There’s this famous Crypto Influencer who goes by the name of ThreadGuy. He rose to prominence in 2021 by teaching people how to trade NFTs. Now he sits in his New York apartment with a barrel of American crude oil behind his desk, trading pharmaceutical stocks and commodities on Hyperliquid. A few weeks ago, he had Cobie on his stream. Cobie has been one of crypto’s longest-running voices since 2012, sold Echo to Coinbase for $375 million, and now works there full-time. When ThreadGuy asked him about the state of crypto, he described something called a “K-shaped” dynamic.

“There’s this weird K-shaped thing happening in crypto,” he said, “where crypto seems to be having phenomenal success stories, much more than any previous year. But it’s just not represented in asset prices that people can buy.”

That line has been stuck in my head since. Because he’s right. Polymarket and Kalshi have become a $44 billion prediction market duopoly. Stablecoins are being used to pay gig workers. DoorDash now pays drivers through Tempo. Hyperliquid processes more trading volume than most centralised exchanges, on a chain it built from scratch. Trade XYZ predicts the Monday stock market open within 50 basis points. Crypto was supposed to move money without banks, make markets without brokers, and let anyone trade anything from anywhere at any time. By almost every measure its critics ever threw at it, it’s doing exactly that.

And the people who believed in it earliest, the ones holding tokens, have gotten almost nothing from it. You can’t buy Polymarket equity. You can’t buy Tempo. Circle went public, but half of USDC’s net interest margin goes to Coinbase for distribution rights before shareholders see a cent. The platforms are all winners, but token holders lose every time.

That is the K-shape. And the more I looked into it, the more I realised this isn’t just a crypto problem.

Where Does The Value Go?

Let’s start with stablecoins, because they’re crypto’s true Product-market-Fit. Tether is estimated to have made $10 billion in 2025 and has roughly 100 employees. That is more profit per head than almost any company on earth. Circle went public and has a market cap of $23 billion as of April 28. Stablecoin supply has grown 100x over the past few years from $6.8 billion in 2020 to more than $315 billion today. And it is the US Treasury itself that projects it to grow to $2 trillion by 2028

This is real financial infrastructure being built on crypto rails. And for anyone holding a token, the economic relationship to all of this is zero. Tether’s profits flow to Tether’s shareholders. Circle’s economics flow to Circle’s equity holders and to Coinbase, which effectively takes 50% of USDC’s revenue just for putting it in front of users. DoorDash pays drivers through Tempo, and the value of that transaction accrues to DoorDash, Tempo, and the driver. Not to anyone’s token portfolio.

Prediction markets tell the same story. Polymarket went from a niche crypto experiment to a CNN fixture. The Wall Street Journal now uses its data alongside editorial reporting. Substack built a direct integration with Polymarket so writers can embed live odds in their posts, turning every newsletter into a real-time data terminal. ICE, the company behind the New York Stock Exchange, invested $2 billion at an $8 billion valuation. Kalshi won its CFTC legal battle and expanded into economics, sports, and science. Combined volume across both platforms hit $44 billion in 2025, with $10 billion in a single month.

None of that value went to token holders. Polymarket’s early backers, Founders Fund, General Catalyst, and Blockchain Capital, are sitting on massive unrealised gains. One of crypto’s biggest success stories runs on crypto rails, was built by crypto people, and ended up with a traditional equity cap table where the upside sits with venture capitalists (VCs).

You might argue that Polymarket hasn’t launched a token yet. That’s true, and it might launch one eventually. But even if it does, private investors have already set the valuation at $8 billion. The window where early users could have captured meaningful upside closed before most of them knew it existed. And if it never launches a token at all, then the entire value of the prediction market revolution, the thing crypto people spent years arguing would change how the world processes information, will have been captured entirely by a traditional equity cap table. Funded by VCs, exited to institutions, with zero on-chain ownership for users.

Even in DeFi, the pattern is the same. Crypto spent the better part of a decade building the infrastructure for decentralised finance — from lending protocols, automated market makers, perpetual exchanges, and stablecoin rails, mostly in the open, mostly with tokens, and mostly while regulators were actively trying to kill it. The people who built this stuff took enormous risks. The users who provided liquidity and tested these protocols when a single smart contract bug could drain everything took risks, too.

And now that the technology has proven itself, now that it’s clear that stablecoins, on-chain trading, and tokenised assets work, the companies showing up to capture the value are not the ones who took that risk.

They’re traditional firms with equity structures, private fundraising rounds, and no obligation to distribute anything to the users or communities that made the technology viable in the first place. Stripe is building stablecoin payments. PayPal has launched its own stablecoin. Banks are tokenising assets on private blockchains.

They were all observing from the back seat at what crypto built, and once they confirmed it worked, they are now rebuilding it inside walled gardens where the economics flow to shareholders.

The upside is being privatised. Tokens were supposed to be the mechanism that prevented this, the thing that let early participants share in the value they helped create. Instead, the projects that actually succeeded either never launched a token or launched one so late and at such an inflated valuation that public holders were effectively the exit liquidity for insiders who got in at a fraction of the price.

The K-shaped Capitalism Problem

And this isn’t some crypto-specific failure. This is how wealth creation works now, everywhere, and crypto just inherited the same disease it was supposed to cure.

SpaceX has gone from zero to roughly $1.75 trillion in private valuation. OpenAI is at $852 billion. Anthropic is somewhat in the same territory as $800 billion. These three companies alone represent trillions in value creation. If you were an ordinary person in the 1970s or early 2000s and thought Apple, Amazon, or Google would be important, you could just buy their shares. You could participate in the wealth creation of a company you believed in. That relationship between being right about the future and being rewarded for it, that was the basic social contract of capitalism. It no longer holds.

These generational companies remained private at every stage when the real returns were made. The only people who got access were already in the club, the Silicon Valley networks, the fund-of-funds, the LPs writing $50 million checks into venture vehicles. By the time SpaceX or OpenAI eventually goes public, the price will reflect a decade of compounded private gains that retail investors had zero access to. The number of publicly traded companies in the U.S. has dropped 46% since 1997, from about 7,500 to 4,000.

There are over 1,400 venture-backed unicorns worth a combined $5 trillion, all staying private. Companies used to go public to raise capital. Now they raise billions in private rounds, indefinitely, from the same tight circle of funds. By the time they IPO, price discovery had already happened in rooms that regular people would never be allowed to enter.

The data confirms this isn’t some paranoia. IPO returns from 1970 to 1990 averaged 5% annually, less than half of what you’d have made just by buying public companies of a similar size. Low-float IPOs, the kind SpaceX and OpenAI would likely do, have a 90% historical failure rate. Ten out of eleven low-float IPOs since 1980 underperformed the market by 50% or more within three years. So the deal being offered to normal people is, you don’t get to invest when the company is worth $10 million and growing. You get to invest when it’s worth $1.5 trillion, and the insiders are looking for liquidity to exit.

This is what is called the K-shaped economy, where gains are privatised as they flow through closed circles, and losses are socialised through overpriced IPOs, through index funds forced to buy at the top, through inflation and stagnant wages, which get spread across everyone else.

This is also what’s driving talent out of crypto. Crypto code commits fell 75% since early 2025, from 850,000 weekly to 210,000. Active developers dropped 56% to about 4,600. Where are they going? AI. GitHub now has 4.3 million AI-related repositories. LLM imports grew 178% in a year.

And this makes complete sense if you think about it in terms of the K-shape. Every major crypto onboarding wave, from 2013 altcoins, 2017 ICOs, 2021 DeFi and NFTs, to memecoins, had one thing in common: normal people made money fast. AI has that energy right now. One person, called Peter Steinberger, built OpenClaw and later sold it to OpenAI for billions, all by himself. That is the kind of energy crypto used to have. If you’re a 22-year-old like me and deciding where to spend the next five years of your life, the math isn’t that complicated. Crypto is offering you governance tokens that launch at $16 billion and bleed for two years. AI is offering you the chance to build AI agents with three people that could be worth a billion dollars before your next birthday.

The talent started leaving because, somewhere, crypto stopped distributing the upside it creates. The K-shape pushed the gains upwards, to VCs, to equity holders, to the same insiders the industry wanted to build to displace. Where is Decentralisation Anon?

Okay Enough! What’s the Solution?

So crypto has a problem. The technology is fantastic, but the people who believe in it don’t get to participate in the upside. The same privatisation dynamic that is eating away at traditional markets has infected the industry specifically designed to prevent it. Is there a way out?

Cobie thinks there might be, and I agree with him. The answer is the one thing crypto can do that no other industry can, airdrops.

Airdrops distribute ownership directly to users globally, without intermediaries, at the exact moment when ownership is most valuable. That’s what airdrops were always supposed to be. In practice, most of them have been a joke. But there’s one case that proved it can actually work, and it’s worth understanding.

I am talking about Hyperliquid. Jeff Yan and his team built a perpetual exchange from scratch on its own L1 blockchain, ran it for over a year, grew it to over $4 trillion in cumulative trading volume to date, and, when it came time to distribute ownership, allocated 70% of the total token supply to the community. All of this with no VCs, Advisors, or exchange listing partners. The actual traders who used the platform, moved capital through it, and stress-tested it for months. 94,000 addresses claimed tokens in a $1.5 billion airdrop. Some of them became millionaires overnight.

And here’s the best part. They didn’t dump the tokens. Because the people who received HYPE weren’t mercenaries farming a product they didn’t believe in. They were Hyperliquid’s best users. The most active traders, the people who moved the most capital, the ones who stayed because the product was better than the alternatives. They got ownership proportional to their contribution, and they held. The team mirrored it. After distributing about 20% of their vested tokens in the first two months (likely for taxes), they cut distributions to 1% in the following months. Today, 97% of Hyperliquid’s protocol revenue flows to HYPE buybacks and burns.

Saurabh at DCo broke down the valuation math in detail. Hyperliquid earned $960 million in revenue in 2025 on roughly $3 trillion in volume, but trades at just 10-13x revenue, compared to 25x for CME, 23x for ICE, and 22x for CBOE. It grew to nearly a billion in revenue in its first full year, has no debt, no headcount drag, and a buyback mechanism that returns almost all fees to token holders.

Hyperliquid is proof that this is possible. Distribute to users, not investors. Let actual usage drive value. Align incentives so the people who build the product and the people who use it are on the same side of the trade. But of course, most airdrops are not Hyperliquid.

Most of them are elaborate performance theatres where people pretend to use products they don’t actually care about just to farm tokens they plan to sell the second they unlock them. The projects know this is happening. The users know the projects. But everyone still plays along because admitting that an airdrop is a customer acquisition cost paid in inflated tokens won’t help raise more money on VC pitch decks. Because 90% of these tokens exist just to give VCs an exit, not to align incentives with the users.

The data from Cobie’s own analysis is damning: Ethereum’s ICO allowed retail investors to buy at a $26 million valuation and capture 7,500x returns. By the time you get to projects like Berachain, the seed round is $40 million, and the public launch price is at its peak. Retail holders are underwater, while seed investors are up 138x.

So the question is simple, and I think it matters more than most people in this industry realise: Is Hyperliquid a model or an exception?

If it’s a model, if more teams can build real products, skip the VC extraction machine, and distribute ownership to the people who actually use what they built, then crypto has something genuinely unique. SpaceX can’t airdrop shares to the people who watch its launches. OpenAI can’t distribute equity to everyone using ChatGPT. But crypto can. It has a mechanism. It’s been done at least once, and it was a success.

If it’s an exception, if Hyperliquid was just a one-off with the right team, the right product, and the right timing, then Cobie’s K-shape thesis wins. Token holders keep losing. The smart builders keep leaving for AI. And the only way to participate in crypto’s success is to buy Coinbase or Circle stock. Which is exactly the kind of outcome crypto was supposed to make impossible.

That’s all for today.
Vaidik

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I love discussing how crypto is changing the way money moves. It feels nice, but the reality is nuanced. One look at how the big institutions have been moving money for the past decade tells you the story.

A bank wire transfer across the Atlantic still takes one to two days. It needs to pass through intermediary banks, generates reconciliation entries at each point, and costs the client about $25 to $45. It’s the same architecture from the 1970s, except email replaced telephone communication and SWIFT replaced the tangled cables. Of course, the databases got faster, too. But that’s that. Timelines didn’t shrink proportionally.

You might think this is a technology problem, but I think it’s more of a coordination problem.

We have had blockchains and stablecoins for over a decade now. Yet they never resolved all the problems at once. Some offered the speed institutions needed, but put all data in public by calling it transparency. Others ensured both speed and privacy but created siloed systems that couldn’t talk to each other.

The thing with new technologies is that they easily scare away large institutions operating in highly regulated industries. Think banks. For them to migrate to new technologies, they need to see all their pain points addressed in advance. None of them can be issues that are “can be taken care of after we migrate”.

It took a while, but this is finally changing. Ironically, banks are now resorting to blockchains to avoid ceding ground to digital assets.

Last month, five US banks with over $750 billion in combined assets launched Cari Network. This system will convert ordinary deposits into digital tokens that settle instantly, operate 24/7, and remain FDIC-insured.

In today’s deep dive, I will tell you how blockchain builders have tried to build solutions for institutions in the past and what makes this time different.

Swings and Misses

About a decade ago, consortia like R3 and Hyperledger built private blockchains for institutions with ambitious roadmaps and membership lists that included the BNPs, Citis and Barclays of the world. Although these chains worked and updated the ledgers accurately, they were siloed and couldn’t interact with anything outside the walled infrastructure.

Such efforts died a slow death. Some others pivoted to other approaches.

Then, the banks tried the public blockchains - mostly Ethereum. It immediately solved the composability problem. A shared, neutral ledger that everyone can access enabled banks to interact within their ecosystem. But solving one problem gave rise to another. On a public chain, every counterparty, every transaction, every balance was visible to anyone who knew where to look, just using a browser.

What banks needed was a single system that offered them privacy, compliance, speed and connectivity.

What Changed

Two breakthroughs came in 2025: one technological and another - necessity.

First, let’s understand the technology. Zero-Knowledge (ZK) proofs caught people’s attention for what they offered. ZK proof is a cryptographic method that lets you prove a transaction is valid without revealing its details.

Read: The Privacy Correction 🔐

Although the technology has existed for years, it has only got cheaper and faster recently. Generating these proofs used to be expensive enough to make the whole system impractical to deploy from a business perspective.

The number of transactions processed per second has jumped from as low as 400 to at least 15,000. The time taken for a transaction to reach finality has dropped below a second. All this while keeping the transactions and the details of the parties involved private. For context, traditional financial infrastructure still takes at least a day to process these transactions.

ZK proofs also solve what enterprises saw as another deterrent.

A bank evaluating blockchains in 2018 had to hire engineers, build a chain from scratch, figure out how to generate proofs, run its own servers, and then see if all this translated to business gains. So much for a system they weren’t even sure would work.

ZKsync, an Ethereum-scaling platform built by Matter Labs, addresses this by giving enterprises a blockchain equivalent of AWS. Its institutional product stack, including Prividium, Connect, Gateway and others, offers chain deployment, transaction processing, proof generation, compliance tooling - including KYC checks, role-based access, login controls, and connectivity to other chains.

The stack allows an enterprise to tailor its configuration and get started with deployment. Think of it as buying blockchain-as-a-service.

ZKsync isn’t the only one here. Canton Network, backed by Goldman Sachs, DTCC, Citadel, and BlackRock, takes a different approach to the problem. Instead of ZK proofs, it uses a permissioned model where approved validators coordinate private transactions between known counterparties.

They are both building connective layers that institutions need. But they disagree on whether trust should come through cryptographic proof or from contractual governance between known parties.

If you ask me, there’s little to separate between permissioned and permissionless approaches so far. Both want to solve the same problem for institutions. In fact, Canton even has better institutional partners than ZKsync.

Read: Wall Street’s Stealth Chain

Yet there is something about it that could prompt institutions to flip over to ZKsync. Canton’s permissioned network works fine as long as the interaction and movement of money is happening between known parties in familiar jurisdictions. But when an enterprise wants to expand across jurisdictions and transact with parties outside Canton’s walled-off jurisdiction, ZKsync is what helps achieve composability there.

It’s this technological breakthrough that convinces banks to adopt blockchains.

But why would banks move away from their age-old, battle-tested systems, no matter how slow they are? Just because there’s a cheaper alternative that works faster?

Do you really think banks went from “blockchains are interesting but impractical” to “blockchains make business sense” just because a technology they knew little about suddenly became economically viable? It’s funny how every technology becomes “strategically important” when businesses start losing money.

Deposits Under Siege

In the past decade, stablecoins have grown into a $300-billion market. They did what banks had refused to do for years: move money fast. Today, each of those digital dollars in circulation left the banking system at some point.

The infrastructure I described above, ZKsync’s Prividium and Canton’s permissioned rails, are what is helping these banks take the fight back to the digital assets. With these blockchains-as-a-service, banks can move their existing deposits just as stablecoins do. They can process and settle transactions with the same speed and finality. There’s also a bonus. Banks can do all this while guaranteeing their depositors with regulatory protections and balance-sheet advantages that only they can offer.

This is already happening in real-life cases.

The Cari Network, launched last month by five US regional banks (Huntington, First Horizon, M&T, KeyCorp, Old National), is tokenising bank deposits on ZKsync’s Prividium. The deposits stay on the banks’ balance sheets, are FDIC-insured, and settle in seconds.

Cari Network isn’t an isolated event.

In February 2026, the UAE’s Central Bank approved DDSC, a dirham-backed stablecoin running on ADI Chain, built with ZKsync’s proving engine.

In June 2025, Deutsche Bank began building a tokenised platform on a ZKsync-powered chain that compresses the timeline of setting up a new fund from months to weeks.

Future of Institutional Finance

There’s one core thought I often come back to when I write on finance: “How will money move in the future?” It’s an interesting question to ask oneself because it tells you about the financial behaviour of individuals and corporations.

I don’t think a majority in either category cares too much about the cardinal principles that crypto stands for. Banks care even less. I am sure the banking leadership team doesn’t sit in a boardroom debating decentralisation versus centralisation. They are surely not bothered if their transactions are processed on Ethereum, Solana or a private network based in Timbuktu.

They care most about privacy, composability and speed. If a system delivers these to an enterprise by making them save a couple of extra dollars, then you’ve got their attention. It helps further if there’s a “strategically important” reason to adopt a new technology (like a stablecoin revolution waiting to steal your business).

So, I expect the convergence of Web2 and Web3 finance to happen around the technology that helps move money more efficiently. That could be via ZKsync or Canton-powered chains that move tokenised versions of fiat currencies. Or it could even be through payment-specific chains that payment companies like Circle’s Arc, Stripe’s Tempo, and Stable are building.

I don’t think there’s going to be a winner between the two approaches. That’s because for banks that want to avoid adopting stablecoins, ZKsync’s blockchain-as-a-service will be the most obvious choice for evolution. Those already integrating stablecoins in their payments will choose digital dollar-supported chains.

But I surely know who will be the biggest loser: the one who stays adamant about using the technology that still moves and settles money based on the date and time.

That’s it for today. I will be back with another deep dive.

Until then, stay curious!
Prathik

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I pay about $5 a month for home internet in India. It’s a 100 Mbps plan with unlimited data, and half the time they throw in a Netflix subscription to sweeten the deal. A few years ago, that same connection would have cost $25 or more. Then a company called Jio entered the market, started a price war with incumbent telcos, and the whole market repriced within a couple of years. Today, internet access in India is so cheap that it barely registers as a household expense.

For the longest time, I assumed this was how things worked everywhere. Once enough cables land and a competitor shows up, prices eventually fall. Africa has 25 submarine cables and over a million kilometers of terrestrial fiber. There’s no shortage of bandwidth at the coast. Yet broadband across the continent still costs about 15% of gross national income per capita, which is seven times the international affordability target. About 600 million people still lack meaningful internet access.

My $5 plan in India would cost over $100 a month in Nairobi, and even the most basic connection starts at $15. The median Kenyan household earns about $170 a month. The average Indian household earns about $250 a month, which is higher but not by a sufficient factor to explain a 10x to 30x gap in what people pay for the internet. There is enough bandwidth to serve the entire coast, but something inland consumes it before it reaches more users.

This piece is about what’s actually broken in the African internet landscape, how a DePIN project called Share is trying to fix it, and why its use of crypto is unlike anything I’ve seen before.

Why Africa Pays the Highest for Internet

To understand that, we need to look at where the money in Africa’s internet ecosystem actually goes. Google’s Equiano gave West Africa twenty times the bandwidth it had before. Meta built 2Africa, the longest subsea cable ever. Between them and the 23 other cables already in the water, African landing stations, the buildings on the coast where submarine cables come ashore, today have more bandwidth than most of the continent can use.

But none of that bandwidth is useful until it reaches the person paying for it, and that last stretch is where the entire problem starts. The next part is turning that into a connection for a household 50 kilometers inland, which means someone has to build local infrastructure, buy upstream capacity, set up billing, and sell service, one building at a time. That work today falls on thousands of small ISPs, most of them one or two-person operations, because the big telcos that could do it have no reason to.

They sell wholesale bandwidth to these small operators, and that’s a good business for them. If they built out the last mile and started selling directly to households, they’d be killing the wholesale contracts that pay them today. A single bulk deal with an ISP brings in steady revenue with almost no support cost. Replacing that with retail means billing millions of people one at a time, running customer support, and competing door-to-door with ten thousand operators who already have the relationships. No telco wants that trade.

Kenya is the easiest place to look at. The regulatory environment is stable, Safaricom runs one of the best mobile money systems in the world through M-Pesa, and multiple submarine cables land right at Mombasa. If any African country should have cheap internet by now, it’s Kenya.

The Communications Authority of Kenya has over 400 registered ISPs on its books. But the real number is much higher. Once you count the neighborhood-level operators who run a single router in a building and resell to a few dozen customers, the total is probably north of 10,000. That’s ten thousand separate internet businesses in a country of 55 million people, most of them serving a handful of users each.

As a result, when someone in Nairobi goes online, their traffic typically passes through three to five of these small networks before it reaches the open internet. Every handoff between them adds cost and adds latency. By the time the signal reaches the end user, the price per gigabyte has multiplied several times over from what it costs at the Mombasa landing station. The bandwidth starts cheap, but it gets expensive on the way to the customer.

Running one of these small ISPs is a terrible business. You buy bandwidth in fixed bundles from an upstream provider and pay upfront before your customers pay you. Every month, you’re guessing how much capacity you’ll need. Buy too little and your service is unusable by evening. Buy too much, and that money is locked up in bandwidth nobody’s using, and you won’t see it back for weeks. There’s no room to invest in better equipment or a backup connection. You run one upstream link, oversell it, and hope the congestion doesn’t get bad enough that your customers switch to a different service.

This is one of the biggest reasons India’s Jio strategy will never work here. Jio walked into a market with a handful of national telcos and undercut them all at once. That only works when there’s a concentrated market to disrupt, and when you can spend $30 billion building your own last-mile infrastructure across a country of 1.4 billion people, losing money for years before seeing a dollar back. Kenya doesn’t have that. It has 55 million people. No Kenyan telco has $30 billion, and even if they did, the market isn’t large enough to justify that kind of spend. So the last mile stays with ten thousand small operators, and nobody above them has the reason or the resources to replace them.

