I hear a loose thought floating around me, used so often at this point: AI will take away our jobs and make us redundant. The bigger irony is that people across domains use this without really questioning exactly what these AI models are replacing in their line of work.

As writers, my team often discusses this idea in our internal calls. Although there are a lot of ideas about how AI will evolve from here, there’s one thought we all seem to agree on. When everyone has access to the same data, similar models and common building blocks, data no longer remains the moat. The content creation game flattens out at the level of data aggregation and research. But there’s something else that AI also does.

Every door closed shut, more often than not opens another one. Once these AI models and the software built on top of them make building things easier, they force humans to differentiate based on our ability to imagine and express diverse tastes.

What I find under-appreciated about AI-enabled software is that they strip away the excuse that building something is difficult or costly. What hurts humans more about AI is not that it takes away our jobs or makes us redundant. But it’s that they act as beautiful filters and ask a difficult question: “Do you actually have a vision that separates you from the rest? Can you build something different when the playground is levelled for everyone to build?

Today’s piece by Kinjal Shah, General Partner at Blockchain Capital and Co-founder of Komorebi DAO, takes that instinct and grounds it in what’s actually happening. It’s about the explosion of personal social software and why open protocol infrastructure like the AT Protocol ensures that small, specific, human experiences don’t have to start from scratch. She explains why the bottleneck isn’t code anymore but imagination.

Give it a read.

Onto Kinjal’s story…

Do you remember when your friendships translated for the first time? I was thirteen, ranking my “top eight” shelf on MySpace, only to realise I didn’t have eight friends I’d include. Ranking them made my stomach sink.

Fast forward to 2026, and numbers are still the fastest way for a stranger to determine your status. The platform on which you’ve gained them adds context. Your name, profession, and appearance are all scrutinised in the flick of a scroll, quickly adding up to a first impression.

What’s real or not is an afterthought. Perception is reality.

The early internet was a companion to many users, whether it was through Tumblr communities or the early blogging world. It allows anyone to expand their network beyond geographies and gain access previously held by gatekeepers.

When the algorithm became the discovery tool for default social experiences, it forced everyone into the same doomscroll. In doing so, it fundamentally changed how humans form connections online, creating parasocial relationships that are optimised for the wrong metrics.

What if it wasn’t the desire for human connection that broke — but the game itself?

The barrier just collapsed. With today’s agent functionality, the cost of creating software has collapsed to nearly zero.

But a more interesting consequence of this is the friction AI removed.

Before, if you had an idea for an app specific to your community or context, you had two options: find an existing platform that approximated it, or hire someone to build it and hope they understood what you meant. Either way, building yourself was for a technical user. It involved real friction for an app that most people might not even want.

That friction is effectively gone. Intent can now translate directly to action.

My brother-in-law recently built an app for his friends where they share weekly sports parlays. He vibe-coded it in a week, and now they use it every week. That wasn’t possible 12 months ago.

We’ve moved from personal computers to personal software.

The parlay app will never have a million users, but it doesn’t need to. It is working perfectly on the one metric that matters the most: deepening specific relationships.

The numbers confirm this.

Apple app store submission grew 30% in 2025, followed by an 84% year-over-year jump in Q1 2026, the largest surge in a decade.

This is after declining 48% from 2016 to 2024. The inflexion point correlates precisely with the release of more accessible agentic coding tools.

What’s even crazier is 63% of the vibe-coding users today classify themselves as “non-developers,” many of whom have never written a line of code.

Personal Social Software is the Future

When I think of the early web, I remember the cosy corners where lifestyle blogs, independent journalism, and the personal website proliferated. One of the biggest enablers of websites was an open-source content management system called WordPress.

As of 2026, WordPress powers nearly 44% of all websites published on the internet.

WordPress didn’t succeed because a single blog had millions of readers. Most WordPress sites have relatively low traffic.

It succeeded because it enabled millions of distinct, self-publishing experiences on shared infrastructure.

The metric that mattered was the number of websites deployed. That’s the same frame for what’s coming.

What would a world of thousands of social experiences, many of which are pop-ups, look like? Each is built for a specific group, ritual, context or use case.

A weekly parlay app for eight friends. A darkroom photography community for a neighbourhood. A shared reading log for a family. A group planning tool for a climbing crew.

None of these needs to win the internet. All of them deepen specific relationships in ways that no generalised platform can, because none of those generalised platforms was designed with those specific people in mind.

When software doesn’t need to scale, it allows for personalisation and community formation.

When the cost of building a social experience approaches zero, the bottleneck shifts from infrastructure to imagination.

Why AT Protocol Matters as Infrastructure

The problem with building your own social experience from scratch is that you start from zero. Your social graph lives somewhere else. Your identity lives somewhere else. You’re effectively building on sand, where the ground can shift quickly under your feet.

This is what killed most of the ‘build your own community’ tools of the last decade. The only audience you’ve been able to own is your email list. Every new network asks users to start over - new account identity, new followers, new context. AT Protocol breaks this constraint.

When you build on AT Protocol, you’re not building on a platform. You’re building into a network that users already belong to. Their identity travels with them. Their followers travel with them. Their context travels with them. The parlay app isn’t a closed garden but a node in an existing social graph.

This means a builder who creates something for eight friends doesn’t have to solve the cold start problem. The network is already there. When someone discovers the parlay app and joins with their existing AT Protocol identity, their connections see that they joined and the context compounds across deployments rather than within each one.

Why Should You Build on AT Protocol?

Shared identity on the AT protocol. Social graph portability lets you bring your users with you. Moderation primitives let you focus on the product rather than on trust- and-safety tools. A whole suite of à la carte building blocks is coming to you.

The things that take months to build from scratch, AT Protocol gives you right away, out of the box.

Try AT Protocol

Attie, the feed-building tool the Bluesky team recently launched, is a live demonstration of what this infrastructure unlocks. It’s a portal into creating your own feed experience on top of the underlying network. What you find there is a vibrant set of users already organising events around science and academia, sports, news, analogue hobbies, and niche interests that you rarely see spaces made for. The like-minded users are already in the network. The tools to build for them are already available.

There are some really unique examples being built today.

One of my personal favourites, Anisota, created a gamified social interface where each post becomes a collectable trading card with rarity ratings and stamina limits to discourage compulsive scrolling. It makes social feel like play. It’s built on AT Protocol, which means it inherits the network rather than having to recruit it.

Tangled is another example, building a social coding platform where coding is a social, owned experience rather than a solitary professional one.

These aren’t competitors to Bluesky. They’re what a healthy protocol ecosystem looks like: multiple distinct experiences, all running on a shared identity and data layer, each finding the specific community it was built for.

The Open Question

The thing I keep coming back to is if AI makes creation cheap for everyone, doesn’t everything converge toward the same AI-generated aesthetic? If the tools are the same, don’t the outputs homogenise?

I don’t think so, and here’s why. The inputs to a 1-of-1 social experience are human taste, specific relationships, and local context. Those don’t homogenise. The medium becomes generative, but the intent stays personal. My brother’s parlay app is shaped by the specific way his friend group talks about sports, the running jokes, and the particular format of their picks. No amount of AI tooling makes someone else’s version of that app feel like his.

The broader ‘human-only’ framing emerging across new social apps is responding to this desire to prioritise human connection. When synthetic content saturates the feed, genuine human context becomes a scarce resource. We are seeing this permeate our everyday interactions. Recently, the World launched a “humans only” concert to address the challenge of bots sniping tickets online.

We’ve also seen this in our digital spaces, on apps like Retro or Subtext, which emphasise private social for humans only.

1-of-1 social is, among other things, a structural defence against that. It’s a social space designed for specific people, making it legible to them in ways that generic content can never be.

Build Something

Cosy corners of the internet are coming back. Not as a nostalgic throwback but as a return to the fundamentals that made the internet a meaningful place for connection. This is the structural consequence of tools that enable personal software.

The social graph can be open. The identity layer can be portable. The moderation primitives are available. The barrier isn’t technical anymore. It’s imagination.

Think about the ritual your group already has that no app serves perfectly. The shared behaviour that happens in spite of the tools you’re using, not because of them. The group chat that’s doing work it was never designed for.

That’s the brief. Build the thing that makes it better — and build it on infrastructure that doesn’t make you start bringing together your users from square one.

That’s it for today,
Kinjal Shah

Try AT Protocol

Try Attie

Disclaimer: This piece was originally published as an X article.

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As a writer, I have been pleasantly amazed by what Substack has become over the past few years. It’s not so much what the platform chose to do that made me stick around as what it chose not to do. Substack doesn’t crowd my screen with engagement metrics or algorithmic noise. It doesn’t turn every interaction into a performance. Each time I open it, I see a clean surface to write on, discover people who align with or oppose my thoughts, and communities I feel like engaging with in some cases or ignoring in others. In the era of short-form content with even shorter shelf lives, platforms like Substack choose the path that slowly builds trust between a creator and a consumer.

It’s this restraint that I find extremely rare in most social networks. This phenomenon becomes clearer when you take a step back and look at other platforms.

I find most of them suffocating with metrics thrown all over the screen, including likes, shares, view counts, and boosted replies. All of these factors collectively determine what you see in your feed. The platform has already decided what the content means, so there’s nothing left for you to decide. You stop participating and start performing. The medium eventually eats itself with too much optimisation.

In today’s guest piece, Anderl makes this argument, albeit with much better examples. He uses McLuhan’s hot-and-cool media framework to explain why SocialFi collapsed, why NFT culture evaporated, and why the platforms that actually work are the ones that know where to let money in without letting it take over.

Onto the story,
Prathik

Follow Anderl’s Works

There is a sentence McLuhan wrote in 1964 that has been quoted so often it has lost most of its meaning. The medium is the message. By now, it sounds like the kind of thing you put on a tote bag. But if you stop and read it as a working diagnostic rather than a slogan, it does something useful, especially for anyone trying to understand why so many recent attempts to fuse social networks with finance have collapsed in slow motion.

McLuhan’s actual argument was narrower and stranger than the slogan suggests. He thought that every medium reshapes the people who use it, not through what it says, but through the shape of the signal it sends. A medium that delivers a finished, high-resolution signal turns its users into receivers. A medium that delivers a partial, low-resolution signal forces its users to fill in the gaps, and in doing so, they become participants. He called the first kind hot and the second, cool.

Print is hot because the page is fully written. Radio is hot because the broadcast is fully produced. A lecture is hot because the speaker controls the signal. By contrast, a telephone call is cool because voice alone carries too little information, and the listener has to construct the missing context. A cartoon is cool because the brain finishes the drawing. Television, in McLuhan’s analysis, was cool because the early signal was so low-resolution that watching required constant active reconstruction. He thought, controversially, that this is why television felt addictive in a way that cinema did not.

The point that matters here is not the specific examples, which date badly, but the underlying claim. The temperature of a medium predicts the kind of behaviour it produces. Hot media produce consumption. Cool media produce participation. And, crucially for what comes next, you cannot turn one into the other without changing what the medium fundamentally is.

What’s This Got to Do with Social Networks?

In McLuhan’s terms, most of what we call social media is cool. A tweet is a fragment. A photo without context is a fragment. A ‘like’ is a fragment. None of these are finished signals. Their meaning emerges only through others’ participation, replies, reposts, threading, and association. A post without engagement is barely a thing. A post with two thousand replies becomes something else entirely, even though the original content has not changed by a single character. This is exactly the McLuhan signature of a cool medium: the artefact is incomplete on arrival and gets completed through use.

This is also why social networks feel the way they do. They are not content delivery systems. They are participation engines that happen to look like content from the outside. The platforms that have understood this, even without ever reading McLuhan, have flourished. Most platforms that tried to professionalise their participation and deliver finished signals to passive consumers have drifted into irrelevance.

The interesting thing is what happens when someone tries to add an economic layer to a cool medium. This is where SocialFi enters the story.

What Did SocialFi Try to Do?

The promise of SocialFi was elegant on paper. The argument was that social capital is real economic value. People generate it constantly, but the platforms capture it all. If we could put social acts directly on a market, then the people who actually create the value would also capture it. Each follow becomes a stake. Each post becomes a tradeable asset. Each connection has a price. The result, in theory, would be a social network that is also an economy, where reputation has a market and creators get paid in real time for the attention they generate.

For a few weeks in late 2023, with Friend.tech, this looked like it might be a real category. People bought and sold each other’s keys. Influencers commanded thousands of dollars in opening prices. The interface looked like a social network and behaved like a brokerage account. Other projects followed quickly, each promising a slightly different version of the same logic. Stamps, gated chats, social tokens, attention markets, and on-chain creator economies. The pitch decks were everywhere.

Then the whole category collapsed. Friend.tech faded. The follow-on projects mostly never reached escape velocity. Token prices crashed and never recovered again. By 2024, SocialFi had become a slightly embarrassing phrase that founders avoided in their next deck.

The standard explanation is that it was a speculative cycle, that people were there for the gains and left when the gains stopped. This is true but shallow. Speculation cycles do not explain why participation collapsed in the underlying social product. People did not just stop trading the keys. They stopped posting, reading, and showing up. The social activity died, along with the financial activity. Why?

The McLuhan Reading

The deeper diagnosis is that SocialFi did not fail because of speculation. Speculation was the symptom, not the cause. The problem was that the entire category was built on a misreading of its own medium.

Social networks are cool media. Their value lies in the fact that participation completes the signal, and that meaning accumulates through repeated low-resolution acts whose significance becomes visible only over time. SocialFi took that medium and replaced its constitutive signal, the social act, with a high-resolution one: a price.

The moment you put a real-time, visible, tradeable price on a ‘follow’ or a post, you have not added an economic layer to a social medium. You have replaced the medium. The new artefact is a fully resolved signal. There is no gap to fill in. The ‘follow’ no longer means anything ambiguous. It means this exact dollar amount right now. And once a signal is that resolved, the rational response is no longer participation. The rational response becomes allocation.

This is why Friend.tech, in its own internal logic, was not a social network. It was a Bloomberg terminal for micro-reputation, with a social network-shaped interface on top. Users were not posting. They were trading. The fact that the trades happened to be on each other’s identities did not make the activity social. It made the activity a financial one that was using social vocabulary as the skin. And once the financial dynamics turned (when prices stopped rising, when the obvious arbitrages closed, and when speculation became less profitable), there was no underlying social medium left to fall back on. The social layer had been consumed by the financial layer at the moment of creation.

This is what McLuhan would have predicted. Hot signals do not coexist with cool media. They replace them. You cannot have a partial, ambiguous, participation-driven act when one of the simultaneous attributes of that act is its current market price, updated in real time, visible to everyone. The price wins. It always wins, because it is more resolved than anything else on the screen.

The early SocialFi designers thought they were building a social network with an economy underneath. But what they were, in fact, building was a market with a social aesthetic on top. The category failed not because of excessive speculation, but because it had quietly become a hot medium and was still being marketed as a cool one.

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Why This Matters beyond Crypto

It would be tempting to read this as a niche post-mortem on a niche product category. But the same logic applies far more broadly, and it explains a pattern in platform history that goes back decades.

Cool media die when they get too hot. This is not a metaphor; it is a recurring failure mode. Platforms that begin as low-resolution participation engines tend to add features that raise their resolution over time. Think of verified accounts, engagement metrics that are visible to everyone, creator funds that pay per view, and algorithmic ranking that shows you exactly how well your post performed. Each of these additions seems harmless or even helpful. But collectively, they describe a slow thermal drift from cool to hot. The medium gets clearer, the signals become more finished, and at some point, the user shifts from participating to performing, and from performing to consuming the performance metrics, and then increasingly stops showing up at all because there is nothing left to fill in.

This is why platforms that look unstoppable at peak engagement often turn out hollow a few years later. They have removed themselves from the regime where they actually generated value. Twitter circa 2012 was cool. Twitter circa 2024 is mostly hot. The drift is not anyone’s fault in particular. It is the natural pull of every metric, every monetisation layer, and every product team trying to make the signal sharper. Hotness is what optimisation looks like, applied to a medium that does not benefit from being optimised.

SocialFi made this same drift in fast-forward, compressed into months instead of decades. By starting with the hottest possible signal, a real-time market price, it skipped the entire cool phase that gives a medium its initial gravity. There was nothing to drift away from. It was hot from the first day, and it died quickly because hot media without distribution moats die quickly.

The Way Out: Condensation Points

If you accept this diagnosis, an obvious question follows. Does this mean that any attempt to fuse social participation with capital is doomed?

No, because there is a third option that early SocialFi missed entirely. You can leave the medium cool and let capital condense at specific points within it, rather than dissolving capital into the medium itself.

The metaphor is borrowed from physics. In a fluid that stays mostly gaseous, there are specific local conditions under which droplets form. The droplets are not the gas. The gas is not the droplets. Both coexist, and the interesting thing is the geometry of where condensation happens. The bulk of the medium remains in its original state, while a small number of points become dense, liquid, and load-bearing.

Cool media can work the same way. The base substrate stays cool. Most acts in the medium remain low-resolution, ambiguous, and participation-driven. But at chosen, specific moments, capital is allowed to condense out of the social substrate and become real, financially anchored, weight-bearing. Crucially, these condensation points are not the medium. They are local intensifications inside it. The rest of the medium is left alone.

I think this is the correct way to read certain platforms that quietly worked while SocialFi did not. Substack is a cool medium for writing. The writing itself is fragmentary, ongoing, accumulative, and completed by readers who reply, forward and quote the posts. Capital condenses at one specific point: the recurring subscription. That subscription is a hot signal, an explicit recurring price, but it is structured as a long commitment rather than a spot trade, which means it does not contaminate the rest of the medium with continuous price discovery. You do not see real-time tradable share prices for individual essays. The medium stays cool, and capital condenses at the subscription edge.

Bandcamp does the same thing for music. Wikipedia does it through donations rather than per-edit pricing. Patreon does it for creators. Each of these platforms has intuitively positioned the condensation points where capital can enter without heating the entire medium. None of them has tried to put a market price on every social act. They have all understood that the substrate must stay cool for the platform to keep generating gravity.

The lesson SocialFi missed is that capital and cool media are compatible, but only on specific terms. The capital has to be local, infrequent, illiquid in the right ways, and structurally separate from the bulk of social acts. It has to condense, not saturate. The moment you try to make every act capitalisable, you have replaced the social medium with an economy. And economies do not produce the kind of accumulating, ambiguous, participation-driven meaning that cool media generate.

What Comes Next

There is a generation of projects that quietly figured this out, often without naming it in these terms, and the pattern is beginning to look stable. They tend to share a few characteristics. The base layer is a social or cultural artefact whose meaning accumulates through participation.

If there is a single sentence that captures the lesson of SocialFi’s collapse, it might be this. Liquidity is heat. Adding it to a cool medium does not make the medium more efficient. It changes the medium into something that can no longer do the thing the original was good for.

The interesting design space, then, is not how to put a price on every social act. It is the much harder, much more specific question of where exactly to let capital condense inside a cool substrate without disturbing it. That question has barely been explored. SocialFi failed to ask it, because it was too busy trying to dissolve everything into a market. The next wave, the one that actually works, will probably be the one that takes McLuhan seriously enough to leave most of the medium alone.

NFTs as the Sharper Case

If SocialFi shows what happens when you build a hot medium and call it social, NFTs show something more revealing. They show what happens when you take a deeply cool medium that has worked for centuries and watch it heat up in real time.

Collecting is one of the oldest forms of cool media. Browsing record bins, stopping in antique shops, trading Pokémon cards on a school playground, and showing a stamp collection at a club meeting are all activities where the object itself carries only half the meaning. The other half is built through participation, recognition, the slow accumulation of a collection over the years, stories attached to specific pieces, and the conversations in which someone notices what you have. The value of a collected object is low-resolution, ambiguous, and context-dependent. That is not a deficiency. It is the mechanism that makes collecting a cultural practice rather than a transactional one.

The early NFT waves, in 2020 and early 2021, still carried some of this logic. CryptoPunks began as an insider thing, almost a joke among crypto natives, with unclear meaning and a value that came from shared culture rather than from a price feed. Early Art Blocks drops had a similar texture. There were forums, Discord channels, places where people talked about individual pieces, traded stories, and built community. The collecting was cool. The artefact was unfinished. It needed participation to mean something.

Then the marketplaces matured, and the thermal drift began, in a form so extreme it deserves to be studied as a case in itself. OpenSea made floor prices visible everywhere. Rarity tools quantified every trait into a numerical score. Real-time charts made every collection look like a stock ticker. Sniping bots made human reaction times irrelevant. Wash-trading volume became a status signal. Each of these features, taken individually, was a rational market optimisation. Collectively, they tipped the medium from cool to hot at a speed no cultural practice had ever experienced before.

The result was almost painfully consistent with what McLuhan would have predicted. The collector became a trader. The trader became a bot operator. The bot operator reduced the artefact’s meaning to a single floor-price number, and once that number fell, nothing was left. The communities that had formed around early collections did not mature into a richer cultural form. They evaporated the moment the market stopped moving. This is not how collectors behave. Collectors stay when prices fall. They keep talking, trading, and tending to their collection. What happened to NFT communities after the crash was not a collector exodus. It was proof that there were no collectors left. Only market participants disguised as collectors stayed, and when the market closed, the veil came off.

This is an even sharper illustration of the medium thesis than SocialFi. SocialFi was a new medium that was hot from its birth. So its failure could plausibly be blamed on novelty or speculation cycles. NFTs took a medium that had worked for centuries, survived wars, technological revolutions and changes in taste, and destroyed its working dynamics in barely thirty months. The medium had worked. The platforms broke it; not by neglect, but by relentless optimisation. Each step made the experience more precise, more measurable, and more efficient. It also made it slightly less collectable, until at some point, there was nothing left to collect.

