheaper alternatives have emerged.

Meanwhile, exchanges are responding by expanding their trading hours. The London Stock Exchange just announced LSE 24, a venue that will trade for 23.5 hours from Monday to Friday starting from H1 2027. CME took its crypto futures 24/7 in May. Nasdaq has also planned to enable 23-hour trading days later this year.

Although trading is expanding its office hours, settlement of these trades still lags behind. This further punishes the trader by blocking capital.

This tax has grown to the point where it accounts for more than a fifth of global GDP.

Global corporates alone transferred over $30 trillion in cross-border payments last year. They incur transaction costs of more than $120 billion per annum.

This is the cost of this problem that the operators of the legacy financial infrastructure are beginning to take notice of.

In July 2026, they began taking first concrete steps to replace the legacy infrastructure with crypto rails.

The Infra Swap

On July 15, the DTCC, the backbone of the U.S. financial markets, ran its first live production trades of tokenised securities. The trades involved tokenised versions of the original underlying listed company shares, Treasuries, and ETFs.

As part of DTCC’s first on-chain trades, JPMorgan converted holdings of the Invesco QQQ Trust (QQQ), one of the world’s most actively traded and liquid ETFs, into tokenised form and posted them as margin at CME. Goldman Sachs, BlackRock, Vanguard and the NYSE were among more than 30 firms in the room. These tokens moved through repo, collateral pledges, securities lending and clearinghouse margin on production infrastructure.

This comes just months before the scheduled launch of the DTCC Tokenization Service in October 2026.

This single infrastructure move gives us a quantifiable magnitude of the economic benefit more efficient systems could bring to capital markets. In May 2024, US equities moved from settling in two days to settling in one. That single day cut in the settlement cycle reduced the margin that members must park at the clearinghouse by $3 billion, or 23%, from a three-month average of $12.8 billion in the T+2 cycle to $9.8 billion in the T+1 cycle.

If one day saved in one country’s equity market could free $3 billion in collateral, the value of collapsing settlement to minutes across equities, Treasuries, repo and FX, across borders and over weekends can blow up exponentially.

This is what blockchains commoditise. A stablecoin transfer settles in seconds for a few cents in cost, at any hour, on any day. On the other hand, a tokenised security can change hands and simultaneously serve as collateral without waiting for the infrastructure to open on Monday.

This is why operators of legacy infrastructure are warming up to the idea of using crypto rails as their backend. Because if they don’t, they risk losing business to their competitor who offers its clients the same services at much lower prices and faster speeds.

Crypto infrastructure allows customers to put their money to work more efficiently by eliminating idle time. A security that settles tomorrow cannot be used as collateral today. A tokenised security can be pledged and lent in minutes, around the clock. Collateral mobility is the difference between capital working in parts and capital working continuously.

Nine days earlier, SWIFT, the cooperative whose messages coordinate payments between more than 11,500 institutions, said 17 banks from six continents, including Citi, HSBC, UBS, Standard Chartered, and MUFG, are preparing to pilot tokenised deposits on its new shared ledger.

Tokenised deposits are bank money sans time barriers. Blockchains move funds overnight and on weekends while still remaining as a claim on a regulated bank. This is the perfect alternative for those who avoid bank-issued stablecoins due to the lack of FDIC coverage. Tokenised deposits give users the same convenience as stablecoins, while keeping their money within their own regulatory perimeters.

I wrote about this last month, in Defending the Deposit.

Even card networks like Visa are adopting crypto infrastructure.

On July 16, Cuy Sheffield, Head of Visa Crypto Labs, announced the launch of a platform that lets banks mint, move, and redeem stablecoins within the treasury systems they already run, hiding every key, gas fee, and chain from the client.

The biggest appeal for traditional finance giants in adopting crypto infrastructure as their backend is the ability to pass on cost and time efficiencies across their wide distribution. Roughly 15,000 financial institutions and more than 200 million merchants already sit on Visa’s network.

Its competitor, Mastercard, has built on its earlier pilots and initial live deployments by expanding stablecoin settlement options for banks across six regulated stablecoins.

Mastercard now supports settlement across Circle’s USDC, Paxos’s PYUSD, USDG and USDP, Ripple’s RLUSD and SoFi’s SoFiUSD. These stablecoins will be enabled across a range of supported blockchain networks including Arbitrum, Base, Canton, Ethereum, Polygon, Solana, Tempo and XRPL.

The proof that this class of infrastructure works at scale already exists inside a bank. JPMorgan’s Kinexys has processed over $4 trillion in cumulative volume and now moves more than $7 billion a day, every day, including on days when the rest of the financial sector is closed.

Those still unconvinced and resistant to crypto infrastructure need to look no further than how money market funds have adopted blockchains. BlackRock’s BUIDL, a tokenised Treasury fund with roughly $2.5 billion in assets, is now accepted as collateral for derivatives at major venues. Standard Chartered and OKX, a fintech and crypto trading platform, came together to build that framework.

This is the real-world utility of adopting crypto as a backend. It has enabled collateral to earn Treasury yields while posted as margin.

This is the strongest pitch I’d make to anyone who asks “Why should anyone choose crypto rails?”

The single most important job of any new financial innovation should be to help you move, grow and store your money more efficiently.

By enabling these innovations, incumbent crypto companies are finding new roles.

Joining Them, Instead of Fighting Them

Instead of replacing traditional financial companies, as many crypto ideologues had envisioned, crypto companies are becoming the builders of the infrastructure that traditional companies demand.

Half a dozen crypto companies came together to make the DTCC’s July a reality. Chainlink wired the networks together; Digital Asset’s Canton network carried the Treasuries; Fireblocks and BitGo supported custody; and Circle and Ondo designed the service for the entire working group.

Some of these firms spent a decade building for a parallel financial system, but are now supporting traditional financial companies in building faster, cheaper infrastructure to move money and assets. Their revenue model has changed from replacing Wall Street to invoicing its companies.

These invoices are also stretching halfway across the globe.

On July 16, Ondo Finance, the largest tokeniser of equities, announced a partnership with Japan’s SBI Group to tokenise Japanese stocks. The tokenised equities will be distributed across SBI’s ecosystem and settled with JPYSC, SBI’s yen stablecoin.

SBI manages over $250 billion in assets. If it had to build tokenisation capability in-house, it’d have to start from scratch. Instead, it just procured the technology from a vendor that already runs on blockchains and paid rent for its expertise. Ondo already accounts for more than 70% of the tokenised equity issuer market and has a distribution arrangement with Deutsche Börse’s Clearstream in Europe.

Securitize plays the same role by supporting the issuance of BlackRock’s BUIDL.

What Happens Next?

There’s a precedent for what follows.

In 1956, a trucker named Malcom McLean put cargo in a standard metal box. This reduced loading costs from $5.86 per ton to $0.16 per ton. World trade reorganised around the container. Ironically, the carriers who owned the ships captured almost none of the value. That’s because the container box became a commodity and freight became a price war. The riches went to the firms that rebuilt their operations around cheap, reliable shipping. The great beneficiary of the container innovation was the retail giant Walmart, and not logistics giant Maersk.

A similar format could repeat in fintech.

For the container innovation to transform the logistics industry, an entire ecosystem of cranes, ports, chassis and customs had to be rebuilt around it. Similarly, tokenisation works only once custody, compliance and interoperability are rebuilt around it. This is where the value accrues as the settlement layer in banks and financial institutions gets commoditised. It’s this precise ecosystem that Chainlink, Fireblocks and Digital Asset are now targeting.

Tokens or chains will no longer capture significant value. Instead, value will pool in two places.

The first is in the utilities that adopt the crypto rails. DTCC, SWIFT, and Visa will charge for tokenised settlement, deposits, and stablecoins, just as they do for traditional, non-crypto systems. But there’s larger value elsewhere to capture. There will be institutions that reorganise their operations around continuous, atomic settlement by running treasury intraday, making collateral work more efficiently, and offering round-the-clock access to working capital. Think of the BUIDL fund that lets you earn Treasury yields on collateral posted as margin.

Crypto has already spent more than 15 years building a parallel, better financial product. I think crypto builders with foresight will stop building such products. Because crypto’s bigger triumph is being the backstage protagonist that makes your money move more cheaply and faster.

That’s it for today. I will be back with the next one.

Until next time, stay curious,
Prathik

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Each of the twenty districts is run out of a dzong, a whitewashed fort with sloping walls and a monastery in the courtyard, usually planted on high ground above a river. Many are three centuries old. They were built to be hard to reach, because they were built to survive sieges.

Which worked beautifully when the job was defence.

Bhutan has around 786,000 people scattered across a very steep country. Roughly eight in ten work the land. Roads follow ridges instead of cutting through them, so two villages facing each other across a valley can be half a day apart. To get a document, you went down the mountain and up to the fort, and you waited, and you carried photocopies of everything you owned. Forget one paper, and you came back another day. The cost to the citizen is the day of farm work they lost.

In October 2023, Bhutan switched on the National Digital Identity (NDI), built to delete the whole tiring process the people went through. Two weeks ago, Bhutan started exporting it. We need to understand if the success belongs to the tech, or to Bhutan’s society.

The National Digital Identity puts your credentials in an app, locked with your face or your fingerprint. The records are on citizens’ phones, without a central vault holding everyone’s records. The state can confirm a credential is real without keeping a copy of it. A highly practical use case of zero-knowledge proof.

Say a service needs to know you’re over eighteen. The old way, you hand over a card carrying your birth date, your address, your ID number and your face, all of it, to settle one small fact. The NDI lets you prove the fact alone. Yes, over eighteen. You prove that is true without showing the file it came from.

Bhutan moved rails three times. It started on Hyperledger Indy, a closed ledger, the cautious institutional pick. In August 2024, it moved to Polygon for speed.

In October 2025, with Vitalik Buterin and the Ethereum Foundation’s president standing in the room, Bhutan anchored the system to Ethereum itself. First country on earth to put a live national identity system on a public chain, with full migration due this year.

Zero personal details are stored on-chain; it acts purely as a cryptographic ledger verifying that a credential remains valid and unaltered. The chain is a notary that no ministry can rewrite, including Bhutan’s own. The GovTech secretary’s reasoning was that Ethereum is spread across so many machines worldwide that it’s very hard to knock over. Bhutan selected a widely distributed public network to ensure its identity system stays online even if foreign infrastructure crashes. Because if a small nation like Bhutan relied on infrastructure controlled by a superpower (like US-based AWS or Google servers) and those servers suffered an outage, cyberattack, or political sanction, Bhutan would be left completely helpless. Since they cannot fix another country’s or company’s servers, they would just have to wait in the dark.

In February 2024, four months after launch, about 24,000 people had signed up. A year later, that was 219,506 registered users, out of 280,757 attempts, so not everyone who tried got through.

By the end of March 2025, the count of foundational IDs issued reached 234,568, covering citizens and foreign workers. A ninefold jump in twelve months, and it’s also roughly three in ten people. There’s been no official update published since, though the system has kept adding pieces.

On March 13, 2026, the Bhutanese Ministry of Foreign Affairs and External Trade, in collaboration with the GovTech Agency, issued an official press release announcing the integration of the Bhutan NDI wallet and eKYC with the national passport system. This means citizens no longer need to fill out physical forms or scan documents when applying for a passport. Instead, they can log into the G2C (Government to Citizen) website, scan a QR code using their NDI app, and their verified details, photograph, and e-signature are instantly synced to the passport office.

How did the 3 out of 10 that signed up get there? They got there because things people already had to do were routed through the app. Civil servants were required to register. Enrolment for Gyalsung, the national service programme every young Bhutanese goes through, runs on it. Three of the country’s banks, BOB, BNB and BDBL, wired it into remote account opening, so you can open an account without the trip to the branch. Telecom SIMs carry verifiable credentials. Passports followed.

High trust is what let Bhutan try. Ordinary usefulness, plus a few mandates, is what moved people. They might have downloaded it because the bank won’t open the account otherwise, and because the alternative is climbing up the fort.

But then, plenty of governments issue mandates. Very few get obeyed without a fight.

That’s where I get to romanticise this whole thing. Bhutan measures itself by Gross National Happiness, an idea its fourth king put forward in the 1970s that the constitution now instructs the state to pursue. Easy to file that under the tourism brochure that we all see and get excited. In practice it works as a test that proposals have to pass, and the test is whether the thing improves how people live, not only what it earns. A digital ID that saves a farmer two days of walking clears that bar without question.

The country also has a strange history with power. The monarchy handed authority to an elected parliament in 2008, and the king spent years persuading a reluctant public to take it. Because the monarchy willingly surrendered its power to the people, the Bhutanese public does not have an ingrained fear of an oppressive government. They do not automatically suspect that state tech initiatives are secret surveillance plots designed to track them.

When that state introduces a digital ID and promises it is actually better for privacy than a physical ID card (since you only share the necessary data, not the whole card), the public takes them at their word. The NDI Act passed both houses unanimously.

The same sovereign fund that built the identity system, Druk Holding and Investments, has been mining Bitcoin with surplus hydropower since around 2019. Holdings peaked near 13,000 BTC in late 2024 and have since been sold down to somewhere around 3,100, with hundreds of millions moving out to wallets nobody has identified. In May, the fund’s chief executive said he did not recall selling any. On-chain trackers say otherwise. A citizen-controlled identity system and an opaque treasury at the same time. After all, it’s a small state making bets, some of them as murky as anyone else’s.