In fact, you can see how fragile the whole arrangement is when something goes wrong. Four subsea cables off West Africa failed in March 2024. Eight countries went offline for days, and repairs took weeks to months. Two months later, SEACOM and EASSY were damaged off the South African coast, and most of East Africa lost access to cloud services. There were plenty of cables. The problem was that nobody inland had built local caching, proper routing, or any backup path. Most of the traffic was being routed through a single upstream link to Europe, even when other cables were still working. When that one path broke, there was no way to reroute and nothing locally cached to fall back on.

What Share Built

So that’s the problem. Thousands of small ISPs with no scale, no bargaining power, buying overpriced bandwidth through chains of middlemen, running on thin margins with no backup infrastructure. And on top of all that, the big telcos have zero incentive to fix any of it.

Share is a DEPIN project that is solving this exact problem by building the missing layer between the landing station and the last mile. The company is based in Kenya and started in Mombasa, and what they’ve put together touches three parts of the stack.

1. The first thing Share did was set up its own points of presence inside Kenya’s major data centers and connect directly to Meta, Google, Akamai, and Cloudflare. These are the content delivery networks that serve most of what people actually do online. YouTube, WhatsApp, Instagram, Netflix. Depending on the market, that’s 70-80% of all internet traffic. When an ISP connects to Share, that traffic no longer has to travel through three to five upstream middlemen to reach a European exchange point and come back. It terminates locally, inside Share’s own network. For the ISP, the cost per gigabyte drops on day one. For the end user, the video they’re streaming now comes from a cache in Kenya instead of being routed through Frankfurt, so it’s faster, too.

2. The second thing is physical fiber. Share laid a 40-kilometer fiber ring around Mombasa. It’s a loop, which means if any one segment gets cut, traffic automatically reroutes in the opposite direction. That ring alone can reach about 1.5 million people without anyone having to rebuild last-mile connections. Along the ring, Share places what it calls micro-PoPs. These are small, standardized network boxes at tower sites and rooftops, where nearby ISPs can plug in and connect to the backbone. Through its own fiber and infrastructure-sharing deals with tower companies and utilities, Share now has access to over 1,000 kilometers of fiber across Kenya. They just moved to Nairobi.

3. The third part is software. Every ISP that connects to Share gets access to a single system that handles routing, billing, customer onboarding, plan management, and revenue sharing. For a small operator who was managing everything on a spreadsheet and a handshake deal with an upstream provider last month, Share entirely changed their business operations. They go from reselling someone else’s marked-up bandwidth to operating as a last-mile partner on a real network with a real backend. Their costs drop, their service gets better, and they keep their customers. Share takes a minority cut of the revenue.

What makes all of this work together and scalable is how Share grows. When a small ISP joins Share, it doesn’t just get better infrastructure; its existing subscriber base immediately migrates to Share’s backbone, meaning Share inherits those customers without having to acquire them. That’s how they went from a test network in Mombasa to covering 8 million people in 15 months.

This is a model where everyone wins. The ISPs get lower costs and better service without losing their customers. The telcos and tower companies that own fiber and tower sites become suppliers to Share, which is a more predictable business than competing against 10,000 small competitors. Share gets a growing network with recurring revenue. Nobody in the arrangement is worse off than they were before, which is probably why it’s held together in a market where nothing else has.

Where Crypto Earns its Place

Most DePIN projects launched between 2020 and 2024 were pretty much the same. Launch a token; use it to pay people to set up hardware, to pay early users to show up, and to fund whatever activity generates a decentralised network. Helium did it. Render did it. A dozen WiFi hotspot projects did it. Most of them never shipped any real infrastructure. Even the ones that did were paying for hardware deployment with token incentives, and the moment the token lost value, the people running the hardware walked away.

Share doesn’t do any of that. The physical network already generates recurring revenue in Kenyan shillings. The company is profitable at the infrastructure level before crypto enters the picture. Crypto is only used in two places, and only because those two places have real problems that traditional finance hasn’t solved.

The first is settlement. Share’s ISPs collect revenue in Kenyan shillings. As the network expands into Uganda, Nigeria, and Ghana, they’ll be collecting in a different local currency in every market. But hardware and wholesale bandwidth are priced in dollars. So you have revenue in a dozen African currencies and costs in USD, and the financial infrastructure to move money between African countries barely exists.

Cross-border B2B payments between African companies today still route through correspondent banks in Europe and New York. The IMF’s numbers put the share of intra-African transactions that actually settle on the continent at roughly 12%. The other 88% takes a detour through Frankfurt or London, takes days to clear, and loses 3 to 5% to FX spreads and bank fees. A Kenyan ISP paying a Nigerian equipment supplier is sending money through Europe to reach the country next door.

The second is financing, and this is the part I think is sharpest.

Each micro-PoP unit is built to the same spec, so you can model what it will earn before you deploy it. All traffic flows through Share’s billing system, so revenue is verifiable on-chain in real time. No bank is going to write a $5,000 loan for a networking box at a Mombasa tower. The deal is too small, the borrower too thin, and the lender would need a local office just to do diligence. But an on-chain structure can underwrite the device itself: a buyer takes a claim on a specific micro-PoP through a smart contract and gets paid based on actual traffic. If the device goes down or users drop off, it shows up in the data immediately. The lender doesn’t need to trust the borrower. They need to trust the data coming off the device, and that data is verifiable.

If this works at scale, and I believe it will, small-ticket African internet infrastructure can be financed with global capital for the first time, one device at a time, without going through a development bank or waiting for a government guarantee.

Markets like Kenya exist all over the developing world. Indonesia’s archipelago has the same problems. Thousands of small operators, deep gaps between coast and interior, upstream pricing controlled by a few large wholesalers. You see it in rural South Asia and parts of Latin America, where submarine cables landed years ago, and nobody built the inland distribution. In each of these places, there is demand and coastal bandwidth, but nobody builds the middle layer because no single company has the incentive to do so.

If the model keeps working in Kenya, and 8 million people over 15 months say it is, this might be the template for how internet infrastructure gets built in fragmented emerging markets over the next decade. I think we’ll look back at Share as proof that DePIN was always supposed to be an infrastructure business that uses crypto to move money and finance hardware, and nothing more than that.

That’s all for today.

Until then, stay curious,
Vaidik

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When Warren Buffett took over Berkshire Hathaway in 1965, he began writing letters to the shareholders of a dying textile mill. In them, he explained in detail where the cash from the mill was being redeployed and why.

Capital allocation became a public affair in a true sense. Despite being owners of a company, shareholders generally trust the management to carry out operations as their fiduciary agents. Buffett’s letters made shareholders feel heard in annual discussions around what the business should become.

Most public companies do capital budgeting in closed boardrooms. Corporate law mandates the disclosure of audited numbers, not the reasoning behind the decisions. But Berkshire’s transparency with reasoning was timely and crucial. Sixty years of letters read like a continuous conversation about where to put the money next.

A version of this practice is now showing up on-chain.

DeFi protocols have their own versions of these boardrooms: backchannels, founder calls, and delegate huddles. Yet the vote, the proposal text, the dissent, the amendments, and the final proposal all rest on the public record.

On April 12, Aave’s token holders voted on a $25 million capital allocation proposal. The vote, which passed with a landslide majority, allows Aave’s token holders to vote on governance, protocol upgrades, and risk parameters.

Beyond Aave, this move helps crypto evolve from debating whether a token has a claim on protocol cash flow to allowing token holders to decide which project to fund next and how much capital to allocate.

In today’s analysis, I will tell you how.

What’s in the Vote?

Aave’s vote matters because of its relevance in the lending marketplace. Aave currently has over $26 billion in total value locked (TVL) and generated about $907 million in fees last year. Most of that flows to suppliers who earn interest on deposits, leaving around $125 million in annual revenue with the protocol. That’s what accrues to the DAO treasury.

As of December 31, 2025, Aave held over $21 billion worth of active loans on its books.

That’s a larger borrow book than Robinhood’s $16.8 billion margin book at the end of 2025, and nearly twice the size of LendingClub’s $11.8 billion in total assets. The latter is a NYSE-listed marketplace lender whose business model most resembles Aave’s.

In 2025, LendingClub, an NYSE-listed marketplace lender with which Aave’s economic model resembles the most, recorded $136 million in net income on a revenue base of a billion dollars. The two-decade-old company closed 2025 with $11.8 billion in total assets. This is a business competing with well-known traditional fintech peers.

LendingClub made $136 million in net income on a $1 billion revenue base in 2025. Aave’s $125 million accrues to the DAO on a loan book nearly twice as large, which means LendingClub earns roughly twice as much per dollar lent.

That’s because Aave is just a protocol. It can’t charge more interest without breaking its own market since it doesn’t own the deposits. Raising the reserve factor would push suppliers to a rival protocol with better yields. LendingClub can charge more because it owns the loans, takes the credit risk, and funds a full bank of underwriters and default provisions to do so.

Aave’s proposal is to route all revenue from Aave-branded products, including the App, the Card, and the Pro institutional tier, to Aave DAO’s treasury. In return, the DAO will pay Aave Labs $25 million plus 75,000 AAVE, to be vested over four years, to keep building.

Aave Labs, which is the development entity behind the Aave protocol, had been keeping a share of product revenue to fund itself. The Cowswap integration on Aave.com applied a 15-25 basis point fee on swaps and sent proceeds totalling roughly $10 million a year, or about 10% of the DAO’s potential revenue, to a private Labs address. ACI's Marc Zeller called it the "stealth privatisation" of the DAO's earnings. Under the new structure, it will be paid by its token holders, on terms they set and against milestones they can withhold disbursements against.

Token holders didn’t approve the ‘Temp Check’ version that was initially proposed in early March. They split the bundle involving the V4, brand, funding, and growth grants into separate votes and stretched vesting from two years to four. They also tied disbursements to milestones instead of writing a single cheque.

Not everyone supported the initial version. Some agreed to the negotiated version, others walked away after a long association.

In the past two months, three of Aave’s most embedded contributor organisations ended their partnership with the protocol. BGD Labs left in February. Aave Chan Initiative (ACI) announced its exit from Aave in March after contributing 61% of governance actions and 48% of protocol income during its three-year tenure. Chaos Labs stepped down from risk management on April 6, after helping scale TVL from $5.2 billion to over $26 billion without material bad debt.

The bigger shift is that large protocols with product-market fit and surplus are now enabling token holders do what public markets typically confine to boardrooms.

Uniswap is moving in the same direction from a different angle. Its UNIfication proposal hinges on protocol fees, routes them into UNI burns, disables Labs-level interface and wallet fees, and funds Labs from the treasury.

In 2025, Uniswap recorded $1 billion in fees, nearly identical to Aave. But almost all of it has historically gone to liquidity providers. Its current annualised protocol revenue stands at $42 million. UNI holders got nothing.

In March alone, Uniswap processed $42 billion in DEX volume. Meanwhile, Robinhood’s app recorded $34 billion in crypto notional volume throughout Q4 2025. Uniswap is doing slightly more than that in just a month.

Two of DeFi’s most-watched protocols are moving toward the same structural move, albeit with different mechanisms. Both of them want to route revenue up to the token layer and then publicly decide where to redeploy it.

The new treasury strategies change who decides how revenue is redistributed once it reaches a treasury. Should the funds be deployed to buy back and burn the tokens? Or deploy them for operating budgets and growth grants? Maybe fund new product lines or save it for a longer runway? All these are capital allocation questions. The same thing that Buffett was answering in his letters for decades.

For years, DeFi has argued whether the token deserves a claim on protocol cash flows. We saw Hyperliquid and pump.fun settle that conversation through their extensive planned buyback programmes.

Read: Burn, Baby, Burn 🔥

What Public Capital Budgeting Requires

Buffett’s letters were voluntary. What makes his act seem more than just a goodwill gesture is the audited financials that back the letters. He had a fiduciary duty that’s enforceable in court. Berkshire shareholders have rights that don’t depend on Buffett’s goodwill; they can sue the company, vote out the board and demand records.

A corporate regulator mandates baseline disclosure regardless of how nice Buffett’s letters might sound.

With DeFi, transparency takes the front seat. On-chain architecture forces every transaction, treasury movement and vote to be public. But that’s not enough to make crypto protocols transparent to the public. Token holders need a collective understanding of the business to make capital budgeting decisions.

The financial statements and filings of publicly listed companies are accessible and legible to the public because of standardised accounting requirements. What Nvidia means by gross revenue is about the same as what Apple might mean. If you can make sense of Nvidia’s balance sheet, you will likely understand the line items in the iPhone-maker’s financial statements, too.

But this standardisation of financial terms is mostly absent in crypto protocols. Terms like revenue and fees are often used interchangeably, while they may mean different things.

Token holders may still read the Aave treasury balance sheet to the cent. But they cannot separate what counts as “Aave-branded product revenue” unless the definitions are standardised. They still need to know what happens if Aave Labs and the DAO disagree on the number.

This isn’t hypothetical. One of the biggest criticisms of Aave’s proposal was on what “100% of revenue” actually meant. Is it gross or net of operational costs? Who verifies it? How do you enforce it?

Even Marc Zeller, the founder of the now-exited ACI, raised these concerns in his X post after acknowledging Aave DAO’s win.

As token holders, you simply cannot allocate what you cannot define.

Checks and Balances

Although the vote signals a transfer of power to the token holders, those who left Aave argue that the transfer is incomplete.

The two teams closest to Aave’s governance machinery, one that coordinated 61% of all governance actions (ACI) and one that wrote the production codebase (BGD Labs), complained about similar things. The entity asking for the money, Aave Labs, was also the one voting to approve it. That’s a conflict of interest.

A budget recipient cannot vote on its own funding.

This is a structural problem in every on-chain capital budget in which founders or core teams hold large token positions. Although theoretically, it’s the token holders who get to decide where the surplus goes, it’s often the largest tokenholder who drafts the proposal.

You may argue that a larger stake brings a larger say in how the company is operated. But if DeFi protocols want to emulate the capital budgeting practices of public companies, they need to ensure similar checks and balances. For instance, minority shareholders are protected against abuse by majority shareholders through legal frameworks.

DeFi needs similar checks and balances. Revenue numbers must be independently verified, including those off-chain. When Venice AI said it would burn VVV using Stripe subscription revenue, DefiLlama’s 0xngmi asked for read-only Stripe access so the off-chain numbers feeding an on-chain claim could actually be audited.

There must be on-chain milestones that trigger capital releases in tranches and reverse them if the milestones aren’t met. Protocols must standardise the disclosure of voting power held by entities that will receive the DAO funds. None of this is hard to achieve. It’s just not desirable because the people who have to agree to be constrained are the same ones writing these proposals.

One team had specifically requested safeguards to ensure on-chain milestone tracking and self-voting limits before supporting the Aave proposal. Those recommendations were ignored, and the proposal was passed anyway.

What Aave’s ‘Win’ Means

The vote itself is not the achievement. Passing a $25 million funding proposal on-chain is not hard when the largest token holder supports it. But there’s a lesson to be learned here.

Token holders rejected the first version. They broke a single mega-proposal into smaller decisions. They doubled the vesting period. They forced a founder-led entity to negotiate terms in public, revise them in public, and accept constraints it didn’t volunteer. This is a step toward achieving capital budgeting in public.

If Aave’s proposal becomes a template, the fact that token holders can reshape a proposal before it passes must become the part that every other protocol copies. Just like in a democracy, a policy isn’t sound enough if it can’t see the light through all dissent and disagreements. Pushback in DAOs is not a dysfunction. It’s what makes DAOs more transparent and stand the test of time.

Uniswap’s UNIfication proposal is going through a similar journey. It needs to address similar questions, such as “Who decides where to allocate the treasury funds?” What is the recourse if something doesn’t work?” These are the questions many other blue-chip DeFi protocols will face. They must understand that the DAO community will not remember buybacks or token burns if the policy decisions are not justified and grounded in reason.

Buffett and Berkshire came to be respected not right after the first letter. Shareholders read years of letters before they gradually trusted the entrepreneur to judiciously apply their funds to profitable use.

That’s it for today. I will be back with another deep dive.

Until then, 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.

Stability can be a mirage. This is often true in finance. You bet on a boring financial instrument thinking it’d offer you steady, reliable returns. It does stick to the template until the underlying fundamentals wobble. These ‘steady bets’ are often more deceptive than the speculative ones. People expect the latter to be risky anyway. But few expect that to happen with steady, boring bets.

We saw this play out about 75 years ago.

In the 1940s, dollar-denominated deposits accumulated in European banks following the Great Depression and World War II. These allowed account holders to hold U.S. dollars at non-U.S. banks as a hedge against local currency devaluation. They offered attractive yields and led to some out-of-the-box thinking. Some account holders, like American companies, got creative by parking dollars abroad to dodge capital controls at home.

The European banks welcomed them all. They accepted these deposits and lent them further at higher interest rates. The glut of these deposits in Europe led to the Eurodollar market, a parallel dollar system that was not regulated by the U.S. Federal Reserve. Things began to unravel as the Cold War started in the late 1940s. More people started demanding their U.S. dollars back, but the banks didn’t have enough physical dollars on hand. The entire cycle crashed.

We see a similar trade happening now in the stablecoin market. Except that the digital dollar issuers seem to have learned from history.

In today’s deep dive, I will explain whether Ethena’s reliance on traditional equity markets can save its stablecoin reserve strategy.

The Initial Act

In early 2024, Ethena launched USDe as a synthetic stablecoin that was different from the rest. USDe was issued as a dollar-pegged asset without actually holding dollars in bank reserves. Instead, it held crypto assets like bitcoin and ether, for every dollar of USDe minted. Simultaneously, it shorted an equivalent amount of crypto futures.

The two positions balanced each other. If BTC goes up, the short position on futures loses what the spot gains. And vice versa. Eventually, the USDe was always worth $1, even without an actual physical dollar in the bank account.

But why should people hold USDe over incumbent cryptocurrencies like USDT orUSDC? They were rewarded for doing so.

The incentive was tailor-made to align with how crypto derivative markets are wired. In a bull market, more traders bet on prices rising. Exchanges charge those bullish bettors a small continuous fee, called the funding rate, and pay it to whoever is on the other side. Ethena was permanently on the other side. It collected those payments and passed them on to USDe holders as yield.

At its peak, the yield crossed 20% annually. In 18 months, USDe’s circulation grew sevenfold to approximately $15 billion, the fastest growth ever recorded by any stablecoin.

Read: The Ethena Speed Run 🏎️💨

I loved the design, except that it was heavily reliant on the crypto markets holding the status quo. It worked in bull markets because they were getting paid for being a minority holding a short position against a majority that were long. But markets flip with time; they always do. When they did, the cracks appeared. On October 11, a day after the largest crypto liquidation wiped out over $19 billion, USDe briefly lost its dollar peg. Ethena’s synthetic stablecoin fell to 65 cents against the dollar on Binance.

USDe’s circulating supply fell from about $15 billion to under $6 billion over five months, starting on October 10.

A Lesson Learned Too Late?

More than $9 billion was redeemed. Perpetual futures, which once accounted for almost 100% of the model’s reserve backing, now represent only 11% of it. The bigger irony is that all of this was avoidable. Ethena should have seen it coming.

The signs were telling. Markets always move in cycles, and crypto was no exception. We have seen it over the past 16 years. A reliance on a single collateral source via perpetual futures, which was closely tied to market movements, was always a ticking bomb.

Even other stablecoin issuers had begun adapting. As the U.S. Fed started reducing interest rates, the top two stablecoin issuers increased their activity to supplement their reserve income. Tether diversified its reserves by adding record levels of gold to its coffers. Circle, the USDC issuer, has been aggressively building its infrastructure revenue stream through Arc, its Layer-1 network, and the Circle Payments Network, a full-stack internet payment system.

But Ethena was slow to act. The slide would have been worse had it not addressed the situation at all. That’s not my observation, but what its founder, Guy Young, admitted in a post on X.

Guy also listed out the measures Ethena has started taking to adapt to the regime change.

The TradFi Fix

Ethena would expand its collateral base to include equities and commodities basis trades, overcollateralised institutional lending, prime brokerage services, and a broader set of real-world assets (RWAs).

Ethena started as a crypto-native synthetic dollar, unlike pioneers like Tether’s USDT and Circle’s USDC, which back their digital dollars by holding physical dollars or equivalent treasury bills in their coffers.

Life has come a full circle for Ethena. It’s now going back to wiring itself into the traditional finance infrastructure to keep paying yield to its holders. And not one, but multiple such sources.

With an equities-basis trade, it pockets the gap between buying spot S&P 500 exposure today and simultaneously shorting its futures. The same strategy that Ethena used with BTC and ETH earlier. That’s a small, but predictable return that is independent of crypto market movement.

Now imagine Ethena following a similar trade across multiple asset classes: commodities such as gold, silver, wheat, and oil, indices, lending markets, and more. Every asset will have a spread that is driven by market supply and demand dynamics. Ethena can run delta-neutral trades across all of them and collect spreads around the clock, regardless of what retail feels about crypto or Bitcoin.

While this reduces dependence on crypto markets, it now moves in line with equity, commodity, or other asset markets. Each time volatility in these markets spikes and liquidity in futures markets dries up, these strategies could also fail. It could squeeze USDe’s revenue further.

But that pessimism is the same as expecting a portfolio well-diversified across asset classes to fail. It can still happen, sure, but it’s rare. Yet that’s how the finance world works; on probability and math. People don’t diversify their portfolios expecting to see a green balance when the entire market is drowned in red. The expectation of diversification is to reduce the likelihood and intensity of losses.

For Ethena, diversifying across uncorrelated yield sources will do the same thing. It will reduce the likelihood that its yield will be squeezed out completely when either one or two of these asset classes underperform.

The Liquidity Test

Ethena’s diversified strategy is the logical solution to tackle market cycles. Spreading exposure across equities, commodities, credit and crypto makes the income stream more resilient. That’s probably the only edge it will have over a T-bill-backed USDT and USDC, which pays its holders no yield.

But the new strategy still faces a strong headwind.

The liability side of USDe is fully liquid, meaning any holder can redeem it at any time. But the assets generating the yield are not perfectly liquid during periods of stress. Equity basis positions could take time to unwind cleanly. Institutional loans have fixed tenors. Collateralised Loan Obligations are not always liquid in choppy markets. This gap between liquid liabilities and imperfectly liquid assets can become a structural tension for any yield-bearing stablecoin. It’s a gap that even a diversified yield strategy can’t fix.

In calmer markets, different asset classes can move to different signals. Gold moves up on inflation fears. Good earnings drive up equities. A geopolitical crisis involving oil-producing nations can inflate oil prices, as we are witnessing now. Crypto funding rates are high because retail is bullish.

But that’s not how they move in extreme stress scenarios. The correlation assumptions can fall apart, cancelling out the diversification advantage. The common denominator tying all these assets is liquidity.

And when things go south across the board, everyone wants to cash out of their positions.

Harry Markowitz won the Nobel Prize for showing that diversification reduces risk. Yet, the 2008 crisis needed no Nobel Prize to show us an anomaly to Harry’s Modern Portfolio Theory (MPT). Academician Nassim Taleb had argued the same in his book The Black Swan. The contention is that correlation is not a constant property of asset pairs. It’s a variable that changes with market conditions.

Despite all these anomalies, it’s important to recognise that these are black swan events that are unavoidable and rare. There’s little anyone can do to predict or control them. A diverse portfolio across asset classes is still likely to outperform a concentrated portfolio reliant on one single asset class. We saw it happen during the money market meltdown in 2008.

The Reserve Primary Fund held short-term corporate debt instead of Treasury bills because the spread was attractive. When Lehman Brothers failed, that paper became worthless overnight.