The cautionary lesson is that thermal drift is not slow. It can happen on a timescale measured in product cycles, especially when the platform layer is built by people who do not recognise that they are operating inside a cool medium. The temptation to add another metric, another leaderboard, and another real-time price feed is constant. Each of these additions raises the temperature by a small amount that feels harmless in isolation. But the cumulative effect is the disappearance of the practice that the platform was supposed to host.

That’s it for today,
Anderl

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Disclaimer: This piece was originally published on Anderl’s Substack.

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

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

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

A lot of crypto conversations still orbit around the speed, cost and finality of infrastructure. They are all important, I agree. But they all rank far lower than something more basic and fundamental when it comes to adoption. Something qualitative and human. I wonder how builders expect a customer to adopt a new technology when they can’t help them understand how the it’s going to improve their life.

Humans evolved as a dominant social animal species because of our superior cooperation and communication skills. Yet, today, we have sidelined the very communication aspect of telling why a new technology matters in the pursuit of seeking better adoption.

Although the crypto landscape has witnessed some of the most useful technologies and products being built, few have focused on building the all-important relationship layer. I am thinking of trust, a user-friendly interface, the regulatory comfort that makes a treasurer or a retail saver actually move their money.

It is true that good infrastructure enables better movement of money, but a robust relationship layer is what can direct and trigger that move.

In today’s guest op-ed, Sebastien Davies, Partner at Primal Capital, writes about how distribution is the mechanism that turns infrastructure into outcomes.

Onto the story,
Prathik

P.S.: This was first published on Interop Markets.

The defining delusion of the last ten years in crypto was the “Field of Dreams” fallacy. Builders and investors operated with the assumption that properly engineered rails would automatically magnetise the world’s capital. This was the Infrastructure Phase, a massively capital-intensive epoch dedicated entirely to building empty containers. Between 2020 and 2024, the fundamental barriers to entry were strict regulatory prohibition and structural impossibility. Fiduciaries lacked the legal mandate to participate, and the baseline plumbing of custody, execution, and reporting simply did not exist at an enterprise-grade level. The industry deployed billions of dollars and dedicated millions of hours to engineering and lobbying solely to overcome these compliance and mechanical realities.

By 2025, the industry reached a quiet consensus. The “Battle for the Rails” had effectively ended in a draw between standardised, institutional-grade multi-party computation (MPC) custody stack and regulated stablecoin frameworks. The mechanical question of how to safely move a billion dollars on-chain has been answered. This technical victory, however, produced a troubling realisation. Infrastructure is fundamentally a commodity. It is a necessary precursor to activity, but it remains entirely agnostic regarding value capture.

In the traditional financial hierarchy, power is rarely held by the entity providing the ledger. It is held by the entity that controls the entry point. We are now witnessing the pivot from the Infrastructure Phase to the Balance Sheet Phase, but the catalyst for this transition is not more technology. It is distribution.

The Friction of the Blank Slate

Infrastructure enables a better system, but it does not account for the “gravity” of legacy balance sheets. A corporate treasurer does not evaluate a new financial rail based on its cryptographic elegance or its sub-second finality. They evaluate it based on the friction required to reach it.

Historically, financial power has accrued to those who minimise this activation energy. In the 1970s, the emergence of Money Market Funds (MMFs) offered higher yields than traditional bank deposits. However, the technology (the ability to pool short-term debt) was not the breakthrough. The breakthrough was distribution through retail brokerages like Merrill Lynch, which placed the “new container” directly into the investor’s existing workflow. The capital moved because the distribution channels made the migration invisible.

In digital finance, we see a similar pattern. The existence of a high-yield, on-chain Real-World Assets (RWA) vault is irrelevant if it sits outside the institutional user’s primary interface. Infrastructure provides the destination, but without distribution, the “audience” never leaves the traditional bank’s lobby.

Distribution Directs Liquidity

If the balance sheet is the strategic asset that determines the winner of the interest rate spread, distribution is the navigator that directs the flow toward that asset. We must view distribution as the “connective tissue” of market structure. It encompasses the presence, trust, regulatory licenses, and API integrations that allow capital to reside in a specific container.

The current market structure is bifurcated. On one side, we have highly efficient, crypto-native infrastructure capable of managing programmable liquidity with unprecedented precision. On the other, we have $100 trillion in institutional balance sheets sitting in “static” containers (traditional bank accounts and custody systems) where returns are suppressed by layers of intermediation.

Value capture in the coming decade will bypass protocols competing purely on marginal fees or throughput. The economic rents will accrue directly to the “Web2.5“ hybrids that monopolise both the customer interface and the regulatory perimeter. These new gatekeepers serve as the critical bridge, offering the “one-click” migration of a balance sheet from a zero-yield checking account into a 24/7 programmable liquidity pool.

The Shift in Gravitational Centres

We are moving into an era in which the distinction between “crypto” and “finance” is dissolving, with a battle for the front-end relationship. As infrastructure becomes commoditised and invisible, the “Interface War” begins.

When a treasurer can park cash in a tokenised Treasury fund as easily as they can in a commercial bank account, one of the bank’s primary moats (the difficulty of leaving) is challenged. However, this shift occurs only when the digital container is distributed through the treasurer’s existing terminal, auditor, and risk framework.

Infrastructure enables, balance sheets fund, and distribution allocates.

In the “Infrastructure Phase,” we treated liquidity as a stagnant pool that merely needed a better pipe. We assumed that superior efficiency alone would naturally drain it. This fundamentally misunderstands financial physics. Institutional capital operates as a dense bundle of permissions, risk mandates, and operational habits. Distribution is the force that actively reconfigures those bundles.

Distribution dictates the path of capital. In any competitive market, economic power accrues to the entity that owns the customer’s attention, systematically commoditising the underlying providers, who still earn a rent.

The Anatomy of Institutional Distribution

For institutional allocators, distribution represents a formidable, three-dimensional moat:

1. Regulatory Reciprocity: The access provider must hold licenses in the allocator’s exact jurisdiction and strictly comply with the allocator’s specific fiduciary requirements.

2. Workflow Integration: The asset has to sit inside existing enterprise command centres, integrated directly into systems like Bloomberg Terminals, BlackRock’s Aladdin, or State Street custodial dashboards.

3. Technical Proximity: The infrastructure must execute within existing legacy settlement cycles and integrate directly into the accounting software used for reporting.

Without these pillars, even the most attractive digital assets remain peripheral. Distribution turns them into balance-sheet allocations.

The “Default” Advantage

The history of financial infrastructure shows that technical elegance often loses to entrenched distribution. The persistence of the SWIFT network and the ACH system illustrates this dynamic. While both are modernising to improve speed and reduce friction, modern blockchain architectures outpace them in programmability, transparency, and marginal cost. Yet these legacy systems remain deeply embedded in enterprise connectivity. Corporate treasuries, payroll providers, and commercial banks are already wired into them.

The true friction of switching extends far beyond transaction fees. It sits in the operational risk of overhauling an entire corporate stack. As a result, value accrues to the gatekeepers who provide seamless compatibility with existing systems. The defining infrastructure of this cycle will be built by those who can bridge legacy capital into modern digital frameworks.

Distribution as a Filter for Signal

In a world of programmable liquidity, the sheer volume of “containers” (protocols, vaults, and yield strategies) creates a massive discovery problem. An institutional treasurer cannot, and will not, perform due diligence on 50 different DeFi protocols. They require a distributor to act as a curator.

This is where the hybrid model begins to take hold. These entities act as the institutional front end, performing risk assessment and compliance, and distributing structured yield to their clients. The underlying infrastructure provides the yield, and the balance sheet provides the scale, but the trusted orchestrator captures the highest-margin economics by controlling the point of access.

Redirected Flow: We are beginning to see the first signs of this “Distribution Arbitrage.” Neobanks and crypto-first exchanges are no longer just offering Bitcoin trading. They are beginning to introduce tokenised money market funds and stablecoin-based yield products directly alongside traditional savings accounts.

When a user’s primary banking interface offers 5% on a tokenised product and 0.5% on a traditional deposit, and the switch requires no change in workflow, the distribution channel has effectively broken the bank’s hold on that capital. The infrastructure was ready years ago. The balance sheet was always there. It is the distribution and integration into the financial service interface that finally trigger the migration.

Victorious Networks

Financial history is instructive here. The firms that scaled were the ones that made their products accessible to existing pools of capital and integrated them into established systems. Distribution, not just design, is what translated innovation into adoption.

Distribution via Jurisdiction

The rise of the Eurodollar market in the 1960s provides the definitive historical precedent for balance sheet migration driven entirely by distribution. The underlying infrastructure (the US Dollar and commercial bank ledgers) remained static. The catalyst was a pure geographic shift in the access point.

By launching dollar-denominated accounts in London, financial institutions systematically bypassed domestic interest rate caps and reserve requirements, engineering a profound innovation in regulatory distribution. This manoeuvre provided global capital with a highly-optimised container maximising both utility and yield. Establishing this offshore channel triggered a balance-sheet migration so complete that it permanently forged the parallel global financial system operating today. The currency rail held firm, while the geographic pivot in distribution simply unlocked a vastly superior economic container.

The Interface Revolution

In the late 1970s, as inflation surged, traditional bank deposits became a liability for savers because interest rates were capped. The “Infrastructure” for a solution (short-term government debt) already existed. However, the average investor could not easily buy T-bills in small increments.

The rise of the money market fund is a useful example. Firms like Fidelity and Merrill Lynch embedded these funds into brokerage accounts with check-writing and sweep features, allowing them to function like cash balances. This made higher-yielding instruments accessible within familiar workflows and gradually shifted a meaningful share of cash away from traditional deposits.

Integration Over Innovation

The rise of card networks is a useful example. In the 1950s and 60s, many banks launched proprietary travel and entertainment cards. Most failed to scale, but it had nothing to do with inferior plastic or slower processing times. They never established distribution across both sides of the transaction.

The networks that succeeded solved this problem in different ways. Visa, originally BankAmericard, expanded through a licensing model that allowed thousands of banks to issue cards, leveraging existing customer relationships. Mastercard followed a similar path through a bank consortium, building broad acceptance and reach. American Express took a different approach, issuing cards directly and owning both the customer and merchant relationships within a closed-loop system.

The structure varied, but the outcome was consistent. Each model achieved scale by embedding itself into both sides of the transaction, becoming the default interface for commerce by controlling access.

The Lesson for Digital Assets

These precedents reveal a recurring law: Infrastructure is the invitation, but distribution is the mandate.

● The Eurodollar proved that capital will migrate to wherever the distribution is most efficient and least constrained.

● The MMF proved that the interface (cheque-writing on a brokerage account) determines which container the balance sheet chooses.

● The Credit Card proved that leveraging existing trust networks is faster than building a new network from scratch.

In 2026, the crypto-native system is still in its early stages of distribution. The infrastructure for yield and continuous settlement is already in place, but it has not yet been integrated into the interfaces institutions rely on. Adoption will come from embedding these capabilities into existing workflows, from consumer financial apps to the treasurer’s daily operating environment.

Distribution in Digital Assets

The 2026 landscape makes one thing clear. Decentralised infrastructure is in place, but distribution remains concentrated. With a total market cap of roughly $2.5 trillion, economic activity is already clustering around a small number of access points.

The relevant question is where default relationships are forming. These are the platforms that sit at the interface with the user, and increasingly, at the centre of capital allocation.

ETF Familiarity

The approval and maturation of spot ETFs have provided a clear example of how distribution drives adoption. By placing digital assets within an established regulatory wrapper, firms like BlackRock, Fidelity Investments, and Morgan Stanley have made them immediately accessible through existing wealth management channels.

This has translated into scale. As of Q1 2026, U.S. spot Bitcoin ETFs hold over $128 billion in assets, reflecting not just demand for the asset, but the reach of the distribution layer through which it is delivered.

BlackRock’s IBIT has emerged as a benchmark because it sits inside these systems and is backed by one of the most trusted brands in global finance. It appears alongside other ETFs, within familiar workflows and allocation models. Adoption followed integration, not novelty. In effect, the asset class has been mapped directly onto the balance sheet workflows of the world’s largest pools of capital.

Neobank Proximity

A different form of distribution is emerging through neobanks and fintech platforms. Applications like Revolut, Chime, Nubank, and Robinhood increasingly serve as the primary financial interface for a large segment of users. Within these environments, new products do not need to be discovered. They simply appear alongside existing balances.

As crypto-native yield, whether through staking or tokenised assets, is placed next to traditional accounts, the decision to allocate becomes a matter of interface design rather than infrastructure. The distinction between a USD balance and a USDC balance begins to collapse into a simple choice within the same system, subject to what these platforms are permitted to offer.

In 2026, roughly 30% of American adults hold some form of crypto exposure. For many, their primary relationship is no longer with a physical bank, but with an application. Distribution, in this context, is not about access to a new system. It is about integration into the one users already rely on.

Custody Opportunity

Firms like Coinbase, Fidelity Digital Assets, Anchorage Digital, and BitGo are becoming core distribution nodes for institutional capital.

Their role extends beyond safekeeping. They provide the compliance, reporting, and operational integration required for institutions to participate at scale. In this context, custody becomes the interface through which capital is allocated, not just where assets are held.

As these platforms expand into trading, financing, and settlement, they increasingly resemble full-service financial environments. The underlying infrastructure remains important, but allocation decisions are made through these controlled interfaces. Distribution, in this layer, is defined by permission, integration, and trust.

Stablecoin Settlement

Stablecoins are moving beyond their role within crypto markets and becoming part of broader financial and operational workflows. Their relevance now extends into payments, settlement, and treasury functions, where they are increasingly integrated into existing systems.

Firms like Circle have focused on building this distribution through partnerships with banks, payment providers, and financial platforms. The objective is not just issuance, but placement within the systems where transactions already occur.

A similar pattern is beginning to emerge in software and AI-driven environments. As developers build applications and autonomous agents that operate programmatically, stablecoins are being integrated as a native payment mechanism. In this context, adoption will follow the stablecoins that are most accessible within developer tools, platforms, and APIs, extending distribution beyond financial interfaces into software itself.

Emerging Hierarchy

The structure has shifted. Early efforts focused on building the rails. Today, the advantage lies with those who control the interface.

Whether it is an ETF ticker, a neobank application, or a prime brokerage platform, the entities capturing the economics are the ones that present new capabilities within familiar systems. They translate complex infrastructure into formats that align with existing habits, and in doing so, become the default point of access.

This is what ultimately determines where balance sheets move. Capital does not migrate because the infrastructure improves. It migrates when the interface makes allocation seamless within the systems it already uses.

Stablecoins as the Clearest Example

Stablecoins are the purest manifestation of the distribution thesis. They are not merely “digital dollars”; they are the primary distribution vehicle for the US financial system in the 21st century. While the industry spent years debating the merits of different Layer 1 protocols, stablecoins quietly became the “killer app” by solving a distribution problem rather than a technical one. They made the world’s most trusted balance sheet (the US Treasury) accessible to anyone with an internet connection, 24/7.

Stablecoins are introducing a new form of competition in the deposit market. They package short-duration government-backed assets into a programmable, portable, and continuously accessible format. As distribution improves, capital can move more easily between traditional accounts and these digital alternatives.

The Utility Gap

The persistence of Tether (USDT) is the ultimate proof that distribution beats “better” infrastructure. For years, critics pointed to USDC’s superior transparency, regulatory standing, and institutional backing. In a vacuum, USDC is the “better” product.

Tether established early distribution in offshore trading markets and across many emerging economies. It became a primary liquidity instrument across exchanges and a widely used medium for cross-border transactions.

By the time regulated alternatives entered the market, Tether was already deeply embedded in trading, settlement, and informal financial flows. Its presence across platforms and use cases created a level of integration that is difficult to displace.

Programmable Liquidity

The next phase of stablecoin distribution is the shift from passive holdings to active use. In 2026, these assets are increasingly being integrated into operational workflows.

This is showing up across a few key areas:

● In supply chain finance, large corporates are beginning to use stablecoins to accelerate settlement with suppliers, reducing reliance on traditional correspondent banking timelines.

● In commerce platforms, companies like Shopify and Stripe are enabling merchants to hold and manage balances in stablecoin form, introducing new options for liquidity management.

● In software environments, as applications and autonomous systems transact programmatically, stablecoins are being integrated as a payment layer for real-time, granular transactions.

In each case, adoption is driven by utility within existing systems rather than by exposure to new asset class.

Extending Distribution

Banks are responding to stablecoins by extending their own distribution. Deposit tokens and bank-issued digital assets will allow them to bring existing balance sheets onto new rails while maintaining control of access.

The objective is to preserve their role at the point where dollar-denominated value is accessed and deployed. As these instruments are integrated and eventually embedded into payroll systems, trade platforms, and software environments, the competitive dynamic shifts toward distribution.

As the market continues to scale, value accrues to the entities that control the interface through which transactions are initiated and managed.

Institutional Constraints

If the technical rails are ready and the economic incentives of the balance sheet are clear, why has the “Great Migration” not yet reached its terminal velocity? The answer lies in the final, and most formidable layer of the distribution moat: institutional friction. For a Chief Investment Officer or a Corporate Treasurer, capital allocation is governed by fiduciary responsibility, regulatory constraints, and operational requirements.

Distribution, in an institutional context, is the process of neutralising these three specific types of friction.

The Regulatory Distribution Gate

In the retail world, distribution is about “eyeballs.” In the institutional world, distribution is about licenses. An institution cannot legally park a balance sheet on a protocol, no matter how efficient, if that protocol sits outside its regulatory perimeter.

In 2026, distribution is increasingly concentrated around assets packaged within familiar legal and regulatory structures. Tokenised Treasury funds such as BlackRock’s BUIDL and Franklin Templeton’s FOBXX illustrate this pattern.

These instruments allow institutions to hold digital assets within existing investment frameworks, including structures that qualify as regulated investment companies. The format is new, but the pathway to allocation remains unchanged. These assets are accessed through standard brokerage systems and integrated into existing balance sheet management.

Workflow Lock-in

Large-scale capital does not move via a browser extension or a mobile app. It moves through established “Workflow Hubs” like the Bloomberg Terminal, Aladdin, or Charles River. These platforms are the ultimate distribution monopolies because they own the daily habits of the financial professional.

Early digital asset infrastructure was built as a parallel system. It required users to step outside their existing workflows to access it. For institutions, this created friction at the point of allocation.

Distribution is now shifting toward integration. Digital asset custody and exposure are being embedded into existing reporting, risk management, and portfolio systems. The objective is to make on-chain positions appear alongside traditional assets and behave consistently within the same operational framework.

Distribution Runs on Trust

In finance, trust is embedded in the distribution layer. Capital is allocated through counterparties that meet established standards for regulation, creditworthiness, and legal recourse.

The failures of major crypto intermediaries in 2022 and 2023, including FTX and Celsius, reinforced the importance of this framework. Established institutions such as BNY Mellon and State Street entering digital asset custody extend that layer of trust into new formats. Their role is not just to provide infrastructure, but to make digital assets compatible with existing expectations for balance sheet allocation.

Compliance at the Interface

The final piece of institutional distribution is integrating compliance into the interface itself. To access large pools of capital, digital asset systems must meet real-time requirements for transaction monitoring and anti-money laundering.

The firms gaining traction are embedding these controls directly into the point of access. By the time capital reaches the underlying system, the relevant checks have already been performed. Compliance, in this structure, becomes part of the distribution layer rather than a separate process.

This allows institutions to interact with programmable liquidity within established regulatory expectations, making allocation operationally viable at scale.

Where Distribution is Moving

As we look toward the 2027–2030 horizon, the “Interface War” is entering a phase of total invisibility. The goal of distribution is no longer to convince a user to “use crypto,” but to embed digital asset utility so deeply into existing platforms that the end-user (whether a retail saver or a corporate treasurer) doesn’t even realise they have migrated their balance sheet.

Invisible Distribution

The next great capital reallocation will be driven by Embedded Finance. In this model, the distribution node isn’t a bank or an exchange; it’s the software in which the economic activity already occurs.

● ERP Integration: SAP and Oracle sit at the centre of institutional financial workflows. As new forms of liquidity integrate into these systems, allocation decisions can be executed within existing treasury processes. When excess cash can be directed into tokenised instruments from within the same system used for cash management, the balance sheet moves as part of the workflow rather than through a separate interface.

● Supply Chain as a Ledger: Distribution is extending into supply chain and trade systems. Platforms that manage global logistics are beginning to integrate stablecoin-based settlement into their core software, connecting payment and transaction data more directly. As settlement becomes embedded within these workflows, financial activity moves closer to the underlying commercial process, creating new pathways for liquidity and credit to be applied in context.

Banking Platforms

Traditional banks have long served as the primary distribution layer for capital. Leading incumbents are now extending this role into programmable liquidity, leveraging their decisive structural advantages: decades of fiduciary relationships, comprehensive regulatory licenses across jurisdictions, deep integration into enterprise systems (Bloomberg Terminals, Aladdin, custodial dashboards), and the bedrock of deposit insurance together with general balance-sheet trust. These moats make it exceptionally difficult for neobanks or crypto-native platforms to achieve meaningful distribution at an institutional scale.

This advantage is decisive. While fintechs and crypto platforms can capture retail flows and smaller corporate wallets through superior user experience, meaningful “distribution arbitrage” at the multi-trillion-dollar institutional level remains limited. Banks do not need to out-innovate the underlying rails. They simply need to embed on-chain yield, settlement, and programmability into the interfaces and trust networks they already own. In this sense, the Interface War is one that banks are structurally wired to win.

● White-Label Liquidity: A hybrid model is beginning to take shape. Banks provide the trust, regulatory framework, and client interface, while yield is sometimes sourced from external, on-chain systems. In this structure, the bank’s role evolves from holding static pools of capital to managing flows across a broader set of financial environments.

● Deposit Tokens: The bank account of 2028 is likely to take a different form: a licensed deposit token that remains compatible with existing banking systems while extending into digital asset networks.