Compare it with the United States, which for the last twenty years has been trying to standardise a driver’s licence.

REAL ID went into a wartime spending bill in 2005. It was a law requiring higher-security driver’s licenses to board domestic flights or enter federal buildings. Twenty-five states passed statutes or resolutions rejecting it. Fifteen wrote laws forbidding their own officials to comply. The opposition coalition ran from the ACLU (American Civil Liberties Union) to Gun Owners of America, groups that agree on nothing else, and they held for two decades. Enforcement finally came into force in 2025. Basically, the country took twenty years to settle the format of a card everybody already carries.

Because there’s a belief most Americans hold without being taught it. A government that can identify you reliably will eventually use that against you.

Barry Goldwater said it in 1974, warning that a universal identifier would leave a trail behind a person for life, ready to be reassembled and used to press on them. That instinct comes from a country with a long memory of files kept on the wrong people.

In fact, in America, proving who you are is an industry. Credit bureaus, verification vendors, background checkers, brokers reselling the fragments. When we talked about the paperwork in Bhutan, it was the effort and the time they lost on it that made it a problem. In this case, it’s the product itself.

So the same thing looks like a bridge over a mountain in Thimphu and as the first page of a dossier in Washington.

On July 5 this year, Sierra Leone’s technology ministry signed an agreement with Bhutan NDI and the SIGN Foundation to build the same kind of system there.

Bhutan is sharing its battle-tested, open-source digital wallet architecture, prioritising the training of Sierra Leonean developers so the country can manage its own W3C-standard system instead of paying perpetual vendor fees.

Sierra Leone has almost none of Bhutan’s advantages. It’s far bigger, far poorer, with a civil war inside living memory, and a long public record of corruption. If the theory is that only small, stable, high-trust countries can pull this off, Sierra Leone is the case that tests it. If it works there, the theory was wrong, and the useful ingredient was not Bhutanese serenity. The true formula came down to open tech standards, targeted state mandates, and a government with everything to gain by lowering bureaucratic hurdles — if it works.

The dominant narrative around this technology is still the one that promises escape; dodge the state, route around the rules. Bhutan used it to run the other way and make the state easier to reach, and it’s now sharing that with whoever wants it, while its own rollout is still in progress.

The result is mundane, people don’t NEED to climb the mountains too much.

—Thejaswini

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A company that wants to borrow $200 million can either tap into a commercial paper programme or use a slice of its medium-term note (MTN) shelf. The former helps fund immediate cash needs through a continuous, revolving issuance facility. The MTN route allows corporates to utilise a “shelf registration” filed with regulators once, to sell tranches of notes on demand when market conditions look favourable. But if the same company wants to raise $200 million by selling its own shares, it must hire bankers, tour fund managers for weeks, and pay up to 7% of the proceeds to cover the costs of the process.

This is one of the oldest problems in corporate finance. Raising debt is routine, but issuing equity involves a ceremony.

Paperwork or regulation are not the only reasons for this asymmetry. The bigger problem is demand. A company’s shares trade in one pool on an exchange during the market hours. When it wants to sell more shares than that pool can absorb, a bank or a fund manager has to go out and find new buyers through a roadshow.

Blockchains can address this asymmetry by broadening the geographic market from which demand for fresh equity flows.

In today’s piece, I explore how tokenised rails can let equity behave like debt and who captures the value in this process.

On to the story…

Stripping the Ceremony

While IPOs involve a roadshow and 5-7% processing cost in the form of bank commissions, raising follow-on equity has become relatively easier over the past few decades. In 1982, the US SEC adopted Rule 415 that created “shelf registration,” allowing qualifying companies to register securities they plan to issue over the next two years and sell them piecemeal later.

The at-the-market (ATM) programme took this one step further. In this, the company issues new shares to an appointed broker-dealer in the secondary market. The broker then drips these shares into the primary public markets in small amounts to avoid a sudden supply glut. Often, the market notices this only after the company files its quarterly report.

An ATM could cost the issuer only 1-3% in commissions, half of what IPOs cost.

Still, a problem persists with these ATMs. If the company’s broker-dealer pushes one too many shares into a thin order book, then it manufactures its own price drop. This is why the route is only ideal for those seeking to raise modest sums. For higher raises, companies still prefer to go for the roadshow. That’s what the IPO fees buy from the company’s partner bank - the ability to find buyers for their new shares.

Blockchains can fix this problem.

Widening the Pipe

Last week, Cantor Fitzgerald partnered with Securitize to let companies issue shares directly on a blockchain. It is different from other tokenised versions of stocks that have emerged on the blockchain. Vaidik and I wrote about how ownership works across these versions. Some of these tokenised versions are merely wrappers that give price exposure without voting and ownership rights.

But Securitize isn’t wrapping the stocks. Cantor, the bank that topped the US IPO table in 2025 for funds raised through Equity, SPAC, and ATM placements, understands well that there is value to be captured in widening the surface area over which demand accumulates for US public companies.

On July 2, Securitize became the first US company to go public and on-chain on the same day. About $270 million of its common stock (SECZ) went live on Solana and Avalanche on the same morning it was listed on the NYSE.

Two weeks later, Securitize joined hands with Cantor to take the proof of concept as a product and sell it to other companies. Cantor will contribute with its equity capital markets desk and trading relationships. Securitize offers the tokenisation infrastructure around issuance, distribution and settlement through its SEC-registered broker-dealer - Securitize Markets. Together, they will offer companies IPOs and follow-ons in which some portion of the shares are born on-chain.

On-chain issuance, in principle, can let investors across the globe access and own US securities in the same way a US-domiciled investor does. A token issued through Securitize carries the same voting rights and dividend claim as the underlying share that is recorded on the official share register.

But whether this parity reaches non-US investors depends on the regulatory landscape. The issuing company must issue a parallel Reg S tranche alongside the US-registered offering. While the shares issued under this tranche carry similar voting rights and dividend claims, Securitize’s own SECZ tokens today are restricted to eligible US investors.

If this parity can be ensured, then a company issuing on-chain is no longer capped by the depth of its own listed order book. The drip of new shares gets wider demand.

The tokenisation of the issuance layer of stocks has also coincided with the tokenisation of the settlement layer.

DTCC, the institution that clears almost every US stock trade, settled its first live tokenised trades of SPY, QQQ and Treasuries with more than 50 institutions, ahead of a full launch scheduled for October this year.

Streamlining the Demand

Setting up the infrastructure alone isn’t enough to get adoption. Only crypto-native investors straightaway understand the ease and value in preferring tokenised stocks. For the majority of investors who are not crypto-native, tokenisation and blockchain are foreign concepts.

This is where companies are assembling a market in a language best understood by their retail, traditional investors. Robinhood has spent the past year making tokenised stocks a key offering for their 28 million funded accounts. It recently launched stock tokens on its native Robinhood chain for retail users who want to hold on-chain instruments without knowing or caring what chain they sit on.

Read: Building a Financial Supermarket

Although Robinhood’s wrappers raise no capital for anyone, they help the issuance side by addressing one of its pressing needs. Retail platforms like Robinhood train an audience to hold a tokenised share through a familiar app without touching a seed phrase. Such an investor is more likely to become a future buyer of a directly issued tokenised stock from the pipeline being built by Cantor and Securtize.

This pipeline removes complications from a follow-on offering and makes it as easy as a treasury operation. Raising debt is easier for companies because it lets them raise funds on an ongoing basis, offers a deep pool of buyers, including money market funds, insurers, and bond desks, and has a relatively lower impact on the company’s share price. While the ‘shelf registration’ rule introduced in 1982 allows companies to raise equity on a continuous basis, it remains less effective because a fresh issue of shares in a shallow order book can lead to large price swings. Tokenised share issuance closes these gaps and makes equity behave like debt.

What’s at Stake?

US companies raised approximately $207 billion of new equity in 2024 and $219 billion in 2025 through IPOs and follow-on offerings, per SEC data. When you include SPACs and other blank-check vehicles, the number goes up to $216 billion and $246 billion, respectively. Follow-ons alone brought in $175 billion each year, spread across 1,000 deals annually.

2026 has kept up the pace. Companies raised about $115 billion through IPOs alone in the first half, driven largely by SpaceX’s $75 billion debut in the second quarter. Follow-on issuance is holding steady at a $175-180 billion annual run rate, per the SEC.

Cantor’s own equities desk expects issuers to test tokenisation with 5-10% of an offering. Even with a conservative starting range of 1 to 2%, earnings could reach $220 million, depending on the fee percentage.

At 1% adoption, roughly $2.2 billion flows through on-chain rails every year, larger than the entire current stock of tokenised equity. At 5%, the fee pool approaches $330 million a year, or a fifth of JPMorgan’s 2025 equity underwriting revenue.

The tokenised layer is a market opportunity for whoever owns the rails. As the fee for underwriting IPOs compresses due to the unbundling of IPOs (Read: The Unbundled IPO), tokenised stock issuance works like a hedge for underwriters like Cantor that are trying to capture value at this new layer.

A Bet on Incremental Demand

Today, tokenised versions of major stocks trade less than 1% of the volume of their primary listings. In its current form, the adoption looks like capital being largely rerouted from existing crypto users. But there is an incremental pool that tokenised stock issuance taps into. A retail investor in Bangalore or Lagos with stablecoins and no path to a US brokerage account can still own a share in the same way a US resident does. The size of this pool hasn’t been counted yet. But the growth of tokenised stocks (four times in the last 12 months) signals what is possible.

The Art of Capturing Value

Cantor’s positioned to capture the utmost value here. Its number-one IPO ranking is built heavily on SPAC underwriting. A lot of other banks charge 5-7% of IPO proceeds to tour institutional investors and find demand that exceeds what the company can supply. It’s this business that the on-chain issuance would erode. Cantor’s business is not heavily reliant on roadshows. In fact, it was Cantor’s SPAC that took Securitize to debut at the NYSE at a $1.25 billion valuation. If tokenised issuance scales, Cantor profits through its stake regardless of who runs the offerings.

You can see Cantor’s value-capturing strategy across its other deals. Cantor custodies Tether’s Treasury holdings. It also co-founded the bitcoin treasury vehicle Twenty One Capital with Tether and SoftBank. The template is to take equity in the crypto counterparties it serves, so it can own a piece of any value that accrues in the future layer.

When a function commoditises in this industry, the fee moves to the adjacent layer that is not yet overpopulated with competitors.

In the corporate world, we saw pricing commoditise first through blockchain-enabled trading tools like perp contracts, prediction markets and tokenised stock wrappers. Markets now signal a company’s IPO price level before bankers open their books. Settlement is commoditising as we speak, with DTCC racing to tokenise. The Cantor-Securitize deal is an attempt to commoditise demand-manufacturing and make a banker’s job redundant for every round of fresh stock issuance.

Although I believe the bet on incremental demand is premature, its direction is right. Today’s on-chain buyer pool would not fund a mid-cap follow-on. But over time, those demand pools will be built with the help of centralised platforms like Robinhood that onboard millions of retail users and offer them these tokenised stocks. They will not need to know that there is an underlying chain powering all this. The more that happens, the higher the likelihood that companies will choose the tokenised issuance route.

Roadshows and ceremonies might still not die. They will perhaps retreat to where demand still has to be manufactured. For companies and sectors that don’t enjoy liquidity as deep as SpaceX’s and OpenAI’s on the blockchain, roadshows and ceremonies will remain relevant. But for cost efficiency and ease of raising funds, most companies prefer raising equity to borrowing.

That’s it for today. I will be back with the next one.

Until next time, stay curious,
Prathik

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. If you want to reach out to 170,000+ subscriber community of the Token Dispatch, you can explore the partnership opportunities with us 🙌

📩 Fill out this form to submit your details and book a meeting with us directly.

Disclaimer: This newsletter contains analysis and opinions of the author. Content is for informational purposes only, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

Paradigm, which is one of the largest dedicated crypto funds ever assembled, recently raised $1.2 billion to start backing startups in AI, robotics, and aerospace. They have also entirely scrubbed “crypto” from their website! Their thesis is that crypto was their first frontier, but there’s so much else happening right now that they can’t ignore it.

Framework Ventures also closed a $400 million fund in June to start investing beyond crypto, and they’re far from alone. Nearly every major crypto-specialist fund has started drifting towards broader themes and mandates over the past year. In Q1 2026, we only had eight new crypto-only venture funds launched, which is the lowest since 2020.

Today I will dig into whether crypto-specialised VC as a fund category is actually dying. If so, how does the shakeout map into the lifecycle of these funds, and what does it mean for crypto startups, which will now be competing for attention inside multi-sector portfolios?

The Specialist Fund Lifecycle

The reason crypto-specialised funds became a thing was that they were willing to spend time building the competitive advantage and were the only people willing to underwrite the risk at all. Understanding how Solidity contracts actually work and forging relationships with pseudonymous developers building in Discord channels was not something accessible to a growth equity partner at Tiger Global in 2017.

And to understand whether crypto VC is dying as a category, it helps to look at how specialised fund categories have lived before, because this has happened more than once in the past.