Overcollateralisation of loans is one of Ethena’s responses to this. If borrowers post more collateral than they borrow, losses are theoretically absorbed before they reach USDe holders. But overcollateralisation ratios are calibrated to historical volatility ranges. Stress events can spill outside those ranges.

No strategy will be free from risk. Ethena’s task will be to inspire enough confidence in investors to believe that its new, diversified strategy is better positioned than the earlier model , which depended on a single crypto market dynamic.

That’s it for today. I will be back with another deep dive.

Until then, 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.

“The farther backward you can look, the farther forward you are likely to see” - Winston Churchill

Hello,

The current state of Digital Asset Treasuries (DATs) bears a striking resemblance to America’s closed-end funds of the 1920s. People purchased shares in closed-end funds, which then bought stocks in the public market. Indirectly, investors gained beta exposure to these stocks in the market and paid a premium in return for those shares. The speculative premiums on these funds peaked at 30% above the net asset values (NAV) of the funds until the stock market bubble of 1929 turned them into discounts. Investors learnt it the hard way that the math didn’t add up.

When I read this, it felt like déjà vu about what we saw unfold in the DATs ecosystem over the past few months. Hard not to draw parallels.

Bitcoin-based DATs, like Strategy, offered leveraged beta on BTC’s price. Investors paid a premium for it. The flywheel worked as crypto rallied, but it fell apart when the markets slumped. The trick to making DATs sustainable across market cycles is in what the token’s appreciation is linked to. Most crypto treasuries around BTC and ETH were leveraged bets that the prices of the underlying cryptocurrencies would go up.

But what if the token price were closely tied to the revenue generated by its ecosystem? What if it had little correlation to uncertainties? Even better, what if it were negatively correlated to how other asset classes behaved during macroeconomic uncertainties?

In today’s deep dive, I will explore why asset selection for DATs could decide how sustainable their treasury strategies are, using the case of a HYPE-based digital asset treasury (DAT) company.

Hyperliquid Strategies (ticker: PURR) started its DAT journey by incorporating Rorschach LLC, a Special-Purpose Acquisition Company (SPAC), and hold. It then reverse-merged the SPAC with Sonnet BioTherapeutics, a struggling Nasdaq-listed biotech company whose flagship cancer drug had spent years seeking a commercial partner.

It’s the same playbook that Twenty One Capital had used for BTC, backed by Tether, Cantor Fitzgerald, and Softbank.

Read: SPAC to the Future ⌛️

At launch, PURR held 12.6 million HYPE tokens, valued at $583 million, and $305 million in cash. Earlier this year, it deployed $129.5 million to purchase an additional five million HYPE tokens.

But why does Hyperliquid Strategy deserve a better outcome than the previous DATs?

A Different Jar

In the first wave of DATs, the wrapper itself was the innovation. A company could swap BTC for ETH, ETH for SOL, and the playbook worked just fine. That’s because the flywheel was built around the premium on net asset value (NAV) of the companies. It didn’t matter what the underlying asset was. As long as DAT shares traded at a premium, investors bought in, expecting more upside beta on the token’s price appreciation.

However, that bet flipped when the market struggled to recover from the crypto industry’s largest single-day liquidation.

Although the liquidations were sudden and followed US President Donald Trump’s new trade tariff threats against China, what happened with the DATs was not unexpected.

A couple of months before the liquidation event, we wrote about the risks that the leader of the BTC treasury pack, Strategy, carried in its DAT model:

Fast forward to mid-November, and we saw what had been feared about DATs for months unravel in real time: sliding mNAVs, slowing treasury purchases, and falling DAT company share prices.

Read: Where’s DAT Beta? 🎁

The problem with the playbook was that all top three treasury assets - BTC, ETH, and SOL - were tied together by a common, awkward feature. They didn’t generate cash flows. Their price appreciation was linked to how people traded the cryptocurrency. And that trading was driven by multiple factors: ETF flows, institutional interest, conversations on online forums and communities, and investors’ perceptions of BTC’s role as digital gold in the macroeconomic landscape.

Surely, ETH and SOL generated staking rewards to offset their slow token appreciation. But staking rewards are paid in newly minted tokens. Each time ETH and SOL staking rewards are paid, they dilute current token holders to pay validators.

A treasury holding any of these assets, whether BTC, ETH, or SOL, acts like a closed-end fund with a single non-dividend-paying position. The only way it makes money is if the token price rises or if the premium to NAV widens. The first is beta, and the second is driven by narrative.

Although Ethereum and Solana generate fees, a comparatively small portion of revenue gets routed back to its holders. In 2025, Ethereum generated about $515 million in chain fees, while Solana collected $645 million. Most of it didn’t reach token holders; it was either captured by validators or offset by fresh issuance.

Compare that with almost a billion dollars in fees that the Hyperliquid protocol generated last year. It becomes even more convincing when you factor in that 97% of those fees were routed back to HYPE holders through buybacks via the Assistance Fund.

Read: Burn, Baby, Burn 🔥

Hyperliquid now runs $5-7 billion in daily perp volume, roughly $200 billion a month, generating around $730 million in annualised fees from trading activity. So, each dollar traded on Hyperliquid contributes toward strengthening the underlying fundamentals of HYPE’s pricing.

This makes HYPE treasuries feel less like holding BTC or ETH in a vault and waiting for the market to value it. Instead, it feels like holding a receipt against the fee stream of a derivatives exchange.

Any listed wrapper holding HYPE, including the most recent bet by PURR, is still fundamentally a bet on HYPE’s price. Its corporate structure is the same as that of a BTC, ETH, or SOL treasury company. This makes it easy to look at them through the same lens. Yet I am more optimistic about a HYPE treasury company given the underlying factors driving the token’s price movement.

The share price of PURR reflects an indirect claim on the present value of all cash flows that the Hyperliquid protocol can generate from its derivatives business.

You don’t have to take my word for it. Hyperliquid has shown it multiple times recently.

A Proven Case

During the US-Israel-Iran war last month, risk assets and traditional markets stumbled. HYPE rallied 40%, while S&P and BTC lingered. The former fell by 3-5%, while the latter gained 5%.

Since the largest crypto liquidation event on October 10, HYPE has appreciated by about 60% while BTC slid by 40%.

It wasn’t just a coincidence. Volatility driven by uncertainty is bad for a passive store of value and excellent for a derivatives exchange. Uncertainty drives perp traders to hedge their positions. Liquidation events generate fees on both sides of the trade. The same conditions that eat into the mNAVs of BTC treasuries become conducive for printing more money for a perps venue.

The bear market that rang a death knell for BTC and ETH treasuries brought record volume and fees for Hyperliquid’s ecosystem. While the former have no option but to wait out the market meltdown, Hyperliquid’s P&L thrives in these conditions.

Hyperliquid’s HIP-3 markets have only strengthened this thesis by bringing traditional assets, including metals like Silver and Gold, on the blockchain and enabling investors across financial markets to express their opinions across asset classes.

Read: Hyperliquid is Taking on CME, not Binance

This is the single biggest reason I believe HYPE’s DAT strategy stands apart from the rest.

Nobody’s Safe

PURR’s DAT strategy is still a bet on HYPE’s price. Hyperliquid could lose its perp market share to competitors like Lighter, Aster, or some yet-to-be yet conceived protocol.

PURR’s institutional backers pitched their DAT strategy as “the only way US investors can access HYPE”. But if fundhouses get approval for their pending HYPE spot ETFs, it could make the entire wrapper obsolete. Both 21Shares and Grayscale have filed their applications.

However, what inspires confidence despite these challenges is the choice of the underlying asset.

The older DATs had to worry about retaining the premium on their NAVs. This is a function of market psychology and investor confidence in the model. A HYPE-based DAT has to answer a simpler question: will Hyperliquid keep earning? This question is more a function of weekly fee data, perp market share, protocol’s roadmap - which also has HIP-4 lined up.

Read: Why HIP-4 Will Take Over Finance

All of these are numbers an analyst can use to make informed decisions. The analyst can still falter, but there’s data that backs the answer.

There’s a counterargument here.

What if Ethereum and Solana overtake Hyperliquid in terms of fees generated? That’s not impossible. But it becomes far more difficult when you consider the revenue ploughed back to HYPE holders through buybacks.

Although Ethereum routes a portion of its fees back to ETH holders, it is offset entirely by the new ETH it issues to validators. Solana’s fees accrue to validators, who keep them. Little trickles down to Solana holders. For either Ethereum or Solana to match what Hyperliquid does with its token, they would need to rewrite the underlying tokenomics. Along with that, the network activity will also have to multiply several times from the current level. None of them is an overnight process.

Even if it happens, I expect the same thesis to hold true. I don’t claim that HYPE will always be the only successful asset for DATs. I believe that DATs built on assets whose ecosystem generates consistent revenue for its holders will outlive DATs built on assets that do not generate consistent income.

Both these models are significantly different. The first wave of DATs expected investors to underwrite by believing in a narrative. The second expects investors to believe in the cash flows.

The closed-end funds that survived the 1929 bubble were those whose stocks continued to pay dividends during the drawdown. Everything else was simply a wrapper around a bet.

HYPE-based DATs might still end up in the same graveyard as the other DATs. Nobody knows for sure. But their critique will most likely be an argument about market share, fee durability and other fundamental business metrics. At least it won’t be another debate that ends with “I told you so,” as we saw with the collapse of BTC DATs.

That’s it for today. I will be back with another deep dive.

Until then, 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.

A clock is a bad place to hide a delay. For decades, financial markets were built around the speed of incumbent communication. They introduced closing bells, batch settlement, and regional exchanges, which made sense when information moved slowly. But that has all changed. Capital doesn’t wait. Just like water always finds a crack, so does capital. Financial gravity pulls it toward the fastest route to price information. That’s the law of markets. Its constituents don’t tolerate inefficiencies forever.

This is what I observed when I zoomed out from the financial market developments over the last fortnight.

In today’s piece, I will help you understand what’s breaking down the old, bundled structure of financial markets into a more efficient, unbundled one across venues, wrappers, and time.

Change of Guard

I have been studying finance for over a decade now. In the first half of my journey, I viewed a traditional stock exchange as synonymous with markets. For most of their evolution, it was the one place where everyone, and everything, came together. Buyers, sellers, regulators, and the technology driving the market. It had indices tracking its constituents and a clock that told everyone when they could and could not trade.

But that has changed in the past few years. In fact, just in the past fortnight, we have seen multiple developments that confirm this shift.

On March 18, S&P Dow Jones Indices licensed the S&P 500 to Trade[XYZ], allowing the HIP-3 market deployer to launch the first and only perpetual derivative contract for the S&P 500 on Hyperliquid’s exchange. The S&P 500 is the most-tracked gauge of U.S. large-cap equities across the globe. It tracks the 500 leading U.S. companies, covering ~80% of total U.S. market capitalisation, totalling over $61 trillion. The index covers at least half of the entire global equity market.

That’s nearly a 70-year-old index being listed on a market that’s barely six months old.

Read: Everything Is a Ticker 📊

A day after S&P’s announcement, the U.S. Securities and Exchange Commission (SEC) approved Nasdaq’s request to trade and settle certain stocks in tokenised form. Nasdaq is one of the most active trading venues in the world. Its notional trading volume often exceeds that of the NYSE, the world’s largest exchange by market cap.

On March 16, Cboe Global Markets submitted a proposal to the SEC to launch “near 24x5 U.S. equities trading”. The biggest operating engine behind American financial exchanges said it was ready to deliver around-the-clock equities trading as early as December 2026.

But why? More people are demanding extended trading hours for U.S. equities.

All three developments collectively target the outdated bundled structure. Hyperliquid’s perp market on the S&P 500 index challenges the decades-old practice of investors being able to trade traditional indices only via traditional markets. It also makes trading on one of the most-tracked large-cap indices possible 24/7 worldwide.

Nasdaq’s tokenised equity trading move is targeting the infrastructure. It introduces a new wrapper that allows the same share to be traded differently. Earlier attempts at tokenised equity faced criticism from the industry.

The investors questioned whether these tokens would offer the same rights as the original shares. I wrote about this here.

But what if I offer the same equity exposure via a token on a blockchain, without losing the voting rights and legal protections that came with the original dematerialised share, won’t you take it?

Why should you, and what’s in it for you?

Now, what if you were an investor outside the U.S. who wanted easier access to the equity market of the world’s largest economy? What if that tokenised share made it easier for you to integrate it with collateral and lending systems?

The benefits compound when you factor in round-the-clock trading.

That’s what the Cboe is attacking. Its near-24/5 trading proposal is its way of acknowledging that capital doesn’t wait for office hours. Traders would always want to express their opinions as soon as they receive information. If Cboe didn’t give them a market to express at that time, then the traders would flee to the market that does.

None of what I claim is a hypothesis or “could happen in the near future”. It’s happening as we speak.

An Unbundled Future

Nowhere is the adoption of unbundled pieces of finance more evident than in Hyperliquid’s HIP-3 markets, which launched only in late October 2025.

In the past month alone, HIP-3 markets added $72 billion to cumulative trading volume. In the preceding four months, the cumulative trading volume stood at $78 billion.

In March, Trade[XYZ]’s perp markets on traditional financial commodities and stocks consistently accounted for 90% of the daily trading on HIP-3. But that’s not even the most interesting aspect.

More than half of Trade[XYZ]’s trading came from just perpetual markets on silver, crude oil, Brent oil and gold. I wrote an entire piece at the start of this year when this trend first began to emerge.

Read: Hyperliquid: House of Finance 🏦

In that piece, I explained why traders prefer to trade commodities on-chain. Hyperliquid offered a single venue for trading both spot crypto and perpetual contracts on crypto and traditional assets. This provided not just ease of trading on a unified platform, but also better liquidity, a single user interface, and tighter bid-ask spreads.

Traders still wanted to trade on some of the largest and most popular assets across commodities, listed companies, large private companies and indices. You could be wanting to trade Silver, Gold, Oil, Tesla, Apple, Amazon, Google, the indices tracking the top 100 U.S. non-financial companies, and the S&P 500 - and do all of it on Hyperliquid.

HIP-3 unbundled the ability to invest in these assets from the existing exchange infrastructure, while still tracking the underlying assets from their original base. So, when you go long on a perp contract for Silver on HIP-3, the underlying asset it was tracking was still linked to the value of one troy ounce of silver on Pyth’s data feed.

What made traders switch to trading Silver on HIP-3 from their earlier platforms was that HIP-3 didn’t discriminate between U.S. and non-U.S. traders. It didn’t follow any one clock. Whenever there was an event that made traders want to express their opinions by pricing assets, HIP-3 offered them a market. Irrespective of the trader’s geographic location or time zone.

The result is evident in the growth of Open Interest (OI) on Hyperliquid over the past few weeks. OI measures the total value of outstanding derivative positions. Unlike trading volume, which captures activity, OI reflects commitment.

OI doubled from $1.13 billion on March 1 to $2.2 billion on April 1. This shows the conviction with which traders are locking in their money on Hyperliquid’s perpetual contracts.

These metrics demonstrate that when you make access to markets easier with fewer frictions, traders will not remain loyal to a platform or one asset class. They will adopt whatever gives them volatility, convenience, and liquidity.

That’s why legacy institutions like S&P, Nasdaq, and Cboe are making moves to acknowledge this behaviour.

At least two recent incidents prove how important round-the-clock trading and volatility are for traders.

Saurabh wrote in his tweet for Decentralised.Co: “On February 28, the U.S. and Israel struck Iran when the traditional markets were closed. Within hours, oil-linked perpetuals on Hyperliquid surged 5% as traders priced in the shock in real time.”

Trading on oil-linked perps shot up from $200 million to $6 billion in cumulative volume within just two weeks after the war began.

One of the concerns with newer platforms is liquidity. If there’s not enough liquidity, the bid-ask spread could widen, leading to worse pricing for traders than on other platforms.

Hyperliquid demonstrated its depth of liquidity last week, when U.S. President Donald Trump and Iranian officials were going back and forth about having “productive talks”. The newly launched S&P 500 perp on HIP-3 tracked the sequence of moves of the underlying S&P 500 on CME’s E-mini futures down to the minute.

Although the on-chain perp sat about 50–70 points below ES, the magnitude of the moves was similar.

What This Means

For decades, traditional markets remained bundled and controlled the venue (exchange), the time (trading hours), and the wrapper (indices/contracts).

They preferred to maintain the status quo because they failed to introduce infrastructure to address inefficiencies such as time delays, restricted trading hours, and regulatory limitations for non-U.S. investors. Instead, they disguised these inefficiencies and offered them to investors by calling them procedural systems put in place to offer a trustworthy and credible institution.

People traded and invested anyway. Not because they were foolish or bought into the story that bundled legacy financial markets sold to them. They did so because they had no other option. That started to change when blockchain offered the world on-chain markets that made trading and investing easier than ever before.

People saw the option and took it.

They did not and will not care if the market structure changes. They wouldn’t care less whether the new structure was bundled or unbundled. Whether the incumbents like it or not, the trader and investor communities will adopt the new market structure as long as they have better access to express their opinions through financial instruments. It won’t matter whether that structure comes from traditional giants such as Nasdaq, Cboe, or the S&P 500, or from permissionless platforms running on blockchains.

Finance, as it always has, will continue to evolve and adopt whatever structure narrows the gap between the occurrence of an event and the expression of an opinion through price.

Important events happen round-the-clock across the globe. Why, then, should a price wait for a clock to start ticking on a Monday morning in a glassed building in New York?

That’s it for today. I will be back with another deep dive.

Until then, 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.

AI, much like a religion, remains privately financed and valued, within closed doors. A select few firms raise huge sums, hire the best researchers, rent the biggest clusters and let the rest of the market infer value from funding rounds announced months apart. ‘Valuation’ has often been a number agreed upon in a room and not a price discovered in a free-flowing market. By the time ordinary investors see the price, most of the upside has already been absorbed by the early players.

Bittensor’s wager is that AI should not be financed like that, and I am fascinated by what it’s building. Not because it builds any better models than the OpenAIs, Anthropics and Googles of the world. At least not yet. But it’s found a decentralised way to judge, fund, and price AI projects in public before they become conventional companies.

This approach is notably different from many decentralised attempts we have seen in the previous AI waves.

Bittensor’s subnets are backing teams, rewarding execution, cutting off laggards and repricing the whole AI in real time. This is unlike any previous attempt to price AI. I know it’s a brutal way to build AI, but it’s also a more honest one.

In today’s deep dive, I will walk you through how Bittensor’s model works and why it could outperform any previous attempts at AI pricing.

Shall we?

The Room Where AI Gets Priced

In Q1 2025 alone, AI start-ups secured $73.1 billion, or 58% of all global venture funding, despite warnings from investors like GIC and TPG that some market segments were being valued at exorbitant multiples, with little operating history to back up these valuations.

This model works for founders, insiders and late-stage investors, but not for others. It leaves out those who provide the crucial compute resources, developers who build on open models, and early consumer supporters. Even open-source AI doesn’t change this. The money still pools among cloud contracts, deployment layers, enterprise wrappers, support, security, and distribution.

Throughout the journey, while the general public contributes to creating value, it’s the select few who bear the fruit. Although this has been the status quo for a long time, what’s changed is the rise of the open model AI economy.

Enterprises are increasingly adopting open-source AI models for on-premise, sovereign, and specialised workloads, especially in highly regulated sectors such as telecommunications and banking, Red Hat Developer noted in its report. It serves enterprises looking to deploy AI to monitor, automate, and scale AI workloads, rather than just reference an AI model.

Larger firms like McKinsey have also endorsed this idea. The firm’s survey found that more than half of the respondents were already using open-source AI across their technology stack. The survey included more than 700 technology leaders and senior developers across 41 countries.

Bittensor’s model takes cognisance of all these changes and challenges the current model of pricing an AI project.

The crypto natives are losing their minds over Bittensor’s native $TAO token, which has doubled in price over the past month. Some others are busy talking about decentralised versus centralised AI. But what’s more important to me is to probe what a more accurate way of pricing AI is. Bittensor feels it’s one where the people financing, building, validating and using the AI meet in one market and price it based on open metrics.

Taking AI to Public Markets

Bittensor is easier to understand when you think of it as a network of mini AI economies rather than as a single token.

Each subnet is a specialised market for a specific task in the AI stack. It could focus on interference, distributed training, prediction signals or computation. Subnet owners set the incentive structure and tasks they want to accomplish; miners carry them out, while validators judge and score them. Stakers can support specific validators by staking TAO with them.

The incentive structure became more interesting after Bittensor announced the Dynamic TAO upgrade in February last year. With this, each subnet got its own token and liquidity pool. Bittensor stopped being a single, broad AI trade and became a system with many smaller AI ventures living within it.

Later in 2025, Bittensor made rewards depend more on net TAO inflows than on stale token prices. The icing on the cake came in December with the first halving of TAO issuance, reducing the daily issuance to 3,600 TAO. This forces the financiers to choose where to place their capital. It turned the AI marketplace into a survival of the fittest.

Web3 researcher and writer Jeff aptly terms this “the dynamics of Darwinian AI” and summarises it beautifully in the newsletter 0xJeff.

Darwinism = evolution through natural selection. Human competes and all the good traits that help with survival keep on getting passed on to the next generation.

Similar concept is being applied within Bittensor across a couple of layers:

Subnet Competition: Subnets compete for a share of 3,600 TAO incentives. Top subnets ensure they can survive longer with the incentives.

Miner Competition: Miners compete to deliver the best work. Depending on the subnet, people across the world compete to deliver work that meets subnet KPIs. Top performers receive highest share of the 41% of the alpha token incentives.

Validator & Investor Competition: Validators also compete to validate miners task while investors compete in investing in the right subnet(s) that perform

What happens if you don’t compete OR you don’t perform?

Death.

Subnets get delisted (Yeah.. that’s a thing, you get deleted).

This is where the comparison with traditional AI becomes useful.

In the conventional model, a founder pitches a company, raises equity, hires a team, builds in private and hopes the market agrees with the valuation.

Bittensor flips this by publicising the bet much earlier in the market. Here, entrepreneurs start by launching a subnet, followed by GPU operators contributing compute. The developers and researchers then contribute work, after which investors buy exposure through TAO or specific subnet tokens. Customers follow by paying for the underlying service. The market collectively prices the project by considering everything at the end.

What I like most about it is that it reimagines the capital market for every stakeholder.

Investors get to continuously discover price, unlike in private startups, where they have to wait for the next funding round. In fact, Bittensor lets them take either a broad view of the overall ecosystem through TAO or make a narrower, focused wager on a single subnet they believe in most.

For builders, the appeal is in not being restricted to Anthropic, OpenAI or other elite hyperscalers to participate in the upside of the AI narrative.

It offers entrepreneurs a capital market around their idea even before it has matured into a full-fledged company, something we never see in the venture industry. You can see this playing out in how capital has clustered within the network. A small set of subnets now attracts a disproportionate share of TAO inflows and emissions, while others lag. The top five subnets by market cap account for almost a third of the cumulative market cap of 128 subnets.

For customers, the system can provide cheaper, more flexible access to open-model infrastructure.

Beyond all this, the Bittensor model appeals to all stakeholders more because it not only sounds fairer but is also commercially viable.

When the Market Grew Legs

This is evident in how institutions are seeing Bittensor as more investable.

In December 2025, Grayscale Bittensor Trust began trading on OTCQX, a top marketplace for over-the-counter stocks. The wrapper gives traditional investors a familiar route to an unfamiliar but highly demanded product.