Agentic Distribution

A further shift is emerging as financial activity becomes more automated. As software systems and autonomous agents begin to manage capital, distribution extends beyond human interfaces and into code.

In this environment, allocation decisions are shaped by parameters such as integration, programmability, and capital efficiency. Systems that are easier to incorporate into software workflows become more likely to be used.

Distribution, in this context, is determined by presence within the tools and environments where these decisions are executed. Assets and protocols that integrate cleanly into developer ecosystems and meet operational and compliance requirements are more likely to be selected as default components within these systems.

The Point of Allocation

The arc of the last decade is clear. The underlying systems have been built. Capital can now move across them. What matters now is how that movement is directed.

The infrastructure is in place: secure custody, scalable networks, and programmable assets. These capabilities made participation possible. The next phase is defined by how capital is allocated across them.

As we have seen, capital does not move on technical capability alone. It moves when the pathway is integrated into existing systems and aligned with economic incentives. Distribution is what makes that movement operational.

Where Value Settles

As we move toward 2030, the distinction between digital assets and traditional finance becomes less relevant. The underlying systems are converging, combining the efficiency of new infrastructure with the stability of existing balance sheets.

In this environment, financial power sits with those who control the interface through which liquidity and collateral are accessed and allocated. The role of financial institutions evolves accordingly, from holding assets to managing flows across increasingly integrated systems.

The infrastructure is in place. The balance sheet is becoming more mobile. What determines outcomes now is distribution.

That’s it for today.

See you with the next one,
Sebastien Davies

Disclaimer: The piece was originally published in Edition 3 of Interop Markets

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

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

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

Last week, my sister asked me the one thing I absolutely dread in my line of work. ‘Can you teach me how to invest in crypto and become rich?’ On most occasions, I politely evade the topic. But since it was my sister, I conceded.

For the next couple of minutes, I explained to her about on-ramps, off-ramps, centralised and decentralised exchanges, switching, bridging, chains, and a few other concepts. I told her how these form the base for moving money between on- and off-chain financial worlds.

She thanked me, perhaps sarcastically, and told me she was content with moderate yields on equities and commodities. I got out of the predicament, but a thought lingered. This wasn’t the first time I’d seen someone feeling overwhelmed by trying to wrap their mind around how crypto works. Not that it is as difficult to understand, but the thought of having to trust a smart contract without any recourse to a centralised body, like a bank, to go back to, scares many.

I think this ‘trust problem’ is the single biggest reason to keep the masses away from adopting crypto. But I also feel crypto, for what it offers, can change the way the world moves money for the better. This is why the ‘trust problem’ needs to be addressed.

In today’s guest piece, SysLS writes about how the timing of AI-based primitives couldn’t have been better to help crypto change the world of finance for good.

You can follow his works on X and Substack here 👇🏾

X

Substack

Onto the story now,
Prathik

P.S.: This piece was first published on Systematic Long Short.

Betting on crypto has essentially become a bet that humanity will continue to seek acceleration in its processes. That seems like an easy bet.

I think the time is now because of the birth of meaningful artificial intelligence, which finally gives us the tools to drastically reshape how we interact with crypto.

This article explains why crypto will become a strategically important asset class.

Bottlenecked by Due Diligence

Humans have sought acceleration since the dawn of time. We measure success by efficiency and have consistently reduced friction in everything we do. Where it once took weeks to wire money across distances, it now takes seconds.

Today, most human processes are no longer bottlenecked by technology, but by the need for verification. Getting a job, opening a bank account, or raising funds still takes weeks. That’s not because the technology to complete these processes quickly doesn’t exist, but because humans must bear the cost of verification.

In an employment process, the employer needs to verify that you are not a lemon. It’s not that you have never been hired before, but it’s still worth doing independent verification because your previous employers will not take responsibility if you turn out to be a poor hire. Further, there is an argument that the best employees stay employed. Lastly, different environments and job scopes also imply that past performance may not be indicative of future performance.

So, employers pay the cost of due diligence by way of several rounds of interviews and take-home assignments. This process takes time and human effort — it is messy, unstructured, and non-deterministic; and also why hiring processes are as much a function of luck (did your interviewer have a good morning before meeting you? Or did they just have a massive argument with their spouse?) as a function of skill.

It is fairly trivial to reason that all costs in such processes are verification costs.

The actual act of officiating employment is quick and relatively painless — an email and a digital signature. This means that, in theory, suppose there was a magic scoring box that could output the absolute scores of a candidate employee across every dimension you could possibly care about, and you trusted this score with a high degree of confidence. Then, the time taken to hire someone would be reduced to the algorithmic time of filtering for and sorting the scores you care about, then sending over an employment contract and having them sign it.

Forming A Trust Daisy Chain

The reason you are able to hire someone near-instantly with the addition of a magic scoring box is that you have delegated the responsibility of verification to it, and you have learned to trust it.

In practice, this happens all the time.

Potential employers within the same industry borrow the due diligence of past employers — your resume is less likely to be binned if you have been to top-tier institutions and have done difficult things before.

Whenever possible, humans pass the cost of verification to a higher entity and trust that it has acted in their interest and done the prerequisite verification. For example, a vast majority of humans simply trust that the government’s banking oversight arm has done its job, rather than conducting lengthy, detailed, and expensive due diligence on a bank before opening an account with it.

If we trust the government sufficiently and its ability to uphold the law, then we can take its word that the bank is solvent and safe for our financial affairs.

This “trust daisy chain” happens everywhere, all the time, in things - big and small. A start-up has no brand equity and therefore commands no inherent trust, but a large, reputable, and successful Venture Capital (VC) firm can lend the start-up brand equity by simply investing in it. The public, though unfamiliar with the start-up, trusts it if they trust the VC, since they are delegating verification to the VC’s due diligence process.

The Problem With Crypto

Crypto has traditionally offered no “higher entity” to which we can pass on the cost of verification. Having no higher entity to arbitrate honest mistakes, like swapping $50 million USDC for $5,000 worth of tokens or even sending it to the wrong address, implies that the cost of verification falls squarely on the user.

This is genuinely difficult because smart contracts are not designed to be parsed by humans in under a second. This is essentially why most crypto has remained relatively niche. Where there has been widespread adoption of crypto products by the retail masses, it has mostly come in the form of large, centralised institutions that abstract away the complexity of smart contracts (e.g., Binance and Coinbase).

These retail users may not understand how Aave smart contracts work, but they have learned to trust Binance; therefore, Binance can build a business out of abstracting the complexities of the smart contract from the user and wrapping it in a simple interface.

This means that, technically, light users really only have two options when it comes to crypto: wait for a centralised entity like Binance to offer an abstracted version with some fees, or interact directly with the protocols and risk catastrophe.

Despite crypto’s relative maturity, it is still extremely high-friction to work with and fundamentally scary to approve transactions, mostly because you know there is no recourse if you mess up. So you diligently verify, but it is not trivial to read and parse through every transaction you do on-chain, let alone deeply understand the smart contracts you are interacting with.

For those who understand software and its infinite composability, the allure of crypto has always been an ecosystem of modular components that can interact with each other in a trustless manner upheld by algorithmic law. The headwind on the way to that potential utopia is that bad actors and poorly designed edge cases require humans to pay the cost and friction of verifying each modular component.

Where Does AI Help Crypto?

The rise of meaningful artificial intelligence allows us, for the first time, to delegate verification to a higher entity. This drastically changes our mode of interaction with smart contracts. We will no longer need to personally verify the design and behaviour of smart contracts, or even necessarily understand the details of our transactions.

Instead, we learn to trust a single entity — our agents. This is already showing great promise, as agents demonstrate considerable expertise in understanding and reasoning about code. They can tirelessly parse and check transactions and understand the algorithmic law that each smart contract upholds within seconds.

This implies that for the first time, through our agents, we can realise the potential of crypto. Need to interact with nine smart contracts in one atomic transaction to get what you want most efficiently? Have your agent verify that the transaction achieves the outcome you want and that no foul play is involved. Done.

With each successive generation of agents, they will only get better at this.

Implications of Algorithmic Verification

If we can resolve the problem of verifying smart contracts and the transactions they generate, then we move toward the utopia of having all kinds of interactions available to us while remaining permissionless, trustless, and upheld by algorithmic law. If the cost of verifying a smart contract goes to zero, then we gain the benefits of all the verification and guarantees the smart contract brings for free.

The major consequence is that all processes that remain within this paradigm now move at the speed of compute. For a civilisation determined to move faster, remove friction from processes, and become more efficient, it is hard to imagine us straying from this paradigm.

It only makes sense that more and more goods and services will have smart contract interfaces that determine exactly what you will get and what you will need to exchange to get it. It is also a paradigm that compounds on itself — every successful product would create a composable piece that can play into another product later on. For example, suppose a decentralised exchange created a reputation system for trading proficiency. People looking to hire traders using a trustless employment protocol might filter based on the reputation contract of an unrelated decentralised exchange. A lending protocol might use that as one dimension of credit scoring.

Such a paradigm would not only be extremely efficient — all processes and transactions moving at the speed of compute — but boundless, growing more powerful and unlocking more possibilities as a function of participation and time. It is a positively compounding paradigm.

So, if you believe that humans will continue moving in the direction of least resistance and seeking out solutions that allow us to move faster, be more efficient, and do more, it seems the time for crypto is now.

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.

Most of the AI conversations I’ve come across have largely been dominated by GPUs. Nvidia’s stock price, chip export bans, and data centre buildouts - is all that anyone talks about. But there’s a lot more that’s brewing underneath that seldom get the attention it deserves. So, when I read a piece about the memory industry that powers the entire AI stack, it felt under-appreciated.

The fact is that the GPUs are only as powerful as the memory that feeds them data. Without enough bandwidth, the most advanced chip in the world is useless.

Memory companies like Micron and SK Hynix have historically been treated as commodity players whose stocks rise and fall with supply gluts. But that perception is chaging. AI workloads need memory more than traditional computing ever commanded. So, a handful of companies that know how to manufacture high-bandwidth memory at scale are finding themselves with pricing power they’ve never had before.

In today’s guest piece, Kerman Kohli and Nicolas break down the memory industry from first principles, including what the different layers of memory actually are, why HBM has become the critical bottleneck in the AI buildout, and what makes these companies so hard to compete with.

You can follow their works here:

Kerman's Substack

Nicolas's Substack

Onto the story,
Prathik

Hello

Everyday it feels that memory stocks are going up. Micron, one of the largest memory players, is up almost 3x in the past year alone. Many investors are stuck seeing similar names go up day after day, waiting for a pullback. However, they fail to really understand what the product really is.

In this piece, Nicolas and I are here to break it down in an easy to understand way to understand the opportunity at hand. Let’s get into it.

Intro

So what is memory and why is it so important?

Memory is what enables a computer or device to store information while ephemeral computation is being performed. This is done predominantly through read and write operations. Each layer of memory has different profiles around read/write speeds, cost and capacity.

In AI, memory has become even more important because models need to process massive amounts of data all at once. When we use tools like chatbots, image generators, or recommendation algorithms, memory is constantly moving huge datasets in and out at high bandwidths.

The more intelligent and capable AI models get, the more memory they need to function effectively. Without powerful memory systems, advances in Large Language Models and Machine Learning use cases stall.

The Memory Hierarchy (Storage vs Working)

To better understand memory, we first need to break down the layers of memory.

Computers split memory into working memory (used while the system is actively performing computations) and storage memory (used to save data long-term at the expense of slower read/write speeds). This separation exists as memory that is high bandwidth (low read/write times) is expensive, while long-term memory that is cheap, is lower bandwidth (high read/write times).

Many concepts around memory boil down to the distance that the chip is from the processing unit. The further the distance, the slower the throughput.

1. Processor Registers & CPU Cache (SRAM):

What it is: This is often the highest throughput memory in the entire system as it is sitting inside or right next to the XPU (XPU = CPU or GPU). It holds tiny bits of data the processor needs right now.

What it’s made of: SRAM (static memory built directly on logic silicon)

Cost & size: Extremely expensive per bit, tiny capacity

Where it’s made: On the same chip as the CPU

Key manufacturers: Intel, AMD, Apple

2. Physical Memory (DRAM / RAM)

Designated random access memory / Random Access Memory

What it is: This is the computer’s main working memory, the desk where active programs live. Throughput is required here as delays cause a queue of computations to occur.

What it is made of: DRAM cells (one transistor + one capacitor per bit)

Cost & size: Somewhat expensive, medium capacity (GBs)

Where it is made: Mostly fabricated in South Korea, Taiwan, and the U.S.

Key manufacturers: SK Hynix, Samsung Electronics, Micron

3. High Bandwidth Memory (HBM)

Specialised DRAM

What it is (simple): Ultra-fast DRAM stacked vertically and placed next to AI chips. Due to the vertical stacked nature of HBM, it has higher throughput at the expense of manufacturing complexity.

What it’s made of: DRAM dies stacked with through-silicon vias (TSVs)

Cost & size: Very expensive, smaller capacity relative to DRAM; although much faster than it

Where it’s made: Taiwan & South Korea, due to the advanced packaging requirement (physical vertical integration)

Key manufacturers: SK Hynix, Samsung, Micron

4. Solid-State Storage (NAND / SSDs)

NAND is non-volatile flash memory that stores data without power, used in high-density storage devices like SSDs, USB drives, and memory cards.

What it is (simple): Long-term storage for files, apps, and data when power is off

What it is made of: NAND flash cells storing electrical charge

Cost & size: Cheap per Gigabyte, large capacity (hundreds of GBs to TBs), lower throughput than HBM and DRAM, but often sufficient for less latency critical computational workloads.

Where it is made: Asia mainly (Korea, China, Japan)

Key manufacturers: Samsung, SK Hynix, Sandisk, Micron, Kioxia

5. Hard Disk Drives (HDDs)

What it is (simple): Traditional spinning disks for cheap bulk storage

What it is made of: Magnetic platters and mechanical parts

Cost & size: Very cheap, physically large, slow throughput

Where it’s made: Asia

Key manufacturers: Seagate, Western Digital, Toshiba

The closer memory is to the processor, the faster, smaller, and more expensive it gets, AI pushes demand toward the very top of the pyramid. This is due to the extremely parallel nature of GPUs that are performing trillions of computations per second.

HBM and NAND

HBM is the most critical memory layer as it sits directly next to AI GPUs, while NAND is the “warehouse” storage that holds datasets, model checkpoints, and logs.

In AI data centres, NAND-based SSDs feed data into DRAM/HBM, and HBM then feeds the GPU fast enough to keep the compute busy. LLM models utilise this tiered architecture of memory to ensure the most efficient use of all storage layers. However, the preference is always to have as much computation as close to the GPU as possible.

Over the past few years of the AI buildout, both have seen unprecedented demand. HBM demand is exploding because bandwidth is the limiter, while SSD demand rises because data inputs & outputs keep growing (training data, retrieval, inference logs). An often under-appreciated fact about memory needs is the recursive nature of agentic workflows that consume compute resources as they call other agents, which call even more agents. Agentic activity can therefore lead to situations where demand scales beyond human induced demand.

Historically, DRAM and NAND have been viewed as commodities by investors and the broader market. This has meant that supply is monitored very carefully and matched to meet demand as it is needed. Overbuilding has dire consequences as semiconductor fabs are expensive to spin up and costly in their ongoing operations. Due to this nature, supply is gradually increased in the market to avoid an over build. However, as AI demand has exploded, very suddenly all forms of memory are becoming key bottlenecks and giving memory players significant pricing leverage over customers. This pricing leverage allows them to record sky high profits as they are the critical bottleneck in the AI supply chain. GPUs without memory are rendered useless. No computation can happen without memory. In order to understand why and how they can maintain pricing leverage, the next section talks about the technological moat they hold.

Memory Defensibility

What makes the memory players turn from commodity to the overlords of the AI race is their advanced specialisation in semiconductor manufacturing processes. These processes can be broken down into three key elements:

• Manufacturing complexity (how to make the chips)

• Yield (how many successful chips you make per batch)

• Qualification processes (does the chip meet requirements for consumption)

The moat is a game of making billions of tiny cells reliably, at massive scale, with razor-thin margins. For HBM specifically, you need advanced DRAM and complex 3D stacking/packaging (TSVs, thermals, interposers) that only a few players can do at high yield, and customers must validate parts over long cycles.

It’s for this reason that there are only three companies that qualify in this game. Leadership shifts matter when one vendor ships next-gen stacks earlier as it gives them a distinct advantage in perfecting the manufacturing process of the next generation. HBM is also structurally premium-priced versus standard DRAM due to being co-packaged with the processor and not being homogenous like previous generations of DRAM (which were “commodities”).

Spinning up a memory company that can compete at the scale of the current players would take over two decades of expertise and over $50 billion in funds. China’s YMTC has been able to catch up in legacy DRAM manufacturing processes but has struggled to do it with high yields and without government support. They are also locked out of more advanced generation of semiconductor manufacturing capabilities due to material and technology export restrictions imposed by the United States. Furthermore, despite memory being “hardware”, there is still a chain of software in the form of chip firmware that requires deep integration. China or any other state players have to be able to overcome deep software lock ins in addition to all the other challenges that present. It is for this reason memory companies are far more defensible than any other point in their lifecycles.

Closing

Raw compute power has scaled faster than memory’s ability to move data, this is the “memory wall”. Chips can do math insanely fast, but they stall if data can’t reach them quickly enough.

A lot of time and energy goes into shuttling model weights and activations between memory and compute, not the math itself, so bandwidth becomes the limiter.

HBM is the current best workaround because it puts wide, fast memory right beside the GPU, but it’s capacity- and supply-constrained, so memory ends up setting the pace for how quickly AI systems can scale.

What we’re experiencing right now is a set of 10 or less companies that hold the manufacturing specialisation to develop memory chips that power the future of AI which isn’t just a matter of productivity, but slowly national security as these chips enable next generation warfare to take place.

If you believe:
a) AI is here to stay and that
b) AI’s demands will only increase over time,

then the future belongs to these 40-50 year old companies that have been making “commodities” that are now the core bottleneck in the AI build out. Their immense pricing power has already allowed them to start extorting many companies downstream in their supply chain and we believe that this trend will continue to extend, impacting their customers’ margins.

We are at a point of structural change in the world and memory may well be one of the earliest signs of this new world order.

That’s all for this weekend.

Our team at the Token Dispatch will be back with interesting reads.

P.S.: This piece was first published on Kerman Kohli and Nicolas’ Substacks.

Kerman's Substack

Nicolas's Substack

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I find a lot of AI debate still stuck between two positions. One side thinks AI will take away every job overnight. The other dismisses the entire AI wave by declaring that the tools are still inconsistent and need supervision. The problem is that none of these stances is particularly helpful. New technologies don’t need to be perfect to trigger a seismic shift. They just need to become good enough to make ignoring them look more dangerous than engaging with them.

This is where moving in the right direction matters more than the speed of the movement. A vehicle moving at 1 mph in the right direction will still travel farther than one standing still. Starting early works the same way: it gives people room to be wrong, to learn, and to course-correct, while still ending up ahead of the laggards described in diffusion of innovation theory.

None of this means that humans must become obsolete with each introduction of new technology. What new innovations do is they move the bar for what is disposable. This conversation is timely given we see AI agents start an economy of their own - making payments, signing contracts, and even hiring humans to help them with their tasks.

So what should you do in a world where predictions about the future become outdated before people have gotten to debate over the predictions?

In today’s guest op-ed, SysLS writes about how to reason through that kind of future without waiting for certainty. It is a piece about moving before the window closes, recognising which edges are temporary, and understanding why the people who start early often earn the right to course-correct in public.

You can follow his works on X and Substack here 👇🏾

X

Substack

Onto the story now,
Prathik

Introduction

The first time I realised we were heading towards an inflexion point was when I heard the music slowing down at my previous role, even as everyone around me pretended nothing would change.

I was managing a team of nearly 20 people in a hedge fund, doing the thing I had been doing for years. For all intents and purposes, I was likely going to do even greater things there. And yet, I moved from a position people would kill for to building a startup from ground zero with a skeleton crew - a move so little understood and widely seen as crazy. With the recent news of massive layoffs, people quitting explicitly to build startups, or quietly quitting and burning tokens at night doing the same, my actions seem a lot less insane now.

I’ve had a few people ask me where I think all this goes. This article is the answer to that. The honest truth is that I’m not really sure about the magnitude of these changes, but if quant finance has taught me anything, it’s that being directionally correct is often enough.

Writing On The Wall

It was ChatGPT o1 that did it for me. Up until that point, I had referred to them only as “LLMs” and not “AI”. I was not yet convinced that any semblance of real intelligence would emerge from them.

But with o1, it was the first time these LLMs could credibly produce code from well-structured prompts. It was still messy. They still suffered from the occasional bout of hallucination and confusion. But what mattered was that they could actually produce useful code.

The line of reasoning I took was this: once AI could reproduce useful code, it would recursively write improvements to its own logic and accelerate development at a scale we could not comprehend. Whenever I shared this, people would counter-argue that the code agents wrote was still buggy and not “production-ready.” This misses the point that humans write buggy code, too.

We don’t need flawless code to stop writing code entirely. We stop writing code the instant we realise that agents produce fewer bugs than we do, at a pace that far exceeds us. The bar for fully relegating the burden of coding to agents was so low that once I saw o1 up close, I knew the future was going to change dramatically.

Quant Finance And The Moat of Knowledge

I initially believedAI would eventually eat away a vast majority of quant finance. But I expected it to take a while, since there was little publicly available institutional code for LLMs to train on. I imagined software engineering as a pyramid: at the base was basic code monkey work, above that was your senior developer with some architectural thinking, and above that were specialised developers: data scientists, quant developers, and so on. The more your profession required specialised knowledge, the safer you would be.