Between 2006 and 2011, climate tech went mainstream as an investment thesis, and VCs started raising dedicated clean energy funds for the same reason crypto VCs raised dedicated blockchain funds: thinking they spotted a generational technology shift before the generalists caught on, and wanted to build entire franchises around that conviction.

They poured in over $25 billion into clean energy startups and lost more than half of it. What’s Interesting is that the technology actually worked, and today’s clean energy market is enormous. It led to solar costs falling 85% over that period. But what VCs misinterpreted was that they applied the same software-company model and wrote $5 million seed cheques into companies that, in reality, needed $200 million of project financing and fifteen years to reach profitability.

MIT’s Energy Initiative ran a post-mortem and found that the venture model was fundamentally flawed for the sector. The specialist VCs who funded the experimental phase by taking the technical risk funded the early R&D and gave the sector the credibility to attract bigger capital, but once the technology matured enough for infrastructure lenders and project finance facilities to underwrite it, the specialists’ informational edge had evaporated.

SPACs played out a similar pattern. For context, a SPAC is a blank-cheque company that raises money through an IPO without having an actual business. It then later uses that cash to merge with a private company to take it public faster than a traditional IPO would allow. In 2020 and 2021, some investors saw this as a repeatable vehicle and built entire firms around them.

Chamath Palihapitiya had raised $1.6 billion in dedicated SPAC capital. But by 2022, two-thirds of 2021’s SPACs hadn’t completed a merger, and Chamath had to return the money he had raised. All of this happened in less than twenty-four months, which can give you a sense of how fast things change once the specialist edge disappears.

And there’s a big reason this keeps repeating itself across completely different industries. Carlota Perez documented it across 250 years of technological revolutions, calling it the techno-economic paradigm. She stated that every major technology goes through an early phase where only insiders understand it, and the people closest to the technology become its most valuable investors because they’re the only ones who can tell what’s real. Then the technology matures and starts integrating into existing institutions.

At that point, the insider edge that built these specialists doesn’t matter anymore because the asset class becomes legible to generalists with bigger balance sheets. Fred Wilson saw this coming for crypto specifically. He wrote about it in 2015, predicting that crypto would hit a major “financial break point” as it crosses from what Perez calls installation into the deployment phase.

That break point is hitting now, and you see what the deployment phase for crypto looks like. We had fintech like Stripe acquiring Bridge, and launching their own stablecoin chain. Institutions like BlackRock and Fidelity have launched their own tokenised money market funds. Even traditional payment giants like Visa and Mastercard are now building settlement layers on top of stablecoin rails.

These companies don’t need a crypto-specialist VC to explain MEV extraction and Validator economics because the specialist crypto knowledge doesn’t matter to them. What they need instead is regulatory approvals, distribution, and banking partnerships. Something that any other fintech would need to scale. Today, a generalist at Sequoia or Founders Fund can evaluate a crypto deal the same way they’d evaluate Stripe or Plaid.

The Barbell and the Drift

So if the specialist edge has dissolved, what actually happens to the funds that were built on it? Their fate depends entirely on the economics of their fund size.

See, venture capital has been splitting into a barbell for years. At one end, you have mega-platforms like a16z, Sequoia, and Founders Fund that can absorb entire asset classes as verticals inside their portfolio. On the other end are tiny cottage-industry funds that write small conviction-driven cheques into things they understand very deeply and can return the whole fund off a single breakout. Everything in between has become a kill zone, and that’s where most crypto-specialist funds sit right now.

A $500 million fund needs to generate roughly $1.5 billion in total exits to return 3x net to its LPs, so you can’t get there from seed cheques alone because no seed portfolio produces enough breakouts at that scale. And you also can’t compete for growth-stage deals against $5 billion megafunds that are willing to write $100 million cheques without thinking twice about it. For example, in 2025, Founders Fund alone raised 1.7 times what every emerging manager combined raised in the first half of the year. The capital is concentrating at the extremes.

This barbell is also why Framework Ventures and Paradigm look like they’re doing the same thing, but in reality they are very different. Framework sits at $400 million, which is too large to return the fund off a few seed bets and too small to compete with megafunds for growth deals. At that size, crypto alone doesn’t generate enough exits, so they had to broaden. But Paradigm, at $1.2 billion, is large enough to try becoming a multi-sector platform altogether, which is strategically different. In simple terms, the size of your fund determines which end of the barbell you land on, and that determines what options are available to you.

Even the crypto VCs that say they’re staying on the course have completely redefined what ‘crypto’ means. Dragonfly had raised $650 million in February, which was oversubscribed by 30%. Still, they have been explicit that non-financial crypto has completely failed, and the firm is betting exclusively on stablecoins and prediction markets. A16z’s latest $2.2 billion crypto fund was raised in May 2026, and it’s half the $4.5 billion they raised in 2022; not just that, Chris Dixon has even shifted his framing from crypto being a new computing paradigm to finance being the foundation for everything in the space.

What these firms now call ‘crypto-only’ investing is a bet on financial infrastructure built on blockchain rails, which is exactly what the generalist funds with bigger cheques will fund too.

A major force driving all of this is also the LPs’ behaviour. The Venture industry is currently in a DPI crisis where 2021-vintage funds have returned roughly 0.08x. And LPs who got burned during the 2022 crypto crash now have an obvious alternative in AI, which is absorbing 70% of global funding this year. So when your LPs have been sitting on dead capital for four years and see AI companies generate the returns they once expected from crypto, the fund manager has no choice but to create exposure to AI forcefully.

For crypto founders who are still building, this is concerning because it leaves a shrinking pool of investors who actually understand what they’re working on and are committed to backing them. The obvious response to the shrinking is to say, founders should just raise from generalists instead. And on paper that might sound accurate - Sequoia and Founders Fund can write bigger cheques, and they also bring in distribution that no crypto-native fund can match.

But there’s a problem with that. As AI companies are sucking up the majority of the dealflow today, a crypto founder inside a generalist portfolio will be competing for attention against that, and the deal would need to be exceptional just to get on the agenda, which is a very different game than pitching to a crypto-specialist who eats, sleeps, and breathes this stuff.

Another problem is the growth of the crypto ecosystem as a whole. Specialist VCs didn’t just write cheques but also funded the infrastructure layer that made the next generation of applications possible. Paradigm funded research into MEV, Dragonfly backed cross-chain tooling, and all this obviously doesn’t have the commercial returns on a deal-by-deal basis, but it builds the commons that the whole ecosystem runs on. A generalist fund will never fund that because they evaluate deals on standalone returns.

I think in a few more years, calling yourself a Crypto Investor will feel the same as calling yourself an internet investor. Crypto has now become plumbing, a set of rails that enable financial products. And you don’t build a fund thesis around the plumbing; you build on top of it. And if Perez’s framework holds, this is exactly what’s happening - Crypto is no longer the thing you invest in; it’s the infrastructure underneath the things you invest in.

But that doesn’t mean specialist crypto funds disappear entirely. As tokenisation and onchain securities like new categories keep emerging, there will be niches that generalists can’t touch, and small funds will keep forming around them every cycle. What’s dying is the current generation of large dedicated crypto funds that are too big to survive on niche crypto deals alone. The category will keep on reshuffling around the barbell, where generalists will take the big cheques, and small specialists take the frontier bets.

The early specialist funds of 2017-18 financed Uniswap and Ethereum, the tooling that made stablecoins work. But this era is changing; there are also cases where few of the most successful recent crypto projects, like Hyperliquid and MegaETH, have raised entirely through community rounds and zero-VC models. The specialist funds made crypto legible enough for generalists to move in, but there are also founders realising they can do it without them.

That’s all for today!

Vaidik

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It feels like a modern sickness, this premium we pay just to hold something from somewhere else. Until now, I looked at it as a globalised supermarket problem. Then I read the book, A Splendid Exchange by William Bernstein. Published in 2008. This book is about humans, so is every book.

This one follows it all the way down to a single piece of glass, carried across a Stone Age sea. That’s where we want to start.

Twelve thousand years ago, long before the invention of the wheel, the first writing, or the concept of a sovereign state, human beings were already risking their lives to trade. Deep within the dark recesses of Greece’s Franchthi Cave, archaeologists unearthed shards of obsidian. It is a razor-sharp, volcanic glass that could only have come from the island of Melos, over a hundred miles away across the open waters of the Aegean Sea. Why did these early humans risk drowning in primitive boats just to fetch shiny black rocks?

We know where it came from because obsidian keeps a secret. Bernstein notes that atomic fingerprinting can trace these obsidian flakes as they travel thousands of miles from their volcanic origins.

Every volcano lays down its glass with a slightly different mix of atoms, like a chemical signature. You cannot fake it or lose it. The archaeologist Colin Renfrew followed those signatures across the Fertile Crescent and found the pattern that gives the whole game away. Two hundred and fifty miles from an Armenian source, half the cutting stone in a village was obsidian. Five hundred miles out, it was two per cent. The farther the glass travelled from the mouth of its volcano, the rarer and dearer it became.

I find this almost mind-blowingly beautiful. A sliver of glass, sharper than a modern scalpel, moving hand to hand across a roadless world, each village keeping a little and passing the rest along. A peer-to-peer network running eight thousand years before we decided we invented the idea.

Trade is older than farming and older than the written word. It might be the oldest thing we do that isn’t eating or sex.

Why did we do it? Because we are a little bit insane.

Pepper grew on one coast of India, and nowhere the Romans could reach. To get it, ships had to catch the monsoon at the right week, run open ocean with no sight of land. They trusted the wind to carry them home, hoped for it, but it turned and drowned plenty of them. The ships went, again and again, because a sack of peppercorns bought at the source came back to Rome multiplied many times over. This might sound silly for all the effort, but a rich Roman just wanted his meat to taste of somewhere far away.

Pliny grumbled that pepper had no real merit beyond its bite. Romans crossed the earth and paid for it by weight, like gold. When Alaric and his Goths finally had Rome by the throat in 408, part of the ransom they demanded was three thousand pounds of pepper. The city that ruled the world bought its life partly in spice.

When Alaric and his Goths finally had Rome by the throat in 408, part of the ransom they demanded was three thousand pounds of pepper. The city that ruled the world bought its life partly in spice.

I have to stop here because this one is personal. That coast the Romans were dying to reach, the one place their pepper grew, is my coast. I’m from Calicut, on the Malabar shore, the pepper capital of the medieval world. The black spice Alaric took as ransom for Rome grew in the hills behind my hometown, cheap as weeds, close to free where it stood.

Everything that made it precious got added on the way out, by distance and danger and the men who owned the ships.

Bernstein tells this story from the buyer’s chair. He talks about how ancient Rome, old Europe, and big markets always wanted rare things from far away. Funny to read, the view from here is uglier. Not to be all emotional about it, but markup was never really the reward for the risk. It was the prize for controlling the gap between the source and those who really wanted it. And sooner or later, the people who controlled the gap will come and take the source itself. In 1498, Vasco da Gama’s ships reached the coast, and he sailed back a few years later with cannons. But the coast just got a new owner. For a thousand years, the world paid huge premiums for goods from far away. When the buyers finally reached the actual source of those goods, they brought warships to take control of it by force.

Setting the Indian textbook aside and going back to Bernstein, he has a chapter he calls “The Captives of Trade.” The same ships that carried the pepper carried people. Between about 1200 and 1500, Italian merchants became the richest slave traders on earth, buying human beings on the shores of the Black Sea and selling them into Egypt. People far away would pay money for them, and the middlemen who controlled the narrow routes kept the extra profits.

Trade routes also acted like an early version of the internet. They carried things that moved much faster than regular cargo, like new ideas, religions, and deadly diseases. For example, religions like Islam and Buddhism spread across the world along the exact same paths used by merchants. The roads moved silk and spice, and they moved gods. Then, in 1347, the network delivered its most efficient shipment ever. The Black Death rode the same Silk Road caravans and Genoese ships that carried the luxuries, and it killed something like a third of everyone between China and Ireland. Bernstein calls the plague a stowaway, and the word is perfect if you ask me. Mind-virus and the actual virus riding along beside trades, unpriced.

For a while, we thought crypto was that. We really believed, a few years ago, that these networks were the modern Silk Road (not that one) and that the ideas riding them, open money, code instead of banks, ownership without a landlord. We said it would spread like a faith and rewire how the world thinks about value. Tough to believe now, and reading Bernstein is part of why.

I see crypto as the pepper, not the plague, in this set-up. Exciting, a niche luxury product traded by a small group. Most of the planet has never been touched and is not being thought about.

Then what is the thing that spreads like Islam down the incense road right now? It’s the dollar, slipping into every weak-currency country in the world through a stablecoin, so that a shopkeeper in a collapsing economy saves in someone else’s money. And the thing spreading like the Black Death is whatever is loose in the models now, the synthetic flood, the machine-made everything. Crypto flatters itself that it is the contagion. On the evidence, it looks like a spice. Is that a win-win?

What crypto did keep, perfectly, is the old shape. It promised to kill the markup, to cut out the merchant and the king and the temple and let value move hand to hand like obsidian. All we could end up doing was creating new markups, such as for early investors and token issuers. Regular retail investors take all the financial risk, and when markets crash, they lose their money while the new middlemen keep the profits.

William Bernstein trained as a neurologist and then became one of the most trusted investing writers alive. He once said that all the things that make us human make us terrible investors, and you have to learn what they are and how to avoid them. The fear, the greed, the herd pull, the certainty/uncertainity. A Splendid Exchange is the long proof of that message.