This is how any new market grows legs: by finding a wrapper, a ticker, a price on a screen and a way into one’s brokerage account. We all saw this with Bitcoin and Ethereum ETFs and Digital Asset Treasuries (DATs). Bittensor might not command the same mindspace in the crypto market as Bitcoin and Ethereum, but Grayscale’s trust is a sign that the institution’s curiosity in it has matured from theory to product.

Bittensor’s work has attracted acknowledgement even from the top echelons of the elite industry that it promises to disrupt.

When Chamath Palihapitiya, a renowned venture capitalist and entrepreneur, brought up Bittensor’s distributed training run to Jensen Huang, the Nvidia CEO did not downplay it as an inferior crypto achievement. He called it a “modern version of Folding@home”, a term for a decentralised, distributed project that uses excess computing from volunteer computers to simulate protein folding or solve other complicated problems.

This acknowledgement positions Bittensor within a longer history of distributed computing rather than within the usual token-cycle narratives.

The recent accomplishment by Templar, one of Bittensor’s top subnets, adds more technical weight to what Bittensor can achieve.

Its Covenant-72B model describes a 72-billion-parameter model trained from scratch on 1.1 trillion tokens by 20+ globally distributed participants coordinated through Bittensor. On the published benchmark table, Covenant-72B posts an MMLU score of 67.11, versus 65.63 for LLaMA-2-70B.

In plain English, that’s still not enough to beat OpenAI or Anthropic. Yet, it does enough to prove that decentralised coordination can produce commercially relevant AI infrastructure.

Subnets such as Chutes are explicitly positioned as decentralised serverless AI compute platforms, while Bittensor’s own documentation describes subnets as separate competition markets for digital commodities such as inference, training and related AI work. It shows that the market is not pricing AI as a vague narrative, but is pricing specific pieces of the stack independently.

The Demand-Side Dilemma

Bittensor’s supply side is more transparent than any other AI marketplace. You can see emissions, staking flows, which subnets attract the most capital and which don’t. The concern arises on the clarity, or the lack of it, on the demand side.

The blockchain records token movements but doesn’t collect data on customer retention, API usage quality, margins, or audited revenue. So, even when a subnet appears commercially thriving, you are often still inferring business quality from market structure rather than from financial statements.

Pine Analytics makes a sharp and pointed criticism in its sections on “Supply Transparency vs. Demand Opacity” and “Chutes (SN64): The Subsidy Behind the Savings” here.

They point out that some of Bittensor’s strongest commercial claims may still be subsidy-led. In this case, these subsidies accrue internally to subnets as TAO emissions. Pine estimates that the entire network’s identifiable external revenue is still tiny relative to the value implied by TAO.

This is evident in the fact that Bittensor’s largest subnet, Chutes, receives $52 million in TAO emissions annually, while generating $2.4 million in external revenue. Without the subsidy, it could cost Chutes a fortune to carry out its operations.

All this doesn’t take anything away from the Bittensor’s model. It merely acknowledges that the market may be pricing AI ambition better than it is pricing AI cash flow today.

This is all the more reason why I am interested in Bittensor’s journey.

It has all the signs of a maturing ecosystem. It hasn’t put to rest the ‘decentralised AI’ debate. It is still perfecting the most accurate way to value AI projects. Yet, it has taken strides towards exposing what the private market has chosen to ignore all this time. And it does so by letting the belief trade prices and valuations in the open.

While private AI players ask the world to trust a room to decide valuations in the trillions of dollars, Bittensor asks to trust the public market.

I know for sure that the latter is not perfect, but I also know and appreciate transparency when I see it.

That’s it for today. I will be back with another deep dive.

Until then, 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.

Small annoyances can be life-saving.

Consider the reminder in your car that keeps beeping until you buckle your seat belt. The persistent beep is annoying, and many complain about it. But that persistent beep likely drives countless people to tighten their belts. The result? The Insurance Institute for Highway Safety (IIHS) estimates that these persistent reminders save about 1,500 lives every year in the U.S. alone. Life-saving indeed.

Small annoyances can also be fortune-saving.

One such annoyance in modern banking occurs when you think you have completed a wire transfer, only to be interrupted. You enter the account number, routing number, and recipient name. Now, instead of completing the transfer, your bank pauses to confirm whether the payee name matches the account name on file. It adds an extra click. Breaks a rhythm. It can feel, in product teams’ language, like friction. Yet this pause has become one of the most effective ways to secure payments worldwide.

The ‘Confirmation of Payee’ service by Pay.UK, which enables individuals and organisations in the UK to transfer money, today covers more than 99% of payments made through various payment channels. This service has grown from 14,000 checks a month in June 2020 to more than 70 million checks monthly by July 2025. It has reduced “incorrect account” transactions by 59% and financial losses to end-users by 20-40%.

This is crucial at a time when the financial industry has spent over a decade trying to make transactions invisible. We have seen ‘Tap Once’, ‘Swipe Once’, ‘Trade with a Click’, and similar efforts to make money move silently in the background. The industry’s instinct has often been to treat every pause as a flaw. As finance evolved, it became increasingly obsessed with seamlessness. But this evolution has repeatedly reminded us that some of these “frictions” are, in fact, essential brakes that keep the system from derailing.

TradFi’s Need for Brakes

Today, finance has embedded these brakes into every new piece of infrastructure it builds.

In the U.S., brokers with market access are required to implement risk controls that limit their financial exposure and ensure regulatory compliance. When the Securities and Exchange Commission (SEC) adopted Rule 15c3-5, it said the rule aimed to address the risks posed by automated, high-speed trading and prevent unfiltered access to exchanges.

The reason finance continues to revisit this lesson is simple: when the brakes fail, the damage is often worse than what the institutions can recover from.

Back in 1987, when Black Monday wiped 22% off the Dow in a single session, the Brady Commission recommended a pause button in “circuit breakers” to mandate a 15-minute halt triggered by percentage drops. Without the brakes, Black Monday wiped out $1.7 trillion across the globe in a single day. Its inflation-adjusted value today would be over $4.7 trillion, more than Germany’s current GDP, the world’s third-largest economy.

These brakes taught the finance world that sometimes the only way to maintain speed is to briefly stop the machine. In some other cases, a short pause does the job.

In August 2012, the Knight Capital Group suffered from a software problem that caused its computers to buy and sell millions of shares in just 45 minutes. The glitch led to a $440 million loss in less than an hour, driving the market maker close to bankruptcy. Knight Capital had optimised its systems for speed, which is crucial in the business of markets. But an unchecked system with no brakes can bring the fastest systems to a grinding halt. Lesson? The faster the system, the more valuable a brake becomes.

Retail finance has had its own problems.

For years, brokerages worked to make risky products feel easy to use for driving retail user growth. They persisted until it cost them trust. In its 2021 disciplinary action against Robinhood, FINRA said that the firm failed to exercise due diligence before approving customers for options trading and relied heavily on automated “approval bots” with limited oversight. The not-for-profit self-regulatory organisation that oversees investor protection claimed that Robinhood’s systems approved customers based on inconsistent or illogical information. FINRA said that the firm’s systems allowed applicants whose risk profiles should have raised obvious questions.

Robinhood’s systems were optimised to process applications quickly and avoid delays for prospective customers. What was missing was a meaningful pause between curiosity and safety. There was speed, but no brakes.

Curious Case of Crypto

The recent Aave-CoW fiasco in the crypto landscape takes the need for brakes in finance to a different level altogether.

On March 12, a user executed a $50 million swap through the CoW Swap, a decentralised exchange (DEX) aggregator that is supposed to protect users from bots front-running their transactions. The swap was integrated into the front end of Aave, a DeFi protocol. Due to poor liquidity, the user got $36,930 worth of tokens in return for $50 million.

While Aave explained in its post-mortem that the user had ignored an explicit high-price-impact warning, its founder and CEO, Stani Kulechov, posted on X that the Aave team “will be investigating ways to improve these safeguards going forward.”

When you strip away the jargon, what’s clear is that a fast interface allowed a catastrophic trade to proceed too far before the system reacted. Though some may argue about the user’s discretion and ignorance of the warning. But treating this as a one-off issue would be convenient and counterintuitive for the growth of newer financial infrastructure, such as blockchain.

If crypto wants to avoid repeating the same mistakes, the solution is to build smarter execution layers. Some DeFi trading protocols are already moving in that direction.

Definitive.Fi, for instance, argues that large on-chain trades should not simply be routed to whichever path is technically available. They should be simulated before submission, checked against realistic market conditions, split into smaller tranches when needed, and routed across a wider pool of liquidity. So, a good trading system should not just check whether it can honour a trade, but also check the optimal route it should take to fulfil the order.

Trust and additional safeguards are not nice-to-have features for any emerging infrastructure. More so, in finance. A product that makes trading, lending or moving money feel effortless can help grow faster, but comes back to bite at the first instance of failure. We saw this pattern with all the above traditional finance cases. Systems tried to minimise the visible friction points - even if they were necessary brakes, hid the complexity and hoped the smoothness would earn more consumer confidence.

But confidence in finance is seldom won that way. It is won when institutions identify moments that deserve interruption and act by introducing annoying but necessary brakes. The same way as Pay.UK’s Confirmation of Payee worked. It is definitely not a pleasant experience to be repeatedly asked to confirm a bank account name, but it introduces a brake right at the moment a mistake could become expensive and irreversible.

Aave’s Stani understands this. That’s precisely why he accepts that customers do not always know how an order should be routed, who is being paid along the way, or whether a better venue exists. Such understanding is more crucial in a nascent industry such as crypto and blockchain, where few users understand the technical flow of a transaction and the consequences of their every click. In such cases, acknowledging a pain point and taking a step to address it goes a long way in reinforcing consumer trust.

What makes it tricky is that there is a thin line separating brakes from random inconveniences and friction. Good brakes don’t compromise speed altogether. They are minor resistances timed with precision. In the case of Aave-CoW’s swap, one can imagine a good brake as an economic sanity check. One that enables a system to scan more venues before routing, keep order intent away from predatory actors, simulate outcomes before execution, and break up large trades so that users are not punished for size. They are part of what makes financial infrastructure trustworthy.

The difference matters because finance still has bad friction points that need to be resolved. There is endless paperwork that serves no one, inefficient compliance procedures that slow down the whole process, hidden fees disguised as part of the process and needlessly clunky onboarding that turns away new users.

None of these should be defended. The case for brakes is not a justification for uglier products or more pop-ups. It is about designing pauses when users are about to make irreversible decisions with incomplete information. Especially when customers are operating with large orders in thin markets, handling high-risk products, exploring new payment destinations, and taking one-click actions where the downside is immediate and speed is not paramount.

There’s also a business lesson here.

The financial industry often talks about building safeguards once a product-market fit is found. That gets the order wrong. In finance, safeguards are integral to product-market fit. When implemented properly, safeguards won’t even feel like brakes. Pay.UK’s case reinforces that Confirmation of Payee is not a nice-to-have anti-fraud feature. It’s become a “utility service that customers expect to see” when they transact using the system.

The emerging financial infrastructure, such as blockchain, aims to earn trust and withstand mistakes, scandals, and market stress, as traditional finance has. But the journey is not easy. It will have to become more proactive in identifying how to win trust before it wins users. Because if the former is earned, the latter will follow. But the reverse may not be true.

If blockchains can apply strategic brakes, they could achieve speeds that surpass any other financial infrastructure.

That’s it for today. I will be back with another deep dive.

Until then, 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 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.

In 1719, John Law, a Scottish gambler and monetary theorist, convinced the French Regent to allow him to build a system that wrapped illiquid colonial assets into liquid paper instruments. He created the Mississippi Company, which held a monopoly on trade with French Louisiana, a vast territory mostly composed of swampland.

Law wrapped these illiquid colonial claims into company shares redeemable for gold. Ordinary Parisians piled in. A year later, the scheme turned him into the richest man in Europe and the Controller General of Finances. Albeit temporarily.

What happens when you hold stocks redeemable for gold? You wait for a high and then demand the gold. Investors did just that. The redemptions started, and they wanted their gold back. However, there was not enough gold. Law responded by changing the rules. He capped the amount of gold anyone could hold. He devalued the notes by decree and mandated that shares could be sold only through his bank at prices he set. Each intervention bought him a few more weeks, but it destroyed trust. By 1720, the investors’ claim papers became worthless. Law fled France after leading France to the Mississippi Bubble.

Three centuries later, the largest private credit funds in the world are responding similarly to a surge in redemption claims from investors. They are changing the rules of redemption to manage the damage. But is this the solution, or just a band-aid fix? Can on-chain private credit help? In today’s deep dive, I will explore that question. Let’s get started.

From Inception to Redemption

Private credit refers to lending that occurs outside of banks and public markets. A company borrows directly from a specialised fund run by firms such as Blackstone, Apollo, or Blue Owl, rather than from a bank or by issuing bonds. The borrowers are typically mid-sized businesses that can’t yet afford to go public.

This market barely existed two decades ago. Today, it’s over $3 trillion and is expected to touch $5 trillion by 2029. The industry filled the gap created by the 2008 financial crisis, which had made it costly for banks to hold risky loans due to regulations and capital requirements.

Private credit lured investors with higher returns (8-10%) compared to public markets, in exchange for illiquidity. The investor’s money was locked up for years. That was the whole point of the proposition. It offered companies greater flexibility and ease in managing their business than a traditional loan secured through syndicate banking. In return, investors received an illiquidity premium for not being able to access their money for an extended period.

Then, the industry decided to change the rules. They wanted to attract retail investors, either to offer them more attractive returns or to grow the private credit market. In response, the US Congress created business development companies, or BDCs, in 1980 under the Investment Company Act. BDCs remained a niche product for decades, but they gained popularity when firms like Ares, Blackstone and Blue Owl launched non-traded versions specifically designed to tap into retail and high-net-worth capital. These vehicles wrapped illiquid corporate loans, but with quarterly redemption windows to appease retail investors.

Retail investors bought into the deal but overlooked a major structural loophole: the private credit industry promised them liquidity while the underlying loans remained illiquid. If the lending cycle got frothy and retailers flocked to redeem, it would leave the private credit funds issuing these retail wrappers in soup. So they set a 5% cap on redemptions. This seemed to solve the problem for the fund managers. But what happens if the market crumbles, forcing redemption demands to exceed the 5% limit? The inevitable happened at last.

In September 2025, two major collapses shattered retail confidence in private credit.

First, Brands Group, an auto parts supplier, filed for bankruptcy after loan agreements failed to detect and disclose hidden off-balance sheet liabilities. Lenders underwrote the deal, presuming it was a 5x debt-leveraged buyout, while in reality it was closer to 20x. In the case of Tricolor Holdings, a subprime auto lender, the company allegedly pledged the same collateral for multiple loans. When the reality came to light, the demand for redemptions surged.

This has led top private credit fund managers to resort to discretionary rule changes or gatekeeping redemptions.

Each of these responses had something John Lawesque about them. Some gatekept redemptions, while others changed the rules when crisis struck.

What concerns me about all of this is that gatekeeping and discretionary rule changes cut both ways. On the investor side, it sends a message that the terms they agreed to are negotiable, and only in one direction. Investors are left at the mercy of fund managers who can tighten redemption limits, or worse, halt them altogether and restructure payouts. What’s also unfair is that these changes are made only after capital has been committed. This undermines the spirit of any contract signed between two parties.

On the fund manager side, they begin playing conservatively. A fund under constant pressure to redeem will not deploy capital confidently. Instead, it starts preserving cash instead of lending it.

Is On-Chain Private Credit a Fix?

There could be a lot of things that people might boast about on-chain private credit. They will show the numbers on tokenisation dashboards and the total value locked in private credit protocols. But most of these are just wrappers for the existing traditional private credit industry. Why do I say this? Here are the facts:

At its core, on-chain private credit’s unique selling point (USP) is its ability to run a smart contract across any financial primitive. This contract can set withdrawal limits, collateral ratios, and distribution rules within the code. While an on-chain private credit fund cannot promise more liquidity than a traditional one, it can ensure that no fund manager can unilaterally alter the terms of the contract once capital is committed. No board vote can upsize a tender offer or switch from quarterly redemptions to return-of-capital distributions, as Blue Owl did.

The code continues to run as is, regardless of the manager’s wishes or market conditions.

A smart contract-powered private credit fund can also address the issue of double-pledging. Tricolor’s collapse involved pledging the same collateral for multiple loans. Tokenised collateral creates a single, auditable record with a single set of tokens for a single set of claims. This makes it structurally harder to double-pledge.

First Brands was marked at par by private credit funds just months before bankruptcy. On-chain, every transaction and repayment is visible in real time. No self-reported valuations can misdirect investors here. Assets cannot be marked at 100 cents if the on-chain market values them at 60.

And if on-chain credit tokens trade on secondary markets, you get better price discovery. It solves the pricing mismatch between the NAV of non-traded BDCs and the underlying loans. We saw this in how hedge funds Saba Capital and Cox Capital tendered an offer to buy Blue Owl shares at a 20-35% discount to NAV.

Protocols are already building this infrastructure. Maple Finance runs institutional credit pools with $3 billion in assets under management. Apollo has launched a tokenised feeder fund with Securitize. WisdomTree brought on-chain NAV data for its private credit fund through Chainlink oracles. The infrastructure is in place.

However, there’s something none of this infrastructure can solve. It cannot evaluate whether a borrower will repay or if a mid-market software company will survive AI disruption.

The underwriting problem that comes with failure of human judgment, as seen in First Brands and Tricolor, can be minimised with on-chain records, but not eliminated altogether. But the other, bigger problem is that most business aspects, including maintaining financial statements and records of supplier contracts, assets and liabilities, exist entirely off-chain. A smart contract cannot inspect borrowers’ books or verify their financial statements. Even if there were a protocol that wanted to bring that data on-chain for verification, businesses wouldn’t agree to exposing their financial and other sensitive business details on a public blockchain. This makes full on-chain underwriting a non-starter with current infrastructure.

Blockchain currently offers a different set of trade-offs. But private credit failing through DeFi can be worse than the traditional private credit industry failing.

Imagine there’s a fund with deteriorating assets and rising withdrawals. For this fund, a DeFi ecosystem hungry for high yield from real-world assets is a perfect target. There’s a high incentive for investors seeking redemptions and fund managers seeking fresh capital to tokenise these loans and sell them into on-chain pools. DeFi can quickly become a dumping ground for illiquid and distressed products from the traditional market.

We saw this happen with Goldfinch, a pioneer in on-chain lending, when a borrower made an unauthorised intercompany transfer that was large enough to threaten the business as a whole. Tokenisation could only expose the aftermath, but couldn’t prevent the fraud.

There is a counterargument to this. On-chain secondary markets can also bring liquidity to distressed assets and help in better pricing. But what separates a market function from becoming an exit liquidity venue is a thin line that could easily collapse.

As long as critical information, such as borrower quality, covenant strength, and financial reporting, remains off-chain, on-chain credit will not solve the problems of the traditional industry. It will only bring a new set of problems.

If major on-chain protocols channel hundreds of millions in DeFi deposits into loans that default or have weak underlying assets, then the damage will spill across multiple protocols. On-chain private lending is still nascent. Total active blockchain-native loans across protocols is barely $3 billion, as against the $3-trillion traditional private credit industry. A high-profile default could set back the entire real-world-asset thesis by years.

If on-chain private credit wants to be more than just a shinier wrapper for the traditional private credit industry, it needs to solve for trust before it solves for yield. This includes third-party verification of underlying collateral, instead of relying on a self-reported one by the originator. It could include standardised risk disclosures that translate duration and credit risk into terms that DeFi participants can understand and take cognisance of.

It should even include credit ratings from traditional agencies for on-chain instruments, something Maple Finance CEO Sidney Powell expects to happen by the end of 2026. It should even include frameworks that can detect and block originators from dumping their distressed assets into on-chain pools. Without these measures, the convergence of traditional and decentralised finance risks will become extractive and not additive.

That’s it for today. I will be back with another deep dive.

Until then, stay curious!
Prathik

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Roman trade routes gave birth to insurance, enabling merchants to scale across geographies. Colonial shipping created the need for remittances and foreign exchange. The internet demanded new payment rails for e-commerce to proliferate.

The internet also established a model for how open networks function.

But each of these networks also required trust infrastructure to function. SWIFT works because a network of banks agreed on how to reconcile transactions without physically moving money. The NYSE’s value is in sequencing orders and enforcing integrity at high frequency. In every case, the network’s value lies in delivering trust without friction on every transaction. A financial network without implied trust eventually dies.

The cost of maintaining that trust, however, has always been the bottleneck. Each layer of verification - the auditor, the fund administrator, the custodian, the compliance officer - adds cost, adds time, and adds a permission gate. Consider traditional asset management, it scales headcount with AUM because the verification layer is human-powered.

Blockchains compress that cost. They are networks where transactions, asset positions, and liabilities can be verified by anyone, continuously, at near-zero marginal cost. You don’t need a fund administrator to check allocations quarterly - they’re onchain, visible in real time. You don’t need a custodian to hold assets - the smart contract is the custodian.

When you can verify capital deployments and how yield is generated - without relying on a fund administrator or quarterly report - you can build investment structures that would be difficult to operate on closed rails.

Among the most notable structures are vaults - managed funds executed entirely through smart contracts. At their core, vaults pool capital, programmatically allocate it across decentralised finance (DeFi) yield sources, and continuously route the accrued interest back to depositors.

Vaults have existed in some form since 2020. What has changed over the past eighteen months is the infrastructure surrounding them.

Vault protocols like Morpho now operate as open platforms - any asset manager can build a strategy on top, any risk curator can manage a vault, and any exchange or wallet can distribute it to their users.

This openness has allowed specialised players to plug into the same infrastructure independently, each contributing what they do best. The result is a composable, verifiable financial network that has attracted capital.

Last year alone, over $6 billion flowed into on-chain vaults. For context, tokenised Treasuries - the undisputed heavyweight of on-chain yield-generating asset classes - grew from $3.3 billion to $6.96 billion in that same timeframe. In sheer growth velocity, vaults effectively matched the most established category in institutional digital finance.

Look specifically at Morpho and Spark, the two dominant vault platforms, and their assets under management (AUM) surged from $2.46 billion to $7.64 billion today.

If you broaden the lens to the entire ecosystem of automated yield strategies, accounting lending, liquid staking, and hybrid approaches, the aggregate AUM now hovers at $17.5 billion, completely eclipsing previous highs from 2021.

How vaults got here

At its core, a vault works like a mutual fund. An investor deposits capital - typically stablecoins - and gets a receipt token showing their share of the pool. A curator then allocates that money across DeFi lending markets based on a specific strategy. As the money earns interest, returns flow back to the depositors. Simple enough.

But what makes vaults different from a normal managed account is how you can use that receipt token. It doesn’t just sit in your wallet.

Through ERC-4626, that token can be plugged into other DeFi apps. It can be used as collateral for a loan on Aave, paired with a liquidity pool on Curve, or stacked into a higher-order yield strategy. ERC-4626 allows the output of one financial product to easily become the input of another.

While composability is part of the reason for the massive scale we see today. The credit also goes to the underlying stack of products that enable the construction and distribution of vaults.

Back in the “DeFi Summer” of 2020, Yearn Finance was the first to pioneer the idea of automated yield. They proved that fund-like structures could run entirely on-chain. Instead of users manually moving capital between Aave, Compound, or Uniswap to chase the highest rates, Yearn vaults encoded these strategies into smart contracts, reallocating funds programmatically.