I thought we would wipe out the entire tranche of code monkeys within two years. Then, senior developers would start to go. And layer by layer, specialised knowledge would also be incorporated into the LLMs, and they too would be wiped out then.

It quickly became obvious that the frontier model providers would eventually hire specialised knowledge workers to contribute industry know-how to these models. Specialised knowledge seemed like it would be a moat for the next couple of years, but would also be eaten away gradually.

The Remaining Moats

There were still a few business categories I thought would be safe from trivial disruption within the next five years.

The first is proprietary data. Businesses that produced a lot of proprietary data as exhaust would be hard to disrupt. Large podshops like Millennium come to mind; they can collect analyst readings, detailed analyses, recommendations, and actual price changes, and use this data to fine-tune frontier models into something that cannot be easily replicated. Any business producing proprietary data not trivially obtained by the frontier models would have a longer lease of life.

The second is regulatory friction. Businesses where other humans are a bottleneck seemed much harder to disrupt. Being able to trade in many TradFi markets meant opening broker accounts, getting licenses, and signing contracts around the globe. It’s easy to trade crypto, but much harder for a non-Chinese firm to trade iron ore in China. If you need a human to rubber-stamp your progress, the speed of that industry will always be bottlenecked by the cost and speed of that approval.

The third is authority-as-a-service. It’s not too hard now to get an agent to draft a legal opinion, given a comprehensive study of the matter and the relevant laws. And yet we’re still going to pay tens of thousands of dollars for one drafted by a lawyer, because an AI’s legal opinion is worth nothing at this point in time. Smart contract audits are another example. We’re probably already at a level where agents can review smart contracts as well as, or better than, the top decile of humans, yet most people still buy the stamp of authority from a branded firm. The opinion isn’t what you’re paying for. The authority behind it is.

The fourth is the physical intelligence lag. Hardware moves much more slowly than software, and breaking hardware is a lot harder to fix. Physical businesses that interact with the real world are a lot less likely to be disrupted soon. That said, once hardware catches up, the same pyramid logic applies: lower-level jobs go first, then the more specialised ones.

These moats are real, but none of them are permanent. The honest read is that they buy time, not safety.

Reasoning About A Messy Future

When the future is genuinely noisy, and the rate of change is fast enough that most analogies break down, people tend to do one of two things. They either wait for certainty before acting, or they pattern-match to the past (”this is like the internet boom”) and act on the wrong model. Both are mistakes.

It is worth reasoning from first principles under incomplete information. You don’t need to know exactly how something plays out. You just need to be directionally correct and structure your bets so that being early and wrong is survivable, while being early and right is disproportionately rewarding.

Asymmetry is the whole game when the future is uncertain.

The practical version of this is: ask what has to be true for a given outcome to happen, and then ask how legible the inputs to that outcome already are. The inflexion we’re living through was not unforeseeable; the inputs were visible. Code that could write code. Models that improved recursively. Institutional knowledge that could be bought, not just grown. Anyone willing to stare at those inputs clearly could see roughly where they pointed, even without knowing the exact path.

You can recursively reason about this and extrapolate further. I don’t even think we’ve yet caught a glimpse of what it will be like when agents can train themselves, replicate, and become truly autonomous. An agent that can increase its intelligence by 0.1% through a series of actions may not seem significant, but any number that is not 0 increases the probability that the next increment is greater, and so on, so forth. There are vast power laws at play here, and it is worth imagining what the future looks like under those power laws.

By the time the signal becomes obvious, the trade is crowded. In markets, you pay for early conviction with uncertainty. In careers and startups, the currency is the same.

So the real question isn’t really “what’s going to happen?” The question is: “What do I already know, what direction does it point to, and what’s the cost of acting on it now versus waiting?”

One thing that I often see people missing is noting that action creates information. Action does not happen in a vacuum. When you act on the world, the world replies with information. That information powers iteration. Iteration begets more informed action. That is the nature of progress.

Being still with incomplete information is decay.

Moving towards action is discovery.

Thinking About Next Steps

I knew I had a few years if I wanted to milk the status quo. But a large part of me felt like if I wanted to do something, I would have to start sooner rather than later. I had always wanted to build something truly mine, and it seemed like the window to do that was quickly closing.

To be clear, I know that the largest hedge funds in the world would be fine. They have proprietary data that makes them very difficult to replace. TradFi markets are also bottlenecked by human signatures, both on a regulatory and, at times, even a trading front. What I do think, however, is that these largest funds will use AI to replace most of their workforce, even terminal career seats like Portfolio Managers. Not immediately, but eventually, surely.

What I felt was that I had about 4-5 years before the foundation model providers hired enough specialised talent to make being an upstart trading firm nearly impossible. In certain markets, like U.S. equities, it already feels that way. I can’t imagine how much more efficient it’s going to look in just a few more years.

There was clearly not going to be space for “second best” pretty soon. I could keep working for the “best”, but it seemed more aligned with my goals to strike now, in a market where I had a genuine edge and knowledge that would not be trivially replicated. So, having that dawg in me, I called it quits and went all in on what eventually became @openforage.

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Inflexion Point

Today, it’s really starting to feel like the window is visibly closing. The pace of change has stopped feeling gradual, and most people in space are beginning to realise that what used to take months of improvement now takes weeks.

I don’t think jobs will vanish entirely within the next couple of years. There will always be a need for humans. Humans are social creatures. As long as humans are in charge, we want other humans around. And humans don’t trust AI yet, so stamps of authority still need to come from a human. I imagine AI CEOs in the next couple of years, but there will still likely be a human CEO having to “approve” and certify the AI CEO. This idea of human certification cascades down the pyramid. A human manager will manage and certify a bunch of agents working under him.

But the arithmetic of hires will change. If a CEO can prompt an agent more easily than they can prompt you, there’s no need to hire you. Shallow, code-monkey work will be difficult to find going forward.

To be irreplaceable, you need to operate at a timescale far above current agent limitations - receiving instruction, managing agents, and working with them for weeks, months, or years. Long-term strategic thinking and policy planning are some of the strongest job moats for the foreseeable future. You also need to operate at a scope greater than the current agent limitations. Agents have limited context. They know everything about anything, yet cannot see how component A interacts with component B, which in turn interacts with component C, causing cascading effects to component D. They lack scope.

If you can think far and wide, absorb information quickly, make decisions for the long term, and are likeable, you will hold down a job, at least for the foreseeable future.

If you do intend to be an employee, it’s worth taking stock of what your work is actually made of. Some tasks are deeply human defensible. Some will be replaced cheaply over the next couple of years. Do more of the former and less of the latter.

Working for a great firm in a deeply defensible position, one that sits behind real moats, may give you a career runway while the rest of the workforce gets eaten by the foundation models. You can still spend your tokens at night, rolling the dice, trying to build something meaningful.

But if you have a burning desire to contribute a unique verse to the world, think carefully about where your market of choice is heading. If your window to build something defensible is closing, you need to begin operating before the market fully prices in the competition that is coming.

Conclusion

The inputs that create inflexion points are legible ahead of time, if you’re willing to look. Most people don’t look, or they look and don’t act, or they wait until the signal is so obvious that the opportunity has already disappeared.

Don’t ignore the shifting sands. Don’t stay somewhere that’s losing ground while telling yourself you’ll make the leap when the timing is better. There’s no better timing, and the timing rarely announces itself. When it becomes obvious to everyone, the window has normally already closed.

I looked, I made a bet, and now I’m living inside the outcome of that bet — for better or worse.

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 world of finance has an extremism problem. I have seen maximalists convinced that blockchain will dismantle every financial institution ever built. Then there’s the TradFi camp, which thinks Bitcoin is synonymous with crypto and vice versa. The sad thing is, both camps show little patience for nuance.

I don’t buy the binary. As we can already see, both will most likely converge rather than collide. Visa and Mastercard are busy striking partnerships in the blockchain payments landscape. Stripe, the traditional financial services giant, has launched a blockchain to process payments exclusively. Our team at the Token Dispatch has been writing on the convergence of the two financial worlds almost every week now.

In crypto commentaries, I often see people selling blockchains themselves as the unique selling point (USP) because they enable speedy and low-cost transactions. Yes, it’s indeed cheaper to move money via blockchains. But that itself isn’t a significant factor in driving blockchain adoption, given that legacy infrastructure with relatively higher costs of moving money has stood the test of time for decades. Businesses don’t change their banking partners overnight because another bank offered a couple of basis points discount in processing their transactions. Financial habits are sticky, and businesses need more than just cost savings to feel confident about changing how they move, hold, and invest their money.

What helps here are quantifiable outcomes. For the masses to change how they move their money, they need to know how the entire money flow can be optimised. The pitch here should focus on how blockchains integrate with the platform that lets people hold, invest, and borrow money seamlessly.

In today’s guest op-ed, Sebastien Davies, Partner at Primal Capital, writes about how crypto’s infrastructure cannot elicit mass adoption, and what does.

Onto the story,
Prathik

The Infrastructure Mirage

For the better part of a decade, the global financial community has been transfixed by a fascination with “rails.” The discourse surrounding digital assets has focused almost exclusively on the mechanical throughput of blockchains, the cryptographic security of decentralised applications, and the theoretical elegance of smart contract logic. This was the Infrastructure Phase. An era defined by the building of “containers.” From 2020 to 2024, the industry frantically constructed the pipes, the vaults, and the gateways intended to modernise the movement of value.

During this period, the development of cryptocurrency markets was overwhelmingly infrastructure-focused because participation was structurally impossible without it. We built enterprise-grade custody platforms, standardised exchange APIs, and on-chain compliance services to solve five critical gaps: custody, exchange, execution, stablecoin utility, and regulatory reporting.

However, the industry is now confronting a fundamental truth of financial history. Infrastructure is a necessary precursor to activity, but balance sheets determine who captures the economics. The mere existence of a faster or more transparent rail does not, in itself, shift the gravitational centre of a market. Infrastructure answers the mechanical question of how institutions can participate, but it remains agnostic to a more consequential question of who captures the value. During the infrastructure-heavy years, the answer to the latter remained stubbornly traditional. Centralised market makers captured spreads, early holders captured appreciation, and validators earned transaction fees. What this phase failed to do was create new balance sheet structures that shifted where deposits must reside or fundamentally change the structure of credit creation.

A common counter-argument to this thesis posits that the “rails” are the primary driver of value because they lower the cost of entry, thereby democratising finance and naturally shifting economic power to the edges. Proponents of this view argue that the technology itself, by being open-source and permissionless, is the transformative force. While this is a compelling narrative for the retail-driven “crypto-native” world, it fails the test of institutional reality. In sophisticated financial markets, cost efficiency is a secondary concern to capital efficiency and risk-adjusted yield. An institution does not move a billion dollars because the transaction fee is lower; it moves it because the balance sheet upon which that capital sits offers a superior return or more efficient collateral utility. Infrastructure is a commodity that enables entry; the balance sheet is the strategic asset that determines the winner of the interest rate spread.

Financial history repeatedly demonstrates that infrastructure does not determine market power. Balance sheets do. The rise of the Eurodollar market in the 1960s did not require new payment rails or financial technologies. It required only that dollar deposits migrate outside the United States banking system. Once those balance sheets moved, a parallel dollar system emerged, operating at scale and largely outside domestic regulatory control.

We are now transitioning into a new Institutional Balance Sheet Restructuring Phase, an era beginning in 2025, where the “battleground” has shifted from the protocol layer to the allocation of liquidity. The first phase was about building the stage; the next phase is about the audience’s movement and their capital. A treasurer evaluating where to park cash in 2024 could technically use mature custody infrastructure to hold USDC, but the economics favoured traditional bank deposits, which offered FDIC insurance and competitive rates. Infrastructure was ready, but balance sheets had not yet shifted. That repositioning is only now becoming possible as the regulatory landscape moves from the abstract world of policy design into the concrete reality of implementation.

The next phase of crypto adoption will not be determined by infrastructure. It will be determined by where the balance sheets move.

The Implementation Gateway

For most of the past decade, institutional participation was not limited by a lack of imagination or technology, but by the structural impossibility of integrating digital assets into a regulated balance sheet. Institutions require more than just a functional wallet. Legal clarity, specific accounting treatments, and rigorous governance structures are minimum requirements. Without a recognised definition of “custody” or a clear path for compliance, the risk of “balance sheet contamination” was too high for any regulated entity to ignore. Large-scale adoption was held in a “waiting game” as banks and asset managers waited for a clear signal that they could deploy capital without incurring existential legal risk.

That era of policy debate has finally begun to sunset, replaced by a phase of operational implementation. The passage of the GENIUS Act in May 2025 served as the definitive catalyst, establishing a national regulatory framework for payment with stablecoins and finally providing the legal mandate for balance-sheet allocation. By providing a federal licensing process and requiring 100% reserve backing with government-approved instruments, the Act transformed digital assets from speculative novelties into recognised financial instruments. This shift was further cemented in August 2025, when the SEC concluded its long-standing investigation into the Aave protocol without enforcement action, effectively removing the regulatory “overhang” that had previously paralysed institutional DeFi participation.

The focus has now shifted to the regulators’ rulebooks. In February 2026, the Office of the Comptroller of the Currency (OCC) issued a comprehensive proposed rule implementing the GENIUS Act, establishing a framework for “Permitted Payment Stablecoin Issuers” (PPSIs). This move is significant because it provides the granular prudential standards (covering reserve composition, capital sufficiency, and operational resilience) that allow a Chief Risk Officer or an Asset-Liability Committee (ALCO) to sign off on a digital asset strategy. The passage of GENIUS has embedded blockchain regulation into the governance structures of the world’s largest financial institutions.

However, understanding why this shift is happening now also requires acknowledging the “balance sheet inertia” that defines institutional behaviour. Banks operate under strict regulatory capital ratios under which every dollar of risk-weighted assets must be backed by capital. If a bank loses deposits to a stablecoin, it must reduce its lending proportionally to maintain these ratios. It’s a painful and expensive contraction with knock-on effects across the economy. This explains why adoption has appeared slow. It takes six to eighteen months for full technological integration and even longer for the governance cycles of audit and board review to complete.

The current environment is one of “compounding acceleration.” As first-movers like JPMorgan, Citibank, and US Bancorp begin to launch stablecoin settlement initiatives, they’re sending a clear signal to the market that the risk of being first has been replaced by the risk of being last. We are seeing a competitive pressure phase where peer-bank participation reduces adoption risk across the entire sector. As these institutional constraints ease, the path is cleared for the migration of liquidity from legacy systems into the new, programmable containers of the digital age. This transition forces us to reconsider the very nature of where money lives, shifting our focus to the “containers” that will hold the next generation of global liquidity.

Where Liquidity Sits

To grasp the magnitude of the shift currently underway, one must first appreciate the historical stability of financial “containers.” In every monetary era, liquidity must eventually find a home. It’s simply a function of technical storage, but it satisfies the chronic global demand for safe, short-term assets. For centuries, this home was remarkably consolidated within a few well-defined structures: commercial bank balance sheets, central bank reserves, and money market funds. Each of these legacy containers functioned as an intermediary, capturing the economic value generated by the capital they housed.

The “Mathematics of Sitting” dictates that financial intermediation exists to solve a mismatch. Namely, that the world generates more cash from operations than it has immediate productive uses for, creating a permanent surplus of liquidity seeking safety. Traditionally, a commercial bank would capture this surplus as deposits, invest it in longer-dated assets like mortgages or corporate loans, and earn a substantial spread. This net interest margin (NIM) is the North Star for commercial and retail bankers. The bank’s shareholders are the primary beneficiaries of the “spread,” while the depositor receives a fraction of the yield in exchange for liquidity and government-backed insurance.

Digital asset infrastructure has introduced a new typology of “containers” that compete directly for this capital. These economic reconfigurations go beyond mere technological upgrades. When liquidity moves from a bank to a stablecoin reserve pool or a tokenised Treasury fund, the entity that captures the yield changes fundamentally. In a stablecoin reserve pool, for example, the issuer (such as Circle or Tether) earns the spread between the yield on the underlying Treasuries and the interest paid to token holders, which is often zero. This effectively transfers the “economics of sitting” from the commercial banking sector to the digital asset issuer.

Furthermore, these new containers offer a degree of transparency and programmability that legacy structures cannot match. Tokenised Treasury funds, which reached a market value of over $11.5 billion in March 2026, represent a structural evolution in which the yield of the underlying asset accrues directly to the holder. This creates a powerful economic incentive. A sophisticated treasurer no longer has to choose between the safety of a bank and the yield of a fund; they can hold a tokenised fund that serves as both a yield-bearing asset and a high-velocity settlement medium. By redefining where liquidity sits, digital infrastructure is not just building new rails; it is creating a competitive market for the balance sheets that support the global economy.

Stablecoins Drive Relocation

Blockchain dollars represent the first large-scale migration of liquidity onto these new financial balance sheets, marking a transition from digital currency being a novelty to becoming a core component of financial plumbing. The stablecoin market sits near all-time highs at $311 billion, growing at an annual rate of 50-70%. This growth eliminates the notion that this is a speculative phenomenon. We are witnessing a tangible “dollar relocation” away from traditional banking infrastructure and into programmable settlement systems.

The economic impact of this migration is most visible through the lens of deposit substitution. When a corporation or institutional investor moves $100 billion from a traditional bank deposit into a stablecoin container like USDC, the banking system experiences a profound loss of earnings power. In a traditional model, that $100 billion would support a bank’s ability to issue loans, yielding a net interest margin of roughly $3 billion annually. When that capital migrates to a stablecoin issuer’s reserve, those earnings are disintermediated. The bank loses the deposit, the ability to fund loans contracts, and the spread is instead captured by the stablecoin issuer.

This shift has profound implications for credit creation and financial stability.

Research published by Federal Reserve economists in late 2025 emphasises that high-adoption scenarios for stablecoins could lead to a reduction in bank deposits ranging from $65 billion to $1.26 trillion. This reduction has the potential to reshape how credit is provided to the economy. Regional banks, which rely heavily on stable deposit bases to fund local lending, are most vulnerable to this migration. As retail and corporate depositors seek the 24/7 settlement advantages of stablecoins, the traditional “float” that banks have long relied upon (earning spreads on in-transit payments) is rapidly becoming less compelling.

In response, the banking sector has moved from scepticism to a posture of participation.

The announcements by JPMorgan, Citibank, and US Bancorp to launch their own stablecoin settlement infrastructures in late 2025 and early 2026 are not attempts to “disrupt” their own business, but rather to retain their importance as liquidity containers. These institutions recognise that the economics of the future favour the issuer of the digital container. By becoming issuers themselves, banks hope to capture the reserve yields that would otherwise flow to new entrants. Of course, this first great cash relocation is only the opening act. As these new liquidity containers stabilise, the battleground is shifting toward the more complex world of collateral and the leverage that underpins global finance.

Programming Collateral

If the relocation of cash via stablecoins represents the first wave of this transformation, the migration of collateral represents a more fundamental restructuring of the financial system’s core leverage mechanics. Modern financial markets are essentially a vast network of collateralised obligations. The U.S. repo market alone, which facilitates the borrowing and lending of securities, moves between $2 trillion and $4 trillion every day. However, this critical infrastructure remains burdened by the “discrete settlement windows” of traditional banking. In the current world, collateral moves only during banking hours, and custody fragmentation means that a security held at one bank cannot be instantly used to satisfy a margin requirement at another. This friction creates periods where capital is locked, unproductive, and unable to respond to real-time market volatility.

Tokenisation transforms collateral from a static, location-bound asset into a programmable, high-velocity instrument.

By converting U.S. Treasuries and other real-world assets (RWAs) into on-chain tokens, institutions can move them 24/7 and settle them atomically. The growth of this market has been rapid; as of April 1, 2026, the tokenised RWA market reached approximately $28 billion, with tokenised Treasuries accounting for roughly half of that total. This surge is driven by institutional-grade products such as BlackRock’s BUIDL and Franklin Templeton’s BENJI, which allow holders to earn a 5% yield on underlying government securities while the tokens themselves remain mobile and deployable.

The true innovation lies in “collateral efficiency.”

In a traditional repo transaction, an investor might be required to accept significant haircuts or face delays of several days to unlock and move securities between custodians. In contrast, tokenised collateral is “composable.” An institutional investor can hold $100 million in BUIDL tokens, deposit them into a protocol like Aave at a 95% loan-to-value (LTV) ratio, and instantly borrow stablecoins to fund a tactical opportunity. The collateral never leaves the digital environment. Instead, it is continuously re-valued by automated price feeds, and any margin calls are handled via instantaneous, automated liquidations.

This shift moves the “economics of the dealer” toward the “economics of the protocol.”

In the traditional repo market, large dealer banks act as intermediaries, capturing a spread of roughly 50 basis points by borrowing at one rate and lending at another. In a tokenised ecosystem, collateral holders can self-match in DeFi lending markets, using software as an intermediary and capturing the full interest rate spread. We’re years away from seeing this at scale, but such a shift could move billions in annual earnings away from traditional dealer desks and toward protocol governance and asset holders.

To further appreciate the magnitude of the shift from cash to collateral, one must examine the institutional plumbing that has historically governed these movements. For decades, the global financial system has operated on a “T+X” settlement logic, where the “T” represents the transaction and the “X” represents a multi-day lag necessitated by manual reconciliation and inter-bank clearing cycles. In the traditional repo market, this delay acts as a silent tax on capital. When a dealer bank facilitates a repo, the collateral must be physically moved between custodians, often requiring human intervention to verify haircuts and legal titles. This creates a “liquidity moat” around the largest dealer banks, which derive their power not just from their balance sheets but also from their control over these proprietary settlement silos.

The mechanics of tokenised collateral dismantle this moat through atomic settlement. In a step-by-step institutional flow, the transition functions as follows:

1. Tokenisation: A high-quality liquid asset (HQLA), such as a U.S. Treasury, is moved into a digital wrapper (e.g., BlackRock’s BUIDL), turning it into a 24/7 mobile token.