The people who win in investing are the ones who stay completely calm when everyone else panics or gets greedy. Money always moves in one direction, which is away from normal, emotional people and into the pockets of the few who control their feelings. Holding power is about controlling your own humanness. The small group of people at the top stay rich simply because they keep a clear head while the rest of the world loses theirs.

This is where part one leaves me, halfway through a book about how trade built the world. The stone changes. Whether it is obsidian, pepper, silk, or crypto tokens, the specific item being traded doesn’t matter anymore and that’s evolution. We realised that tokens and all the shiny things were a distraction from the system, its flaws, and its corruption.

Being human is expensive, and someone standing at the narrow point has always known it. The second half of the book is where that machine goes industrial, where companies get their own armies and free trade gets a philosophy, and the whole thing scales up into the world we live in now. That’s part two. I will look more closely at the insane psychological wiring that drives us. Until then, hold this thought.

—Thejaswini

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Two decades ago, I used to accompany my mom to the vegetable market. I’d try to help by picking a few tomatoes and some onions. They never made it to the final basket. She would quietly set aside my picks and choose her own. Each one that made the cut was pressed, turned over, held up against some standard only she could see.

For most people, grocery shopping is a chore. For the chef in my mom, it was a high-precision job. The right tomatoes meant the curry would taste the way she intended. Choosing wasn’t merely a step before cooking. It was where the cooking began.

That’s the thing about shopping, it’s not one activity. Some of it we’d delegate to anyone who’d take it. Some of it we won’t hand over even to our own kids. And any attempt to delegate how we buy things has to start by understanding which is which, not by assuming that automated robots are the default solution to everything.

In today’s guest op-ed, Anderl takes apart the “give the agent a wallet” thesis and shows why paying was never the hard part of shopping.

On to Anderl’s story,
Prathik

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There is a line going around the AI and crypto world right now: give an agent a wallet, let it shop for you. The ultimate use case. It sounds clean, it sounds like the future, and it still doesn’t feel quite right. The mismatch is worth unpacking because it shows that the line confuses the hard part of shopping with the easy part and then puts the easy part at the centre.

Let’s start with shopping itself, not with payment.

Shopping Splits into Two Things

Shopping is really two activities that today only look fused. One is search, the other is judgment. Search (gathering, filtering, comparing, pre-sorting) is mechanical and delegable, almost entirely. Judgment (is it any good, does it suit me, do I trust the seller) is the part that a human is attached to.

It is measurable that search is already migrating. Adobe Analytics reported a roughly 4,700% rise in traffic from generative AI referrals to US retail sites between July 2024 and July 2025. The wallet thesis now quietly assumes the agent takes on both search and judgment. This is where the sleight of hand sits. One can be handed off, the other only under conditions, and sometimes not at all.

Judgment Splits Again

The interesting move is that judgment isn’t monolithic either. It breaks into two parts. One is evaluation, which involves checking options against a utility function. The other is authorship, where you set that utility function in the first place: which dimensions count, how they are weighted, which values bind, and what “good” ends up meaning.

Evaluation automates. Authorship doesn’t. And it doesn’t sit as a single gate up front that you pass through once. It runs as a thin thread through every layer. Conformance is about which specifications matter to you. Quality is about whether a broken zipper is a deal-breaker or beside the point. And the choice of merchant turns on which values bind you. Every layer does (human criterion × agent evaluation). In every case, what automation eats is the evaluation half. What’s left is the authorial half.

This has a consequence that everyone underestimates who thinks the human writes one spec sheet and walks away. You can’t. It’s one of the most robust findings in decision research. Since Paul Slovic’s work on decision-making under risk, we speak of constructed preferences. The American professor and psychologist found that we don’t carry a finished liking inside us that we simply retrieve; we form it in the act of choosing (Slovic 1995; Lichtenstein & Slovic 2006). The evidence is preference reversals. Normatively equivalent elicitation methods like choosing versus pricing produce systematically different rankings, violating the basic axiom of rational choice. Ariely, Loewenstein and Prelec (2003), in their work on coherent arbitrariness, showed that even an arbitrary number (the last digits of a Social Security Number) anchors willingness to pay for familiar products, and that the effect disappears neither with experience nor through market forces. The “stable preferences” picture is largely an illusion of order.

The realistic interface is therefore not the spec sheet but an iterative one. The agent surfaces, at each layer, the decision a criterion needs (”you said durable, at what premium does durability stop being worth it?”), and the human writes exactly that.

The Real Axis: Chore or Pleasure

Now, the distinction that orders everything. We like to talk about “standardised” versus “individual” products, as if it were about specifiability. It isn’t. The real axis is different. On one side, choosing is a pure chore. On the other hand, choosing is part of the point.

For a commodity like printer paper, batteries or the recurring reorder, the act of choosing has zero consumption value. Nobody enjoys deciding between two identical toner cartridges. That’s why commodities are the natural home of full delegation: nothing is lost when the agent silently reorders the right thing.

With pleasure goods, it’s the reverse. The wine, the piece of furniture, the coat, and the book. Here, choosing is part of the good itself. Whoever hands off the judgment not only saves effort but also destroys part of what they wanted to consume. And that holds even if the follow-up questions were free. You wouldn’t want to delegate it even at zero friction.

With pleasure goods, the agent therefore doesn’t withdraw but should switch roles. From buyer to scout. It still does the search, the shortlisting, the spec matching, the merchant verification, and the pulling of recurring weaknesses out of a thousand reviews. It narrows 200 to 5. And then it stops. The human savours the final choice.

The Friction Trilemma

“But the agent could just ask for my criteria.” It could, and that’s exactly the annoying variant that people resort to doing themselves. Worse, interrogating degrades the choice. Wilson and Schooler (1991) had participants rate jams. Those asked to analyse the reasons for their feeling beforehand ended up with rankings that matched expert judgment less well than the control group’s. In a follow-up study, people who spelt out their reasons chose different posters and were less happy with them weeks later. Articulating directs attention to what is easy to put into words, not to what actually carries the preference. Taste is recognised, not verbalised.

So there is a trilemma:

Interrogate. Faithful to your current self, but high friction, and it can even worsen the choice.

Infer from the past. Low friction, but it locks you into your past self and shuts down discovery. You only get more of what you already want.

Judge yourself. Full autonomy, full labour.

There is a fourth mode that avoids the bad corners: recognition instead of interrogation. “Show me three, I’ll point to one.” Low friction and accurate at once, because it doesn’t require naming criteria in the abstract that you often can’t name. Here, the most famous study on choice overload helps too. Iyengar and Lepper (2000) sold jam at a tasting stand. With six varieties, far more people bought than with 24. Still, the effect is disputed, and honesty requires saying so. A meta-analysis by Scheibehenne and colleagues (2010) found, averaged over many studies, almost no general choice-overload effect. A second one across 99 studies (Chernev, Böckenholt & Goodman, 2015) showed that it appears only under certain conditions, such as high complexity, a hard decision, and an unclear preference. Telling is the original authors’ self-criticism. Perhaps, faced with 24 varieties, customers simply didn’t have enough time to “determine their preferences”. The line where autonomy actually lives is the one between “the agent applies my criteria” and “the agent invents them from my history”.

Back to the Wallet

With all that behind us, we can finally name why the wallet line sounds off. It throws together three things that are separable: who decides, who executes and who holds the funds. “Give the agent a wallet” answers only the third, and that only matters if the first falls to the agent, too.

Three cases. Human decides and pays themselves. Here, the agent doesn’t pay but remains a scout. In the second, the human decides and delegates execution (”yes, buy that one”). Now, the agent runs the checkout, but it needs no custody of money, only a narrow, revocable authorisation for exactly this approved purchase. Only in the third case, when the agent decides and pays autonomously, with no human at checkout, does the wallet itself become load-bearing.

And here it gets interesting because the payments industry built exactly this separation in 2025. Not custody, but authorisation. The Agentic Commerce Protocol, developed by OpenAI and Stripe, issues a “Shared Payment Token” bound to a single merchant, with a fixed amount, that is time-limited and single-use. Mastercard’s Agent Pay (April 2025) issues “Agentic Tokens” scoped to a specific agent, a merchant scope and a consent policy. The agent never sees the raw card number. Google’s Agent Payments Protocol (AP2, September 2025) even cleanly separates an Intent Mandate (what the human wants) from a Cart Mandate (what the agent proposes to buy), both as signed verifiable credentials, which is exactly the authorship-versus-evaluation axis cast in cryptography. Visa’s Trusted Agent Protocol (October 2025) takes the same route. None of these approaches hands the agent funds. All of them hand agents a narrowly bounded authority. The industry independently confirms the article’s thesis.

So where does the agent-owned wallet become native? Precisely in the commodity tier and in the machine room. The genuinely strong crypto cases don’t lie in consumer shopping. The x402 protocol, backed by Coinbase and Cloudflare, fills exactly the gap that card rails don’t close: fully autonomous agent-to-agent payments with no human in the loop, billed per API call, around the clock. Over 100 million transactions in the first months. Mastercard, in turn, announced “Agent Pay for Machines” for high-frequency, low-latency micro-payments between machines. That is infrastructure for a machine economy, not shopping. So the thesis isn’t wrong. But its importance is inverted. The wallet of its own becomes load-bearing where the goods are most interchangeable and the amount per transaction is often the smallest.

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Where the Wallet Really Belongs

This explains, in passing, why crypto has shifted its centre of gravity over the past two years, away from the consumer-driven culture of liberation, toward rails for companies: stablecoin settlement, tokenisation, and institutional infrastructure. That isn’t a turn away from agent shopping but is a homecoming to the one tier where the funds-holding wallet actually fits. Corporations are its anchor tenants for structural reasons. A procurement department is the institutionalisation of “choosing is a pure chore”. Its purpose is to replace taste and gut feeling with specification, price, reliability and contract terms. Procurement is agentic shopping, carried out by rule-following humans. So the agent wallet teaches corporations no new behaviour, and instead automates one they perfected long ago.

You can see it in an entire industry layer built for exactly this. Many companies have outsourced the purchasing of C-items, such as office supplies, to specialised platforms, including Mercateo and Amazon Business. Their promise is not the lowest price. It’s the lowest effort: one catalogue instead of twenty suppliers, one invoice instead of many. The company accepts a slightly higher unit price and saves the process costs, which for C-items often exceed the value of the goods themselves. The agent attacks exactly this logic. It pushes the ordering effort toward zero, while simultaneously searching the fragmented market nobody had time for before. What remains for the platforms is only conformance: approved suppliers, a clean invoice, protection against counterfeits. This verification, further down, turns out to be the real bottleneck.

The recommendation is therefore more precise than “wallets for firms instead of consumers”. It reads: ‘match the instrument to the tier’. The autonomous, custodial wallet (the agent decides, holds, pays) has its market in the procurement of standard goods and in machine-to-machine payments. The buying there is high-volume and repetitive, driven by specifications, so largely B2B and M2M. The consumer side, by contrast, wants authorisation instead of custody, meaning a narrowly bounded, single-use token on existing rails, only when the human approves a purchase. “Give the agent a wallet”, as a consumer headline, therefore, aims at the weakest slice. The product’s actual bridgehead is the machine room of companies.

A caveat that stays honest. Corporations don’t buy only commodities either. They have their own non-delegable tier, just one driven by consequence rather than pleasure: the choice of a law firm, an acquisition target, or a strategic supplier. There, the human stays, and the autonomous wallet has as little business as it does with the consumer’s wine.

The rule is domain-independent. The wallet rides the commodity layer wherever it sits, and that layer is simply the largest and densest inside companies.

What the Bottleneck Really Is

Paying was never the bottleneck. Moving money is solved, several times over. The two real bottlenecks are different.

One is trust in the inputs. Automating judgment is only a gain if the data ground holds. If it doesn’t, a judging agent is worse than a sceptical human. It launders manipulated signals at machine speed. That this ground is shaky today is official. The US trade regulator, the FTC, issued a rule in 2024 (effective 21 October 2024) banning fake reviews, noted that such fakes are widespread, and explicitly named generative AI as a tool that eases their mass production. By late 2025, the first warning letters followed, with penalties of around $51,744 per violation. Add the physical counterpart. Per OECD/EUIPO (2025), global trade in fakes amounted to roughly $467 billion in 2021, or 2.3% of world trade, and in the EU to 4.7% of imports, with clothing, shoes and handbags at the top. Pleasure goods, of all things. Anchored product identity, verifiable reviews, a verifier independent of the seller, and provenance records at the unit level (as the EU anti-counterfeiting directive and the US DSCSA have long required per pack in pharma) are the precondition that tips judgment automation from dangerous to useful.

The other bottleneck is authorship. Everything downstream of a defined wanting becomes increasingly automatable. Defining the wanting stays human, not out of nostalgia but structurally. To automate it, the agent would have to want for you, and a wanting fabricated for you is not yours.

Give the agent a wallet, and you’ve solved the easiest part. The interesting part is making judgment partly and safely automatable, and leaving the human where they belong: as the author of the criteria and as the one who savours the final choice.