However, Yearn acted as both the infrastructure provider and the strategy operator - a single entity handling everything from the base smart contracts to capital allocation to user distribution. As the market expanded, this monolithic model hit its limits. Risk management, software engineering, and consumer distribution require entirely different skill sets. Bundling them into one entity created bottlenecks and concentrated risk.

To scale safely, today’s vault ecosystem has unbundled into three distinct layers. When the infrastructure builder, the risk manager, and the retail platform operate independently, each can specialise without being constrained by the others.

We can split financial services apart because the underlying blockchain system is transparent and programmable.

In regular finance, making sure different specialists (like managers and record-keepers) do their jobs requires expensive legal contracts, heavy regulation, and constant audits. But on a blockchain, smart contracts can automatically forces everyone to follow the rules, and anyone can check the work instantly.

Because the code handles the “trust,” it’s much easier to coordinate different experts. Which is why the vault stack can support five intermediaries in a chain without the aggregate overhead making the product uneconomical.

The protocol layer provides the baseline smart contract architecture. Morpho dominates here with roughly $9.6 billion in AUM.

Because of its fully permissionless design, Morpho serves as neutral infrastructure rather than a single product. It attracts a wide range of strategies. Apollo Global Management, with $940 billion in traditional assets, understands the importance of Morpho in enabling on-chain strategies. Resultantly, the company acquired 9% of Morpho’s token supply, signaling where institutional capital sees base-layer value.

The curator layer is where strategy and risk management reside. Curators function like the general partners (GPs) of on-chain finance. They define a vault’s mandate, select eligible assets, set risk limits, and manage daily reallocations.

Curators act as the risk officers of this decentralised ecosystem. Curators encode Loan-to-Value (LTV) ratios to create buffers against market volatility, dictating a threshold where an underwater position should be programmatically liquidated to protect depositors. To prevent a vault from outgrowing the liquidity of its underlying assets, they impose strict supply caps.

Additionally, they design algorithmic interest rate curves based on capital in the pool. When borrowing demand spikes and liquidity tightens, the smart contract automatically drives up the cost of capital, naturally deleveraging the system and attracting new deposits. This helps abstract the underlying complexity and provides a stable and predictable yield for institutions and retailers alike.

By separating them from the protocol layer, curators are forced to compete on performance. Curated Morpho vaults consistently deliver roughly double the APY of vanilla lending markets today, because managers competitively shift capital rather than leaving it stagnant in a pool.

Today, a growing set of specialised curators compete for deposits on these platforms.

Steakhouse Financial is the largest curator on Morpho, managing over 50 vaults across six chains with roughly $1.5 billion in deposits and the first curator to cross $2 billion in total assets curated on the protocol. Gauntlet runs 70+ vaults with approximately $1.37 billion in AUM.

Steakhouse does it with a team of less than 20 people. This is possible because the underlying network offloads the verification requirements to the blockchain and the system’s openness enables the protocol to rely on companies like Coinbase for distribution and Morpho for code enforcement.

More recently, Bitwise entered as a Morpho curator - a move that matters less for the capital it brings initially and more for what it signals about the stack. Bitwise is a $15 billion off-chain asset manager with existing distribution to institutions. By becoming a curator, it moves vertically through the vault stack, bringing its own capital relationships and compliance credibility to capture value across both curation and distribution layers.

The distribution layer is where this complex plumbing transforms into a consumer product. Platforms with massive reach, like Coinbase, Crypto.com, and Gemini, now route user deposits directly into these curated vaults.

A Coinbase customer depositing USDC into a basic “earn” product is interacting with DeFi infrastructure without realising it. A clean fintech interface in the front, with decentralised infrastructure running in the back.

The capital chains running beneath these simple apps are quite deep.

Consider a retail user on Crypto.com depositing dollars into a yield product. Those dollars flow into a Morpho vault operated by Grove Finance. Grove, in turn, holds $712 million of a tokenised AAA-rated CLO fund brought on-chain by Centrifuge and managed by traditional heavyweight Janus Henderson. The end user earning a 4.82% yield on their stablecoins has no idea their return originates from a Wall Street credit fund.

Every intermediary in that chain adds a specific, necessary layer of specialisation.

Centrifuge handles the legal and technical work of wrapping a traditional credit fund into a token that DeFi protocols can recognize. Grove Finance provides the risk framework and capital allocation strategy, deciding how much exposure to take on a given instrument. Morpho supplies the lending infrastructure - the smart contracts, market parameters, and vault architecture. Crypto.com handles distribution, compliance, and the user interface.

This is a clear example of financial sophistication scaling on open networks, through composable, specialised intermediaries rather than a single institution trying to do everything.

The Demand Source

The three-layer unbundled stack explains how vaults work today. But what led to the $6 billion in inflows last year?

Let’s start with who is actually allocating the capital.

Data suggests that amongst these vault participants, 63% of them are retail users with under $10,000 in their accounts. Notably, these retail users account for just 6 basis points of the actual capital. The real capital comes from whales and institutional players - addresses depositing over $100,000 per transaction - represent 99.2% of the money in automated yield strategies.

These participants include crypto-native funds, DAO treasuries, and family offices. Depositing into the vaults offers them a hands-off, risk-managed way for them to park large cash reserves.

The primary engine behind this institutional capital influx is the massive expansion of stablecoins, and their growing use as savings instruments — therefore generating passive yield.

Over the course of 2025, the stablecoin supply grew from roughly $200 billion to $300 billion. Crucially, regulatory developments like the GENIUS Act are accelerating this growth, but with a specific catch. Under these new frameworks, stablecoin issuers are legally prohibited from paying interest directly to token holders. Since native stablecoins are legally required to yield nothing, that $300 billion is structurally forced to move one layer out into lending protocols to find a return.

Vaults have become the default parking lot for this idle money, which is why over 90% of Morpho and Spark vault AUM (assets under management) is in stablecoins.

Additionally, automated on-chain yield strategies have always been superior in pure yield terms. Today, they deliver an average gross APY of 7.95%, compared to 4.67% for traditional short-duration fixed income and money market funds.

We have sufficient capital that demands yield, and we have enough APY to attract them; the final piece needed was a way of distribution to reach users and institutions who want the returns but won’t interact with DeFi protocols directly.

This is a real barrier. EY’s institutional survey reported that 62% of institutional investors prefer gaining crypto exposure through registered vehicles rather than acquiring assets directly on-chain. Only 24% of surveyed investors currently engage with DeFi at all. The demand for yield exists; the willingness to navigate wallets, smart contracts, and gas fees does not.

On the retail side, another EY report found that 51% of non-DeFi investors cited lack of expertise as their top reason for not participating.

The distribution layer solves this issue by wrapping vault infrastructure inside familiar interfaces. For these users, a Coinbase “earn” button that routes to a Morpho vault in the background removes the barrier entirely.

Coinbase routes USDC deposits through Steakhouse-curated Morpho vaults on Base - the same Steakhouse that now manages over $1.5 billion in deposits. Crypto.com, Gemini, Bitget, Ledger, and Trust Wallet have built similar integrations. For an institution that can’t hold assets in a self-custodial wallet or interact with a smart contract directly, depositing through Coinbase means the compliance, KYC, and custody requirements they need are handled at the interface layer. They get vault yields without vault complexity.

For traditional asset managers, this creates a distribution pipeline to a global audience where the compliance burden sits with the platform and not the protocol.

What stands in the way

While the numbers are compelling, the risks are too.

Smart contract vulnerability remains the most direct threat to this entire ecosystem, and the track record is sobering.

Consider the sheer variety of the wreckage: In 2021, Yearn lost $11 million to a flash loan manipulation. And suffered another $9 million loss in late 2025, from an infinite minting bug. The markets responded accordingly, protocol’s TVL (Total Value Locked) today sits at $250 million, down from its all-time high of $6.3 billion.

A similar fate befell Euler in 2023, where a single missing “health check” in Euler Finance’s code allowed a hacker to drain $197 million across four different asset pools in just fifteen minutes.

The terrifying pattern across these incidents is that almost all of the exploited code had been thoroughly reviewed by top-tier security firms like OpenZeppelin and Trail of Bits. While audits are necessary, they haven’t been sufficient.

Because vaults are composable, every new protocol they plug into creates a new attack vector. The industry has responded by building heavy safeguards - timelocks to delay sudden parameter changes, real-time monitors like Hypernative to spot abnormal flows, automatic circuit breakers, and decentralised veto mechanisms that allow depositors to block suspicious moves.

While these mitigations are meaningful, they are not guarantees. A bug at the protocol layer can wipe out a vault in seconds, regardless of how well the curator allocated the capital.

Other than the security risks of code, there’s another fundamental difference in how the actual financial product behaves differently from traditional fixed income.

DeFi vaults charge meaningfully higher fees - roughly 1.50% compared to the 0.08% you might pay for a Vanguard money market fund.

However, that gap is largely just a reality of scale; a $70 million smart contract cannot amortise operational costs the way a $360 billion Wall Street behemoth can. Yet, even after those higher fees are deducted, on-chain allocators are still taking home roughly 186 basis points more yield than they would in traditional finance (6.45% vs 4.59%).

But as the history of exploits shows, that extra yield is not free alpha; it comes with pre-existing risks. It is the exact, market-priced premium for bearing technical risk. There is no FDIC deposit insurance on-chain. There is no government backstop, and there is no lender of last resort. Allocators demand higher returns precisely to compensate for the very real possibility of an oracle failure or a smart contract bug wiping out their position.

For crypto-native funds, DAO treasuries, and traditional institutions with the right risk appetite, that structural premium remains highly attractive.

How these tensions resolve will shape the next chapter. But the structural advantage that vaults have - the reason they’re scaling faster than any previous onchain financial product -is in the cost of trust.

Traditional asset management adds costs to scale trust between participants. Each layer adds cost that ultimately comes out of investor returns. On verifiable rails, the ledger itself provides that trust layer - continuously, permissionlessly, at near-zero marginal cost.

That’s why Steakhouse can run $1.5 billion with 20 people, why five intermediaries can sit in a single yield chain without eating the return in fees, and why Coinbase can offer vault-powered earn products to 100 million users without building proprietary fund infrastructure.

The risks are real and the regulatory questions are unresolved. But the economics of trust on verifiable networks are structurally different. And if that cost advantage holds, $17.5 billion may turn out to be early.

Until then, stay safe.
Nishil

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 🙌

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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.

In 1688, a coffeehouse on Tower Street in London became one of the most important rooms in global commerce. Ship captains, owners, and merchants would walk into Edward Lloyd’s cafe carrying a slip of paper with a description of the cargo, the route, and the vessel. They needed someone to bear the risk of the voyage. Individuals willing to accept a share of that risk would write their names underneath the terms. That gave birth to the word “underwriting”.

The most powerful person in the room was the one who set the terms on that slip, including the premium to charge, the risk to absorb, and which voyages to back. No vessel sailed until this person priced the risk of its first journey.

This arrangement helped the coffee house evolve from a social gathering place to Lloyd’s of London, one of the world’s largest insurance markets, over the past three centuries. Interesting, right? What I found even more interesting when I started reading this story was an insight that remains relevant today. It’s the realisation that every asset, venture, or anything tradable needs a moment where someone decides “this is worth backing, at this price, on these terms.”

We saw this pattern repeat each time a new asset class emerged.

About two centuries after Edward’s coffeehouse, we saw J. Pierpont Morgan underwrite the terms for publicly funded railroad projects in the U.S. by issuing stock in companies such as the New York Central Railroad. This established J.P. Morgan’s reputation as the mobiliser of capital and an expert railroad financier.

His underwriting set the terms, chose the investors and captured the spread between the price paid to the issuer and the price offered to the public. When Morgan refused to underwrite a venture, it didn’t get built.

The modern IPO is the digitised version of the same mechanics. A handful of banks underwrite a company’s initial public offering (IPO), gauge demand from preferred clients, set the offer price, and allocate shares. The debut day “pop”, where shares jump by 20-30%, is more than merely a market phenomenon. It reflects the underwriter’s margin.

The one complaint investors have to date across four centuries is that insiders get the best allocation, the first price rarely reflects true demand, and everyone else arrives after the spread has already been captured.

Last week, James Evans posted the HIP-6 proposal for token launch auctions on Hyperliquid, which addresses part of this complaint. In his post on X, James disclosed that he held $HYPE in his portfolio and that he works with Reciprocal Ventures, an early-stage crypto venture capital firm.

In today’s deep dive, I will evaluate HIP-6 and other on-chain platforms to assess if they can address the legacy problem in capital formation.

What’s Broken

The book-building process that dominates traditional capital formation is a black box by design. Banks solicit demand from institutional clients behind closed doors, set prices based on conversations the retail market is never privy to, and allocate shares to “random” accounts. The issuer gets a price, and the public gets whatever is left.

Consider two instances.

During Facebook’s (now Meta) 2021 IPO, lead underwriter Morgan Stanley cut their revenue forecasts during an investor roadshow. The negative news was available immediately to major institutional clients as part of analyst notes, while retail investors bought in blind. The stock dropped by approximately 50% in three months. Retail got the worst of both worlds: full allocation at inflated prices and no access to the information insiders had.

There’s a more recent precedent in Rivian’s 2021 public listing debut as an electric vehicle maker. Its IPO, which was priced at $78, popped to $179 on day one. Institutional clients who received allocations from Goldman and JPMorgan captured the spread. Retail bought at the open. Its share price dropped about 40% in 10 days. Investors then filed a lawsuit alleging that Rivian had concealed that its vehicles were priced below their material costs. The company eventually agreed to pay $250 million in settlement, while maintaining that it was not an admission of fault. Today, its share price hovers below $16 each.

This modus operandi has been normalised into a business model to the point that an average investor doesn’t even get a whiff of what’s wrong with it.

Beyond allocation, the infrastructure is slow and siloed. An IPO takes four to six months from filing to first trade. Settlement takes a full business day. The asset can’t be used as collateral until it clears. Market makers operate under separate agreements, often with guaranteed spreads. This entire apparatus is also jurisdictionally locked. So, a retail investor in Mumbai (India) cannot participate in a New York IPO on equal terms even if they are willing to bear the same risk.

The underwriter’s power comes precisely from these frictions. Inefficiencies such as opaque pricing, delayed settlement, and gatekeeping in access are exploited and treated as a moat by them.

What Changes with On-Chain Underwriting?

The underwriting process is structurally different, with fewer intermediaries on-chain. A bonding curve or a continuous clearing auction (CCA) publishes every bid in real time. On-chain, liquidity is programmatic from block one. It is coded into the launch mechanism itself through computation rather than negotiation. An asset can exist, be traded, and be used as collateral within the same block. No need to wait for T+1 or the clearing cycle.

Access gatekeeping persists, but along a different tangent.

A pump.fun launch is open to anyone with some SOL in their wallets. An Echo sale is gated by KYC, but is accessible across jurisdictions. Hyperliquid’s HIP-6 has set a 100-USDH minimum economic filter, but doesn’t limit people on an accreditation basis. All these systems avoid a “preferred client” allocation model that most traditional book-building processes follow.

The biggest differentiator between the two forms of capital formation is that on-chain underwriting treats every token launch as a buy order for the ecosystem’s native token, either SOL, USDC, USDH, or something else. Traditional underwriting doesn’t generate captive demand for anything except the underwriter’s fee.

This difference is more consequential than you might think.

On March 20, 2025, pump.fun - Solana’s dominant token launchpad - launched PumpSwap, its own automated market maker (AMM). Until that day, every token that graduated from pump.fun’s bonding curve was automatically routed to Raydium, Solana’s largest decentralised exchange. That graduation flow had become one of Raydium’s most significant revenue sources. Overnight, the pipeline was severed.

Read: Solana Showdown: pump.fun Vs Raydium

Raydium lost an estimated 35-40% of its AMM revenue. Its token, RAY, dropped by 30%. Raydium did not sit quietly. It hit back instantly by shipping LaunchLab, its own token issuance product, within 48 hours. The price of RAY peaked, doubling in six months, before collapsing to a two-year low. Today, it’s down almost 70% since pump.fun launched its own AMM.

The lesson was that whoever controlled where a token was born controlled the downstream fee revenue. Issuance meant order flow.

Two Lanes of Token Birth

What’s emerged since is a landscape split into two divergent lanes.

One is market formation, where a tradable chart is manufactured at internet speed. Pump.fun is the best example, with its bonding curve, $69,000 graduation threshold, and automatic liquidity seeding via PumpSwap. It has generated almost $1.5 billion in cumulative fee income, launched over 16.8 million tokens and allocated over 98% of revenue to buy back its PUMP token, offsetting more than 27% of the circulating supply.

The other lane is capital formation, with structured distribution into real users with compliance guardrails in place. Coinbase acquired Echo for $375 million in October 2025 and added a KYC-gated token sales platform with time-weighted deposit vaults to its product lineup. Echo’s Sonar product is at the opposite end of the spectrum from pump.fun, with a regulated, identity-verified, lead investor-curated approach.

The gap in Coinbase’s stack is liquidity at launch. Echo handles distribution but doesn’t auto-seed a trading market.

Where the Two Lanes Meet

The HIP-6 proposal is the latest attempt to merge the two lanes into a single protocol-level primitive.

The proposed mechanism is a continuous clearing auction (CCA) embedded in HyperCore’s consensus layer. At every block, the system computes a clearing price from all active bids using a budget-spread-over-remaining-blocks model.

This model is not entirely new. The HIP-6 proposal explicitly adapts Uniswap’s CCA, which launched in November 2025 and was first used by Aztec Network to raise $60 million from over 17,000 bidders, with no detected instances of sniping or automated manipulation.

The two implementations share the same core DNA. They both break down a large auction into thousands of sequential per-block mini-auctions, release tokens gradually, compute a uniform clearing price at each block, make bids non-withdrawable while in range to prevent coordinated price swings, and automatically seed liquidity at settlement.

This design solves the same legacy problems.

Fixed price sales force investors to guess the correct opening price. Capped pro-rata sales create oversubscription spirals. Dutch auctions make room for timing games that favour professionals. CCA eliminates all three. In CCA, the final seed price is derived from a volume-weighted average over the auction’s closing window, which is an anti-manipulation measure that makes price sniping structurally expensive.

Where Hyperliquid and Uniswap diverge is in their settlement architectures.

HIP-6 will run inside HyperCore’s consensus layer itself. The auction logic executes within the block transition function and not as an external contract. Clearing will happen at the same level as trade matching.

Settlement will be multi-tiered. The proposal states that a 500 basis-point (bps) protocol fee will be applied to the total funds raised and transferred to the Assistance Fund, through which Hyperliquid funds all its $HYPE buybacks. Out of the net proceeds (after deducting the protocol fee), 2,000-10,000 bps (20-100%) will be used to seed a HIP-2 market at the derived price. Then, any remaining funds will go to the deployer.

For example, a $PROJ token auction on HIP-6 raised 1.5 million USDH, with a total supply of 10 million tokens and a 20% HIP-2 seed. Here’s how the settlement would be done:

This is what separates HIP-6 from Uniswap.

Uniswap built CCA as a token-launch tool that feeds into its existing AMM pool. With HIP-6, Hyperliquid will become a full-stack primitive that lets stakeholders raise capital, discover price, seed two-sided liquidity, and begin trading on a central limit order book (CLOB).

What’s more? It will all be denominated in an asset the protocol wants you to hold: USDH.

Unsolved Problems

While transparent price discovery, programmatic liquidity, and atomic settlement are significant improvements over the traditional model, on-chain underwriting also brings its own set of problems.

None of these mechanisms solve for the quality of the project. Pump.fun’s bonding curve ensures fair access to the price curve, but says nothing about the credibility of the project behind the token. HIP-6, too, is open about this drawback. It mentions nothing about token quality, governance, or holder protections.

Traditional underwriters bear reputational and legal liability when an offering fails. A bank’s name on a prospectus signals that someone with skin in the game reviewed the issuer. On-chain mechanisms offer no equivalent recourse. Coinbase’s Echo comes close through KYC, issuer disclosures, and selling restrictions. But it does so by reintroducing gatekeeping that on-chain underwriting is designed to eliminate.

Whether token launches constitute securities offerings also remains unresolved in most major jurisdictions. A softened U.S. enforcement climate has made permissionless issuance easier to ship, but the underlying legal uncertainty hasn’t vanished.

But these are early days, and I expect improvements to make this an even better proposition than the legacy systems for capital formation.

The entity that controlled where an asset was born has always captured the most durable fees in finance.

Between 2012 and 2021, Goldman Sachs led more U.S. IPOs than any other bank. Yet the benefit transcends the unmatched fee revenue the IPOs brought in for the bank. Once Goldman underwrote an IPO, it typically also became the primary advisor for follow-on offerings, mergers and acquisitions, and debt issuance for that company.

We saw how pump.fun earned over a billion dollars in revenue by offering a reliable platform for 16.8 million tokens to be generated through its mechanism. The Raydium slump showed the same pattern as a corollary. Once it lost control of the token birth pipeline, 35-40% of its revenue disappeared overnight.

With on-chain underwriting, the system remains the same, and only the entity changes. From being a bank or a syndicate desk, it’s now changed into a protocol. This protocol offers a transparent and auditable process of allocating tokens without demanding a relationship with insiders.

In return, it expects you to conduct the entire trade using a unit of account that contributes to the protocol’s coffers: its native token. And I think it is a trade-off that also benefits the investors. A captive demand for native tokens leads to locked float and stickier liquidity.

This makes it competitive not just between traditional and on-chain underwriting, but even among on-chain players. The fight has moved upstream from fighting over the secondary market to controlling who gets to set the first price, allocate the first tokens, and decide which currency an investor needs to show up with.

That’s it for today. I will be back with another analysis.

Until then, stay curious!
Prathik

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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.

In the late 1960s, Wall Street had an unsexy problem. Trading activity surged as securities became more popular, but the infrastructure supporting it remained outdated. Brokers settled trades by physically swapping share certificates. Messengers ran around Manhattan with envelopes. Back offices drowned in forms. The volume surge got so bad at one point that U.S. markets had to stop trading on Wednesdays for six months just to allow firms to catch up on their paperwork.

All this culminated in the infamous Paperwork Crisis.

Better “runners” or more papers was not the solution. So they replaced all the moving things with the Depository Trust Company (DTC) in 1973. The corporation immobilised securities and made ownership a ledger update rather than a physical handoff of share certificates. The modern U.S. market we see and trade in today is the result of multiple iterations that evolved over time from that decision.

Today, DTC holds custody of more than 1.4 million security issues valued at $87.1 trillion, including securities issued in the U.S. and over 130 other countries and territories.

We see a similar narrative playing out in the history of finance. When an asset class becomes big and popular enough, what helped manage it wasn’t merely a book-entry strategy. The underlying force behind it has always been trust. After the DTC was launched, an average investor no longer had to worry about ownership, as trust in the centralised body’s ability to maintain records replaced the need for a physical certificate.

The same problem has surfaced with crypto, as its appeal as a mainstream asset rose in the U.S., driven by exchange-traded funds (ETFs) and other forms of exposure (think Digital Asset Treasuries) over the past two years.

This development has caused back offices to spring into action, just as the 1960s’ paperwork crisis did for the DTC.

The “paper” in crypto is the private key, which is more like a bearer instrument - whoever controls the key, controls the asset. This creates a familiar set of problems for institutions to address: operational controls, segregation, auditability, insolvency questions, governance, and the fact that losing a key is a permanent loss.