2. Instantaneous Posting: Instead of waiting for a Monday morning wire transfer, a treasury team can post this tokenised collateral to a lending protocol or a prime broker at 10 PM on a Sunday.

3. Real-Time Valuation: Smart contracts utilise decentralised oracles to mark the collateral to market every few seconds, rather than once per day, allowing for significantly higher loan-to-value (LTV) ratios because the risk of a “flash gap” in valuation is mitigated by continuous monitoring.

4. Yield Preservation: Crucially, the investor continues to earn the underlying Treasury yield while the asset is encumbered as collateral, creating a “yield-on-yield” opportunity that is operationally cumbersome in legacy systems.

For a corporate treasury team or an asset manager, this shift is a fundamental revaluation of their idle assets.

In the traditional paradigm, a treasurer manages a “buffer” of cash that earns minimal interest simply to ensure they can meet sudden margin calls or operational needs. With tokenised collateral, that “buffer” can remain fully invested in yield-bearing Treasuries because the owner knows those assets can be converted to liquidity in seconds, not days. This removes the “liquidity discount” historically applied to long-term holdings.

For the banking sector, the implications are equally profound.

Banks have long profited from the “float” and the intermediation spreads of the repo market. As collateral becomes programmable and self-matching, that toll evaporates. This is why the emergence of institutional “plumbing”, like Anchorage’s Atlas network or JPMorgan’s internal tokenisation efforts, is so critical. They represent an attempt by financial institutions to build new silos before the old ones face competition. The transition from cash to collateral is the moment the financial system moves from a series of “discrete events” to a “continuous flow,” and the institutions that fail to adapt their balance sheets to this new velocity will find themselves holding increasingly static (and thus increasingly expensive) capital.

What appears to be just an improvement in settlement speed is, in reality, a reconfiguration of how capital is deployed, valued, and intermediated.

The S-Curve of Adoption

The migration of institutional balance sheets is not an overnight disruption, but rather a gradual absorption followed by eventual acceleration. It’s a “Web2.5” reality where blockchain technology is integrated into existing financial architecture rather than replacing it. Institutional adoption is currently being shaped by “balance sheet inertia,” a phenomenon where regulatory capital requirements, risk committee approvals, and legacy technology systems act as significant drag factors. Banks, for instance, cannot simply flip a switch to move assets. They must maintain strict Tier 1 capital ratios and ensure that any movement of deposits into a digital container does not force an expensive contraction of their lending books.

Despite these hurdles, the adoption of digital asset infrastructure is following a well-documented historical S-curve, similar to the multi-decade rollout of credit cards and the internet.

Between 2015 and 2024, the market was in an ‘experimental’ and ‘regulatory confusion phase’, where growth was tempered by uncertainty. We have now entered the ‘competitive pressure phase’ (2025–2026), characterised by regulatory clarity and infrastructure standardisation. During this phase, “You’re not the first, but you’re not the last” becomes the primary motivator for institutional treasurers. As more banks see their peers participating in stablecoin settlement or tokenised Treasury funds, the perceived risk of adoption drops precipitously.

The current market scale provides a baseline for accelerating compounding. With Fireblocks securing over $5 trillion in annual digital asset transfers and institutional tokenised asset markets growing rapidly, the “plumbing” of the new system has reached production-grade readiness. This infrastructure standardisation enables banks to build on proven systems rather than reinventing proprietary ones.

As we look toward 2027 and beyond, several “policy levers” remain that could further accelerate this migration. If stablecoin issuers were granted direct access to Federal Reserve Master Accounts, or if the current interest prohibition on payment stablecoins under the GENIUS Act were to be eased through affiliate “reward” structures, the flight of deposits from traditional bank ledgers to digital containers would likely accelerate meaningfully. The system is primed for a feedback loop where more stablecoin liquidity attracts more DeFi applications (likely permissioned), which in turn attracts more institutional capital, ultimately leading to a restructured financial landscape where the “battle for the rails” has been won, and the focus is entirely on the strategic management of the balance sheet.

The Winner of NIM

The transition from the infrastructure phase to the balance sheet phase marks the moment when the “digital asset” conversation moves from the periphery of technology into the heart of global macroeconomics. For years, the industry operated assuming that building better rails would inevitably lead to a better system. We now understand that rails are merely the invitation. The transformation occurs only when the capital itself relocates. The “Battle for the Rails” has effectively been won by a standardised, institutional-grade stack of MPC custody, tokenised Treasury funds, and federally regulated stablecoin frameworks. The new battle (one that will define the next decade of finance) is for the balance sheets that hold the world’s liquidity and collateral.

Heading into the 2027–2030 horizon, the structural advantages will accrue to those who can most efficiently manage these new “digital containers.” We should expect a persistent compression of commercial bank net interest margins (NIM) as depositors increasingly prioritise the 24/7 settlement and higher utility of stablecoin-accessible yields. Large corporates and institutional investors will likely shift their primary savings and treasury functions toward DeFi and RWA markets, where the middleman’s spread is minimised by protocol transparency. This is not the end of the traditional bank, but it is the end of the bank as a static, unchallenged warehouse of cheap capital.

The winners in this new era will be the “Web2.5” hybrids, or institutions that recognise they are no longer just lenders, but managers of programmable liquidity. By 2030, when the stablecoin market is forecasted to approach $2 trillion, the distinction between “crypto” and “finance” will have largely evaporated. The system will have fully absorbed the efficiency of the rail into the stability of the balance sheet. In this restructured landscape, financial power will not belong to those with the most innovative technology, but to those who control the containers in which the world’s liquidity and collateral ultimately reside. The battleground is set, and for the first time, the economics are up for grabs.

Crypto’s last decade was spent building infrastructure to enable institutions to participate. The next decade will determine where institutional balance sheets ultimately reside.

That’s it for today.

See you with the next one,
Sebastien Davies

Disclaimer: The piece was originally published in Edition 3 of Interop Markets

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

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Tough to root for the writer, the creator, the art in you when the world is looking for the thing that ships on time.

One thing I have been sitting with lately is that the most valuable thing is going to be being a human. As human as you possibly can. And tell me how hard can that be? We are making sense of being alive in a direction we didn’t plan, toward a conclusion we couldn’t have predicted.

Ben Roy said something here that I’ve been trying to say for a while. He got there first and got there better. His brain sees the world through his own particular life. His arguments, his places, his half-finished books. Mine does the same. Yours does too. No model has ever lived a day, lost an argument, or changed its mind about something it once believed completely. Yet.

It doesn’t have a nightstand. We do. That’s what you’re about to read.

—Thejaswini

Everyone I know that works in tech is having some flavor of existential crisis these days. People are worried that advanced LLMs are going to replace all knowledge work, possibly even in the near future.

I think part of this anxiety is reasonable. The AI labs have released impressive updates over the last six months, and the industry is alive with what feels like exponential change, but despite all the hoopla, what’s inconsistent to me is that I still find AI systems incredibly underwhelming when it comes to writing.

What I want to do with this essay is reason through why I think that’s the case and by extension wrestle with where I think human writers fit in a world of (increasingly) elite artificial intelligence.

Find more of Ben's writing

To start, I want to be specific about what I mean by writing because it’s important: writing is thinking on paper. It’s an extension of someone’s mind made manifest in the world through words with the purpose of passing along a container of meaning from one person to another.

I realize that’s a broad starting point, so let’s go one level deeper and split writing into two sub-categories: informational writing and interpretive writing. Informational writing is about the transmission of facts. It’s the world of documentation, instruction manuals, and neutral reporting. Interpretive writing is about sharing a perspective. It’s the world of essays, opinions, and commentary.

I acknowledge that life is more complicated than a simple binary, and, yes, every piece of writing has some subjectivity to it with how information is presented, but for the sake of argument, let’s say that all writing has a dominant intent, which is one of those two categories.

LLMs are great at informational writing. They can create a memo from a voice call, summarize an article, draft a simple contract, and so on. That’s useful for work purposes, but it’s not what I’m talking about here. When I say LLMs are weak at writing, what I mean is they’re weak at interpretive writing. They do poorly when trying to write with a consistent subjective lens. They struggle to have an opinion.

One final clarifier before moving forward: let’s use essays as the sole example of interpretive writing so we can agree on a concrete form to keep in mind as we discuss these ideas; and while we’re here, I’ll give some background on what an essay actually is so we’re ultra clear.

The word essay comes from the French, “essai,” which means to try or to attempt. The connotation there is of wrestling with words to work through a problem. So, we can say that an essay is struggle in written form, and so far, the machines can’t write in that manner. There are two reasons why I think this is the case. Let’s consider both.

The first problem with LLMs writing essays is the entire process of prompting one of these systems to get an output misunderstands what the act of writing is.

People fundamentally can’t prompt good essays into existence because writing is not a top-down exercise of applying knowledge you have upfront and asking an LLM to create something. AI agents also can’t create good essays for the same reason. Even though their step-by-step reasoning is more complex and iterative than human prompting, a chain of thought is still trying to accomplish a predefined goal.

By contrast, real writing is bottom up. You don’t know what you want to say in advance. It’s a process of discovery where you start with a set of half-baked ideas and work with them in non-linear ways to find out what you really think.

There’s a Flannery O’Connor quote that speaks to this where she says, “I write because I don’t know what I think until I read what I say.” I’m the same way. I don’t think people can skip doing the work of wrestling with ideas because that’s the core chaotic energy that underpins good writing. It’s how you figure out what you believe and how you want to communicate it.

There’s also a more philosophical extension to this point which is that human brains function differently than LLMs. They’re squishier. There’s a famous book, Thinking Fast and Slow by Daniel Kahneman that has a helpful framework to explain this difference. He talks about two types of thinking. There’s System 1 thinking, which is fast, automatic, and driven by pattern recognition. Then there’s System 2 thinking, which is slow, methodical, and reflective.

Humans think in both modes. LLMs also “think” in both modes.

For System 1 thinking, a human makes snap judgments all the time about people they see, posts they read on the internet, or whatever else. Similarly, an LLM can take in a simple query and give us a one-shot output in response based on the model’s training.

For System 2 thinking, a human takes in ideas, considers them, and through conscious effort can produce new ideas. Similarly, reasoning models can think for extended periods of time, consider a problem, and produce novel outputs.

The difference – in both types of thinking – is that LLM “thought” or inference is mathematically deterministic where human thought is delightfully messy.

Once a model finishes its training, its weights are saved and its thinking function becomes static. This is represented as a set of numbers, which from that point on don’t change. When a model thinks, it takes an input and iteratively chucks that input into a vortex of math (its weights and operations) and that then produces an output. It’s a predictive exercise based on statistical associations, and it only feels alive because when words are generated there’s a pseudo-random sampling involved in that output process.

Now, when a person thinks, our manner of thinking is more like taking ideas and filtering them through a set of “weights” that are constantly in flux, namely our accumulated life experiences and how we’re constantly interpreting and reinterpreting them. The process is alive.

What happens is we take an input thought and refract it through this prism of our humanity, our memories, the places we’ve lived, the arguments we’ve had, the people we know, and infinite other bits and bops of life experience to see multiple, blended, possible outputs on the other side simultaneously. It’s like the Pink Floyd album artwork below where normal light is the input, the rainbow is the set of outputs, and the prism is someone’s brain.

So, both LLMs and human brains can think and compose writing. That’s cool. The issue is the way these machines produce words leads to sterile outputs. Like, it’s always obvious to me when someone shares writing they’ve prompted because the outputs tell on themselves. The reason for this is because LLMs lack the unique perspective of a human mind at work (or play).

There’s a visual analogy I like to use when comparing these two kinds of writing which is that a good essay is like a cathedral of ideas. It’s a work of craft, beauty, and the quirks of time and place. But an LLM attempt at an essay is like a glass skyscraper. It’s functional. It’s a building, sure. But if you looked at a picture of it, you’d have a difficult time telling whether it was located in Portland, Atlanta, or Denver because it has no soul.

The best counterpoint here is that I simply have a skill issue on my hands. Maybe I’m not clever enough, and if only I knew how to more skillfully orchestrate LLMs or swarms of editorial AI agents, then I’d be able to create works of magical, overflowing craftsmanship with them.

Maybe.

I do think people with specialized knowledge of writing can create better outputs with an LLM. Agents can get to slightly better outputs as well through iterative loops. But there’s an upper bound to how far you can get in terms of making an LLM compose something compelling because writing is a complex, adaptive process and these systems operate on a flattened representation of that.

My next point is that LLMs struggle to generate meaningful writing because they lack context. They simply can’t take in (or process) the staggering amount of information that’s involved in the act of a person having an opinion.

I recognize these models have proven that they have PhD-level intelligence in some areas. They can win math Olympiads. They’re trained on most of recorded history. There’s no question that their form of alien cognition is impressive, but it’s just not equivalent to the neural network of my brain or yours when it comes to writing.

Let me use a graphic to explain this view more clearly.

If I write an essay, there are three variables in that process: myself as the writer, my audience, and the essay topic. Also, each of these variables is constantly changing.

A person is dynamic. They’re always in motion. Everything from how I’m feeling and what I’m currently reading to random mood swings and mental biases shape how I write something.

An audience is dynamic in the sense that their relationship to reading is evolving. Attention spans change, content formats rise and fall in popularity, again everything is in motion. For example, people who are familiar with LLMs have noticed that they tend to produce a lot of em dashes in their outputs, which in turn makes writers wary of using them – they don’t want their work to be discounted as “just” generated by AI.

A topic is also dynamic to varying degrees depending on what we’re talking about. Some subjects like ancient history are more static, but generally the world is a fluid place.

To dial this up further, the relationships between these variables are changing as well! A writer shapes the expectations of their audience through what they write over time, and in turn a writer’s audience informs what that writer writes about when they show interest in one subject over another. Both the writer and their audience also have evolving views of a topic as time moves forward and new information emerges.

To tie this together: there’s a lot of social complexity that goes into writing an essay, and an LLM has limited visibility into most of that complexity, which limits its ability to write with the flair of a human or on behalf of one.

Further, this idea that LLMs lack context is more than a raw data problem, it’s a relationship problem. Human writers have a qualitatively different relationship to this information than LLMs do. I don’t have data about myself… I am me. I have an intuition about my audience. When I write about a topic, I don’t know about it, I care about it.

LLMs don’t operate on the same plane. They have a view, but not my view. They have some context, and maybe often too much context, but not the context that’s relevant to play this game well. And since an essay really is just a snapshot in time of a person’s brain as a function of all these variables this makes human writing a lot more defensible than some people suggest.

After chatting about these ideas with friends, I’ve heard a couple good counterarguments to my issues with LLMs and writing. The most convincing of these is that everything will be solved when AI systems get access to infinite (or drastically larger) context windows.

This line of thinking says that if LLMs can offer users, say, 500 million tokens as a context window, then our machine companions will be able to reference everything about us: all our past pictures, writing, social media history, health data, recorded memories through things like wearable glasses, and so on. Then they’ll synthesize all of this data to approximate our decision-making process, which in turn would let them write (and think) on our behalf.

I do think there’s some merit to this. What’s happening right now with AI agents that initiate their sessions with access to memory files, conversation history, active skills, and other reference data is definitely gesturing at this future. See below for my basic bitch graphic.

I will say that I think this stuff is extremely cool, and I do think we’re going to get closer to modeling human consciousness through the combination of agent architectures and larger context windows. But no matter how weirdly fascinating it is to conjure up an agent with specific characteristics, I remain unconvinced that these systems will be able to write on my behalf.

I have two disagreements with this supersized context window argument, both of which are more philosophical than technical.

For one, even if you get infinite context windows, LLMs have an issue with hierarchy of information. There’s no clarity around the weight of some information over other information and how that changes in different contexts. So, Claude might have access to my references, but it doesn’t know when and how to use them. It might know grammar and rules of composition, but it doesn’t know when I might paraphrase something versus quote it outright. And there are far too many exceptions to any rule to ever codify someone’s intuition.

Next, I just find the comparison between an LLM and a human mind misleading. We’ve talked about this a bit already. It’s a case where reasoning by analogy leads to the wrong conclusion because LLMs don’t behave the way human brains behave.

I do think LLMs are useful machines. I’ve used ~20,000 words of my writing as a reference point, written up rules around how an agent should make editorial decisions on my behalf, then with that context I’ve run ideas against the best models that exist today. It’s created some fun outputs. But in every case, something feels off.

In music terms, I think LLMs are like a cover band that’s trying to perform a song where they get aspects of it “correct,” but they’re never able to embody what makes the song special because they lack the essence that is embedded in the original musicians. I might have a great time listening to the music, but I’m not paying $400 for a ticket to see PISS live.\

The AI maximalists will double down and make the case that, again, extra context is all you need to solve these issues, so one day an LLM will simply absorb mass amounts of your data and voila. Apparently, you can model everything about a human.

I disagree.

I’m not convinced we humans are even so legible to ourselves that we could articulate all the relevant context that an AI would require to mimic us.

My favorite example of this is the Greek concept of apophenia, which is the idea that humans perceive connections or patterns in random data. We don’t know why this happens, but this feature of our operating system is why we see different shapes in clouds, where, for example, you might see Bart Simpson and I see Pikachu. That creative expression is unique to each of us. How do you model that?

It’s a bit ironic, but our irrationality might be the most defensible asset we have as far as creative endeavours go. That bug is our best feature in a world of rapidly advancing AI systems because it makes us impossible to model.

Adam Mastroianni put this well in a blog post last year where he said, “Lots of people worry that AI will replace human writers. But I know something the computer doesn’t know, which is what it feels like inside my head. There is no text, no .jpg, no .csv that contains this information, because it is ineffable. My job is to carve off a sliver of the ineffable, and to eff it.”

Okay, this has been long. There are other counterarguments to what I’ve laid out here. I just want address one more.

Some folks bring up coding and point out that it’s a complex, creative activity like writing, and the follow up question is: if LLMs have changed how coding is done to the point where it’s “solved” why can’t writing be solved as well?

I’m no authority on coding, but I do see that LLMs have changed that activity. My pushback there is that coding and writing ultimately have a different telos.

The way you evaluate writing is whether it resonated with an audience or not. It’s about curating an entertainment experience for another human. Coding is evaluated by correctness. It’s functional where writing is experiential and concrete where writing is fluffy.

There are for sure multiple ways to code a piece of software to accomplish a task, but there are more standards to follow than there are in writing, plus, as much as engineers care about the readability of code, the ultimate audience for it is a compiler not a human.

I think LLMs work well in coding because it’s a coherent system: an agent can create code, run tests, iterate, then verify whether it will execute or not. But with writing, that doesn’t apply because it’s not a computational exercise, it’s an interpretive one. As a result, LLM code is mostly coherent these days, and when it’s not it can be concretely edited. LLM writing is way less coherent.

An analogy that I like to think about for LLM writing outputs is they’re similar to the bar scene from Good Will Hunting where there’s a dweebie Harvard student who presents what appears to be a fancy argument about US history, but it turns out he’s borrowing someone else’s thinking, and Will goes, “Were you going to plagiarize the whole thing for us? Do you have any thoughts of your own on this matter?”

That’s what it’s like talking to ChatGPT. It’s more like the illusion of intelligence than actual intelligence.

As I wind this down, I want to say that I’m optimistic about AI. I see LLMs as a complement, not a substitute to our intelligence. They’re super useful tools, and I use them in my writing today for ideation and sometimes for editorial feedback.

That said, even in a world where we see significant improvements in AI systems, I find it unconvincing that they will replace human writers. There’s a special je ne sais quoi about being human and the way we hallucinate our own custom models of the world based on a lifetime of experiences that I don’t think any machine will replicate.

Now, could I be wrong? Possibly. Will GPT 33 be able to write perfect essays? We’ll see. Models have surprised me and I’m sure they will continue to.

But my view is good writing requires something that only humans have, which is the ability to struggle and to speak about that struggle from the point of view of being in the trenches of life. It is sense-making from one human to another, and in my mind as long as humans endure as a species, there will be an audience for that.

Until then, keep writing.

A massive thank you to Devin, Finn, Nuk, and Luffistotle for feedback and review.

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

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. If you want to reach out to 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 your wallet is public, your life is public. People can watch your balances, your trades, your positions, your timing, then say it’s “just data.”That’s why privacy keeps coming back as a narrative.

The issue is that “privacy” is not one feature. It’s five different problems.

This piece is to help you understand what you’re asking for the next time you tweet, ‘We need privacy’.

When people mention privacy, they often mean very different things:

• Intent privacy: observers shouldn’t see your trade before it lands

• Value privacy: your salary, net worth, or trade size shouldn’t be easily observable

• State privacy: positions, liquidation thresholds, vault states, and inventory shouldn’t be public by default

• Execution privacy: strategies shouldn’t be inferable from which paths you trigger and how.

• Graph privacy: observers shouldn’t be able to map who you pay, donate to, or coordinate with.

Many “privacy protocols” address one or two of these, while leaking the rest. Most leaks occur at the peripheries: wallets, Remote Procedure Calls (RPCs) - the bridges between wallets and blockchains, relayers, bridges between blockchains, exchanges, and human predictability.

That’s the frame that makes the landscape legible: separate the surface you want to protect, then look at the tool that protects that surface.

Intent Privacy

On many chains, a transaction doesn’t go straight from your wallet into a block.

Instead, it first sits in a public waiting room called the mempool, where pending transactions are visible before they are included. If you can see pending swaps, you can react to them. This creates the opening for Maximum Extractable Value (MEV) bots. These bots are automated systems that monitor blockchain mempools at high speed to find and exploit profitable transaction opportunities, such as arbitrage, liquidations, and sandwich attacks.

For example, a bot could spot your swap, buy right before you do, causing the price to move against you, and then sell right after you to capture the difference. You still complete your trade, but at a worse execution price.