For Anyone Building Marketplaces

One consequence to close, for pleasure goods. Once agents commoditise sourcing, the goods are findable everywhere. Then your product is no longer the goods. Choosing is. Make yourself maximally legible to the scout agent (verifiable provenance, clean data) so it routes the human to you. And on top of that, occupy the one thing automation can’t take: the discovery that widens taste rather than confirming it, and the pleasure of the final decision. Hand sourcing to the agents. Build your business around the better choices.

That’s all for today.

Until next time,
Anderl

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We will be back with another guest essay soon.

P.S. This piece was originally published here.

We will be featuring good writing and writers we love from time to time. If you have recommendations, send them our way.

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. If you want to reach out to 170,000 subscriber community of the Token Dispatch, you can explore the partnership opportunities with us 🙌

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Disclaimer: This newsletter contains analysis and opinions of the author. Content is for informational purposes only, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

Welcome to Edition 13 of The Reading List — your fortnightly antidote to the noise. Every two weeks, I share my favourite reads across crypto, finance, technology, culture, and beyond. I also share what I’m watching and reading.

What I’m Watching and Reading

I am on a book break this week. I have not quite found the next one yet, and I would rather wait than begin something out of obligation.

I did finish I Will Find You, the eight-episode mini-series. It moves quickly and, unusually for an adaptation, does not feel like it is merely borrowing a book’s reputation. It knows when to keep things moving. If you want an easy-yet-thrilling watch, I’d strongly recommend watching this one on Netflix.

This weekend is for Christopher Nolan’s The Odyssey. Nolan remains, in my view, one of the few filmmakers whose intellectual ambition is matched by control over the actual filmmaking. The film was shot entirely with IMAX cameras, which makes the absence of a proper IMAX screen near me especially annoying. But who knows? I may travel 300 miles at the end of the month to watch it again on the screen it was made for.

Got any recommendations for nice watches or reads? Write to me?

The Fortnight That Was

The past fortnight followed a grim, but familiar rhythm. The fragile US–Iran ceasefire gave way to another round of American strikes, Iranian retaliation against US-aligned Gulf states, and renewed anxiety around shipping through the Strait of Hormuz. The seesaw continues; the difference is that markets are no longer treating each headline as a fresh apocalypse.

A new strike only matters when it threatens oil movement, damages regional infrastructure, or makes shipping through the Hormuz less predictable. That is why crude has remained the only expression of the conflict. WTI is up 18.9% in the past fortnight, while Bitcoin is up 2.1%, the S&P 500 is down 0.7%, and the dollar is broadly unchanged.

Zooming out gives a better picture. Since the start of the conflict on February 28, Oil is up 27%, the S&P 500 gained 8.3%, while Bitcoin is 5.5% in the red.

Nevertheless, our team at The Token Dispatch has been monitoring the infrastructure progress underway despite all the global macroeconomic drama.

What We Wrote Last Fortnight

Over the past fortnight, most of our stories focused on one specific question: when an asset, a network, or a financial product becomes more useful, who controls the infrastructure around it and who captures the value?

Vaidik’s two-part series on compute followed that question from the GPU itself to the market being built around it. In Part II, he looked at the uneasy logic of lending against hardware that depreciates faster than the debt used to finance it. In Part III, he mapped the emerging pricing, clearing, verification and settlement layers that may eventually turn compute into a real capital market.

I wrote about Robinhood’s attempt to build a financial supermarket, where the chain is not really the product and serves as connective tissue among its dozen existing businesses. In Making Capital Reallocate Faster, I explored what changes when capital can move and reprice faster than the institutions designed to contain it.

We also examined the ownership question from two directions. What Does a Token Holder Own? asked whether token holders retain any meaningful claim once crypto protocols begin raising conventional equity. The Aladdin Playbook looked at the other side of that bargain: how BlackRock’s BUIDL is becoming increasingly load-bearing collateral for on-chain finance, and what that does to crypto’s claims of independence.

Thejaswini took a sceptical look at the incentive systems behind two very different networks. The Intelligence Arbitrage asked whether Bittensor’s capital allocation mechanism rewards useful AI work or simply whichever subnet can sustain the strongest token bid. And Aave’s Extraction examined the price users may be willing to pay for convenience: a fixed yield, fewer decisions, and a familiar interface.

We have got more lined up in the coming weeks. Until then, here’s a reading list to give you good company.

Crypto & Tech

• Robinhood’s Chain and Digital Asset Strategy: Insights4vc breaks down Robinhood’s push to build its own chain and tokenised-asset stack.

• Dear Robinhood, Please Do Not Build: Artemis argues against the app-chain land grab, making the case that Robinhood should plug into existing rails rather than fragment liquidity with its own chain.

• Is trade.xyz Existential to Hyperliquid?: A close look at whether the emerging venue trade.xyz genuinely threatens Hyperliquid or whether the incumbent’s liquidity and network effects hold.

• The Always-On Economy: Pantera argues that programmable, 24/7 on-chain markets are quietly rewiring finance into a system that never closes.

• TradFi Doesn’t Want DeFi, It Wants Blockchain: a16z crypto argues incumbents are adopting blockchain rails while sidestepping DeFi’s permissionless ethos.

• How Financial Systems Become Fluid: On how tokenisation and interoperable rails dissolve the settlement frictions that keep today’s financial system siloed.

• Inference in Capital Markets: Galaxy maps how AI compute — GPU futures and inference capacity — is being financialised and brought on-chain as a new crypto-native capital market.

• Privacy Tokens: Chamath makes the case that privacy is becoming core financial infrastructure rather than a fringe feature (behind paywall).

• Securitize Jumps After Partnering With Cantor: Securitize shares popped after the tokenisation firm tied up with Cantor Fitzgerald, another sign of TradFi leaning into on-chain assets (behind paywall).

• The Decade Ahead: Delphi Ventures lays out the three macro forces it’s betting on for the next decade, from synthetic intelligence undercutting labour to the US unwinding the order it built, with crypto positioned as the parallel system (behind paywall).

Finance & Economy

• How Artificial Spotify Streams Broke a Kalshi Market: How manufactured Spotify plays distorted a prediction market on streaming numbers, a case study in how thin the line between market and manipulation can be.

• Citrini on surviving a drawdown: Ahead of CPI, Citrini offers important advice on treating the portfolio as its own position, knowing your tilts, not averaging down just to fix your cost basis, and using an early drawdown to study how you react rather than fighting your own psychology.

• The Ozempic Economy: How private markets are repricing food, fitness and pharma around GLP-1 drugs, and where the capital flows next.

• The Everything Chart: Pieter Levels stitches the macro trends he thinks explain almost everything into a single, attractive one-glance chart.

• Circle and Coinbase’s Stablecoin Squeeze: JPMorgan warns that USDC’s economics face a “prisoner’s dilemma” as distribution deals like Hyperliquid’s siphon reserve income away from Circle and Coinbase (behind paywall).

• Why China Got Rich and India Didn’t: David Oks argues China’s miracle rests less on freeing markets than on decades of hard social modernisation and human-capital investment that India never underwent.

AI & Innovation

• Apple Sues OpenAI: Ben Thompson reads Apple’s trade-secret suit against OpenAI as less about stolen secrets than about a company furious at losing talent and unnerved by an AI shift that threatens the iPhone.

• The Workers Left Behind by China’s Robot Drive: A dispatch from China’s factory floors on the workers displaced as the country races to automate (behind paywall).

• XPeng Aims for 1,000+ Robots a Month: The EV maker plans to mass-produce humanoids and roll them out globally, another sign the humanoid race is accelerating (behind paywall).

• The AI Superforecasters Are Here: Scott Alexander weighs fresh evidence that AI models can now match or beat expert human forecasters, and what that means for judgment work.

• Robotics: Leveraging Human Labour: ARK sizes the shift from fixed-task automation to general-purpose humanoids at a ~$26 trillion opportunity as robots learn to generalise across tasks.

• Latent Space as a New Medium: Kevin Kelly reframes an AI model’s latent space as a creative medium in its own right.

Culture & Beyond

• What Is Web 2.0? Tim O’Reilly’s 2004 essay that coined the term for a paradigm shift is worth revisiting as we argue over what the next one (call it Web 2.5) really is.

• People Reading Was Actually a 500-Year Glitch: Priyanka Desai argues that post-literate is really pre-literate. As AI drops the cost of flooding the zone to zero, deep reading collapses, and a small “clerical class” that still reads inherits a priest-like authority over everyone who delegates it.

• The Postliterate Age: The Atlantic’s cover story on a deepening reading crisis and what a society that stops reading deeply stands to lose (behind paywall).

• The Decline of Deviance (Part 1): Adam Mastroianni on why people seem to break fewer rules and take fewer risks than they once did.

• The Decline of Deviance (Part 2): The follow-up on what a more conformist culture costs us, and whether the trend can reverse.

• Boomermaxxing: The Lost Art of Being Unforgettable: A playful argument for the older-generation habits that make a person genuinely memorable in an age of frictionless, forgettable interaction.

• Ancient Egyptian Princesses Were Powerful Weapon Users: A new analysis suggests that royal women in ancient Egypt were trained in arms, complicating longstanding assumptions about who wielded power.

• Permanent Daylight Saving Is Bad for Your Health: Scientific American on why the science favours permanent standard time over permanent DST for human health.

• A Super-Earth’s Leaking Helium: Helium escaping a super-Earth exoplanet could be the first hint of a surprisingly complex atmosphere.

• Silicon Valley Has a Science Fiction Problem: Ali Rıza Taşkale argues tech titans claim sci-fi inspired them while stripping out its politics and grafting their own worldview onto stories that imagined better futures.

That’s all for this fortnight. Catch you in the next edition.

Until then, happy reading!
Prathik

P.S.: Want to recommend interesting literature? Write to me, and I shall include them in the next edition 👇🏾

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Kalshi just launched markets on GPU compute prices, meaning you can now bet on where GPU rental costs will be three months from now. And for the first time, compute has a forward curve. In Part I & Part II, I covered how compute is becoming tradable and how it is being financed underneath. Today, I want to complete the picture by walking you through every layer of the market forming around it.

Each layer of compute being built is either held by the oldest financial institutions or crypto-native startups that didn’t even exist a few years ago. We’ll map each layer to see where crypto infrastructure is genuinely load-bearing versus where traditional players have an advantage. Let’s dig in!

The Pricing Stack

Let’s start with price. All commodity markets in the world begin here because everything that comes after futures contracts and lending covenants gets settled against this one reference number.

In oil, for instance, the number is published by firms called price reporting agencies. The largest of these agencies today is Platts, which is now part of S&P Global. What Platts basically does every day is survey traders and refineries, collect the prices at which crude is sold, and publish a single reference price. This price is then used in all futures contracts and cargo deals. Warren Platt started this back in 1909 as a trade magazine with $2,500. And over a century later, Platts remains the dominant reference price for physical oil.

Platts survived for a century because once a benchmark is set for the first generation of contracts, switching away from it later becomes almost impossible. You would be surprised, but even Platt’s most vehement detractors still use it because they have legacy contracts and other derivative instruments based on Platts, and adopting any other price source would create a basis risk across their entire book. The benchmark is more permanent than even the companies trading around it.

In Compute Markets, two firms are racing to become the Platts of compute. The first is Silicon Data, which I introduced in Part I. It collects rental-price data from over 30 GPU cloud providers, covering 3.5 million data points, and publishes a daily index, called SDH100RT, on Bloomberg terminals. CME has announced that its compute futures will settle against this index.

The second firm is Ornn, which, instead of surveying providers on what they charged, only counts prices from transactions that actually completed on its own exchange venue, where over 400 data-centre operators and AI companies trade. This is very different from how Silicon Data does it because benchmarks built on surveys can be gamed. In oil, traders have manipulated Platts assessments for decades by submitting inflated quotes during the assessment window to push prices in directions that benefit their positions.

Ornn’s approach of using only completed transactions makes it far harder to pull off, and crypto infrastructure gives an edge: if those transactions settle on-chain, the raw trade data becomes verifiable to anyone who wants to check the ledger. You never have to trust that the benchmark provider filtered the data correctly.

This model of verification does not exist anywhere in traditional commodity markets and could help make compute benchmarks more trustworthy. Ornn has over 400 data-centre operators on its platform and has also announced an integration with ICE to settle their compute futures on Ornn’s index.

Now, the exchange side of this layer is barely developed. The first-ever compute swap was cleared in December 2025, and that too on Ornn’s own venue. The biggest reason is that 78% of compute supply is still concentrated among the four hyperscalers, and there is no standardised, tradable unit. A rating system for GPU clouds was tested that grades providers on networking quality and uptime. Because buyers are willing to pay significantly more per GPU-hour for higher-rated clusters, the annual revenue difference between the lowest and highest tier on the exact same hardware can reach up to $15 million. This tells you how far off compute still is from being a fungible commodity where one unit equals any other.

DePIN platforms like Akash and io.net sit on the other side of it. They provide spot markets where compute can be traded at hourly rates, for a fraction of what hyperscalers charge. But the problem with these is that they are not yet very reliable. A developer who had tested four DePIN providers had two of them shut down on him in just eight months of setting up. But trades here are visible and on-chain, so if DePIN continues to grow, these platforms could become another raw source of verifiable price data, making compute benchmarking more credible.