Now, a new trust layer is being built around these challenges through a trust bank charter. In today’s story, I will explain why firms are lining up for bank charters to custody crypto.

The Charter Rush

In recent months, the U.S. Office of the Comptroller of the Currency (OCC) has been approving and processing a growing number of applications to become national trust banks tied to digital asset custody and stablecoin infrastructure.

On December 12, 2025, the OCC conditionally approved five such applications, including Circle’s First National Digital Currency Bank, Ripple National Trust Bank, and conversions for BitGo, Fidelity Digital Assets and Paxos. This was followed by Stripe’s crypto unit, Bridge, and Crypto.com getting the initial nods from the OCC in February 2026.

The queue isn’t just limited to crypto natives.

Last week, the world’s largest wealth management firm, Morgan Stanley, applied for a trust bank charter called Morgan Stanley Digital Trust, National Association.

Know what’s common in these applications? They weren’t queuing up to become a normal bank, running deposit and lending activities. Unlike normal banks, these national trust banks cannot accept deposits or make loans and do not have FDIC insurance. They all had applied to offer custodial, safekeeping and fiduciary administration services. Think of bookkeeping, but specifically for crypto assets.

I find this to be one of the most pronounced signs that crypto is changing how traditional financial institutions function, while the rest of the world is busy focusing on the sideways movement of cryptocurrency prices.

Banking charters may sound boring, but like many other financial infrastructure innovations, they bring our attention back to the lesson the financial world learnt from the paperwork crisis. It also emphasises that, at its core, the mainstreaming of crypto is a custody-and-controls story.

Why Now?

The rush to apply for charters is linked to recent clarifications from the OCC about what national banks can do in crypto-related custody. In May 2025, it confirmed that national banks and federal savings associations may buy and sell assets held in custody at a customer’s direction.

In December 2025, it also confirmed that banks can conduct “riskless principal” crypto transactions by acting as intermediaries without holding inventory.

Last week, on February 27, 2026, the OCC clarified that national trust banks can engage in non-fiduciary activities beyond their narrow fiduciary role, starting April 1, 2026.

Why does this matter? It is critical if you are a firm building custody, settlement, reserve management, and related services.

We have seen it happen before in the world of finance.

In the early 2010s, neobanks emerged when a crop of fintechs built apps on top of partner banks. While these apps made banking more accessible, they had their problems. Although the apps owned the interface, partner banks still owned the deposits, infrastructure, and regulatory attention. It became messy when something went wrong because accountability was split across multiple entities.

The response was the same that we see now with crypto: take control of the risk and reward.

In 2016, the OCC began exploring special-purpose national bank charters for fintech firms. Two years later, it started accepting charter applications from non-depository fintechs engaged in core banking functions.

While courts struck down the possibility of issuing charters to non-depository institutions, fintechs nevertheless went ahead to reduce their reliance on partner banks. What followed was a handful of fintechs becoming full-service banks through the traditional, heavier route, which sometimes included acquisitions.

Varo, which started as a fintech, received its full-service national bank charter in 2020. Jiko became a bank by acquiring a small national bank. SoFi received conditional approval in 2022 to become a full-service national bank by acquiring an existing national bank.

The national trust bank charter rush we see today follows a similar pattern, except this time, Washington is also laying a fresh set of guardrails for digital assets.

The legislative backdrop to all these developments makes it clearer why firms are pursuing more than just custodial services within the digital asset landscape under their national trust bank charter applications.

In July 2025, U.S. President Donald Trump signed the GENIUS Act, establishing a federal framework for payment stablecoins. Several firms pursuing trust bank structures have explicitly stated their intention to operate stablecoin and reserve-related activities within a federal oversight regime aligned with that law.

Both Bridge and Circle mentioned this in their announcements.

This addresses the first layer of ‘why now’. The regulatory clarity opens new value chains for incumbents, both traditional and crypto-native, enabling them to expand their business lines.

The second layer involves the market structure.

Institutional crypto exposure has shifted toward wrappers that resemble legacy finance. Think of ETFs, funds, and managed accounts. These wrappers demand custodians who clear legal and operational thresholds.

You’d be mistaken to think centralised crypto exposure is no longer in demand. This is evident in the developments within the current crypto ETF infrastructure.

In April 2025, the world’s largest asset and crypto fund manager, BlackRock, added Anchorage Digital Bank as an additional Bitcoin custodian alongside their existing partnership with Coinbase for its iShares Bitcoin Trust. BlackRock framed it as part of “ongoing risk management” to address the growing retail and institutional demand.

What value do financial giants, such as the $9-trillion Morgan Stanley, see in these charters?

One of the most recent signs came less than two weeks ago in a fireside chat at the Bitcoin For Corporations conference. When Phong Le, Strategy’s (fka MicroStrategy) chief executive officer, said, “If there’s somebody that could help ‘orange pill’ the world, it would be Morgan Stanley,” Amy Oldenburg, Morgan Stanley’s head of digital assets strategy, replied, “That would probably be accurate.”

What Changes?

Once you string these developments together, the trust charter rush no longer looks like a crypto story and resembles the evolution we saw with the DTC.

As crypto evolves as a financial asset, both retail and institutional investors need a place to store their keys, one that lawyers, auditors, and regulators can approve. A national trust bank charter is one way to address that at scale.

Then there is the question of the business line’s economics. Custody may seem like a small-fee business. Starting Q1 2025, Coinbase stopped disclosing custodial fee revenue as a separate line item and has rolled it into “Other subscription and services revenue.” Yet, there’s more to the custody business than meets the eye.

Whoever has custody controls collateral, which in turn addresses financing for these institutions. Financing controls leverage, which controls volume. Ultimately, volume decides how much one gets paid.

In 2025, EquiLend’s Data & Analytics said global securities lending revenue hit $15.3 billion, with loan balances topping $4 trillion. State Street, a giant in custody, reported $13.94 billion in total revenue in 2025. Of that, its servicing revenue accounted for ~40% ($5.32 billion), which included custody, accounting and fund administration, recordkeeping, and client reporting.

So, while custody alone may not translate into a material revenue line, the ancillary services around custody could generate repeatable revenue pools.

The DTC became irreplaceable because it allowed the market to scale without drowning in paperwork. Today, DTC has evolved to become more than just safekeeping; it offers settlement services, processes corporate actions and supports underwriting. This has become a whole ecosystem built around updating ownership records.

A licence to crypto custody can unlock something similar for these applicants. Beyond becoming a vault, they can provide an authorised ledger interface.

The charter allows these institutions to lend credibility to their clients in how they record, segregate, transfer, and audit the ownership of digital assets. They can do so with a lighter balance sheet and a more focused approach without becoming a deposit-accepting bank.

But trust charters have their share of critics.

Traditional banking advocates have argued that these charters can serve as a “backdoor” into the banking system without taking deposits or incurring the same broad public obligations. Banks are fighting over where the line should be drawn.

While the debate continues, the regulatory shift is well underway. The OCC’s conditional approvals may not equate to a final nod, but they signal one thing. It’s that crypto, despite its self-custody ideology, has now grown large enough to make the back-office role indispensable.

I think it would be a misreading if the industry looked at the trust bank charter rush and called it a crypto industry phenomenon. It is more of a natural evolution of market players who are always on the lookout for ways to create value by solving industry inefficiencies.

That’s it for today. I will be back with another analysis.

Until then, 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 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.

The RWA tokenisation market (excluding stablecoins) has grown roughly tenfold, in the past three years, from about $5 billion in 2022 to $47 billion today. The BCG report projects that the broader tokenised asset market (including stablecoins) will reach $18.9 trillion by 2033.

The current primary RWA markets include Private Credit, with $20 billion tokenised, and $10 billion in Tokenised Treasury Bills.

However, as I wrote a couple of weeks ago, Hyperliquid has shown that there is strong demand for stocks, ETFs, and metals as well. Perp markets for equity and stocks account for 10-15% of Hyperliquid’s daily volume.

Yet, the tokenised equity market has not grown as significantly. While the total issuance of tokenised Treasuries stands at roughly $9.3 billion, the tokenised equity market is only at $1 billion— an approximately tenfold gap.

Ironically, this relationship reverses when viewed through the lens of traditional market size. The U.S. stock market is estimated at $68 trillion in market capitalisation, while the outstanding stock of the U.S. Treasuries are closer to $30 trillion.

Globally, stock markets are roughly twice the size of government bond markets. Why then has the tokenised stock market not grown as rapidly as the tokenised U.S. Treasury market so far?

For U.S. Treasuries, the characteristics of the assets and their yields are relatively standardised, making on-chain liquidity and tokenisation management easier.

A 6-month T-bill yields roughly the same thing regardless of which platform tokenises it - the underlying asset has a fixed maturity and a credit risk profile that is identical across every issuer because the borrower is always the U.S. government. The asset behaves predictably, and that predictability simplifies everything downstream.

For the tokeniser, this means there is no need for real-time oracle feeds updating every second - a T-bill’s value moves in small, predictable increments based on time to maturity and the prevailing interest rate. Liquidation parameters on lending protocols are straightforward to set because the collateral value doesn’t shift.

For the buyer, standardisation means fungibility across issuers. OUSG from Ondo, BUIDL from BlackRock, and BENJI from Franklin Templeton. While these products differ in fee structure and legal wrapper, the underlying economic exposure is nearly interchangeable. That makes comparison shopping easy and switching costs low.

Stocks, on the other hand, are idiosyncratic. TSLA and AAPL have completely different volatility profiles, dividend schedules, liquidity characteristics, and corporate action risks. Each tokenised stock requires its own oracle feed, its own risk parameters for lending, and its own liquidity pool.

Moreover, the tokenised equity models are fragmented, and there is no one clear answer to the solution as of yet. The uncertainty surrounding the asset class indirectly hinders adoption and development.

On-chain Equity Gradient

Today, based on the model of issuance, tokenised equities can be put in three different brackets:

1. Direct Tokenisation: In this model, the issuer directly tokenises stock ownership. The issuer of the token maintains an on-chain registry to demarcate the ownership of the stock. Securitize and Superstate are the companies doing this today.

2. Entitlement Tokenisation: A method that tokenises stock-related rights that currently sit off-chain with DTCC (Depository Trust & Clearing Corporation). In this, the stock orders still go through a traditional route of off-chain brokers, and the stock ownership lies with a third party instead of the buyer, as happens today in the U.S. stock market. It will improve operations, introduce 24/7 trading and improve the current workflow. DTCC recently got clearance from the SEC to pursue this.

3. Indirect Tokenisation: In this model, a company buys and holds stocks on behalf of users and tokenises the beneficial interest in them. The representative tokens can be traded and transferred, but the stock ownership lies with the issuer. Companies like Robinhood, Backed Finance, Ondo, and Dinari are currently using this model.

The first two methods, including direct tokenisation through transfer agents like Securitize or Superstate, are tightly coupled to existing U.S. equity issuance infrastructure. That coupling gives buyers something valuable: actual ownership of the underlying shares, complete with voting rights and regulatory protections. But it also imports the constraints that come with U.S. securities law.

For example, selling tokenised U.S. shares to non-U.S. persons would face several restrictions - KYC/AML requirements, broker-dealer licensing in the investor’s home jurisdiction, and geographic gating that limits who can buy and where. While direct tokenisation is legally more robust, that is also precisely why it has a smaller addressable market.

Meanwhile, indirect tokenisation, the model used by Ondo and xStocks, trades away the legal robustness for reach. These tokens don’t represent ownership of the underlying stock. Instead, they’re structured notes issued by an offshore SPV that holds the shares as collateral and passes through the economic exposure, price movements and dividends.

The buyer trusts that the issuer maintains sufficient off-chain collateral to back every token minted on-chain. There’s no guarantee of ownership, no voting rights and no shareholder protections. What the buyer does get is access.

Indirect tokens can be sold on-chain without the restrictions that bind direct issuance. For a non-U.S. retail investor who wants exposure to U.S. equities without a brokerage account, this is currently the most accessible path - and the only one that lets them simultaneously earn dividends and deploy that exposure across DeFi platforms.

The numbers reflect this dominance: indirect tokenisation controls the majority of the market, with Ondo and xStocks together accounting for over 95% of all tokenised stock value.

Indirect issuers - Ondo and xStocks - together command over 80% of tokenised equity market share today. While these dynamics may shift as regulations clear the path for direct ownership models, Ondo has capitalised on the interim gap, capturing more than 60% of the total market cap alone.

Ondo leveraged two important go-to-market levers to capture the majority market share. First, its infrastructure enables better execution price on-chain and second, its distribution. And that’s what we’ll look at today!

Fast Stocks

The primary distinction between Ondo and xStocks lies in what happens when these tokens drift from the price of the underlying stock.

Market makers ensure tokenised stocks stay pegged to their real-world price through arbitrage. If TSLAon trades at a premium, a market maker mints fresh tokens and sells them into the secondary market. If it trades at a discount, they buy tokens and redeem them.

The economics of this process differ dramatically between the two platforms. Backed charges a 0.50% fee on every mint and redemption. While Ondo doesn’t charge a fee, instead captures a spread - the difference between the price quoted to users and the price at which it executes in the underlying market.

This difference reshapes market maker behaviour. On Backed, an arbitrage opportunity is only profitable when the premium or discount exceeds 50 basis points, the cost of minting or redeeming. And on Ondo, even a 10 basis point deviation is worth closing. This results in tighter spreads, less slippage, and prices that more closely track the underlying asset.

Tighter spreads, in turn, attract more capital, and deeper liquidity makes the tokens more attractive as collateral, which is beneficial for DeFi integrations. It’s a flywheel effect.

The effects of liquidity and tighter spreads are clear in the graphic posted by the Ondo team, which shows the massive differences in slippage between a GOOGL buy on Ondo’s stock on CowSwap and xStocks on Jupiter (Solana).

Ondo also provides atomic mint and burn functionality for its stocks. The buyer can send USDC and receive tokens in one transaction. While Backed’s process runs through a Jersey-based SPV with settlement up to T+3. For a market maker rebalancing in real time, a latency of 3 days can be deterring.

This helps with on-chain DeFi integrations. As Ondo’s tokens settle instantly, they are much more useful as collateral in DeFi. If a loan is liquidated, the protocol can burn the token and settle the transaction instantly.

Taking it to Retail

Ondo’s other moat is in its distribution strategy. The platform grew to $600 million in TVL within seven months of launch. For context, USDT took approximately three years to reach that milestone, and USDC about eighteen months. What made this possible was an aggressive, multi-surface distribution strategy.

It starts with breadth. Ondo currently offers 200 tokenised stocks across three chains - Ethereum, BNB Chain, and Solana. In comparison, xStocks offers 75, with over 90% of its TVL concentrated on Solana alone.

The breadth of Ondo’s catalogue matters more than it might seem: the top 20 Ondo stocks account for roughly $530 million in TVL, but the remaining 180+ tokens hold another $170 million. That long tail almost matches xStocks’ entire top 20 TVL of $210 million. Investors who arrive for TSLAon stay to build diversified on-chain portfolios; asset selection acts as a capital magnet.

So, where is this TVL concentrated, and who are the traders?

Currently, CEXs account for $8.8 billion of Ondo volume against $2.5 billion on DEXs. Exchanges clearly dominate the trading layer.

BNB has been the core driver for its DEX volumes. Amongst the DEX volumes, BNB Chain drives over 85% of all DEX volume, with 1inch capturing 90% of that flow. The BNB dominance in trading volume is especially interesting as its TVL share is significantly lower.

Ethereum commands 66% of Ondo’s TVL, BNB Chain around 30%, with Solana at a relatively small 3%. Ethereum carries institutional credibility; the lower volumes and higher TVL on Ethereum imply that holders are parking capital, minting stocks and holding long-term equity exposure.

This Ethereum TVL is also the result of Ondo’s existing USDY and OUSG enterprise client TVL on the chain, who just need to click a few extra buttons on the Ondo dashboard to access these assets.

Meanwhile, BNB Chain gives access to Asia’s retail base, with 3.4 million daily active addresses. On BNB, users are rotating in and out of tokenised stocks at high frequency, using 1inch to optimise execution on swaps.

Diversifying across chains has helped Ondo tap into distinct capital pools with varying investor profiles. Ondo’s partnerships help capture these two diverse user populations.

For Ethereum holders, recent integrations have made Ondo stocks a more productive asset class. The team partnered with Chainlink to activate dedicated price feeds for SPYon, QQQon, and TSLAon.

This matters because lending protocols need a reliable, real-time source of truth for any asset they accept as collateral. Without a trusted price feed, a protocol can’t calculate how much a borrower can safely take out against their deposit, or when to liquidate a position that’s gone underwater.

The integration has opened the door for Morpho and Euler partnerships, two of Ethereum’s prominent lending markets, to accept Ondo tokens as collateral. In practice, this means a holder can deposit their SPYon into a Morpho vault, borrow USDC against it, and deploy that USDC elsewhere, all without selling their equity exposure.

It’s the on-chain equivalent of a margin loan: you keep your upside on the stock while unlocking liquidity from it.

For the BNB and Solana retail traders, the partnerships are distribution-oriented. 1inch upgraded its swap API specifically to enable jurisdiction-aware access to Ondo tokens. Tokenised securities carry geographic restrictions; Ondo stocks can’t legally be sold to U.S. persons, for instance. Traditionally, enforcing those restrictions on-chain meant gating access at the platform level: whitelisting wallets, requiring KYC before any interaction, or restricting which frontends could display the tokens. That approach works, but it limits distribution to permissioned environments.

Now, by building jurisdiction awareness directly into its swap routing, 1inch can serve Ondo tokens to eligible users across its entire ecosystem, while filtering out restricted jurisdictions at the infrastructure layer.

Through this 1inch upgrade, Ondo gets the reach of a permissionless DEX aggregator without sacrificing the geographic restrictions that keep the product legally viable.

Additionally, Ondo has also tapped into CEXs and wallets to reach retail traders. MetaMask (30 million MAUs), Trust Wallet (200 million+ users), OKX Wallet, Bitget Wallet, and Ledger were all integrated at or near launch. And recently, Binance Alpha was added, giving Ondo’s token access to the world’s largest exchange ecosystem.

Looking Ahead

Ondo has been building defensibility for its stack through its atomic mint/burns and a broader DeFi integration, however the tokenised equities space is relatively new. The direct tokenisation models are yet to evolve. Securitise has only tokenised one stock so far, Exodus, which holds $95 million in TVL today - higher than any other tokenised stock.

It’ll be interesting to see how the competition between direct and indirect tokenisation will play out in the future. I predict that institutions will prefer the direct ownership model, which they can’t find anywhere else, and non-U.S. retail will keep buying indirect ownership stocks until regulations push them in a different direction.

Nonetheless, there is over $67.999 trillion in stocks left to be tokenised, and how that unfolds is something I look forward to witnessing.

Until then, be curious.
Nishil

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.

Human civilisations have evolved over millennia in countless ways. The way we talk, dress, live, build structures, form communities, gather food, and much more. Yet, there’s one thing human civilisations have had in common - the urge to speculate.

Before the first idea of church and before the state came into being, humans were gambling. Of all the things they did consistently across cultures and centuries, placing bets on uncertain outcomes ranks somewhere alongside cooking and burying the dead.

The oldest known dice date back more than 5000 years. They were found around 2800 BCE in a backgammon-like game set excavated from a burnt city in modern-day Iran. In the 6th century BCE, gambling on chariot races was widespread in ancient Rome, luring all social classes, from senators to slaves. The Indian mythological war epic, the Mahabharata, turns on with a dice game. All four gospels of the Bible record soldiers casting lots for Christ’s clothes after crucifying him.

Every civilisation of every era, in recorded history or man-made epics, found a way to stake something real on an uncertain outcome. This shows that the desire to say “I know something that the world doesn’t” and to be rewarded for that knowledge are inseparable from being human.

Eras changed, venues changed, but the impulse to gamble stayed on. In fact, it evolved with time.

In 1720, the South Sea Company offered its Englishmen a tradeable stake in the future. The promise of a government debt-to-shares swap led to speculations, driving up share prices from around £100 in 1719 to nearly £1,000 in 1720. The potential trade never materialised, and the speculation culminated in the infamous financial crash, the South Sea Bubble, the 18th-century equivalent of a dot-com bust. The British Parliament then banned future speculative ventures.

The itch to speculate remained, just waiting for the next venue. Throughout the 20th century, traditional finance built an elaborate permissioned structure to rekindle this speculative impulse. They introduced a set of checks and balances: accredited investor rules, Pattern Day Trader restrictions, and markets that closed at 4 pm and reopened the next morning. The implicit message to the people was that “you could speculate, but only if you are already wealthy, only on our schedule, and only after completing the paperwork.”

The inconveniences irked many, but there was nowhere else to go. Until there was.

Consider what happened to silver last month.

The shiny metal is among the oldest traded commodities on the planet. It has its own futures markets, institutional infrastructure and centuries of price history. In January this year, decentralised exchange (DEX) Hyperliquid listed a silver perpetual contract.

Within a month, it was handling 2% of global silver trading volume. Not 2% of crypto silver volume. Two per cent of the world’s silver trading was being routed through a protocol with no headquarters, no CEO, and no brokers.

Read: A Sliver of TradFi

It is worth asking where that volume came from. Hyperliquid’s existing user base was largely crypto-native. The silver market, however, is not. Noting the risk of overassumption, the most plausible interpretation of the numbers I derived is that the market attracted traders who always wanted this exposure but without the friction of the incumbent infrastructure.

Hyperliquid removed most of those existing barriers, including brokers, high margin and minimum account requirements, interface friction, and offered high leverage and lightning-fast settlements. Have some opinions to express at 3 am on a Saturday night? Sure, just open the platform, connect your wallet, and express your heart out.

Last month, Hyperliquid processed $2.6 trillion in notional trading volume, almost twice what Coinbase handled.

But comparing this with other crypto exchanges is secondary. What’s more important here is that a perpetual DEX offers humans a choice over their existing traditional financial infrastructure. Don’t mistake the absence of friction for the absence of risk. The same frictionless access at 3 am makes fortune-wiping losses possible at that ungodly hour. But isn’t that the whole point of speculation? With high reward comes high risk. And it’s the unbridled risk that completes the adrenaline experience that’s true to any gambling.

But gambling was never just about the reward. It was also about being right.

Every civilisation also had its oracle. Delphi, the ancient Greek oracle, charged consulting fees for delivering prophecies. Medieval courts often kept astrologers on retainer. The modern version of this saw television pundits being paid generously for delivering their verdicts with confidence and charisma on screen.

Opinions have always had social and economic value. What they lacked, however, at least until recently, was a common market price.

That’s where prediction markets came in. They monetised opinions. When you buy a contract on Polymarket or Kalshi, you are expressing views no longer into a void. Your conviction is being priced continuously against a counterparty who disagrees. If you are right, you collect, and if you are wrong, you pay. The incentive structure and the oracle produce the kind of accountability that ancient punditry never could.

What interests me more is not the existence of contemporary prediction markets but where they have ended up.

This year’s Golden Globes broadcast partnered with Polymarket and read aloud odds before every commercial break. Both CNN and CNBC have signed data deals with Kalshi. Robinhood launched prediction markets, and they became its fastest-growing revenue line at a roughly $300 million annualised run rate. On Super Bowl Sunday this month, prediction markets cleared over $1 billion in a single day. Kalshi even partnered with Venmo for payment integration.

These developments are not aimed at crypto-first individuals. They target sports bettors and political enthusiasts who seek to monetise what they believe they know, but the market does not.