Intent privacy addresses this specific ~12-second window.

The goal is to keep transaction details hidden until it’s too late for random observers to respond.

Private Transaction Delivery

The most practical approach to ensure the privacy of a transaction delivery is to change its path.

Your wallet still creates a normal signed transaction. The difference lies in where it gets sent. Instead of broadcasting it to the public mempool, the transaction is submitted to a private endpoint that forwards it to block builders. These builders assemble candidate blocks by ordering transactions. A validator then publishes one of those blocks.

This is what systems like Flashbots Protect offer: a route that keeps your transaction out of the public mempool until it’s included in a block.

Flashbots is also working on a concept called Single Unifying Auction for Value Expression, or SUAVE, which frames the problem as “order flow as its own system.” The idea is to collect user intents in a private environment, run an auction to determine who executes them, and then settle the outcomes on Ethereum and other chains.

While still evolving, this approach sets a clear direction: privacy should be applied before the transaction ever touches a public mempool.

Why this works is also why it has a trade-off.

It works because public bots never get the early look. The trade-off is that the private pipeline and the builders do get that early look. You’re shrinking the audience, not removing early visibility entirely.

Encrypted Mempools

Encrypted mempools aim to provide stronger privacy by ensuring no one can see your transaction before it is included in a block.

Instead of broadcasting a readable transaction, the network sees an encrypted blob. Observers can tell that something was submitted, but they can’t tell what it does.

Decryption happens only after the order is locked in. One common design uses threshold decryption, where decryption is split across a committee (The Shutter Network calls them Keypers). Each committee member holds a share.

When it is time to reveal the contents, sufficient shares are published to reconstruct the decryption key, allowing the transaction to be executed.

This method eliminates the “problem of the private pipeline being able to read everything early, but it introduces new assumptions: the committee must be online, and must not collude.

Intent privacy ends when the block is published. After inclusion, the chain reveals what it always has unless you pair it with on-chain privacy for values, state, or execution.

Value Privacy

Value privacy answers a simple question: Can I send money without the whole world seeing how much I sent?

On a normal public chain, the answer is no. Every transaction literally publishes the amount. That’s how everyone verifies balances.

Shielded systems change this by separating two things:

• the amount (kept private)

• the proof that the rules were followed (remains public)

Under the hood, the system stores your money as private records. You can think of them as encrypted receipts. Each receipt represents some amount, but only the owner knows what’s inside.

When you spend:

1. You prove you own a valid receipt

2. You prove you haven’t spent it before

3. You create new receipts for the recipient (and change)

4. You publish a proof that the total going out equals the total coming in

The chain checks the proof. If the proof is valid, the transaction is accepted, but the hidden amount remains unknown. This is the core design behind Zcash shielded transfers, a classic example of value privacy in production.

Penumbra uses the same general concept in a multi-asset shielded pool, where all value resides within a private pool and transfers occur via proofs rather than visible amounts.

But this type of privacy has limitations.

Even with perfect math, privacy can still fail.

The leaks usually stem from user behaviour:

• If you deposit a very unusual amount and later withdraw the exact same amount, observers can guess it’s the same person.

• If you enter and exit the private pool within minutes, the timing becomes a clue.

• If only a handful of people are using the private pool, the anonymity set is small.

• If you immediately move funds to a known exchange account, you reconnect your identity.

So, value privacy hides the number inside the system, but it does not automatically hide the patterns surrounding the system.

Graph Privacy

Graph privacy focuses on relationships. Even if you hide the amounts, a public ledger can still reveal patterns: who you send to, who you receive from, how often, and in what amounts. Over time, this network map can be more revealing than balances.

Most graph privacy approaches fall into two categories:

The first is pooled unlinkability. This is the “mixing” idea. A lot of users send funds into the same pool, and later withdraw them in a way that doesn’t publicly tie the withdrawal to a specific deposit. The chain still shows deposits and withdrawals.

Privacy comes from ambiguity. Observers can see the deposits and withdrawals, but they can’t reliably match a specific withdrawal to a specific deposit. Each withdrawal could plausibly belong to many participants. This is the core mechanism behind mixer-style systems like Tornado Cash.

The larger the pool, the less certain an observer is about any single link.

If the pool is busy and many people deposit the same amounts, you blend into the crowd. If the pool is small, the crowd collapses, and the graph starts to reappear through timing and amounts.

Another way to break the graph is to stop reusing the same receiving address.

If every payment goes to one public address, your inbound history becomes a permanent public feed. Anyone can cluster those payments and treat them as belonging to the same person.

Stealth addresses can change that pattern. Instead of a single visible destination, each payment lands at a new address that looks unrelated to the last one.

The sender generates a one-time address for that payment, and only the intended recipient can access it. To outside observers, it appears as money going to unrelated addresses.

This doesn’t hide the amount or the sender. It solves a narrower problem by preventing outsiders from linking all inbound payments to the same identity.

ERC-5564 standardises this pattern for Ethereum. It doesn’t hide the sender or the amount; it stops “all payments to Alice” from being obvious.

Graph privacy still leaks through behaviour. If you withdraw from a pool and immediately bridge to the same place every time, you create a new linkage point.

If you exit and immediately touch a KYC exchange, identity snaps back. If you keep the same timing habits, the graph becomes guessable again. These systems break direct links; they don’t erase your footprint.

State Privacy

State privacy seeks to address a DeFi-specific problem. Your balances, positions, liquidation thresholds, vault composition, and inventory should not be readable by anyone with a block explorer.

This matters because “public state” turns into a strategy leak. If your position is visible, other actors can predict how you’ll behave, when you’ll get liquidated, and what you’re likely to do next. Even worse, they can target you. A wallet with a visible liquidation line is basically a public scoreboard.

So what does state privacy change under the hood?

In a normal chain, the state is the thing everyone agrees on, and everyone can read. A lending protocol maps an address to position details. A vault maps an address to shares and debt. That’s what indexers and bots scrape.

Private-state systems stop writing those details in plaintext. They replace “public state keyed by your address” with “private state represented as hidden records,” and force updates to come with a proof that the update followed the rules.

Here’s the simplest way to picture it:

You still perform actions like “deposit collateral,” “borrow,” “rebalance,” or “swap.”

The chain still has to enforce constraints like ‘you cannot borrow beyond what your collateral allows’; ‘you cannot create value out of thin air’; and ‘you cannot spend the same private balance twice’.

But the chain enforces these constraints by verifying a proof, not by reading your position.

That’s why state privacy and ZK proofs often travel together. You need something that says “this update is valid” while keeping the underlying numbers private.

A useful concrete example is Aztec. The design centres on private execution on the client-side, with the network validating proofs and commitments. That lets a position exist without being stored as a readable table on-chain. You can do DeFi-like actions, while the public chain only sees proof-verified state transitions, not your raw position.

Where does state privacy leak? Mostly at the edges, again.

If you have a private position but periodically exit to a public DEX, the size and timing of those exits can reconstruct your behaviour. If you bridge in and out in predictable patterns, you create a linkage.

If you rely on public keepers for things like liquidations, your “private” position still needs some interface to the outside world, and that interface can leak.

Also, state privacy is hard to make composable. Public DeFi is like Lego because everyone can read everything. Private DeFi has to answer “How do two contracts interact when neither can see the other’s internals?”

The more complex the composition, the more careful the design needs to be.

State privacy is where privacy stops being about “hide a transfer” and becomes about “hide an ongoing financial posture,” and that’s why it’s harder, more useful, and more fragile at the boundaries.

Execution Privacy

This type of privacy goes one level deeper. It hides not only balances or positions but also how the computation happened. This matters for auctions, matching, solver logic, liquidation strategies, private order types, and anything where the strategy becomes exploitable once it’s visible.

There are two common approaches:

One uses Trusted Execution Environments (TEEs), where contracts execute within a hardware enclave, inputs are decrypted within the enclave, outputs are encrypted, and attestation verifies that the correct code ran.

Secret Network and Oasis Sapphire are examples of systems that use this approach to get private execution with lower proofing overhead. The trade is hardware trust and side-channel risk classes.

The other approach uses ZK proofs for private execution, where the system produces evidence that a program ran correctly without revealing the private inputs that drove the execution.

This approach is conceptually clean, typically heavier on tooling and performance, and tends to be rolled out gradually through limited scopes before it becomes general.

Execution privacy is weak in the same areas as every other type of privacy: timing, boundary interactions, and the access layer.

RPC: Tackling the Place Privacy

Even if your on-chain privacy is perfect, if your wallet uses Infura or Alchemy, that RPC provider can see your IP address, which addresses you control (because you queried their balances), what contracts you interact with, and your timing patterns.

In 2022, ConsenSys publicly acknowledged that MetaMask’s default RPC (Infura) collects IP addresses and wallet addresses. This is why protocol privacy often fails in practice: the access layer reveals everything before the cryptography gets a chance to work.

So, privacy is context-shaped. Different contexts shape privacy designs in different ways.

Trading mostly needs intent privacy. Payments need value and recipient-side graph privacy. DeFi wants state privacy. Bridges multiply correlation points. Institutions want confidentiality with a path to verification and accountability.

So, the question ‘Which privacy model wins?’ is usually the wrong one.

A more accurate question is: Which surface are you protecting? What assumptions are you making? And where does the information still leak when the user touches the real world?

That’s all for today.

Yash Chandak

P.S.: Thanks to Nitanshu, Joel and Kunal for helping with their input.

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: The views expressed in this article belong to the author, Yash Chandak, and not Token Dispatch.

For the longest time, crypto functioned much like tribes, built around chain maximalism. You picked one, learned its tools and apps, mingled with its community, followed its conference circuit, and rarely ventured far outside of that bubble.

That initial choice was shaped by whatever pulled you into crypto in the first place. Since the early decentralised finance (DeFi) grew on Ethereum, many early adopters ended up there. Later, the NFT hype and memecoin cycles drew new users into a different ecosystem, Solana. The result was a chain-first onboarding model: once you landed on a chain, you typically stayed there.

For most users, crypto felt like a collection of separate worlds, and you only interacted with one at a time. That mental model is now breaking down.

Today, crypto is increasingly experienced as a single market, not as a collection of chains. Activity is spread across many thriving ecosystems at once. Capital moves to where yields are highest, and assets are purchased where liquidity is deepest. Users no longer choose chains. They choose actions, and they care about results. They want to swap, earn, send, or pay, and they care about what those actions produce: profit, yield, or a transfer of money.

As a result, the dominant user model has shifted. Crypto is no longer chain-first. It’s asset-first. And wherever the asset is, users now expect to be able to go.

This new asset-first economy only works because interoperability (often shortened to interop) enables value to move freely across chains.

What is interoperability?

Interoperability connects the entire crypto ecosystem and makes it feel usable as a whole. Without it, every blockchain would be its own walled garden.

As defined in the State of Interop (2026):

“Interoperability is the ability for value, state, and intent to move seamlessly across independent blockchains. It is what allows composability to operate at scale in crypto, enabling coordination across otherwise separate ecosystems. For users, interoperability compresses a multi-chain ecosystem into a single, interconnected mental model of using crypto as a whole.”

A helpful way to think about this is to treat each chain as its own financial backend. They don’t naturally talk to one another. Assets, liquidity, and applications live in separate environments, each with different rules, costs, and trade-offs.

Interoperability is the layer that connects these backends.

If that sounds abstract, traditional finance offers a familiar parallel. Banks don’t natively interoperate either. What makes the global financial system usable isn’t the existence of one giant bank; rather, it’s the shared rails like Visa, SWIFT, and ACH that sit on top and move money between them. When you send money, you don’t think about which banks’ systems are involved. You just expect it to work.

Crypto is undergoing the same transition. Interoperability enables chains to feel less like isolated networks and more like a single financial system. It’s what lets users swap assets, chase yield, or move capital across chains without having to start from scratch each time.

For a long time, this was mostly theoretical. The tools existed, but the users weren’t ready. That has changed.

Users are already living multi-chain

Today, active crypto users routinely hold assets across multiple chains. While many still have a “home” chain (often Ethereum, especially among high-net-worth users), their on-chain behaviour shows that they are natively multi-chain. Capital moves based on risk, cost, and opportunity, not loyalty to a single chain.

Data from high-activity cross-chain users of Jumper, a multi-chain swapping and bridging exchange, illustrates this shift. Most users distribute their funds across several chains. They tend to park the majority of their capital on one or two primary networks, then move smaller amounts elsewhere when the market presents an opportunity.

This reflects how crypto is actually used today.

Users keep their capital where they feel most comfortable. When a new opportunity emerges, like a better yield, a new app, or a fresh narrative to speculate on, they use interoperability rails like bridges to move funds to wherever that activity is happening.

As a result, the act of ‘bridging’ funds, i.e., moving capital from one chain to another, has become a routine part of participating in crypto, and cross-chain volume is up 100x since 2022. Bridges tend to see their highest activity during these surges, as users move funds to whichever chain is the latest hotbed of speculation and attention.

Three things happening at once are amplifying the importance of interoperability:

First, users are accepting the multi-chain reality of crypto. Liquidity can never be confined to one corner of a global market. It will go where it gets the most bang for its buck, and the average user no longer expects everything to happen on one chain.

Second, chains are being launched at an unprecedented rate. 2025 saw one of the broadest waves of chain launches in the industry’s history. This includes crypto native ecosystems and chains run by fintech companies like Stripe. The surface area of crypto has expanded dramatically.

Lastly, tokenisation is accelerating rapidly. From equities and treasuries to private credit and real-world assets, everything is coming on-chain. At the same time, regulatory clarity, most notably through the GENIUS bill, has unlocked a wave of stablecoin issuance.

This is the reality of crypto today, and interoperability sits at the centre of all three shifts.

For users, interoperability is how crypto is used. Bridges are the primary way users move, trade, and express intent across chains.

For chains, interoperability is economic infrastructure. Without bridge connectivity, chains cannot attract external capital or onboard users at scale. A chain without interoperability (interop) is like a country without trade routes - isolated, constrained, and irrelevant in a global market.

For asset issuers, interoperability is a distribution requirement. Issuers no longer want to launch assets on a single chain; they want assets to be everywhere. That means availability across markets, chains, and liquidity venues. Doing so efficiently and at scale is only possible via interoperable rails.

Taken together, these indicate that interop is the layer through which crypto now expands. As users, chains, and assets multiply, interop becomes the mechanism that keeps the market liquid. Interop is crypto. Interop is inevitable.

State of Interop in 2026

Now that we’ve established that interoperability matters, what does the interop market actually look like?

It’s entering the phase that every infrastructure category eventually reaches: consolidation.

You see this pattern everywhere in finance and technology. In the early days of a category, value is spread thin. Many players coexist. Differentiation is weak. Growth comes less from being the best and more from being early.

Think back to the early days of fintech. Before Stripe emerged as the default payments layer, there were dozens of payment gateways. Before Plaid, every bank integration was custom. Before Bloomberg consolidated financial data, traders stitched information together from multiple terminals and feeds.

Interoperability followed the same arc. As blockchains proliferated, barely any interop protocol saw traction. That phase is now over.

As categories mature, value stops accumulating in the middle. It concentrates on the edges. You either become exceptional at one specific job or you operate at a scale that makes you unavoidable. Everything in between gets squeezed.

In practical terms, this means two things:

• Users gravitate toward the best possible solution for a specific job.

• Developers default to infrastructure that’s proven, reliable, and widely adopted.

Interop today is a textbook example of this dynamic.

On one end are the specialists. These teams focus obsessively on a single outcome and optimise everything around it. They don’t try to be platforms. They aim to win one job.

Think Stripe, which started with payments APIs; Wise which focuses narrowly on cross-border FX or Robinhood, which makes trading simple and cheap. In interop, intent-based bridges fall into this category. Teams like Relay and Gas.zip realised most users just want fast, cheap cross-chain swaps, so they built for speed and low cost, and nothing else.

At the other end are the infrastructure giants. These are generalised platforms with real distribution, deep integrations, and network effects.

Think SWIFT in banking, Visa in payments, or AWS in cloud computing. In interop, large platforms that power many apps, wallets, and chains sit here. This includes the likes of LI.FI, LayerZero, and Wormhole.

Once a team proves it can operate reliably at scale, the market gives it permission to expand into adjacent products. This is happening in interop, with teams expanding into new product offerings like swaps and yield aggregation.

What struggles is the middle.

Projects that are neither sharply focused nor widely adopted end up in a dangerous no-man’s land. They’re too generic to dominate a niche but too small to be foundational infrastructure. They move slower than specialists and lack the distribution of platforms.

This is where consolidation happens. Some teams pivot. Some shut down. Others are acquired for talent or technology, like Circle’s acquisition of Interop Labs’ team and IP.

Interop in 2026 is no longer about being “good enough.” As with every mature market, specialisation and scale are where value now accrues.

Where We’re Headed

If you step back, the shift is obvious.

Crypto now asks you what you want to achieve, irrespective of where you are.

Users don’t need to be conscious of which chain they are on. They act: swap, earn yield, send money, and get exposure to an asset, irrespective of the chain they reside on.

And increasingly, those actions just happen, even when they span multiple chains underneath.

This is the new reality of crypto. Chains still exist, but mostly as infrastructure. To the user, crypto is starting to feel like a single, global system of markets and money.

However, this still requires the users to know which interoperability tools to use and how to use them.

This is where the next step comes in: everything will soon be embedded in app buttons, and things will just work.

Today, interoperability helps you move between chains. Soon, it will help you act across them - automatically, atomically, and in one seamless flow. Swapping, lending, rebalancing, paying, issuing assets, coordinating agents, all with a single click, even if ten different chains are involved.

This is what an asset-first, action-first crypto experience looks like.

For the reader, the implication is that on-chain capabilities are increasing rapidly. Things that once required planning, bridging, and manual coordination are collapsing into single decisions and single clicks.

All to say:

The chain-first era is behind us.
The action-first era is arriving.

And interoperability is what makes it inevitable.

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: The author, Arjun Chand, is the head of narrative at LI.FI, a bridging and DEX aggregation protocol. The views expressed in this article belong to the author and not Token Dispatch.

“The problem is that … the fate of the entire money system depends on the company running the mint, just like a bank” Satoshi Nakamoto had said in the Bitcoin whitepaper they authored in 2008.

The disruptors now want to become the very thing they set out to replace.

Earlier this week, both Circle and Ripple filed applications for US banking charters. Circle wants to establish "First National Digital Currency Bank" while Ripple is chasing both federal oversight and a Fed master account, which the Fed maintains for eligible institutions such as banks and allows them to conduct transactions and access the Federal Reserve's payment systems and services.

Circle manages over $62 billion worth of USDC tokens, while Ripple's RLUSD stablecoin is still growing with ~$480 million in market cap.

In today's News Rollups edition, we examine:

• Why crypto players are seeking banking licences

• What Circle's stock crash tells us about market reality

• How the GENIUS Act is forcing everyone's hand

• Whether this betrays crypto's original mission

Got questions about a hot crypto topic that you want help understanding? Ask your question by replying to this email and our crypto experts may answer it along with your name in our weekly News Rollups.

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Q1: Why are Circle and Ripple applying for banking licences?

Legitimacy.

It’s straightforward. After years of operating in regulatory grey zones, crypto companies have understood that a banking licence is basically a golden ticket to institutional acceptance.

Should we remind you what a Wall Street debut did to Circle’s stock?

Read: Circle’s Wild Ride

"Circle has long sought the highest standards of trust, transparency, governance, compliance," chief executive CEO Jeremy Allaire said.

Circle wants to establish "First National Digital Currency Bank" to manage USDC's $61 billion in reserves directly. Right now, BlackRock manages those reserves and BNY holds them. That's a lot of middlemen taking their cut.

Brad Garlinghouse wants to set a "benchmark for trust in the stablecoin market" by bringing Ripple under proper federal oversight. "If approved, we would have both state (via NYDFS) and federal oversight, a new (and unique!) benchmark for trust in the stablecoin market."

They want every possible regulatory stamp of approval to convince institutional investors they're legitimate.

Think about it this way: if you're a pension fund manager considering crypto, would you rather deal with a crypto player with patchy regulatory background or a federally regulated bank?

It also coincides with regulatory tailwinds.

With the GENIUS Act (stablecoin legislation) moving through Congress and a crypto-friendly administration under US President Donald Trump in power, there wasn’t a more conducive landscape before now.

Circle and Ripple are likely racing to get their applications in before the queue gets too long.

Q: Isn't this ironic? Didn't crypto start out wanting to replace banks?

Early crypto was about "be your own bank" and cutting out financial middlemen, true. Bitcoin's genesis block literally referenced bank bailouts. Circle and Ripple positioned themselves as alternatives to the slow, expensive banking system.

Then why go back to the traditional system of banking? Perhaps pragmatism took over purism. The rebel phase (shouting from outside the bank's walls) is giving way to a collaborative phase (working from inside the vault). It's a bit like you lose some edge but gain a much bigger audience.

The upside? Operating within the rules could bring crypto tech to far more people. And if that means dilution of some of that original revolutionary spirit and purist philosophy, the trade-off is a no-brainer from the perspective of running a business.

Q: How exactly does becoming a bank help?

Numbers show why they want this so badly.

Direct control means direct profits: Circle's proposed trust bank would let them manage USDC's $61 billion in reserves directly instead of paying BlackRock and BNY Mellon to do it. Stablecoin issuers earn interest on those reserves – Circle pulled in an estimated $1.7 billion last year from that alone.

Why share that revenue when you can keep it all?

Fed access is the holy grail: Ripple's master account application is a bid for direct access to the Federal Reserve system. If approved, they could hold USD reserves backing RLUSD with the central bank and settle USD transactions without routing them via other intermediaries that are currently holding Ripple’s USD reserves.