The Intermediary Stack

Once the pricing is in place, someone then has to sit between the GPU owner who wants to sell capacity and the AI lab that wants to buy it. In commodity markets, these middlemen are called dealers. Their job is to take a custom request on one side and match it with the available supply, by managing the price risk in between. In compute markets, the dealer layer has split into two tiers with completely different economics.

At the top, we have the hyperscalers who charge a hefty premium for immediate GPU capacity. For example, Google’s deal with SpaceX runs at $920 million a month for 110,000 GPUs; that pricing is roughly 4x what a typical neocloud will charge for the same 5-year contract. The premium is for getting the capacity now rather than in eighteen months.

Google needed capacity immediately to meet its surging demand for Gemini Enterprise while its own data centres were still being built, and that urgency is what creates the 4x premium. Only a handful of companies can serve this tier because offering large-scale compute on short notice requires owning the hardware outright, without carrying any debt against it.

Next below the hyperscalers, we have the commodity tier, where all the neoclouds and brokers compete on price. Neoclouds have to cover every cost from GPU-hourly revenue alone. This means everything from data-centre construction to daily operations, and for many of them, the unit economics just don’t work without raising additional capital.

Brokers, on the other hand, run live order books without owning any hardware. The biggest example of this currently is SF Compute, which manages over $100 million in GPUs and processes orders as low as $0.25 per GPU-hour from clusters that would otherwise sit idle.

And all the financial infrastructure being built today for Compute is to serve this same commodity tier. Because if you are Meta and your customer is Google, you don’t need a futures market or a clearing layer; Google’s credit is sufficient to make that deal happen. But if you are a neocloud borrowing against hardware that depreciates each year, you need to lock in revenue months in advance and prove that the hardware is performing as promised.

Once a trade is matched, there are two more things to take care of. First, someone has to guarantee that the trade will settle regardless of any party defaulting, which is what a clearinghouse does. Second, someone has to prove that the physical assets exist and are not encumbered. This is done through custody and verification. But in Compute, the clearinghouse does not exist yet because the futures themselves are not live.

For verification, we discussed in Part II how a unique cryptographic key can be used to prove that the chip is genuine. But since compute is a flow good, verification cannot just be a one-time inspection, as it is for metals. GPUs switch workloads every hour, so verification must also be performed continuously. This is why on-chain infrastructure becomes critical here: it allows the asset to self-report its status directly to the ledger, where it can be verified instantaneously.

At the bottom of all this is the Lending layer built around the same collateral bifurcation — whatever the lender actually underwrites as collateral is completely different depending on which tier the borrower sits in. With a hyperscaler, the lender is not really underwriting the GPU. It is underwriting the revenue contract behind it, which is essentially project financing. But with a Neocloud at the commodity tier, the lender doesn’t have that luxury. It has to underwrite the hardware itself and explain why you need everything else above in the stack being built.

Every commodity market that has gone through this cycle has eventually concentrated most of its durable value not in producing the commodity but in the companies that control the financial instruments around it. The oil majors built the wells and the refineries, but the exchanges and the clearing firms ended up with the better economics because they earn on volume and do not have to worry about the price moves.

Compute is still early in that transformation, building all of its financial infrastructure at once, some of it on traditional rails and some of it on-chain. The on-chain part comprises three distinct layers. First is pricing: on-chain transaction settlement makes benchmark data verifiable without trusting that the provider filtered the numbers correctly. Next is on-chain verification, which gives a shared ledger combined with the GPU’s own cryptographic identity, allowing it for continuous, real-time proof that the hardware is genuine and unencumbered.

And lastly, the settlement layer, where stablecoins are the only payment rail that works for AI agents buying compute per inference call, since it doesn’t require them to have a legal identity. At every other layer of this stack, the lenders and traditional infrastructure have an advantage.

That’s all for today!

Vaidik

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That’s how the platforms extracted, taking the decision away. Couch lock – one of my favourite words from Tim Wu’s Age of Extraction.

Can’t pick stock, sure, index funds, S&P…

Not sure about lending. Call it a savings account, be proud.

They all just charge you for removal. Removal of decision-making, also sometimes the removal of the best benefits. People didn’t care.

What DeFi did was add. Which chain, which pool, what rate, when to move, where’s the bridge, is this even the real app or made with Claude Fable before July 12? Aave has 2.5 million users and six years of history. Revolut has 65 million users. Is it fair if we say Aave has to be the smarter one here?

Between January and July, the rate on Aave’s USDC pool wandered between roughly 2% and 9%.

Bouncing around is normal in DeFi. You watch the rate go up and down, and you move your money whenever it makes sense.

But that structure is unsellable everywhere else. Neobanks can’t explain to a user that the rate is set by borrowing demand and could collapse to 2% when it clearly advertises a savings account. People don’t put money in chaos. That is why people never start using crypto apps, let alone crypto savings apps, every day.

On July 9, Aave Labs found a workaround called Stable Vault. Today, I want to show you how it works, who is making money off it, and why I think regular people are going to use it anyway.

Stable Vaults lets any business plug in once and start offering a savings account. A neobank, a wallet, a payroll processor. Deposits route into Aave’s lending markets. The user sees the rate in the app they use every day; if it seems like a good deal, they’re in.

The rate is fixed. I know it’s a tough thing to say in crypto.

Aave’s market pays whatever borrowers are paying that week. Stable Vaults sits on top and hands the operator a dial. The app types in a number. 4 per cent, say. From then on, the vault pays four per cent per second, no matter what Aave is doing underneath. That is the app’s problem, not yours. Anything the strategy earns above that number goes to the operator.

POV: the person putting money in

They get rated insurance. When Aave’s USDC pool paid 2% this spring, a vault promising 4% still paid 4%, and the operator covered the difference.

Handing off risk has a price everywhere else, and it has one here. Look at a fixed-rate mortgage. It costs 50 to 100 basis points more than a floating one, and that premium is the borrower paying for a fixed number.

The person doesn’t have to create a wallet, keep the seed phrase, bridge, or choose a chain. They get a support line, account recovery, Face ID, and a company with an address if something breaks. Aave’s own app runs SOC 2 certification and 2FA and markets both, because those are what the customer is buying.

The top of the range is what the user loses. When the pool paid 9%, they got 4%. When it paid 6%, they got 4%. It’s a fixed rate fixed by the app, based on what tier the user is. A moving rate is a live measurement you can actively check; an unmoving rate completely hides the middleman’s cut.

The user also picked up a second counterparty. By using this setup, they add two new failure modes to their balance sheet. The financial health of the fintech company running the app, and the code quality of a hidden, private script that shuffles their capital around behind the scenes. In plain DeFi, your only risk is the core protocol code. Here, if the middleman company goes bankrupt, or if their private backend script crashes and misplaces the funds, their money is just as gone, even if Aave itself works perfectly.

In a real swap market, the fixed rate is driven down to something close to fair value because both sides can shop. Here, the operator sets the number alone, and the customer has nothing to compare it against. User isn’t comparing 4% to Aave’s 6%. They are comparing it to their bank. Aave’s app page puts its own rate next to the FDIC national savings average of 0.40%, and against that, anything looks generous.

POV: The Operator

Take a neobank with $200 million of idle user stablecoins. It already has the money and users. It paid to acquire them. It wires in one integration, advertises 4%, and if the strategy returns 6%, it books $4 million a year on a balance sheet item that was previously a cost. Low effort 2%, not bad.

Rise is a payroll company. It pays contractors across 190 countries and has processed over $1.5 billion. When a company pre-funds payroll a week early, that USDC used to sit dead, so Rise built Rise Earn to park it in Aave’s USDC pool on Arbitrum until payday.

Rise takes 1% of the interest earned and nothing else. On a 6% yield, that’s six basis points. The worker gets 5.94%, and they just see Aave’s live rate.

A Stable Vault operator on the same money takes 200. The middleman’s cut went up thirty-three times.

POV: Aave and Stable Vault

Aave sells the vault’s ability to set per-user rates for loyalty, campaigns, or tiers, so think that a premium subscriber gets 5% and everyone else gets 3.5% from the same pool of borrower interest. A fintech issuing its own stablecoin can register it as a deposit asset and run a closed loop. And a balance that earns doesn’t leave, which means the yield is also a retention line.

Is the operator getting this for free? No. It’s short the spread in both directions. When Aave paid 2% this spring, every vault promising more than that had to write a cheque.

Which brings us to April 18, when the Kelp DAO bridge exploit on April 18 triggered a massive run on Aave, pool utilisation hit 100%, completely freezing all withdrawals and trapping both the operator’s paper profits and the user’s money in the same locked queue.

When utilisation hits the ceiling, nothing comes out for anyone, including the vault. The surplus stacks up on paper next to the user’s principal.

If liquidity returns, the operator sweeps a surplus that piled up during the days the user couldn’t leave. That surplus is the fee the market was paying for illiquidity. The person supplying the illiquidity was the user. If liquidity doesn’t return and bad debt hits the pool, the vault is short, and Aave’s docs say an authorised party can top up the system. No reserve behind “can”.

Aave will say its contracts were never exploited, that Kelp’s bridge failed and not Aave’s code, and that rsETH was frozen within hours. All true. They had previously voted to accept the risky collateral at a dangerous 93% loan-to-value ratio right before their risk manager resigned, leaving everyday users to bear the brunt of a broken app.

Now Stable Vaults look like the last piece?

Rise runs payroll floats through Aave. Kraken white-labelled Aave v3 into a protocol called Tydro on its own L2, then pointed its retail Earn product at it, so a Kraken customer tapping earn is an Aave user too. Cap Finance parks stablecoin reserves in it.

Horizon lends against tokenised treasuries with Circle and Franklin Templeton in the room. Aave App goes straight at consumers. Stable Vaults lets everyone else in and calls it diversification.

Aave doesn’t need more deposits. Kulechov told The Block in March that there’s a liquidity surplus in DeFi and that the focus has to shift to the borrowing side. He’s right, and it’s why USDC has been paying 2-3% instead of 8%. What Aave has always faced is that DeFi capital is mercenary and leaves for fifty basis points. Routing them through an app that owns the relationship, like the payroll, turns the flightiest money in finance into something that acts like a deposit base.

Aavenomics 3.0 went live on June 27 and now automatically buys AAVE from revenue. Revenue needs to flow through the pipe whether or not anyone is bullish. In a bear market, sticky deposits are what keep the buyback running. How do you get them? Stable Vaults.

Coinbase pays around 4% on USDC balances. Robinhood opened Earn on July 1 at roughly 7%, with 28 million funded accounts. Both call it savings.

Coinbase runs on Morpho and Ethena. Robinhood runs on Morpho and Maple, with the risk parameters set by a firm called Steakhouse.

Both of them had to build that. Custody deals, curators, risk teams, months of lawyers. Aave’s contribution is to make all of it unnecessary. With one integration, any app on earth can put a number on a screen and keep the distance between that number and whatever borrowers happen to be paying.

A bank gets to use it because a century of law stands behind it. Reserve requirements, examinations, deposit insurance, and a regulator who can walk through the door unannounced. All of that was built because everyone agreed long ago that the bank lends your money out and somebody has to be standing there when the lending goes wrong.

Everything Stable Vaults delivers is available to anyone with 20-30 minutes. But you make a wallet, bridge some USDC. Then supply it to Aave. What you don’t have to face in this case is KYC, an operator, or a rebalancer. And you lose nothing to spread. You get 6% instead of 4%, and you can see the pool the whole time.

I understand that the system thinks much longer term than my logic does. Also, when people don’t do that, I don’t think they are stupid.

Iyengar and Huberman’s work on retirement plans found that as the number of fund options went up, the number of people who enrolled went down. Faced with more choice, people picked nothing. Every consumer finance product since has been built on that result.

Self-custody has been right for fifteen years, and everyone has been told. Most on-chain card spending still routes through custodial platforms anyway. It’s a preference, expressed repeatedly, at scale. And their safety maths is better than ours. For someone with $2,000 and no crypto background, the likeliest way to lose it is by losing a seed phrase or sending it to the wrong address. An app with Face ID and account recovery removes the failure mode that would have got them. They’re paying 200 basis points for insurance against themselves, and that’s a rational purchase.

So Aave did the right move. It’s what a business with liquidity and no loyalty is supposed to do, and every consumer app in crypto is racing to the same place because the same logic is sitting everywhere we go.

In the end, this is an acceptance of human nature. People want safety, predictability, and most importantly, ease. Building a life is hard enough without having to run a personal central bank. They just want to close the app, look at a number that sits perfectly still.

—Thejaswini

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The job of any financial market is to move capital out of declining businesses and into those likely to do well. Every other function in the market, including trading, wrapper products, and research, exists to serve that one job. The faster a market does this job, the more efficient it is considered.

For most of financial history, capital movement has been slow for numerous reasons. Investors could have enough information to know that a business was in trouble, but they had to wait for proof. They often had to wait to see quarterly earnings, guidance cuts, and analyst notes before they moved their capital.

On June 30, Circle’s stock fell 16%, its worst day since listing. Nothing had changed in Circle’s business. In fact, that same month, USDC settled a record $1.21 trillion in transactions. The cause was a press release from a consortium of 140 firms announcing a rival stablecoin. Just an announcement of a nonexistent digital dollar. Yet capital moved.

In today’s piece, I will explore how crypto rails have compressed the time between information and capital movement, and why this tells us about crypto’s maturity into fintech.