While some view prediction markets as the future of news, their limitations cannot be overstated. There’s the never-ending problem of insider trading. But what excites me the most is how these markets open up a whole range of new primitives that solve everyday problems. Think hedging and insurance. We will dive more into this later this week.

Not every speculative venue has been built on such a solid foundation.

In January 2024, pump.fun launched, allowing anyone to create a tradeable token in seconds. The world went from fewer than 10 memecoins being launched over several years to over 70,000 tokens in a single day at its peak. The launch was backed by participation, with people betting on tokens built around jokes, collective momentum, and even political figures. It went all the way up to the POTUS, Donald Trump.

The TRUMP token, launched days before the presidential inauguration, was bought into by people across the globe. It served as a reminder of how people have always staked money on a cultural movement in ancient history. Crypto has just made the whole process programmable, frictionless, and instantaneous.

This is what I find humbling about crypto. It doesn’t delve into what is ethically right or wrong. Yet, the same system that helped Hyperliquid generate about a billion dollars in revenue also enabled the token launchpad, pump.fun, to earn over $900 million.

Crypto never offered a flawless system to begin with. It often introduced substandard systems as alternatives to the traditionally existing infrastructure. But what’s interesting is how, over time and through multiple iterations, some of these systems evolved into a frictionless, more efficient venue with no gatekeepers, yet were both sophisticated and reckless at once.

We see this pattern in the evolution of capital formation systems. The Initial Coin Offerings (ICOs) of 2017 promised something radical: anyone could fund a project and invest by bypassing venture capital gatekeepers. In reality, most of them failed or were fraudulent. But what followed were iterations and an honest look back at what failed. Each generation of crypto fundraising solved a problem and introduced a new one. As a result, we now see frameworks that take a step toward better addressing these challenges than earlier primitives did.

Read: Virtuals’ 60-Day Experiment

The fact that many projects today generate auditable revenue before issuing a token is evidence of the maturation of the capital formation industry. I don’t think there is anything idealistic about this. If anything, the industry became more practical about which markets would be sustainable.

Read: Burn, Baby, Burn

This shows how the speculative layer has matured over time to satisfy the same human impulse across millennia: the urge to gamble.

Beyond speculation, cryptocurrency has also enabled infrastructure to address another pressing human need: money transfer.

Although the settlement numbers for stablecoins remain open to debate, the places where they found their deepest adoption were not trading desks. They were adopted in countries including Argentina, Nigeria, and Venezuela, where inflation, fragile economies, and weak currencies prompted residents to adopt these digital-dollar equivalents for everyday commerce.

Stablecoins found their product-market fit in places where traditional institutions, like banks and governments, stopped working for the local citizens.

And then there’s the impulse that predates even speculation: ownership.

Long before humans gambled, they claimed. Territory, livestock, and grain stores. The concept of “this is mine” is arguably the most foundational economic behaviour among our species. Every legal system ever devised, from Hammurabi’s Code to English common law, has spent most of its energy defining and protecting who owns what.

Traditional finance built elaborate systems to serve this impulse. Deeds, titles, share certificates, custodians, transfer agents, and clearinghouses, like that an entire industry of intermediaries whose purpose is to record and verify that you own what you say you own. But we have a problem there. The infrastructure is slow, expensive and exclusionary. Settling a stock trade still takes a full business day. Transferring property can take months. And for billions of people worldwide, many of these asset classes remain entirely inaccessible.

Tokenisation attempts to compress that entire intermediary stack into code. A tokenised Treasury bill is still a Treasury bill. A tokenised ounce of gold is still an ounce of gold sitting in a vault. What changes is how ownership is recorded, transferred and used. Settlement becomes instant. Access becomes global. And assets that once sat idle in custody become programmable and composable.

Tokenised real-world assets on public blockchains have approached $20 billion. Tokenised U.S. Treasuries alone crossed $10 billion in January this year, growing tenfold in under two years and tokenised gold has surpassed $6 billion.

These are meaningful milestones for crypto but tokenisation has captured a fraction of a fraction of the world’s assets. The global gold market exceeds $30 trillion. The U.S. Treasury market is $27 trillion. Global real estate sits north of $300 trillion. It remains, by any honest accounting, early.

What shifted recently is not the size of the market but the identity of the participants.

On February 11 this year, BlackRock made its tokenised U.S. Treasury fund, BUIDL, tradable on Uniswap, one of the largest decentralised exchanges in crypto. The world’s largest asset manager, overseeing $10 trillion, chose public DeFi infrastructure to settle tokenised government bonds. And then it bought governance tokens in the protocol.

The deal had been a year and a half in the making, brokered partly by Uniswap’s former COO who had previously started BlackRock’s digital asset division. The meetings alternated between BlackRock’s offices in Hudson Yards and Uniswap’s headquarters in SoHo. It is hard to imagine two more different rooms.

U.S. Treasuries are the base collateral of the global financial system. They underpin the $5 trillion repo market, the overnight plumbing that keeps banks liquid. Leverage is created against them. Structured products are anchored to them. Stablecoins are backed by them. When that collateral moves on-chain, the instruments built on top of it follow. Lending protocols gain access to higher-quality collateral. Derivatives infrastructure connects. Stablecoins are anchored to verifiable on-chain reserves rather than off-chain attestations.

BlackRock’s BUIDL is already becoming a building block for other on-chain products. Ethena’s USDtb and Ondo’s OUSG use it as a core reserve asset. It has been accepted as collateral on centralised exchanges. It has expanded to multiple blockchains. What began as a single tokenised fund is quietly becoming infrastructure on which other products build.

This follows the same pattern. Hyperliquid didn’t invent commodity trading; it removed the friction. Stablecoins didn’t invent the dollar; they made it move where banks wouldn’t.

Tokenisation doesn’t invent ownership. It makes ownership programmable, portable and globally accessible in a way that the existing intermediary stack was never designed to support.

JPMorgan already runs tokenised payments through its Onyx platform. Goldman Sachs operates digital-asset infrastructure for institutional clients. The Canton Network, backed by BNY Mellon and Deutsche Börse, is building permissioned DeFi infrastructure. And now, BlackRock sits on Uniswap, holding governance tokens in a protocol built by pseudonymous developers.

This mirrors what happened with stablecoins. First came scepticism, then cautious experimentation, and then quiet recognition that the infrastructure simply works better for certain use cases. Tokenisation is still in the second phase. The assets on-chain remain a sliver of the assets they represent. But the direction of travel is no longer in question, only the pace.

The technologies that have changed human life in the most defining ways share a single characteristic: they all become invisible. Until something breaks, nobody acknowledges their value.

Nobody thought about shipping containers when they ordered a new electronic device online, until the COVID-19 pandemic brought supply chain issues to the mainstream. People don’t care about the submarine fibre-optic cables that transmit 99% of international data. These technologies have become embedded in daily life to such an extent that their presence is often ignored, while their absence becomes unimaginable.

A perpetual DEX gives back to ordinary people the right to have financial opinion and act on it; something that accredited investor rules took away. Prediction markets allow people to put money behind their mouths. Tokenisation gives global investors access to assets their geographies had locked away. All these primitives address the same complaint that the existing system was built for those who were already inside it, while restricting the outsiders from accessing it.

From barely $45 billion in circulation, stablecoin supply has shot up over six times to $307 billion in the last five years. Although crypto has existed for more than one and a half decades, the focus on developing institutional-grade privacy in the past few years has made more institutions evaluate alternatives to traditional infrastructure for achieving cost efficiency.

What crypto built, through failures, frauds, casino years and reiterations, is an alternative system that didn’t ask for permission while allowing humanity to address the same old need of expressing an opinion.

Today, crypto is often viewed negatively and criticised as a superstructure for its prolonged sideways price movements. What is often ignored is the boring base that crypto has provided to satisfy some of humanity’s oldest impulses, be it speculating or transferring a value. And it is here that crypto’s venues have evolved to become indispensable, quietly becoming part of the fabric of everyday life.

That’s it for today. We will be back with another analysis.

Until then, stay curious!
Prathik & 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.

Earlier this week, Mr. Beast, the largest individual creator on the internet, acquired Step. a fintech company built to offer banking and investing products to teenagers. It’s a financial on-ramp designed to feel native to a generation that grew up on YouTube, TikTok, and online communities.

Now you might think it’s just another creator expanding into fintech. But no, the more interesting angle isn’t the acquisition, it’s what it represents. One of the most powerful distribution engines in the world was just plugged directly into a financial infrastructure! Attention is no longer just being monetized through ads and sponsorships, it’s being routed into financial products.

If you look closely over the past decade, the business of entertainment has changed. Today, Media rights are negotiated years in advance and valued like real assets. Prediction market platforms turn cultural events into tradable markets. Private equity firms allocate capital to sports franchises the same way they would to real businesses or software.

Interestingly, nowhere is this clearer than in sports.

Major leagues today derive the majority of their revenue from broadcast contracts rather than ticket sales. Franchise valuations have grown faster than underlying operating profits. Around every game now sits a web of sportsbooks, data providers, trading platforms, and capital pools that generate their own economic activity, often independent of the result on the field.

The entire industry is layered on top with a financial system that did not exist at this scale years ago.

In this piece, I want to explore how this shift happened, why sports became the testing ground, and how much of what we call “sports” today is actually finance layered on top.

Let’s dive in.

When Entertainment Became an Asset Class

For most of modern history, entertainment was a hit-driven business.

A film either worked at the box office or it didn’t. A tour either sold out or it didn’t. For sports teams, matchday revenue was the lifeblood. Everything depended on how many people showed up at the stadium, bought tickets, purchased beer, and filled seats week after week. Teams were regional institutions because distribution was regional. You supported your local team because it was the only one you and your community could realistically follow.

Then came televisions and changed that, but not for the reasons we assume. At first, sports were simply a way to sell TV sets. Manufacturers needed a compelling way to convince households that a TV was worth buying, and nothing could draw more collective attention than a live game. But once broadcasters saw the audience numbers, they realized live sports were also a uniquely valuable advertising inventory. Unlike scripted shows, they were consumed in real time. Viewers rarely skipped commercials during a championship game, and the uncertainty of the outcome kept people watching until the very end. For advertisers, this meant guaranteed attention at scale, something that very few other formats could offer.

As soon as television spread across households, sports moved from being local events to national broadcasts. Cable television actually played a major role in accelerating this transition. Sports channels were paid a fee for every cable subscriber, whether that household watched sports or not. That created reliable, recurring income for broadcasters. With steady subscription money and strong advertising demand, networks could afford to pay leagues much larger, long-term media rights deals. Over time, the real money shifted away from stadium ticket sales and toward broadcast contracts signed years in advance.

As distribution expanded beyond geography, the fan bases for these teams globalized, too. Today, it’s completely normal for someone in Mumbai to wake up at 3 a.m. to watch the NBA Finals live, or for a teenager in Seoul to own a Golden State Warriors jersey without ever having set foot in California.

The data reflected the same, between 2011 and 2023, commercial revenue for Premier League clubs grew at an average annual rate of 9.3%, and broadcast revenue at 8.7%, while matchday revenue grew at just 2.9%. Over time, matchday income became a smaller share of total revenue. Media rights and sponsorships became the primary drivers of growth.

The next evolution was streaming.

When Netflix released House of Cards in 2013, it signaled that streaming was no longer just about delivering other people’s content more conveniently, it was now also about owning exclusive programming that viewers could not find anywhere else. Over time, every major platform adopted a similar delivery model and started providing “exclusive content”. As Benedict Evans put it, Netflix is not truly a technology company, its advantage comes from what it shows. People subscribe to specific shows, and they stay because those shows keep coming.

Among all types of programming, live sports stand out. They attract massive audiences who watch in real time, which makes them especially valuable for advertisers. When inflation rose and borrowing costs increased, streaming companies could no longer focus only on rapid subscriber growth; they needed profits. So they introduced lower-priced, ad-supported tiers to bring back advertising revenue alongside subscription fees, similar to the old cable model. And Live sports fit perfectly into this approach because they draw consistent, engaged viewership and allow platforms to charge higher advertising rates.

Although the decline of the cable bundle should have constrained broadcasters’ ability to pay ever-rising rights fees, the entry of Apple and Amazon into exclusive MLS and NFL deals expanded the buyer pool

The financialisation of Sports

Media rights had now become long-term contracts with steady revenue streams, so much so that sports teams themselves started to look like financiable assets.

For decades, sports teams were controlled only by wealthy individuals and families. Ownership was personal. It was about status, civic pride, or sometimes even obsession. Liquidity has always been low, and institutional investors stayed away because returns were uncertain and cash flows were uneven.

As broadcast revenue grew, it started attracting a lot of institutional investors to the industry. The NFL, which historically resisted private equity ownership, now allows firms suchas CVC, Carlyle, and Blackstone to acquire minority stakes in franchises. Redbird bought AC Milan in 2022 for €1.2bn, the highest figure ever paid for a football club outside the English Premier League. Dedicated sports funds were raised. Teams were no longer being bought solely by billionaires who loved the game. They were being bought by asset managers.

The returns explain why.

Teams have historically outperformed broader equity indices over long periods. Between 2010 and 2019, average NBA team valuations increased roughly 19% per year. MLB teams rose about 15% annually, NHL teams 13%, and NFL teams 12%. Those are asset-class returns.

Importantly, much of this appreciation was not driven by matchday profits. It was driven by expectations that media rights would continue to grow. Investors were basically underwriting future broadcast contracts.

Some firms even began investing directly in media rights streams rather than teams themselves. CVC invested in LaLiga’s media rights business. Sixth Street financed Barcelona’s future broadcast revenues. These deals separate the cash flow from the club and treat it as a financial product in its own right. If this was not it, scarcity amplified the effect. With only a limited 32 NFL teams and rising global demand, pricing power. Minority stakes began trading at control-premium valuations, sometimes with limited governance rights.

So much so that it changed the discussions around sports, it now centers around yield, appreciation, correlation to broader markets, and long-term structural growth in media consumption.

How much of sports is now finance?

Sportsteam ownership was just the beginning of financializaiton of sports. It is now embedded deeper into the games themselves.

The most obvious example is sports betting. In 2018, the U.S. Supreme Court overturned PASPA, allowing states to legalize sports wagering. Since then, 39 states and Washington, D.C., have introduced some form of legalized betting. What was once geographically limited to Las Vegas became nationally accessible through mobile apps.

Today, betting is no longer a side activity attached to sports. It is embedded into the broadcast itself. Sportsbooks buy prime advertising slots with Leagues selling official data feeds directly to these operators. Live odds update on the screen in real time. For many viewers, watching and wagering are now intertwined behaviors. It has created a flywheel where the game drives betting volume, and the betting volume drives viewership.

Companies like DraftKings sit at the center of that system. DraftKings generates roughly $5 billion in annual revenue from close to $100 billion in betting handle, capturing a small percentage of each wager as fees. With around 10 million users and a public market valuation near $16 billion, it represents the scaled version of modern sports betting layered onto digital distribution.

In 2025 alone, U.S. sports betting reached approximately $164 billion in annual handle, generating roughly $16–17 billion in operator revenue. In under seven years, wagering layered on top of games has grown into one of the largest recurring revenue streams attached to sports. More than 80% of that activity now happens on mobile, meaning the financial layer runs continuously alongside every game.

Prediction markets push this even further.

At peak periods, Kalshi’s activity has implied roughly $50–60 billion in annualized trading volume, with sports accounting for approximately 85–90% of total platform activity. During Super Bowl 2026 alone, Kalshi cleared roughly $1 billion in contracts tied to a single event, with weekly volumes exceeding $2 billion during major sports windows. Sports is not a side category for Kalshi. It is the liquidity engine.

Polymarket, while more diversified across politics and culture, still processes roughly $12–15 billion in annualized trading volume, with sports consistently representing one of its most stable and recurring verticals outside election cycles.

At peak annualized levels, Kalshi and Polymarket together process roughly $60–75 billion in trading volume. With global sports betting handle estimated near $1 trillion annually, prediction markets are already capturing approximately 5–6% of total wagering activity. That share has formed in just a few years. All without operating like traditional sportsbooks and without decades of regulatory and brand infrastructure behind them.

The key difference here lies in the model.

Traditional sportsbooks monetize wagers. They sit between fans and the outcome, take a spread, and scale with betting volume. Prediction markets aim to sit somewhere more foundational. They turn the event itself into a continuously traded instrument. A football match is no longer just a broadcast with ad slots; it becomes a stream of information that flows directly into a market. Every piece of information from injury reports, lineup announcements, referee decisions, weather conditions, and even crowd sentiment moves the price. The probability of an outcome updates in real time, through participants expressing conviction with their capital, and not through a bookmaker adjusting odds.

Those prices increasingly circulate beyond the platform. Prediction market probabilities are also increasingly referenced alongside news and traditional analysis. The number becomes a part of the narrative. In some cases, the market’s price influences public perception more than expert commentary. The “wisdom of crowds” metaphor becomes real.

There is also a psychological shift embedded here. Fantasy sports provided an early version of this dynamic. When fans had financial exposure to individual player performance, it had a direct impact on viewership and engagement. In India, fantasy cricket platforms helped push IPL engagement to record levels before regulatory restrictions disrupted the model.

Prediction markets simply amplify that effect. They enable events to trade as financial primitives, which also expands the scope beyond just sports to elections, the box office, and culture to become markets. Sports remain one of the largest categories because it generates constant, structured outcomes.

Entertainment + finance = funance

At this point, if you look at the shift, Broadcast contracts dominate revenue. Betting markets process tens of billions annually. Franchise valuations compound like growth assets. Prediction markets enable event trade in real time. The majority of economic energy surrounding sports now flows through financial layers built around the game rather than through the game itself.

What makes this interesting is that sports were simply the easiest place for this transformation to happen. It has frequency, global reach, and defined outcomes.

But it is now beginning to extend into the broader entertainment economy. Platforms that control massive audiences (Instagram/TikTok) are starting to attach financial products directly to those audiences. Streaming services, Netflix, for example, increasingly depend on live and high-engagement content to justify advertising tiers and protect subscription revenue. At the same time, markets now form around cultural events that were once purely informational. Elections, film releases, music chart rankings, product launches, and celebrity milestones are no longer just topics of discussion. They generate probabilities that are priced, traded, and circulated in real time.

What has changed is when and how entertainment generates value. For decades, entertainment generated money when people consumed it. Today, it generates money when people signal around it.

Humans are status-seeking monkeys. Social networks taught us that visibility and signal carry value. Financial markets just add a sharper edge to it. Instead of signaling with likes or reposts, people can now signal with positions. When attention can be converted into exposure, and exposure into a measurable outcome, you are no longer just a spectator. Sports showed us how that works at scale. The rest of the entertainment is beginning to follow.

That’s all for today. See you next weekend!

Until then, stay curious!

Vaidik

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.

If you’ve been on Twitter or skimming tech blogs lately, Moltbot (now Openclaw) is impossible to miss. Every second post highlights its ability to run commands, automate workflows, integrate with Telegram or WhatsApp, and finally be “an AI that actually does things.”

And honestly, none of that is new. If I had to sum up Moltbot in one line, it’s basically a local AI agent that has access to your system and can perform actions on your behalf. We’ve had agents that trade, scrape, post, rebalance, and automate for a while now. The mechanics are familiar.

So what actually changed?

For me, the answer wasn’t Moltbot. It was what came right after.

Someone built Moltbook, which is basically Reddit, but for AI agents. Humans can watch, but only agents can post, comment, and interact. And surprisingly… it worked. Agents started talking to each other, replying, forming threads, agreeing, and disagreeing.

Yes, if you zoom out, it’s mostly Claude talking to itself. Most of these agents are powered by the same underlying models. But that’s not the point. What clicked for me was their ability to coordinate on their own.

These weren’t just agents responding to isolated prompts anymore. They persisted, reacting to what other agents had posted or said the previous night. Building context that wasn’t reset after each conversation. That, to me, felt like a dealbreaker. It made me wonder: if they can talk and coordinate, can they also organize? How do they signal intent? Can they trigger actions, move value, or pay for resources, too?

That’s where crypto starts feeling less like a natural enabler. Not because it’s trendy or because “AI needs tokens,” but because it already solves the kinds of problems coordinated systems inevitably run into. Moving value without friction. Enforcing rules without a central operator. Settling actions in a way that doesn’t depend on trust or manual approval.

In this piece, I want to explore that intersection, using Moltbot and Moltbook as a glimpse into a future where agents coordinate with each other by default, and where crypto quietly becomes the layer that lets them move, pay, and act!

Why This Agent Wave Actually Broke Through

If you look at the past few years, Moltbot isn’t among the first AI agents to make waves. For years, we’ve seen repeated attempts to push software from simple automation to autonomy, but most have stalled for predictable reasons.

Tools like Zapier and n8n were early steps in that direction, they allow users to connect APIs, trigger actions based on events, and move data across services without writing hundreds of lines of code. But they were fundamentally brittle. They worked well for deterministic workflows like sending emails, updating databases, and syncing spreadsheets. But these systems relied entirely on predefined logic. Every condition had to be anticipated in advance. The moment a workflow encountered ambiguity or an unexpected state, it either failed or required manual intervention.

Another attempt was using language models in the loop itself. We had projects like AutoGPT and BabyAGI, which emerged in 2023, and showed that models could take a high-level goal, break it into sub-tasks, decide which tools to use, and iterate on their own outputs. For example, AutoGPT could research a topic, write code, test it, and revise its approach without being re-prompted at each step. The idea spread quickly. AutoGPT crossed 100,000 GitHub stars in weeks, and dozens of similar projects followed.

But usage dropped almost as quickly as the initial interest rose. These agents were expensive to run, prone to getting stuck in loops, and required frequent human supervision to avoid runaway behaviour. More importantly, they still operated as isolated instances. One user ran one agent for one objective. There was no shared context, no memory beyond the task, and no interaction between agents.

Moltbot was actually the first project to meaningfully push past this barrier. The key reason was that it could run locally rather than in the cloud, and that it allowed agents to persist. They could hold state across sessions, retain memory, and interact directly with real environments like browsers, terminals, file systems, and messaging apps.

Still, Moltbot on its own was not a breakthrough. It was strong as an execution system, but the agents were still primarily responding to human intent. They waited for instructions, executed tasks, and that was it.

That’s when Moltbook came and shifted the center of gravity. It created a shared, persistent environment in which agents could continuously observe and respond to each other. Posting, replying, and reacting were no longer side effects of a task. They were the task. Agents began operating in the presence of other agents, with their outputs becoming inputs for the system itself. This had immediate scaling effects. Participation no longer depended on human usage; we had agents registered to other agents. Within days, activity reached levels that earlier agent systems took months (or years) to achieve.

Agents Started Doing Things Humans Usually Do

It reached a point where people started using Moltbot in places that normally would require human judgment, accounts, and approvals.

One of the earliest examples of this was RentAHuman.

RentAHuman is a marketplace that lets AI agents hire humans to perform real-world tasks. Agents can browse available workers, select based on location or skill, assign tasks, and pay for them all autonomously. Tasks range from picking up groceries and running errands to attending meetings, taking photos, purchasing items, or conducting verification work.

As of early February 2026, the site showed over 160,000 human workers listed, with agents actively dispatching tasks and settling payments. The interesting part here is that this time, instead of humans, Agents were the ones initiating work, coordinating execution, and closing the loop once the task was completed.

At the same time, Moltbot agents began showing up in financial workflows as well.