Beyond just cost savings, that would bring a credibility boost that money can't buy. Try explaining to institutional clients that your stablecoin is backed by reserves "directly with the Fed."

Regulatory clarity: A banking charter means playing by the same rules as JPMorgan. Regular audits, capital requirements, and compliance obligations. Sounds like a hassle, but it's actually liberating, no more guessing what regulators want.

The default trust from customers that comes with all this procedural paperwork makes the hassle worth it.

Q: How have investors responded to the news?

Despite the banking charter news, investors didn’t find Circle’s sky-high valuation justified. After a bumper IPO saw CRCL rocket from $31 to nearly $299, the stock saw massive correction at the bourses. It crashed over 40% during the past eight trading sessions, closing Thursday at $189.

Q: Have there been other precedents?

Circle and Ripple aren't the first in chasing a banking licence. Anchorage Digital was the first crypto company to get a national banking charter back in 2021.

Kraken took a different route with Wyoming's Special Purpose Depository Institution charter, a state-level banking licence designed specifically for crypto firms. The walls between crypto and traditional finance are crumbling fast.

That's it for this week's News Rollups.

See you next Friday.

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.

Pump.fun is pumping up the creator economy with its most recent roll-out.

Check out our Wednesday edition to know more.

The International Monetary Fund (IMF) spent decades teaching nations to manage reserves prudently. Now those same nations are betting their treasuries on magic internet money – and the IMF is having a meltdown.

Last week, Pakistan's crypto minister met with US President Donald Trump's digital asset team at the White House to discuss their freshly announced Bitcoin reserve. They join El Salvador, which continues buying despite IMF warnings. Bhutan, a tiny Buddhist nation in the Himalayas, has also amassed over $1.2 billion worth. The US holds more than $21 billion worth of seized BTC.

This isn't a fringe movement anymore.

From zero sovereign Bitcoin holdings in 2020 to tens of billions of dollars worth today.

The movement has led to palpable tension as traditional finance guardians like the IMF scramble to maintain control while countries explore monetary independence through decentralised assets.

As countries race to stack sats, we're witnessing an interesting irony. Nations are using a trustless, borderless currency to escape the very institutions that were supposed to ensure global financial stability. All this while the IMF keeps having its reservations.

For the first time since 1944, countries have found a reserve asset that exists entirely outside the traditional monetary system. No central bank controls it. No international body governs it.

Got questions about a hot crypto topic? Reply to this email to send us your question for a chance to be featured with your name in next week's edition.

Q1: Why are nation states rushing to stack Bitcoin?

Three words: survival, sovereignty and energy.

For inflation-ravaged economies, Bitcoin comes across as a saviour.

It isn’t pegged to the dollar, tied to local economies, or subject to foreign sanctions. It’s a neutral, borderless asset — immune to currency collapse and geopolitical freeze.

Argentina until December last year saw triple-digit inflation. Pakistan's rupee lost ~50% in four years.

When the macro-economic variables are this unstable, Bitcoin's 30-day volatility — which has come down from 5% to 1.39% against US dollar — seems modest and stable.

The sovereignty play runs deeper. El Salvador’s move to make Bitcoin legal tender was about holding an asset that no foreign power could freeze.

Pakistan's 2,000 MW Bitcoin mining allocation transforms surplus electricity into hard money. Bhutan turned excess hydropower into a $1 billion treasury.

Read: Thunder Dragon's $1B Bitcoin Stack 🇧🇹

In digital age, this helps convert trapped energy into portable wealth.

Q2: Why is the IMF trying to stop the Bitcoin treasury trend?

The IMF's opposition is existential. Bitcoin undermines their core power: conditional lending, financial surveillance, and monetary control.

When El Salvador signed a $1.4 billion IMF loan in March, the deal required the “fiscal sector” to stop accumulating Bitcoin. The response? Pure bureaucratic genius. While the "fiscal sector" stopped buying, El Salvador's Bitcoin Office – conveniently outside that definition – kept stacking BTC.

The IMF’s meek response - "efforts will continue" to halt purchases.

Pakistan pulled the same move. While negotiating IMF loans, they simultaneously announced a Bitcoin reserve with Trump's crypto team. The timing wasn't subtle.

The pattern is global. Central African Republic scaled back Bitcoin laws under pressure but kept voluntary adoption.

Why can't the IMF enforce its will? Because desperation cuts both ways.

Countries like Argentina, Sri Lanka, and Pakistan have repeatedly turned to the IMF during debt crises — and the Fund steps in with bailouts, restructuring plans, and conditional loans.

But these lifelines come with strings attached: austerity measures, currency controls, and strict capital guidelines.

So when a country like El Salvador or Pakistan signals a pivot to Bitcoin — an asset that weakens IMF oversight — it threatens the playbook. Too many defections, and the IMF risks losing leverage, legitimacy, and its role as the gatekeeper of financial stability.

Q3: What happens when Bitcoin bets fail in fragile economies?

The math behind the Bitcoin bet could terrify any central banker.

Pakistan carries $131 billion in external debt while proposing to bet on an asset whose daily volatility is still high although on a downtrend in the past decade.

Credit rating agencies aren't amused. When El Salvador adopted Bitcoin, Fitch promptly downgraded its bonds, citing crypto exposure. For countries already dancing on the edge of default, these downgrades mean higher borrowing costs – a vicious cycle.

The volatility isn't theoretical.

When Bitcoin crashed from $69,000 to $15,000 in 2022, El Salvador's holdings lost 70% of their value. For a country with 85% debt-to-GDP ratio, such swings can push finances from precarious to catastrophic.

Then there's the custody nightmare.

One compromised private key, one insider threat, one hardware failure – and millions in national assets vanish forever. No Federal Reserve to call, no reversal mechanism, no insurance.

This vulnerability isn't just theoretical.

Between 2017 and 2025, North Korean hackers, notably the Lazarus Group, have stolen more than $5 billion in cryptocurrency through ~60 cyberattacks, according to a United Nations report. This includes $1.4-billion Bybit exploit - the largest crypto heist ever - that the group pulled off in February this year.

These illicit gains have been reportedly used to fund the country's nuclear weapons development, circumventing international sanctions.

Pakistan's energy gambit adds another layer of risk. Allocating 2,000 MW to Bitcoin mining in a country facing chronic power shortages seems optimistic at best.

The IMF has already demanded "urgent clarification" on how mining squares with Pakistan's energy crisis.

What happens when citizens face blackouts while Bitcoin miners hum along? It exposes the state’s misplaced priorities.

The question that looms is: where should national resources be directed? Investments in education and healthcare have demonstrable, long-term benefits. For instance, a World Bank document shows that each additional year of schooling can increase earnings by about 10%.

Pakistan spent 1.87% of GDP on education in 2023, second-lowest in the preceding decade. Redirecting funds towards these areas could offer more substantial and equitable benefits for the population.

Critics aren't pulling punches

"For a developing economy like Pakistan, where reserves can spell the difference between solvency and crisis, embracing such volatility isn't bold policy; it's reckless," Yousuf Nazar wrote in an opinion piece.

The counterargument from Bitcoin bulls – that long-term appreciation outweighs short-term volatility – requires a luxury these countries don't have: time. When your IMF loan comes due and Bitcoin is down 50%, philosophy won't pay the bills.

That's it for this week's News Rollups.

See ya, next Thursday.

Until then … stay curious,
Prathik

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It was just another week at work for the Trump and Co. First slammed the reports claiming Trump Media was raising funds to buy Bitcoin, only to go back on its statement by … err .. actually announcing the fund raise to stack the sats.

In today's News Rollups edition, we answer:

• How Trump Media went from insulting journos to confirming a Bitcoin fund

• Why Sui validators are voting to forcibly override hacker wallets

• How Coinbase shareholders are suing over "artificially inflated" stock prices

• What happens once all 100% BTC is mined

Got questions about a hot crypto topic that you want help understanding? Ask your question using the form and our crypto experts may answer it along with a shoutout to your name in our weekly News Rollups.

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Q: How did Trump Media go from "dumb writers" to "yes, we're buying Bitcoin"?

In a corporate messaging whiplash, Trump Media and Technology Group (TMTG) — a firm US President Donald Trump has a majority ownership in — went from calling Financial Times reporters "dumb writers listening to even dumber sources" to confirming a $2.5 billion Bitcoin capital raise within 24 hours.

Here's how the drama unfolded:

• May 26: FT reports TMTG’s plans to raise $3 billion to buy Bitcoin, citing six sources

• TMTG's response to FT: "…apparently the Financial Times has dumb writers listening to even dumber sources"

• May 27: TMTG announces $2.5 billion capital raise for Bitcoin purchases

The confirmed deal comprises $1.5 billion in stock sales and $1 billion in convertible bonds (with a 0% coupon rate).

CEO Devin Nunes positioned it as financial freedom strategy, saying Bitcoin would help "defend our Company against harassment and discrimination by financial institutions."

Why the initial denial? TMTG likely wanted to control the narrative timing. The original FT report suggested the announcement would come at Bitcoin 2025 in Las Vegas, but the company may have preferred managing the news cycle on their own terms.

Market reaction? Not great. TMTG shares fell over ~20% following the announcement.

Why? Perhaps the investors were spooked by the dilution from new share issuance, despite the Bitcoin treasury strategy that's worked well for companies like Strategy.

Also, this comes right after a persistent wing of Democrats questioned Trump’s unending love-affair with crypto and resulting conflicts of interest.

The irony? The "dumb writers" turned out to be pretty accurate – they just had their numbers slightly off — by $500 million.

Q: Is Sui actually voting to steal back stolen crypto?

That's exactly what they're trying to do – and it's working so far.

After freezing $162 million of the hacker's funds following the $223 million Cetus exploit, Sui network’s major participants — validators and SUI stakers — are now voting on a protocol upgrade. The vote comes after crypto community accused the 114 Sui validators of taking a unanimous and centralised decision to freeze funds.

Read: SUI Dilemma: Decentralised vs Safety?

The vote, if passed, would forcibly override the attacker's wallet control and transfer the frozen funds to a multisig controlled by Cetus, OtterSec, and the Sui Foundation.

The voting mechanics

• Requires 50%+ participation and majority approval

• Currently at 83.6% "yes" votes with 14.5% yet to vote

• Can close early if the result becomes mathematically decisive after 48 hours

• Vote officially ends June 3

The bailout package: Sui Foundation is providing an emergency loan to Cetus while separately committing $10 million for ecosystem-wide security upgrades (enhanced audits, bigger bug bounties, formal verification tools).

It's reactive damage control disguised as proactive planning – fixing the barn door after the horse bolted, then buying a better lock for next time.

The math: Cetus claims 100% user recovery by combining frozen funds + treasury + Sui Foundation emergency loan. Insurance that actually pays out – rare in crypto.

The debate: 114 validators overriding wallet control equals a neighbourhood watch with nuclear weapons, and not decentralisation.

The precedent: Ethereum faced this with the DAO hack in 2016, forked the chain, and the community still argues about it.

The irony: Same team that negotiated with hackers at Crema Finance ($9M loss) now says "we're taking it back" for a 25x bigger hack.

Bottom line: Vote passes = "code is law" has exceptions. Vote fails = Sui joins the "sorry for your loss" club. Either way, the pragmatism vs purity battle will give us a winner and set a precedent.

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Q: Why are Coinbase shareholders suing over a data breach that didn't steal crypto?

Because the stock tanked when the truth came out.

Investor Brady Nessler filed a class-action lawsuit claiming Coinbase's delayed disclosure of the December 2024 data breach caused "significant losses" when shares dropped 7.2% on May 15. The suit argues Coinbase sat on material information for months while investors bought shares at "artificially inflated prices."

The timing makes it worse.

Coinbase just joined the S&P 500 and closed a $2.9 billion Deribit acquisition while knowing about security failures that would cost $180-400 million in remediation.

Now they're facing multiple class-action suits with CEO Brian Armstrong and CFO Alesia Haas named as defendants. The message from investors: when you're playing in the big leagues, sitting on bad news while your stock trades higher isn't poor judgment – it's potentially securities fraud.

The Crypto Comic 🎭

The IMF said it will "efforts will continue to ensure that the total amount of Bitcoin held across all government-owned wallets remains unchanged" as part of a $1.4B loan deal. Hours later, the country bought more BTC. Again.

Dispatch Decoder 👨🏽‍🏫

93% of BTC is mined. What happens after 100%?

Bitcoin's supply mechanics create a fascinating scarcity dynamic that most people miss. With 19.6 million of the 21 million (93%) total BTC already mined, we're witnessing the effects of an exponential issuance schedule that front-loaded most coins into the early years.

The halving schedule is the key driver.

Starting at 50 BTC per block in 2009, rewards have halved every four years to now reach 3.125 BTC per block. The remaining 6.7% will trickle out until 2140, creating an asymptotic supply curve that approaches but never quite reaches 21 million.

What happens once we hit 100% mining?

There’s a wild card here: the lost Bitcoin — which makes the effective circulating supply much lower than what’s on paper. Conservative estimates suggest about 3 million BTC (~15% of total) is permanently lost through forgotten keys, destroyed wallets, and dormant addresses like Satoshi's 1.1 million coins.

Unlike gold, which can be recycled indefinitely, lost Bitcoin makes what’s scarce scarcer. This gives us a supply that shrinks over time rather than just stopping growth.

When block rewards eventually approach zero, Bitcoin's difficulty adjustment mechanism ensures network security doesn't collapse. If mining becomes unprofitable, hashrate drops, difficulty adjusts downward, and margins restore themselves.

This self-correcting feedback loop was stress-tested during China's 2021 mining ban when hashrate dropped 50% yet the network continued functioning seamlessly.

Under the Radar 🔎

Circle's IPO gets BlackRock backing

USDC issuer Circle is targeting a $5.4 billion valuation in its NYSE debut, as per its amended SEC filing, with BlackRock reportedly planning to buy 10% of the IPO shares. The USDC issuer aims to raise $600 million at $24-26 per share, with ARK Investment also indicating interest in $150 million worth of shares.

Existing shareholders are selling more stock (14.4 million shares) than Circle itself (9.6 million) – unusual for tech IPOs but common when insiders want liquidity.

The timing is strategic.

Circle rejected acquisition bids from Coinbase and Ripple "for at least $5 billion" earlier this month, choosing to go public instead.

Read: Coinbase v Ripple: The Battle for Circle🥊

Meanwhile, JPMorgan, Bank of America, Citigroup, and Wells Fargo are plotting their own joint stablecoin venture through co-owned payment companies, eyeing Circle and Tether's $245 billion market.

The irony: BlackRock already manages Circle's reserve fund and built integrations with USDC, while simultaneously the traditional banking giants that once dismissed crypto are now scrambling to compete with the very companies they ignored. Circle's public listing could be the last hurrah before TradFi brings trillion-dollar balance sheets into the stablecoin wars.

That's it for this week's News Rollups.

See ya, next Thursday.

Until then … stay curious.

Don't forget to whitelist thetokendispatch+news-rollups@substack.com to ensure you’ve got me each week in your primary inbox.

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. You can find all about us here 🙌

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, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

Bitcoin terminology wars are heating up as Jack Dorsey calls for rebranding to promote adoption of the largest cryptocurrency, while the Bitcoin purists are fighting to preserve a legacy left behind by Satoshi Nakamoto.

In today's News Rollups edition, we examine:

• Is Bitcoin’s complicated terminology preventing adoption?

• Why is Saylor's Strategy facing class-action lawsuits and short-seller attack?

• Can Solana's upgrade help Web 3.0 compete with the best of Web 2.0?

• Who shut down LIBRA memecoin’s investigation days after court orders?

Got questions about a hot crypto topic that you want help understanding? Ask your question using the form and our crypto experts may answer it along with a shoutout to your name in our weekly News Rollups.

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Find the Right Ledger Hardware Wallet for You

Crypto security made easy. Owning Ledger crypto wallets is the easiest and safest way to secure crypto, digital assets, and your peace of mind.

Q: Should Bitcoin ditch "satoshis" for good?

Jack Dorsey thinks so. No, not the fractional units of Bitcoin, but the term “satoshis” itself. The Twitter founder backed BIP-177, a proposal authored by software developer John Carvalho, to rebrand Bitcoin's base unit from "satoshis" to "Bitcoins".

That will flip the current system where 100 million sats equal one Bitcoin.

Under this plan, what we call 0.00002525 BTC today would become ₿2,525 Bitcoin (worth about $2.66). Meanwhile, today's "1 Bitcoin" would just be called "1 BTC."

The logic? Carvalho argues Bitcoin's decimal points confuse people and make it seem less appealing for everyday spending. "Sats is definitely the wrong term and is stopping everyday people from acquiring and spending Bitcoin," Dorsey posted on X.

This has got Bitcoin purists furious.

They argue it destroys 15+ years of education about Bitcoin's 21 million fixed supply and dishonours Satoshi Nakamoto's legacy. Podcast host Bram Kanstein said: "‘Please send me 1200 BITCOINS for this Apple’. Totally not confusing. Ant brain proposal."

Carvalho, the author of the proposal, isn't fazed by the backlash: "The proposal is entirely rational, thus difficult to refute, so instead we get emotional displays." He believes the change is "inevitable" and just needs time to grow on stubborn Bitcoiners.

Do you think terminology is keeping people away from buying Bitcoin? True Hodlers will hodl anyway, no?

Q: Is Saylor's Strategy sailing in troubled waters?

The Bitcoin treasury champion, Michael Saylor, is facing a class-action lawsuit from investors who claim he misled them about the risks of his fair-value accounting switch.

The lawsuit centres on Strategy's move to fair-value accounting in January, which means Bitcoin price swings now hit quarterly earnings directly. When Bitcoin dropped, Strategy reported a brutal $4.2 billion Q1 loss despite holding 576,000 BTC worth $62+ billion today.

Investor Anas Hamza claims Strategy "overstated" profitability while downplaying volatility risks, focusing on rosy metrics like "BTC Yield" instead of warning about potential massive losses from the accounting change.

Strategy responded in a filing saying it intended to “vigorously defend against these claims.”

What’s worse? Legendary short-seller Jim Chanos, who was the first to call out fraud at Enron more than two decades ago, is going all short on Strategy and long on Bitcoin.

"They're selling retail investors the idea that they should value [Strategy] at a premium" to Bitcoin itself, he told CNBC. His play? Short Strategy stock and use the proceeds to buy actual Bitcoin.

The irony: Chanos says he is doing "exactly what Michael Saylor is doing" - selling Strategy stock to buy Bitcoin, except he's betting the company's premium will compress over time.

With 100+ copycat companies following the same playbook, the legal scrutiny was probably inevitable.

What’s baffling though is investors suing Strategy for the losses they made when BTC slipped in Q1. What else would happen if one’s betting on a company whose product gives investors exposure to a leverage on Bitcoin — both its rewards and risks?

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Q: Is Solana's “Merge” moment here?

On paper, yes. Solana researchers just proposed the blockchain's biggest upgrade ever, slashing transaction finality from 13 seconds to 0.1 seconds, making it 100x faster.

Named "Alpenglow" after Swiss mountaintop light, this consensus overhaul could enable "apps that feel like TikTok, payments that settle instantly, games without lag," according to the Solana Foundation.

The researchers claim Solana would be "much faster than all the other blockchains". So fast that it could give some of its fastest competitors such as Wall Street markets a run for their money. Some suggest Nasdaq's days as the financial hub are numbered.

The upgrade could launch by end of 2025 after the community approves it. Recent Solana governance has been rocky – a tokenomics proposal just failed after late opposition votes.

But researcher Roger Wattenhofer sounds confident: "This is going to be the new consensus protocol of Solana." He's got backing from co-founder Anatoly Yakovenko and key developers.

If successful, Alpenglow could be Solana's "Merge" moment – except instead of going green like Ethereum, Solana's going for pure speed to compete with Web2 infrastructure.

The Crypto Comic 🎭

CFTC commissioner Kristin Johnson joined her colleagues — Summer Mersinger, Christy Goldsmith Romero, and Acting Chair Caroline Pham — as the fourth one to announced departure plans from the agency. This will potentially leave Trump's nominee Brian Quintenz running a one-man show at crypto's likely primary watchdog.

Dispatch Decoder 👨🏽‍🏫

What do rising 10-year Treasury yields mean for crypto?

The 10-year Treasury yield – currently at 4.585% in the US and 1.57% in Japan – is essentially the "risk-free" return investors can get from lending money to the government for a decade.

When these yields rise, it creates a powerful competitor for crypto investments. Think about it: why take the volatility risk of Bitcoin when you can get a guaranteed 4.58% return from the government?

Rising yields typically hurt crypto in three ways:

1. Capital flight: Money flows out of risky assets like crypto into safer bonds

2. Higher borrowing costs: Crypto platforms and traders face expensive financing

3. Stronger dollar: Makes crypto more expensive for international investors

Recent market action proves this relationship.

When the 30-year Treasury spiked to 5.09% on May 21 – the highest since 2007 – Bitcoin failed to hold its $109,000+ all-time high and stocks crashed 800+ points.

There’s a catch though. Crypto can also benefit as a hedge against the economic uncertainty that drives yields higher. Some traders view rising yields as a sign of a "cracking system," making decentralised alternatives more appealing - just like we saw Bitcoin smash the $111,000 mark later on May 21.

The bottom line? Rising Treasury yields create signal market uncertainties, but they also reinforce Bitcoin's narrative as an alternative store of value when traditional finance gets shaky.

Under the Radar 🔎

Milei shuts down LIBRA memecoin investigation

Argentine President Javier Milei just dissolved the task force investigating his February LIBRA memecoin promotion – conveniently days after a judge ordered his bank records unsealed.

The Solana token Milei endorsed had crashed from a $5 billion market cap to near-zero in what rocked the memecoin and broader crypto ecosystems alike, leaving $251 million in losses for traders across 13,000 wallets.