On to the story…

Waiting for the Proof

In 2000, financial economist Jeffrey Wurgler measured how quickly capital moved into growing industries and out of declining ones across 65 countries. Jeffrey’s research found that the speed at which financial markets moved capital distinguished developed markets from undeveloped ones.

The speed with which you can move capital in traditional markets has seen extremes across the spectrum. In 1975, Kodak’s own engineer built the first digital camera. The market took another 25 years to punish the stock considerably. The price fell from a peak of $100+ in 1975 to under $40 in 2000. It then moved to zero only in 2012, when it filed for bankruptcy.

Phonemaker BlackBerry’s market share also grew for two full years after the iPhone launched, from 9.6% in 2007 to nearly 20% in 2009. Although everyone had seen the iPhone, the market still waited for BlackBerry’s revenue to slip.

The traditional world has even seen the other extreme. When the CEO of US educational services provider Chegg admitted on a May 2023 earnings call that ChatGPT was hurting new customer growth, the stock fell 47% on that day. Chegg’s revenue at that point was down just ~6-7%.

So, the difference between old and new markets is not the willingness to act early. Markets have always tried to price the future if they had enough information.

Chegg’s investors needed the company’s CEO to confirm the extent of the damage during a scheduled call before they could pull their money out. In the smartphone market, investors waited for signs that the iPhone was taking over from its competitors before acting. The market moved only after the signal became credible. For a long time, information availability has been a bottleneck in traditional markets. In the case of public companies, the information was made available when the company chose to share press releases or four times a year during their quarterly earnings. Private competitors reported nothing at all. Analysts would downgrade a company much later.

Crypto removes this bottleneck.

Eliminating the Bottleneck

Every protocol’s revenue, fees, deposits, and user flows are recorded on a public ledger and updated in real time. Nobody has to wait for an earnings call to know how much money a business makes. Anyone with a Dune dashboard or a DeFiLlama tab can see it in the frequency with which these platforms update their datasets. When a layer commoditises and a new player launches something in the adjacent layer expected to accrue more value, the revenue at stake for the incumbent is clearly visible on dashboards.

Over the past three months, my colleagues and I have written about layer after layer of this industry turning into a commodity. Stablecoin issuance, lending infrastructure, blockchains themselves. Each layer is getting attacked by cheaper, modular alternatives, and value keeps migrating to whichever layer stays scarce. That means the repricing trigger and a credible competitor showing up at an existing layer happen every few weeks.

Read: From Issuance to Infrastructure

In such environments, capital can move on the announcement because investors can immediately do the math on the revenue and market share at stake, without waiting for any analyst reports or earnings.

Take Circle for instance.

On June 3, CRCL’s share price fell 11% when reports of a Visa-Mastercard-Stripe stablecoin partnership first surfaced. On June 30, when the 140-firm consortium made OUSD official, it fell 16%. To be fair, another factor could also have driven the fall. FTSE Russell removed Circle from its growth indices on the same day, forcing index funds to sell. But the direction for Circle was apparent almost a month before the index exclusion was announced. Anyone could see what OUSD was attacking. Reserve income accounted for 99% of Circle’s revenue in 2024, and the consortium’s pitch was to return nearly all of that yield to its partners. The market did not need to wait for a single dollar to leave USDC.

A week later, Circle won approval for a national trust bank charter, signalling an improving operating story. But the issuance layer is commoditising, and the capital parked in CRCL will not wait for earnings to move elsewhere.

Transparency of information is just one half of what contributes to faster capital reallocation in crypto. The other half is the tools that make taking an action possible after having access to information.

This is where crypto’s market structure does what traditional markets cannot.

Think about what it takes to express a new opinion in traditional finance. If you hold a mutual fund and change your mind, you redeem at the end-of-day NAV and wait for the cash to settle. If you hold an ETF, you can sell intraday, but only during the six-and-a-half hours the exchange is open, five days a week. If your thesis involves a private company, there is often no instrument at all. You wait for a funding round or a tender offer. And if you are a limited partner in a venture fund, your capital is locked for ten years. You can change your mind, but good luck with moving your money.

Every one of these frictions delays repricing. Even though investors have new information that could convince them otherwise, the infrastructure prevents the free reallocation of capital.

Crypto markets run around the clock, so no opinion has to wait for an opening bell. Settlement is near-instant, so capital that exits one thesis is available for the next one within minutes. And the industry keeps building new instruments to express increasingly specific views.

Spot markets let you back a protocol. Perps let you hold a leveraged short or long position in any traditional or crypto asset or commodity, like gold or oil, without owning the underlying assets. Prediction markets let you price an event, like whether a stablecoin bill passes, separately from pricing the companies affected by it.

Hyperliquid’s permissionless markets have processed around $270 billion since last October, with 99% of that in non-crypto assets. When crude oil moved on Middle East headlines one weekend, Hyperliquid’s perps had priced most of the move before CME even reopened.

Read: Every Exchange Is an ‘Everything Exchange’

Put transparent information together with instruments that let anyone act on it immediately, and you get repricing capabilities that traditional markets can never offer.

Earlier this month, Robinhood made Lighter its in-app perpetuals engine and put $11 million of LIT in front of its 28 million funded accounts. Immediately, the market moved significant capital into the new entrant’s ecosystem.

LIT rose 50% in two weeks simply because investors reviewed a distribution deal and decided to reallocate capital.

Read: Building a Financial Supermarket

This changes the job of everyone allocating capital.

I feel this discipline travels beyond liquid markets. Private valuations famously lag public repricing by quarters, which is how venture funds carried their 2021 valuations deep into 2022. But using crypto infrastructure, liquid markets can also mark illiquid markets in real time.

Read: The Unbundled Term Sheet

The Commoditisation Era

Commoditisation has been the operating condition of every industry. Every few months or years, especially in a maturing industry like crypto, we see various incumbent layers get commoditised due to the concentration of competitors around a single stack within an ecosystem. As competition increases, that layer becomes less valuable, and value shifts to adjacent layers with fewer competitors. The competition then migrates to that new layer. This is what has been happening for years, and this is how industries evolve.

We saw it with open-source software, and now we’re seeing it happen in crypto. Stablecoin issuance, lending infrastructure, exchange venues, and the blockchains themselves - we have covered each of these layers in the past three months. We wrote about how they are being targeted by a cheaper, modular alternative, and every incumbent margin is being eaten away by others. In an industry built on open-source code and permissionless entry, no layer stays scarce for long.

A market where the playground and the reward are migrating often from one layer to another also needs to enable faster and more frequent capital movement between those layers. You cannot penalise the investors for wanting to reallocate capital, lest they move to more efficient and freer markets. The transparency and instruments that blockchains enable allow this precise movement with little to no friction.

This is why I agree with Jeffrey Wurgler’s yardstick to measure a developed market - one that enables its constituents to quickly pull money out of the declining industries and reallocate it into the growing ones. By that measure, this is the most developed capital market ever built.

While equity markets also enable quick reallocation of capital, as we saw in Chegg’s case, the difference between traditional markets and crypto lies in what follows. Crypto compresses the entire process of rotating funds into a single sitting.

The investor who sold CRCL on June 30 could have done so using the equity in the traditional markets. But that could have been done only during market hours. The same investor could also have expressed their opinion on Circle by trading its perpetual contract on Hyperliquid or by betting against the company using an event contract on a prediction market. Both these options are always on and wouldn’t have required the investor to wait for the market to open.

This is not to say that crypto investors will always get their quicker reallocation decisions right. High speed could mean more mistakes. But I’d gladly welcome the ability to make quicker decisions with better information and be occasionally wrong, rather than being shut off from the information flow and being late to decision-making due to market frictions.

Read: Netting Is the Moat

I don’t think there’s a greater liberation for investors in a free market than being empowered to access important information at any time and act on it using the right tools at their disposal.

That’s it for today. I will be back with the next one.

Until next time, stay curious,
Prathik

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This is BlackRock in crypto right now, even though all you can think about when I say this are ETFs.

BlackRock launched one; it swallowed something like a hundred billion dollars. Every outlet on earth ran the same piece about how the suits finally came for crypto. Fine, true. Also, the decoy.

An ETF is a product. You buy it, you sell it, it is right there in your brokerage account next to your index funds. If BlackRock’s Bitcoin fund vanished tomorrow, crypto would shrug and keep moving.

But today, I want to talk about the BUIDL playbook.

BUIDL is BlackRock’s tokenised money fund. It’s a pile of short-term US Treasuries and cash, chopped into on-chain tokens, that pays yield straight to whoever holds them. It launched in 2024, holding about $2.5 billion, which sounds small and is small. But I was looking at what it was turning into.

BUIDL holds Treasuries, so what’s inside the fund is the safest thing you can own. The danger is how you get in and out of it. BUIDL is permissioned. Only wallets that BlackRock and its partner Securitize have approved can hold it or move it, there’s a whitelist, which BlackRock controls. You can only cash it out during set hours, on BlackRock’s terms. BlackRock, or a regulator leaning on BlackRock, can freeze a wallet or halt redemptions. An ordinary crypto token moves the instant you tell it to. In BUIDL’s case, someone else can switch off for you. That is the reason it’s a risk, and it’s why everything built on top of it inherits that risk.

BUIDL is becoming the collateral the rest of on-chain finance gets built on. Today we are talking about that very sovereign takeover.

Start with Ethena and USDe. It is a synthetic dollar that’s now the 3rd-largest stablecoin. Ethena runs a second dollar, called USDtb, and more than 90% of its backing is BUIDL. When USDe’s engine sputters in a rough market, USDtb is the shock absorber it leans on. So BlackRock’s Treasuries already sit a layer below one of crypto’s largest dollar assets.

And a couple of weeks ago, it went further. BUIDL became the main reserve for the stablecoins that Ethena now builds for other companies, a core ingredient in a whole product line.

Let’s be precise about how much of USDe leans on BlackRock, though. On a calm day, barely any of it. USDe is backed mostly by crypto held against short futures, with only about 7% parked in plain stablecoins, including USDtb.

Ethena has $6 billion circulating supply, but only an $65 - $80 million native reserve to absorb market losses. When the funding trade stops paying, Ethena can’t rely on its own tiny buffer. It has to aggressively dump its capital into the Treasury fund.

So BlackRock becomes load-bearing right when things are breaking, the one moment you’d least want to learn your floor belongs to someone else.

In a standard crypto panic, if you want to exit a position, you interact with an automated smart contract. It doesn’t care who you are. But BUIDL is a permissioned, whitelisted token. If BlackRock’s compliance desk flags an address, or if regulatory pressure forces it to pause redemptions, that liquidity instantly freezes.

If the collateral under a stablecoin, or under an exchange’s margin system, can’t be sold at the exact moment everyone needs to sell, then every loan and every leveraged bet resting on it is trapped too, and they all unwind together. Traders think moving into a Treasury-backed asset is the safe play. They’ve traded the risk of crypto prices swinging for the risk that one company, on the worst possible day, won’t let them out.

Since April, big traders on the OKX exchange can post BUIDL as margin, the money they put up to back their positions. Meanwhile, the tokens sit off to the side in custody at Standard Chartered, a proper global bank. The collateral earns Treasury yield while it works. It’s the first time a bank that size has done this for crypto. Idle margin became a paying asset, and the asset is BlackRock’s.

A couple of weeks ago, BlackRock wired USDe into Aladdin.

Aladdin is BlackRock’s risk management system. It’s software that monitors portfolios and models what could go wrong. By adding USDe to Aladdin, BlackRock is now closely tracking it. The system is named after Aladdin, the story where a lamp grants wishes, but in this case, the benefits mostly go to whoever controls the lamp.

BlackRock isn’t doing crypto a favour with the USDe integration if you think so.

What they are doing is using their software to pull the inner data, risk profiles, and structural behaviour of the on-chain financial system into their own brain.

They know which players are overleveraged and roughly where prices have to fall before those positions are forced sold. So when a sell-off starts, BlackRock already knows which dominoes go first. Even if you think you are an independent crypto founder running a sovereign protocol, you are ultimately forced to price your risk using BlackRock’s proprietary math.

USDC, the second-largest stablecoin with around $78 billion in market cap, keeps the bulk of its cash reserves in a fund that BlackRock itself manages.

When you add it all up, BlackRock is a big buyer in crypto and also, crypto is being built on top of BlackRock’s collateral and margin, with its risk system overseeing both.

What does this look like from inside? A trader holds USDe, which leans on USDtb, which is mostly BUIDL, and then borrows against that USDe to place another bet. That’s what collateral does. It disappears into the foundation, and everything heavier gets stacked on top of it, meaning the loans and the leverage other people pile on those dollars, all of it assuming the bottom layer will hold and will let them out. If it doesn’t, they all have the same problem at the same moment.

Ethena may be loud, but other exchanges have started taking tokenised Treasuries as margin too, some from BlackRock, others from rivals like Franklin Templeton. BUIDL is the biggest one in the room. The biggest usually keeps winning. Traders want to hold the same collateral everyone else holds, because that’s the one that’s easiest to borrow against and sell in a hurry. So money keeps flowing to the biggest option, which makes it bigger still.

BlackRock has done this before and won it.

Index funds were cheap and slow, the oatmeal of investing. BlackRock rode its iShares brand as that oatmeal ate the world, and today the three big index shops, BlackRock alongside Vanguard and State Street, are the largest shareholders in close to 90% of the companies in the S&P 500. And for that, they just stayed under everything as the money piled in.