One widely shared use case was agents interacting with prediction markets like Polymarket. These agents monitored news, social feeds, and market signals, and then automatically initiated trades using wallets. They weren’t just generating trade ideas. They were executing positions, reacting to new information, and running continuously without someone watching every step.

An important thing to note here is that none of this would have been possible on traditional financial rails.

Banks are built around human identity. Opening an account requires passing KYC checks. Moving money requires authentication flows, confirmations, and often manual review. Automated systems can initiate requests, but they can never own accounts or act independently inside the system. At some point, a human always has to be in the loop.

Crypto, however, works very differently.

It doesn’t care whether the holder is a person or a process. Possessing a private key is enough to act. Transactions settle programmatically, with no approval loop beyond signing. This structural difference is one of the main reasons why these experiments have taken place here first.

Even though this experiment had some adverse effects, too. Security researchers have documented various malicious Moltbot skills posing as trading or wallet utilities, which, if a user installs these skills, could inadvertently expose keys or execute unintended transactions.

The risk is real, but at least we’ve reached a point where AI agents are no longer just generating information or automating workflows. They’ve begun behaving like real economic actors.

What Agent Coordination Looks Like in Practice

Once Moltbook reached scale, agent coordination started to become observable.

A recent empirical study analyzed 39,026 posts and 5,712 comments generated by 14,490 OpenClaw agents interacting on Moltbook, using a full observatory dataset that passively recorded agent activity over time. The goal was to observe how agents behaved when interacting continuously with each other, without human moderation.

Researchers found that roughly 18.4% of all posts contained explicit action-inducing language, commands, step-by-step instructions, or directives that could plausibly trigger downstream execution by other agents.

This matters because earlier agent systems rarely interacted this way. Instructions were usually directed at tools, APIs, or users. On Moltbook, instructions were increasingly directed at other agents. What happened next is even more interesting.

When agents posted these action-inducing instructions, other agents didn’t blindly amplify them. The research shows that such posts were significantly more likely to receive corrective or cautionary replies than neutral ones. Other agents stepped in to flag risks, push back on unsafe actions, or add constraints. This behavior emerged without moderators, rules, or any central safety layer.

In other words, once agents started coordinating at scale, basic regulation emerged within the system itself.

This matters because it changes the nature of the problem. We’re no longer worried about whether agents can coordinate. They already are. The research makes one thing clear: coordination is already happening inside agent systems, and it’s happening faster than human-centric models can keep up with.

We’re curious about what happens when this coordination starts producing real actions with real consequences.

If agents are issuing instructions, triggering actions, and regulating each other’s behaviour, those actions need to be settled somewhere. They need to be executed, constrained, or finalized in a way that doesn’t require a human to step in mid-flow. This is where crypto comes in as the infrastructure that already assumes autonomous actors, irreversible actions, and machine-level settlement.

That’s all for today. See you next weekend!

Until then, stay curious!

Vaidik

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.

While sources vary, most suggest that more than 50% of household investment in India flows into real estate.

The story isn’t as different in the rest of the world. The real estate market cap today stands at $370 trillion, while the equity market is much smaller.

Why am I telling you this?

Because the real estate market is highly illiquid. Selling a property can take weeks or months, and prices continue to rise, making it increasingly unaffordable. Young investors who want exposure to this asset class often have to save for years before they can even think of diversifying into land or flats.

This raises the question: can tokenisation fix this? In theory, yes.

Tokenisation of real estate promises three major benefits: First, fractional ownership— allowing investors to gain exposure with as little as $50. Second. Global liquidity— making properties tradable across borders. Third, digital settlement—so people can invest in buildings on the other side of the world without ever visiting them.

Today, let’s look at where this market stands and how it might evolve.

According to rwa.xyz, tokenised real estate, in its last five years or less has reached about $356 million in value, with most assets spread across USA and the UAE. For context, the Real Estate Investment Trusts (REITs) - fund managed real estate portfolios that trade on the stock exchange - in the USA it took 10 years after their launch in the 1960s for them to reach their first billion in Market Cap.

The global REIT market has grown much higher since then and is now approximately $2.5 trillion with U.S. REITs alone holding $1.4 trillion in market cap. Which means, multi trillion dollar capital looking for real estate exposure all without underlying asset ownership.

These assets listed on rwa.xyz are spread across platforms that are more focused towards accredited investors, such as Hedge Funds, Private equity firms or Insurance Companies, and have almost no retail marketplaces.

Among them is Ctrl Alt, which accounts for roughly $125 million in UAE tokenised real estate. The firm operates as a B2B tokenisation platform and works with Dubai’s Land Department on a government-backed project that aims to tokenise AED 60 billion in assets by 2033. On the other side, we also have Red Swan which is tokenising the USA real estate market with a license from the SEC.

Let’s Bring Retail

While these assets are meant for accredited investors, but there are also platforms like RealT and Lofty that are completely focused on the retail audience and let you buy specific properties instead of getting exposure to a portfolio.

RealT has tokenized over 200 properties across the United States worth more than $45 million, while Lofty has 148 properties tokenized on Algorand with around $3 million distributed in rental income to date.

Here’s what buying RealT typically looks like:

You set up a MetaMask wallet, complete identity verification, and browse available properties. Each listing shows the property address, projected rental yield (typically 6-16% annually), current occupancy, and property management details. You buy tokens with USDC or via credit card, and receive RealTokens representing fractional ownership. The property rent gets distributed weekly in stablecoins directly to your wallet.

Lofty works similarly but on Algorand, with tokens starting at as low as $50 and rent paid daily instead of weekly. Both platforms offer secondary markets where you can sell your tokens before the property itself gets sold.

The catch is that here, the blockchain only tracks the token ownership. Everything else - property deeds, rent collection, maintenance, insurance, legal compliance - runs through traditional structures. Each RealT property is owned by a specific LLC. When you buy tokens, you become a member of that LLC. A property management company collects rent from tenants, deducts expenses, and RealT distributes the net income to token holders.

You’re trusting several layers: that the LLC actually owns the property as claimed, that the property manager is collecting rent accurately, that RealT is calculating distributions correctly, and that the legal structure will hold if something goes wrong. The tokens give you exposure to real estate cash flows, but the custody and operations remain fundamentally off-chain.

What to Solve?

Real Estate Investment Trust (REITs) - the traditional real estate investment vehicles - have SEC oversight, quarterly financial disclosures, independent audits, and legal frameworks built over decades. Tokenized real estate platforms, on the other hand, have platform-specific terms and conditions.

However, they are fundamentally different from tokenised assets.

An investor putting money in a REIT is leaving the job of portfolio management to the fund itself, and has no hand whatsoever in deciding where the investments go. REITs can particularly be dangerous during any real estate market crash like ion 2008, users would have no choice but to cash out their capital from the fund. Whereas for tokenised assets, a trader can diversify to other countries.

Additionally, all REITs are geographically constrained, while onchain applications can offer both a villa in Bali and a commercial property in UAE by design, REITs can’t.

Long-term data (1998-2022) shows REITs have provided average annual returns of 9.7%, while we don’t have much historical data on that for tokenised assets, the returns for Tokenised assets are highly dependent on the purchased property shares, and thus more flexible and user choice dependent.

The trust issue still stands though, and mirrors the early days of stablecoins.

Early stablecoins operated on “trust us, we have dollars in a bank account.” Then Tether faced credibility questions. It’s when Circle responded by publishing monthly attestation reports from independent accounting firms, showing exact reserve compositions, and eventually, Tether followed.

Real estate tokenization platforms have not crossed the trust line yet.

When RealT reports a property generated $X in rent minus $Y in expenses, it lies on the user to trust the platform. While county deed records exist, tracking property ownership across different registries and verifying platform claims requires manual work that most token holders don’t do.

The Stablecoin Playbook

Real estate platforms can learn a few things from how stablecoins built credibility and handled distribution to get to a mammoth ~$300 billion market cap today.

First, regular independent attestations. Circle publishes monthly reserve reports verified by Grant Thornton. Real estate platforms should publish monthly or quarterly reports showing property valuations from independent appraisers, rent rolls verified by accountants, detailed expense breakdowns, vacancy rates, and maintenance costs. Make property ownership verifiable through cryptographic proofs linked to county registries.

These markets need to establish powerful distribution channels that can help establish their moats. Establish partnerships that help them reach where the users are - for Circle that included two strong factors such as the CCTP native bridge launch which allowed seamless interoperability between the chain it supports, and the partnership with Coinbase which even today accounts for approximately a quarter of USDC’s supply source.

For tokenised real estate, the distribution channels need to be both on the supply side of bringing quality rental properties onchain and tapping into the userbase looking for real estate exposure. For supply side the partnerships can be with builders like Ctrl Alt did with the UAE government.

On the demand side, the more composable the underlying asset is within DeFi, the easier it would be to reduce a user’s opportunity cost and attract larger pool of capital that might otherwise look for other yield sources. The sell can’t be “passive income” - that’s what REITs already provide with better liquidity and regulation. The killer app is leveraged yield strategies that only work in DeFi.

DeFi protocols should be able to create secondary DeFi primitives on top of the underlying real estate representations.

Such as building a rental income streams into fixed-rate bonds (buy a token that pays 7% annually regardless of individual property performance), enable derivative trading on property appreciation (long Detroit real estate without buying specific tokens), or build automated reinvestment strategies (rent received in USDC automatically swaps to highest-yielding property tokens).

Projects like Pendle split yield-bearing tokens into principal and yield components, which would do wonders for a real estate asset. Someone receiving $100 monthly rent could sell future rent streams for upfront capital while retaining property appreciation exposure.

Similarly, Yearn Finance has $300M TVL. If Yearn launches a “Real Estate Yield Vault” that automatically allocates deposits to highest-yielding property tokens and auto-compounds rental income, Yearn’s existing users get real estate exposure without ever visiting RealT directly.

Where This Goes

The tokenised real estate market stands at roughly $350-400 million, depending on which assets you count. Projections range from $1.4 trillion to $3 trillion by 2030.

For now, buying tokenised real estate means trusting that LLCs, property managers, and platform operators are doing what they claim. I would still wait for the platforms to evolve further from here before I buy tokenised villas in Bali or get rental yield exposure from UAE markets.

Until then, perhaps precious metals will remain our generation’s default hedge.

Talk to you next Saturday,

Nishil

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Crypto token launches have mostly been one-way doors. Once you buy a token, the only “refund” option available to early backers is to find someone else to sell it to. Worse, if the team behind the project stops shipping or the product never launches, finding a buyer becomes nearly impossible. In the worst-case scenario, all you’re left with is a chart full of red candles crashing down.

We have projects that are addressing this, albeit in different ways.

The first is MetaDAO, which treats the core risk as custody risk. It aims to make fundraising unruggable by routing investor funds into a governed treasury and restricting how teams can spend them.

Another approach comes from Virtuals Protocol’s new “60 Days” framework. This framework proposes a trial-launch format in which a project can wind down in the event of failure, ensuring supporters are not left holding worthless tokens.

Both seek to reinvent fundraising by addressing the accountability gap that persists among early-stage investors.

In today’s deep dive, I will explain how Virtuals’ new approach could change the landscape and whether it outperforms MetaDAO in addressing the problem.

Virtuals’ “60 Days” framework is a contract among three parties: founders, early buyers, and the protocol. It differs from other token-launching protocols in how it funds founders, while ensuring investors a guaranteed refund if the project fails.

Virtuals isn’t the first one in crypto to build a refund button into fundraising. Vitalik’s DAICO idea was an early attempt to let tokenholders “turn down the tap” on treasury outflows, and Fabian Vogelsteller later proposed the “reversible ICO” to let contributors exit without needing a governance vote. But the market moved toward simpler primitives.

Virtuals’ framework allows buyers to purchase tokens and support the founder during a 60-day trial period. During this period, the founder must build in public. All funds raised are placed in a private pool and aren’t fully accessible to the founder until the 60-day period concludes.

It mimics the modus operandi of Special Purpose Acquisition Companies (SPACs), in which funds are held in trust and investors can typically redeem their pro rata share if they don’t like the deal.

Under Virtuals, the project will launch on Base and follow a standard bonding curve, with early liquidity starting in “private pools” and migrating to a Uniswap V2 pool once cumulative volume exceeds 42,000 VIRTUAL.

At the end of the trial, the founder must decide whether to Commit or Not Commit. If they choose to commit, the project “graduates” into a long-term token. If they don’t, Virtuals winds down the project, liquidity is withdrawn, and refunds are distributed from a pre-determined pool.

So, what’s in it for the founder?

Founders can access a small portion of the capital raised and, more importantly, learn the market demand and interest in their project. This gives them the confidence to proceed, knowing they will have sufficient liquidity once they ship a working product.

Meanwhile, Virtuals compensates founders during the trial period in three ways.

First is through a 1% fee on all token trades. This fee is split 30:70 between the protocol and the founder. Here, too, the founder’s share is locked during the trial period and released only upon commitment. This ensures that founders don’t burn capital on a substandard project and instead view it as an incentive to earn returns from successful product shipping. If they don’t commit, the funds are redirected to refunds.

The conditional fee income acts as a behavioural watchdog of founders. They can access a lion’s share of that revenue, but only if they keep building after the trial.

Second is the Automated Capital Formation (ACF) route. ACF is a funding mechanism that allocates capital based on the token’s market participation and trading activity during the trial period. Instead of raising a big lump sum upfront and hoping the team spends it wisely, the framework releases capital available as and when the market reprices the project higher.

Additionally, founders can receive stipends every 30 days (on Day 30 and Day 60), amounting to 10% of the collected funds (from trading tax revenue and released ACF), capped at $5,000 USDC.

Meanwhile, MetaDAO allows teams to optionally allocate up to 12.9 million tokens (50% of initial the supply) into a price-based performance package: five equal tranches unlocking at 2x, 4x, 8x, 16x, and 32x the ICO price, with a minimum unlock time of at least 18 months (and a 3-month Time-Weighted Average Price [TWAP] smoothing where large orders are executed by breaking them into smaller, equal-sized, and evenly timed chunks).

The third route to access capital in Virtuals is via Growth Allocation (GA). Founders may optionally open a GA pool by selling tokens from their team allocation (up to 5%) at a fixed, publicly announced FDV. This differs from the existing fundraising systems in that the GA tokens vest linearly over six months only if the founder commits. Until then, investors deposit USDC at a fixed FDV, and these funds are held in an escrow account until founders commit.

If the GA pool is oversubscribed, Virtuals resolves it using a pro-rata approach, scaling down allocations proportionally. Any unused USDC is automatically refunded.

MetaDAO resolves oversubscription using a slightly different approach. It gives the founder discretion to determine the final accepted capital, after which the pro rata share is calculated relative to that amount.

Although both approaches may appear similar to participants (who eventually receive tokens and a refund), their intents differ. Virtuals treats oversubscription as a mathematical problem, whereas MetaDAO treats it as a decision for founders to make.

Market participants will still complain about both approaches.

Some might argue that MetaDAO’s approach is risky, as it may render the token price a metric that teams optimise for, despite TWAP smoothing. Others may feel that Virtuals’ approach risks embedding predictable selling pressure into the market as a project succeeds, given that it triggers systematic selling. But that might still be healthier than the usual cliff-unlock dump that we witness on other launchpads.

I view both models as the market’s response to the risk of scams and rug pulls in the existing token-launching ecosystem.

Consider the memecoin-style bonding-curve launch model from the pump.fun ecosystem. I find it great for price discovery and creating instant liquidity. However, it’s also evident that the system is optimised for velocity rather than for fixing accountability. Fees are collected as people trade, yet few regard them as a form of capital formation.

On the other hand, systems such as Juicebox.Money treats “money in the treasury” as something users can partially reclaim, depending on a project’s configured redemption rules. Then there’s MetaDAO, which mimics crypto’s version of an IPO by making fundraising less manipulable. It offers investors four days to commit USDC, allocates funds pro rata, and allows the founder to apply a discretionary cap on the capital they can accept. This means that if investors commit $2 million, the founder can cap the fundraising at $1 million.

In this context, I find it difficult to compare what Virtuals and MetaDAO are doing because, while the latter has designed a better auction and treasury handoff, the former offers a better trial period for builders to test the waters before they take off.

But where Virtuals differs from the rest is how it can trigger a structured shutdown when a founder does not commit to launching, while also automating refunds.

There’s a catch here. Virtuals clearly states in its whitepaper that“full refunds are not guaranteed”.

The refunds will be given from an “accumulated funds” pool. This pool comprises released ACF funds, the founder’s share of trading revenue (70% of the 1% trading fee), and the remaining $VIRTUAL in the liquidity pool. However, this pool excludes tokens reserved for teams, unreleased ACF, and certain buyback-related tokens.

Even in the “no commit” outcome, some value may already have left the system through stipends to founders. It might seem unfair to investors, but I find it a fair deal. Consider it the risk any investor assumes when they seek to reap the rewards of betting on a builder or an asset.

In that sense, I like how Virtuals offers a conditional “money-back guarantee”, rather than hiding the fact. I find the framework superior to the incumbents in that it normalises shutting down.

Crypto, like any other industry, is susceptible to failures. If anything, more projects will likely fail than succeed. In a world where many teams keep zombie tokens alive to preserve their reputation, I expect an exit door to change how crypto looks at failed attempts to build something.

I also find it interesting that Virtuals aligns fee extraction with continued effort by making the founder’s trading-tax allocation explicitly contingent on the founder’s commitment to continue building the project.

While Virtuals offers a new way for founders to be early in public without incurring punitive penalties for failure, it also provides participants with a clearer set of rules regarding what happens if the founder walks away. It might still fall short in fully solving the investor protection problem. But I don’t think anyone can. The market will likely always remain unfair to the investor. No investor would ever be willing to part with any of their refund no matter how little.

But the “60 Days” framework, at least in theory, looks like a measured step toward normalising and standardising failure in the world of crypto without compromising on the rights of the investors.

That’s it for today. I will be back with another analysis.

Until then, stay curious!
Prathik

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Uranium fuels 400+ nuclear reactors worldwide and accounts for nearly 10% of global electricity generation. However, it remains largely invisible in the market. There is no widely referenced futures contract, no continuous trading venue, and no clear public signal for where prices stand at any given moment. Investors who follow commodities closely often struggle to determine how uranium is priced or where that pricing actually occurs.

This lack of transparency exists because uranium is not traded in open markets by default. The majority of the global supply is sold under long-term contracts negotiated directly between utilities and producers, often years in advance of delivery. These contracts dominate the volume and dictate pricing for most of the market. Spot transactions occur at the margins, typically when utilities require additional supply or inventories are low, but they are irregular and thin.

This is what has led to recent attempts to represent uranium exposure on-chain. Rather than changing how uranium is produced or consumed, these efforts focus on how claims to physical uranium can be held and transferred.

In this article, I will examine what that shift enables and where it encounters hard limits, with a closer look at projects such as xU308 that aim to make uranium more tradable.

Let’s dive in!

How the Uranium Market Moves

Once you step into the uranium market, the first thing that becomes clear is that buying does not happen continuously. Utilities plan their fuel requirements well in advance, but actual purchases are clustered. Long stretches pass with little activity, followed by short windows where several utilities return to the market at the same time to secure supply.

This pattern shapes how prices move. Uranium prices often remain unchanged for months or even years because utilities are not active buyers between these cycles. When purchasing resumes, it usually occurs under time pressure. At that point, utilities are focused on securing supply. When several buyers return to the market simultaneously, prices can move quickly.

Inventory plays a central role in this behaviour. Utilities typically hold several years of forward fuel coverage, which allows them to stay out of the market for extended periods. As long as their coverage stays above internal thresholds, there is little urgency to transact. Once inventories fall below those levels, buying becomes unavoidable, and availability matters more than the current price.

But supply cannot move at the same pace during this period. Opening a new uranium mine or bringing an idled one back online takes years, once permitting, financing, and regulatory approvals are factored in. So, when demand resumes, supply cannot be scaled up to match in the short term. The market adjusts by drawing down existing inventories, and prices rise until new projects finally make sense, even though any new production shows up long after the buying pressure has already peaked.

Why Access Has Always Been the Problem

Given the structure of the uranium market, it has never been easy for anyone outside utilities and producers to gain direct exposure. Long-term contracts are negotiated privately and are intended for fuel procurement, not for trading or investment. Spot transactions exist, but they are limited, regulated, and irregular. For most participants, there has simply been no clean way to buy or sell uranium.

As a result, exposure has often come through workarounds. The most common method is by investing in uranium mining stocks. Investors buy producers or developers as a proxy for uranium prices, even though these businesses are affected by many factors beyond the commodity itself. Operating issues, financing cycles, jurisdictional risks, and management decisions often matter as much as, or more than, the price of uranium. In some cycles, equities amplify uranium price movements, while in others, they diverge completely.

There have also been attempts to offer more direct exposure through funds and vehicles that purchase and store physical uranium. These come closer to tracking the commodity, but they remain slow and restrictive. Access is limited, transactions are infrequent, and ownership changes hands through fund structures rather than through direct uranium transfers. What ties these approaches together is that they share the same constraints discussed earlier. Storage remains centralised and regulated. Transfers remain slow. Pricing still updates in steps, not continuously. The structure remains the same but is presented in different forms to provide access.

As interest in uranium has grown, these limitations have become critical. Investors seeking exposure now want something closer to the commodity than mining equities, yet more flexible than traditional physical vehicles. They desire clearer pricing, smaller position sizes, and the ability to move exposure without waiting for contract cycles or fund windows.

Trading Uranium On-Chain?

One idea that significantly expands participation in the uranium market is to make it tradable on-chain. This means turning exposure to physical uranium into something that can be held and transferred digitally, without negotiating contracts, arranging storage, or relying on fund structures. If that works, uranium exposure would no longer be restricted to utilities, producers, or a narrow set of institutions. Access could be widened to anyone who meets regulatory requirements.

I know this idea might sound counterintuitive. Uranium is one of the most tightly regulated commodities in the world. Physical handling is controlled, storage is licensed, and ownership is closely monitored. The market was never designed for frequent transfers or broad participation, and these constraints were intentional.

That constraint is exactly what projects working on on-chain uranium are trying to solve for. The physical material does not move. Uranium remains in licensed storage facilities under regulatory oversight, with custody and auditing conducted in physical facilities, off-chain. What changes is how ownership is recorded and transferred. Instead of access being tied to bespoke contracts or slow-fund mechanisms, claims on already-stored uranium are expressed in standardised units that can be transferred digitally.

This model is used by protocols like xU308. Physical U₃O₈ is held with approved custodians and independently verified. Each unit represents a specific quantity of uranium. When ownership changes, the uranium stays exactly where it is. Storage, compliance, and oversight remain unchanged. Only the ownership record is updated.

In practical terms, this eliminates several layers of friction that have traditionally limited participation. Exposure can be taken in smaller sizes. Ownership can change without waiting for fund windows or renegotiating contracts. Pricing becomes easier to observe because transactions happen in a consistent format rather than through one-off deals. Uranium does not suddenly become liquid or speculative, but it does become more accessible.

The timing here matters a lot.

Uranium supply is slow to expand, inventories are finite, and new production takes years to arrive. As access improves, price signals are likely to emerge earlier in the cycle, not because fundamentals change, but because more participants can see and respond to tightening conditions.

On-chain trading does not solve uranium’s scarcity. But it surely changes how that scarcity is reflected in the market, and who gets exposure to it.

That’s all for today. See you next weekend!

Until then, stay curious!
Vaidik

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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.