Aladdin did the same on the operational side. That risk platform now runs the books on north of $20 trillion in assets, somewhere above a tenth of all the financial assets on the planet. Much of that money belongs to firms that compete with BlackRock and still pay to use its system. So even the competition uses BlackRock’s math to measure its own safety. That means BlackRock sees every card on the table.

You want the measure of how deep that goes; look at 2008. When the crash hit and the US government found itself holding a mountain of toxic mortgage assets it couldn’t price, it hired BlackRock, asking it to put a number on it.

It happened again in 2020. When COVID froze the bond market, the Fed hired BlackRock to run the rescue, buying corporate bonds and bond funds by the billion. A large share of what BlackRock bought, on the government’s behalf, was BlackRock’s own funds. The money wasn’t BlackRock’s. It was public, the Treasury put up the cash, and taxpayers were on the hook for any losses. The government let BlackRock decide where the money went, and a chunk of it went into BlackRock’s own products. Its flagship credit fund swelled from $28 billion to $47 billion in two months on the back of it. BlackRock ran the buying and supplied the thing being bought, and when people cried foul, the reply was that BlackRock was just the agent and the conflicts were handled with care. BlackRock issues the collateral and runs the system that prices it, all handled with care. Look carefully, and that is the seat BlackRock is building in crypto now.

If tokenised dollars keep settling on BUIDL, and DeFi keeps parking its reserves there, and risk keeps getting priced through Aladdin, BlackRock becomes the operating system of crypto.

So why does this matter more than the ETFs? Because an ETF and collateral are different things. An ETF is just demand. People buy it for exposure, and if they change their minds, they sell, and no one else is touched. Collateral is the opposite. Once protocols use BUIDL to back their dollars and their loans, they can’t pull it out easily, because pulling it out means unwinding everything sitting on top of it, every dollar it backs and every leveraged bet resting on those dollars. So nobody pulls it. It stays put by default. People keep it because removing it has become too dangerous to try. You can sell an ETF in a second. You can’t rebuild the foundation of a system while everyone is still standing on it.

But this is the early days. That $2.5 billion in BUIDL is a small next to the stablecoin market, which runs past $300 billion, most of it Tether and Circle. On today’s numbers, BlackRock isn’t the floor of anything.

And you could argue this is good news. Crypto’s whole history of blowups runs on junk collateral, made-up tokens propping up other made-up tokens until the morning they all fall down together. Putting US Treasuries, watched by the most trusted name in the business, under your synthetic dollars is how you stop that. More trust.

But first of all, size is the wrong lens. The right one is position. Ask how much is built on top of BUIDL, not how big BUIDL is on its own. A $2.5 billion fund that a dozen other products lean on matters far more than a $50 billion fund that nothing else touches. BUIDL is the largest single fund in the tokenized-Treasury market, a roughly $15 billion category that has more than tripled in a year, and Boston Consulting Group puts tokenised real assets on a path to $16 trillion by 2030. It’s small today. But it’s the base everything else is starting to settle on.

Secondly, the control. It’s the same deal every industry has already signed with BlackRock. You take the stability, hand over the control. It feels like a steal because the stability is the part you can see, and the control is the part that doesn’t bother you yet. And BUIDL is a permissioned, whitelisted, redeemable fund on BlackRock’s terms.

To grow and avoid crashes, crypto protocols needed ‘safe’ assets to back their tokens and support their trades. That’s why they started, or may start, using BlackRock’s BUIDL fund.

If the whole industry relies on BlackRock’s models to measure risk and its assets to back their dollars, changing the system becomes impossible; any change could destroy the market.

The industry gets the stability it wanted, but at what price?

That’s all for today. See you soon with another one.

—Thejaswini

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When you own a share of a company, you have a residual claim on whatever is left after the company pays everyone else. The company pays off employees first, bondholders and lenders next, then creditors, taxes, and preferred stock. Then comes equity, which is owned by the shareholders.

But that residual claim comes with exclusive privileges too. You get a vote on who runs the company, a share of any dividends the company distributes, and a claim on anything left over if the company is sold or wound down.

For a long time now, a token holder in a crypto protocol has been offered a similar deal, at least in language. If you held a token, you could participate in the network’s decision-making and get a share in its eventual success and earnings. But the deal has always been one-sided. Nobody in crypto admitted it all this while because they didn’t face the conflict. Except until now.

While crypto protocols have found a way to keep their token holders happy due to the lack of regulation, the passage of the CLARITY Act (which is underway) could close that leeway. Some crypto protocols that issue equity shares, even while having a class of investors holding their tokens, have further exposed the distinction between shareholders and token holders.

In today’s story, I will explain what could change for token holders of crypto companies that choose to issue equity.

On to the story…

What Ownership Entails

It’s not the return that makes equity the most durable financial instrument. Bonds often outperform equity with higher returns and lower volatility. Yet, equity is attractive to many because of its structure. It is a contractual claim to own a part of the company. If the company earns a profit, the board may pay a dividend, and shareholders receive it. If the board refuses, shareholders can vote for a new board. If a majority want to sell the company, they can. None of this solely depends on the CEO’s goodwill.

Over the past century, the corporate world has continually adjusted the extent of shareholders’ control over a company’s operations. Yet, the right to economic claims has largely remained untouched.

Google’s 2004 IPO gave founders Larry Page and Sergey Brin and then-CEO Eric Schmidt 10 times the voting power of public shareholders by creating two classes of equity shares. Yet, the economic rights these public shareholders had were on par with those of founders and insiders. Snap Inc., the maker of Snapchat, issued shares with no voting rights in 2017. Berkshire Hathaway has run dual-class shares since 1996.

Although each of these experiments changed how classical shareholding was defined, they all preserved the part that makes equity equity - the legal, court-enforceable claim on the residual value of the business.

A token holder in a crypto protocol has none of this. They have neither a right to receive dividends nor a residual claim on the proceeds of the company’s sale. It is the whole difference between owning something and being told you own something. Every legal system built around ownership assumes the owner can enforce the claim. A token holder cannot enforce anything. All they have is a token whose price the protocol tries to support by using some portion of revenue to buy back the token on the open market and burn it. What’s worse? Even this isn’t set in a contract. The protocol can change it, pause it, or stop it without any board approval. You cannot call a lawyer if you are aggrieved.

But why are we talking about this now? This gap in the nature of ownership and rights was always there. But it didn’t matter for most of crypto’s history because there was no separate class of owners to compare against. The token was the only one that existed. All this while, the incentives of everyone who holds tokens, be it the community or the founding and leadership teams, are aligned in the same direction.

But that’s changing now.

When successful crypto protocols begin to operate like companies, actual revenue, product, and users begin to matter much more. Sooner or later, they will need more capital to scale, and the best way to raise serious money is still to seek it in wider markets. Just like how Google and Snap did when they went public, or like how Tesla and SpaceX did before they went public.

On July 1, Venice AI closed a $65 million Series A round led by Dragonfly and Coinbase Ventures, valuing the company at $1 billion. Investors got 8.98% equity plus a token grant. This changes how the ownership structure works. It exposed a structural flaw crypto has been ignoring for a decade, just because nobody decided to point it out.

Before the raise, Venice had one class of owners. Now it has two. First are the equity investors with contracts, board rights, information rights, anti-dilution protection, and a legally protected claim on 8.98% of the company. Second are the VVV (Venice’s native token) holders, with a burn programme the company runs voluntarily and can stop whenever it wants.

The fundraise puts an official price on Venice’s equity. When the company grows from here, the equity shareholders capture the growth through a legal, contractual mechanism. None of that directly accrues to the token holders. They benefit only if Venice keeps choosing to buy back and burn its tokens. This means that every dollar of future revenue has to be split between the two, that is, if Venice’s leadership decides to be fair to both classes of shareholders. They can always choose not to buy back.

Venice isn’t the only one. Aave routes 100% of protocol income into AAVE buybacks. Hyperliquid runs the largest buyback in crypto, with over $1.2 billion of protocol revenue allocated to HYPE, 97% of fees, and roughly 5-6% of market cap annually. None of these protocols has done a Venice-style equity raise yet. But all of them face the same underlying question. The buyback mechanism sits at the team’s discretion. Nothing prevents Hyperliquid’s team from redirecting the Assistance Fund.

For a small example of how this ends, Sol Strategies acquired Houdini Swap for $18 million in May 2026. The acquirer paid the founders and equity holders. Token holders of Houdini Swap’s LOCK received nothing. The token’s chart flatlined at zero.

In each case, the mechanism meant to protect token holders’ interests turned out to be one the protocol controlled. This meant that what they expected from holding tokens was just at the mercy of the protocol’s management changing its mind.

This is what happens when the acquirer isn’t legally required to buy anyone else.

The Legal Bind

The CLARITY Act, passed by the US House in July 2025 and stalled in the Senate as of July 2026, is likely to make this conflict even more pronounced by using its legal teeth. The legislation plans to sort every crypto token into one of two boxes. Digital commodities will be overseen by the CFTC, the agency that regulates oil, wheat, gold and other commodities. Under investment contract assets, the token will be categorised as a security and will be regulated by the SEC, the agency that regulates stocks and bonds. Almost every protocol wants its token to be in the first category because it allows the token to trade freely on public exchanges. The second would collapse liquidity and impose compliance costs that most tokens can’t survive.

The problem arises when you look at what comes bundled with each category.

The bill explicitly allows commodity tokens to have governance rights, staking rewards, and value that rises with the extent of use of the underlying protocol. It doesn’t allow any issuer to grant its token holders a legal claim to the issuer’s revenues, profits, assets, or debts. It means a token can capture value from the network, but cannot capture the value from the company that runs the network.

This doesn’t stop a protocol from designing a token whose value accrues based on trading activity. But the token cannot be designed to have its value accrue based on the revenue generated by the corporate entity behind the protocol. Buybacks and burns fall in this grey zone. So far, the SEC hasn’t clarified which side of the fence it falls on. But nothing forces the SEC to draw a line in favour of the token holders.

In the status quo, protocols existed in a legal fog where they could claim tokens were something like informal shares. It’s a case exploiting the absence of clarity. But wait, would you even call it exploitation where there is no law yet? There’s no CLARITY Act right now to outlaw the story that protocols continue telling their token holders. But once the Act comes into force, it will make it legally impossible to offer ownership rights to token holders while keeping it in the commodities category.

Some protocols are already trying to bridge the gap without crossing the line. Aave activated Aavenomics 3.0 on June 27, replacing its committee-directed buyback with an automated, non-discretionary on-chain mechanism that routes 100% of protocol and GHO (Aave’s decentralised, overcollateralised stablecoin) revenue into open-market AAVE purchases.

Stani Kulechov, Aave’s founder, called the mechanism immutable and automated. It is probably the farthest any DeFi protocol has gone to make a promise on record.

But Aavenomics 3.0 is still just code doing the job a contract ought to do. Aave’s governance team can still vote to halt the mechanism. An aggrieved token holder cannot sue for breach of promise. At best, it is a policy that most holders trust the governance team to uphold. Every protocol that has tried to build value accrual without securities registration is likely to face the same restraint imposed by the CLARITY Act.

In fact, Aave is also about to face the question Venice just faced. In late June, reports emerged stating Kraken’s parent, Payward, is negotiating a 15% equity stake in Aave Group at a $385 million valuation. But Kulechov disputed the consideration involved in the deal.

However, he didn’t deny that talks were underway. If this deal closes, Aave becomes the second major protocol to add a real equity class on top of a live token.

Is there any way crypto protocols can justify these dual structures?

The industry’s standard defence is often tokens that hold some genuine utility. Venice’s DIEM, a mint credit that buys a dollar of daily AI compute, is an example of a utility token. Fee tokens on trading venues are another example. But the problem here is that tokens whose value is linked to utility cannot appreciate. It’s like the chips a casino sells you so you can use them to play and cash out when you're done. Even if someone chose to hold these chips, they cannot serve as a store of value beyond their utility for playing in the casino. A DIEM that buys a dollar’s worth of compute should also be treated similarly. It can gain temporary value due to demand being higher than supply, but that cannot compound over time.

But the moment the primary pitch for selling a token is that the protocol will use its earnings to make the token more valuable, then it is nothing more than a pseudo-equity. And this instrument will be unable to evade CLARITY’s excluded categories.

The better alternative for protocols is to choose. They should accept that the token is a commodity and stop marketing it as a claim on the company’s success. The other option is to issue actual economic rights to token holders, register the token as a security, and bear the compliance cost.

For a decade, the capital asset framing worked because nobody insisted on reading the fine print. But it worked so long as everyone in the room was at peace with how it worked. Once equity shareholders arrive with signed papers, the act will stop. Aave’s automated buyback could be one of the best ways to reassure the tokenholders. But that will only last until the governance decides to change the rules they play by. That moment is just one term sheet away.

That’s it for today. I will be back with the next one.

Until next time, stay curious,
Prathik

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. If you want to reach out to 170,000+ subscriber community of the Token Dispatch, you can explore the partnership opportunities with us 🙌

📩 Fill out this form to submit your details and book a meeting with us directly.

Disclaimer: This newsletter contains analysis and opinions of the author. Content is for informational purposes only, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.