Read: When Presidents Play With Memes 🏛️

Politically, Milei's timing is smart – he's riding high after stabilising the peso and winning a capital election. "No better moment to prevent bad info from being released before midterms," said James Bosworth, founder of risk analysis consultancy Hxagon.

So much for an accused handling and managing the investigation probing the alleged crime?

LIBRA holders were the happiest - the token almost doubled on the news before correcting and settling down with 30% gains.

That's it for this week's News Rollups.

See ya, next Thursday.

Until then … stay curious.

Don't forget to whitelist thetokendispatch+news-rollups@substack.com to ensure you’ve got me each week in your primary inbox.

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. You can find all about us here 🙌

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, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

There’s a new guest at the Wall Street and the whole finance world (both traditional and decentralised) is going crazy discussing the impact.

This could be one of the biggest moves pushing for crypto adoption.

In today's News Rollups edition, we examine:

• How Coinbase's S&P 500 inclusion will bring crypto to millions

• Growing rift at SEC as Crenshaw pushes back against pro-crypto policies

• How Strategy's aggressive buying is making Bitcoin deflationary

• What’s RWA tokenisation and how it is bridging TradFi and DeFi

Got questions about a hot crypto topic that you want help understanding? Ask your question using the form and our crypto experts may answer it along with a shoutout to your name in our weekly News Rollups.

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Own is Making Things Possible

Ever wanted to own a piece of real-world assets: like real estate, startups, or art, without the red tape, middlemen, or huge upfront costs?

It’s the first Ethereum Layer 2 built specifically for the creation, management, and distribution of tokenised real-world assets (RWAs). That means you can invest in tangible things property, equity, and collectibles fully onchain.

• No paperwork

• No waiting for weeks

• No “just trust us” platforms

You actually own the asset, not just a promise.

It’s faster, cheaper, and open to anyone, not just institutions or the ultra-wealthy.

Whether you're a DeFi native or just crypto-curious, Own is where real-world value meets blockchain - Check it out!

This isn’t hype. This is ownership - finally made real.

Q: Why is Coinbase’s inclusion in S&P 500 a big deal?

"First they fight you, then add you to the S&P 500," sums up Bernstein analysts' take on what's happening here. Do we agree? Well, with all that’s unfolded in the past week, it’d be difficult not to.

Coinbase will become the first pure-play crypto company in the index on May 19, replacing Discover Financial Services. Just months after being locked in "intense litigation" with the SEC (before the case was dropped under Trump), Coinbase is now joining the most prestigious club in American business alongside Apple, Amazon, and Berkshire Hathaway.

Why is this big? We are looking at the financial implications of this inclusion.

With roughly 0.1% weight in the index, Coinbase could see $9 billion in passive inflows from S&P 500-linked funds and another $7 billion from active funds, estimated Bernstein.

That’s not all. An average investor will also feel the impact.

"Crypto is about to be in everyone's 401k," CEO Brian Armstrong put it. With this, millions of regular Americans who've never bought crypto, will now have exposure through their retirement accounts. Your parents, teachers, and that friend who coaxed you into believing crypto was all a scam? They're all about to become inadvertent crypto investors.

For perspective, there's roughly $3 trillion in passive investments tracking the S&P 500. Even a tiny allocation means billions flowing indirectly into the crypto ecosystem.

Coinbase stock has jumped almost 30% after the announcement.

Q: What’s the infighting at the US Securities and Exchange Commission about?

Trump's crypto-friendly SEC and its sole Democratic commissioner Caroline Crenshaw, the agency's lone dissenting voice, are having a bit of an internal stand-off.

At the Monday SEC roundtable, Crenshaw pushed back at SEC Chair Paul Atkins’ words of praise for tokenisation, saying it all “seems a bit like the government picking winners and losers.” Her argument? When SEC should have remained as a “tech-neutral regulator, why is it our place to assess particular forms of blockchains as candidates for industry adoption?”

This follows her harsh criticism of the recent Ripple settlement, which slashed the company's penalty from $125 million to just $50 million. Crenshaw called it a "tremendous disservice to the investing public".

The Democrat does raise important questions around the direction of the SEC under Trump’s administration.

Trump's personal crypto ventures (his memecoin and family-run ventures) have become painful for his Republican peers, with Democrats staging walkouts from hearings and introducing the "MEME Act" to ban officials from profiting off crypto.

Read: The Crypto Bills’ Chaos 📃

What’s worrying for the industry is that Crenshaw, herself, doesn’t boast of an impressive track record with crypto. “These Commission actions are unsound and ahistorical,” were her words more than a year ago, when she dissented to SEC’s Bitcoin ETF approval.

What’s worse? With all this going on, the broader industry suffers. Partisan deadlock means hopes for clear rules keep getting pushed further away.

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Q: Is Bitcoin becoming deflationary? Why is that good?

"Strategy's holdings alone mean a -2.23% annual deflation rate — likely higher with other stable institutional holders," Ki Young Ju, CryptoQuant CEO, posted last week.

Bitcoin is already disinflationary by design - its issuance rate drops by half every four years through the halving. Strategy’s and other corporate Bitcoin treasuries’ aggressive buying has accelerated this. Strategy buys Bitcoin over multiple times faster than miners can produce it, effectively acting as a financial black hole for Bitcoin.

Translation: The circulating supply of Bitcoin that can actually trade is contracting. How does that help?

When large, patient holders like Strategy control more of the supply, there's less Bitcoin available for panic-selling during downturns, smoothing out the wild price swings that once defined crypto markets.

The Crypto Comic 🎭

Ethereum (~30%) has outperformed Bitcoin (~2.6%) and Solana (~12.2%)in the past one week in terms of price rise on the back of its recent updates including the long-awaited Pectra upgrade.

Dispatch Decoder 👨🏽‍🏫

What Is RWA Tokenisation?

"Today BlackRock’s BUIDL tokenised by Securitize reached the $1B mark and it is the largest tokenised asset in the industry besides stable coins,” said Carlos Domingo, CEO of Securitize.

Not just Securitize, even traditional finance giants including Morgan Stanley, JPMorgan and VanEck are jumping onto tokenisation bandwagon. Why?

Real World Asset (RWA) tokenisation is blockchain's bridge to the trillions locked in traditional markets. It's the process of converting physical and financial assets - from real estate to Treasury bills - into digital tokens that live on blockchains.

That Manhattan skyscraper? Now fractionally owned by thousands via blockchain. Those corporate bonds? Trading 24/7 with instant settlement.

The revolution is already underway. VanEck just launched its first RWA fund exposing Treasury bills across multiple blockchains.

Under the Radar 🔎

Trump family-linked firms have raked in $320 million from the TRUMP memecoin despite its 80%+ crash from its peak. While President Trump denied profiting personally, Chainalysis data shows creators netted massive fees as over 760,000 retail wallets – the vast majority of investors – lost money.

Where did the money go, then? Into thin air?

Trump’s token is primarily controlled by CIC Digital LLC and Fight Fight Fight LLC, entities tied to the president’s organisation that collectively own 80% of the supply.

Meanwhile, crypto whales are paying astronomical sums for a seat at Trump's dinner table. The top 25 "VIP" attendees on the leaderboard for the May 22 gala at Trump National Golf Club held an average of $4.8 million worth of TRUMP tokens to qualify.

Background checks are now underway for the 220 winners.

How does one describe all this? Here you go: "The most nakedly corrupt self-enrichment scheme in US presidential history." Well, that’s what Accountable.US called the $TRUMP token leaderboard.

That's it for this week's News Rollups. Until next Thursday, stay curious.

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. You can find all about us here 🙌

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, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

Just as the Republicans were preparing for a regulatory win with crypto legislations in the Congress, they have hit a roadblock against an unexpected opposition from the Democrats.

What’s worse? US President Donald Trump’s crypto adventures (or should we call them misadventures) are coming back to bite the Republicans.

In today's News Rollups edition, we examine:

• Why House and Senate are up in arms over crypto legislations

• Bitcoin-backed loans: Smart financial strategy or risky business?

• Where are Bitcoin, XRP, and Cardano headed in 2025

• How prediction markets player scored a major win

Got questions about a hot crypto topic that you want help understanding? Ask your question using the form and our crypto experts may answer it along with your name in our weekly News Rollups.

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Grayscale Makes Crypto Investing Super Simple

You know how getting into crypto usually means setting up wallets, writing down seed phrases, and hoping you don’t lose everything in a browser tab? Grayscale skips all that mess.

They let you invest in Bitcoin, Ethereum, and other digital assets just like you’d buy stocks through regulated, SEC-reporting products. No keys, no stress, no DIY crypto rabbit holes.

It’s crypto exposure, the Wall Street way.

What does this actually mean?

• Want to invest in Bitcoin? Buy GBTC like a stock

• Curious about Ethereum or Solana? There’s a product for that

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• Want crypto in your retirement account? You can do that too

Grayscale brings crypto to the table without making you sit through a Metamask tutorial. It’s the easiest on-ramp for anyone who wants it, especially institutions.

This isn’t just crypto made accessible. It’s crypto made investable - Check it out.

Q: What's with all the shouting in Congress over crypto bills?

Remember when Trump's crypto czar promised of bringing in the golden era for digital assets? Yes, that one. That’s facing a reality check as lawmakers are now literally walking out of hearings and yelling at each other over the president's crypto ventures.

Let's break down this Washington drama.

Democrats are refusing to support crypto bills, claiming they would directly benefit Trump's wallet. The president's memecoin and family stablecoin business have created what Rep. Waters calls "Trump’s crypto corruption."

The flashpoints:

• House Democrats staged a dramatic walkout from a crypto hearing, holding their own "Trump corruption" meeting instead

• Nine Senate Democrats killed their support for the GENIUS Act stablecoin bill days before a vote

• A $2 billion UAE-backed deal involving Trump's stablecoin and Binance triggered foreign influence alarms

• Trump has offered exclusive dinner opportunities to top $TRUMP memecoin holders

In response, Democrats introduced the "MEME Act" (nope, we ain’t making this up) to ban government officials from profiteering from crypto and other financial involvement.

Meanwhile Republicans are forcing a Thursday vote they'll likely lose (because they ain’t got the numbers on their side) – apparently to paint Democrats as anti-crypto before midterms.

Read: Washington’s Crypto Moves Face Political Roadblocks 🚧

What could come out of all this? A tougher than expected summer if Congress fails to pull its act together and representatives from both sides find a way out of this regulatory stalemate. Lest? They fail the larger industry.

With Trump's executive actions vulnerable to reversal by future administrations, actual legislation remains the holy grail.

The irony? Trump's personal crypto enthusiasm might end up being the very thing that prevents America from getting clearer crypto rules.

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Q: Do Bitcoin-backed loans make sense for hodlers?

They are surely experiencing a renaissance, with Strike, Coinbase, and Xapo Bank all jumping on the bandwagon. Jack Mallers' Strike is the latest entrant, offering 12-month loans starting at $75,000 with a 12% annual percentage rate (APR) using BTC as collateral.

Why Bitcoin? The pitch is simple: access cash without selling your precious Bitcoin.

The math can be compelling. With Bitcoin hovering around $95,000-$99,000, borrowers can tap into significant cash without triggering taxable events. Think of the early adopters holding even 1 bitcoin. That’s almost a $100,000 worth of credit without having to sell it.

This gets crazier. If BTC continues appreciating at even a moderate 25% annually while you pay 12% interest, you're effectively profiting from borrowed money - a "buy, borrow, die" strategy that has helped billionaires save taxes over the years. More on this, later.

There’s a catch, though.

This market imploded spectacularly during the 2022 crash, taking down major players like Celsius and BlockFi who misused customer funds. Today's lending market is still 43% smaller than its 2021 peak.

Bitcoin investors raised red flags. Some remain sceptical, citing "rehypothecation risk" - the danger that lenders reuse your collateral for their own purposes.

With Strike partnering with "carefully selected capital providers" who take custody of your Bitcoin during the loan period, these concerns remain relevant.

HTF Market Intelligence is optimistic though. The research firm projects the Bitcoin loan market to shoot 5x to $45.6 billion by 2030.

With the SEC's January repeal of SAB 121 accounting rules, traditional banks may soon enter the space, potentially bringing stronger consumer protections - and even more liquidity options for Bitcoin holders.

Until then, tread with caution.

Got questions about this week's crypto world? Fill out this form for a chance to have your question featured in our next edition with an exclusive shoutout.

Q: Can we expect to see Bitcoin, XRP, and Cardano rise in price in 2025?

For Bitcoin, institutional momentum stands strong today despite some headwinds in the past couple of months.

Bernstein expects Bitcoin to rake in $330 billion from corporates building their treasuries in the next five years.

With MicroStrategy holding 555,450 BTC worth $55+ billion, increasing spot ETFs, and new Bitcoin-backed financial products emerging, the fundamentals show persistent strength.

Bitcoin’s recent 30% drop from the peak at its worst remains a sober reminder that things can go south. Yet, the latest reinforcement of its decoupling narrative is a strong sign of Bitcoin’s trajectory.

Want more affirmation? Even the states have now joined the federal government to make a Bitcoin reserve with New Hampshire and Arizona signing their respective Bitcoin reserve acts.

For XRP, the biggest win came through the regulatory cloud finally being lifted. The SEC settled the long-standing case in March (reduced to $50 million) and removed XRP's biggest headwind.

Ripple's been busy with its RLUSD stablecoin launch and striking partnerships to build an ecosystem around it - such as the one with Aave V3 Ethereum market and its recent $1.25 billion acquisition of multi-asset prime broker Hidden Road acquisition.

The pending ETF applications, if approved, could clear the way for upside. Caveat is that an ETF green signal doesn’t necessarily equate to green days ahead. Need we look beyond our dear ETH to understand this?

Read: Can Altcoin ETFs Avoid ETH ETFs' Fate? 🌀

XRP also needs to fight back the centralisation claims its critics have been throwing at it for a long time now.

Cardano’s 2025 roadmap focuses on Bitcoin integration (tapping into BTC's massive liquidity), advancing governance and enhancing privacy. Its academic approach has built a solid foundation, but institutional adoption lags behind the others.

While analysts are optimistic of a Cardano ETF nod soon, it might just not be enough for sustained upside.

The verdict? Bitcoin has the clearest path upward with institutional backing. XRP has made some moves with regulatory clarity and strong payment utility. Cardano's ambitious roadmap looks promising but faces adoption hurdles.

Shoutout to our frequent reader, Dave Weitl, for sending across this question.

The Crypto Comic 🎭

Despite delaying decisions on Litecoin, Solana, XRP, and Dogecoin ETFs, the commission hasn't deterred new applicants – with Bitwise and VanEck recently filing for NEAR and BNB ETFs.

Dispatch Decoder 👨🏽‍🏫

What’s the ‘Buy, Borrow, Die’ strategy?

The Bitcoin-backed loans we spoke about bring to crypto holders the tax hack billionaires have used for decades.

1. BUY: Acquire appreciating assets (now Bitcoin)

2. BORROW: Take loans against these assets instead of selling (no capital gains tax)

3. DIE: Pass assets to heirs with stepped-up basis, erasing lifetime gains

The magic? Loans aren't taxable income. If your Bitcoin appreciates annually, you're profiting while paying zero tax. Your collateral keeps growing, allowing you to borrow more.

This explains how the ultra-wealthy live lavishly on paper-thin incomes. The strategy works best with significant assets and careful management of loan-to-value ratios to avoid liquidation during crashes.

Under the Radar 🔎

The crypto case closure saga under Trump’s friendly administration saw prediction market platform Kalshi score a major regulatory win this week. The Commodity Futures Trading Commission (CFTC) moved to dismiss its appeal against the company in a case that dates back two years.

The decision now allows Kalshi to continue offering betting market contracts on US election outcomes.

This follows a pattern similar to the SEC's withdrawal of crypto enforcement actions earlier this year.

Read: Case Closed: SEC’s Crypto Cleanup🧹

Know what’s more interesting? The coincidence. Donald Trump Jr joined Kalshi's board as an advisor in January, just as his father was returning to office.

Election markets here to stay, then? " At least that’s what Kalshi founder Tarek Mansour says.

That's it for this week's News Rollups. Until next Thursday, stay curious.

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. You can find all about us here 🙌

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, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

Despite fulfilling several crypto-friendly campaign promises and appointing industry advocates to key positions, the crypto market cap and Bitcoin are down since US President Donald Trump’s inauguration in January.

In today's News Rollups edition, we examine:

• The gap between Trump's crypto promises and market reality 100 days into his term

• How El Salvador manages to keep accumulating Bitcoin despite IMF restrictions

• Current state of crypto staking and where to find the best yields in 2025

• Why the DOJ is seeking a 20-year sentence for former Celsius CEO Alex Mashinsky

• How NVIDIA is quietly shutting the door on crypto startups in favor of AI

Got questions about a hot crypto topic that you want help understanding? Ask your question using the form and our crypto experts may answer it along with your name in our weekly News Rollups.

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Q: 100 days in, where’s Trump with his crypto promises?

• Most crypto-friendly president in US history ✅

• First president to sign a crypto bill ✅

• Strategic Bitcoin Reserve executive order ✅

• Digital Assets Stockpile ✅

This looks like a dream run for the crypto industry in the first 100 days of Trump’s second term at the White House.

Yet, the reality today stands in stark contrast.

• Crypto market cap? Down 15%+ since his inauguration

• Bitcoin down almost 10% from the all-time high after Trump’s inauguration

To his credit, Trump has fulfilled several campaign promises that signal a regulatory shift.

Silk Road founder Ross Ulbricht got the promised presidential pardon. Trump issued executive orders on the first day of his office banning central bank digital currencies (CBDCs) and protecting miners' rights. Became the first president to sign a crypto bill by overturning an IRS rule for DeFi platforms.

His appointments of crypto-friendly figures like Securities and Exchange Commission (SEC) Chair Paul Atkins and Commerce Secretary Howard Lutnick have already resulted in concrete changes, with the SEC ending nearly all active lawsuits against crypto firms and rescinding restrictive guidance like SAB121.

We have also seen the SEC shift away from the Gary Gensler-era ‘regulation-by-enforcement’ approach. The watchdog has been calling off pre-Trump 2.0 era cases that Gensler had filed against hoard of crypto firms.

However, the administration's more ambitious legislative agenda has stalled.

Despite public promises that both stablecoin and market structure bills would be signed within 100 days, neither has reached the president's desk.

There’s been progress on the stablecoin front, sure. But promises are either fulfilled or broken - no room for work-in-progress.

The Strategic Bitcoin Reserve appears largely symbolic, consisting mainly of assets already in government possession through criminal proceedings rather than new acquisitions.

Meanwhile, Trump's personal involvement in crypto ventures like World Liberty Financial and the $TRUMP memecoin has created concerning conflicts of interest.

Read: Crypto, Trump, and the Conflict💸

Just a week ago, the total assets under management in Bitcoin ETFs managed to climb back to $38 billion, the same level that was seen on the day of Trump’s inauguration.

Has the crypto landscape moved from where it was when Trump re-entered the White House? Sure. The direction of the move, though, is something that can be debated about.

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Q: What's the state of crypto staking in 2025? Is it thriving, and where are the best returns?

Numbers show that staking is booming in 2025, despite a few headwinds. Major chains see impressive participation rates.

About four years ago, JPMorgan predicted the global Ethereum staking market to be worth $40 billion. Today, Ethereum has over 34.3 million ETH locked up (worth more than $60 billion), with more than 28% of all ETH now staked – up from 23.8% in January 2024.

The yield landscape:

• Ethereum: A modest 2-7% APY (averaging 3-4%), with Coinbase offering 2.01%, Kraken 2.5-7%, and Lido around 4-7%

• Solana: Healthy returns of 5.57% on Coinbase

• Polkadot: Up to 15% returns on DOT tokens for those willing to participate in governance

For the yield hunters, Binance offers even higher Annual Percentage Yield (APY) on select tokens, though these typically come with higher risks.

The staking game is evolving too.

Innovations like liquid staking (through Lido, Ether.fi) and restaking (via EigenLayer) let you double-dip, using staked assets in DeFi while still earning base rewards. EigenLayer can potentially boost ETH returns beyond 5% for the technically savvy.

Is it all sunshine? Not quite.

More validators mean shrinking individual rewards (Ethereum's APR dropped from 4.3% to 3.13% last year), and some argue staking has become "anti-growth" without sufficient compensation. Regulatory uncertainty and platform risks still loom large.

Bottom line: Staking remains a cornerstone of crypto passive income, but the days of effortless double-digit yields on major assets are mostly behind us. The smart play in 2025 is diversifying stakes across multiple coins and platforms while keeping a close eye on innovations like restaking that can juice those returns.

Shoutout to our frequent reader, Buck, for sending across this question on staking.

Got questions about this week's crypto world? Fill out this form for a chance to have your question featured in our next edition with an exclusive shoutout.

Q: Who is Alex Mashinsky and why is DOJ seeking a 20-year sentence for him?

Alex Mashinsky, 59, pleaded guilty in December 2024 to two counts of fraud after Celsius, the crypto lending platform he had founded.

Chares: Lying about Celsius’s financial condition to convince investors to deposit their Bitcoin and defrauding buyers of company’s native token, CEL, by manipulating its price and lying about selling his own personal holdings.

Prosecutors argued his "years-long campaign of lies" caused $550 million in losses while he personally profited $48 million.

Mashinsky's lawyers have tried to distance him from FTX founder Sam Bankman-Fried, arguing for a sentence of just one year and one day. Their key argument: "There are no allegations that Alex misappropriated, embezzled or stole any customer assets" and Celsius failed due to market conditions, not fraud.

Prosecutors strongly disagree.

Called his crimes "deliberate, calculated decisions to lie, deceive, and steal." They point out that while SBF was in his 20s, Mashinsky, at nearly 60, was "old enough and experienced enough to better appreciate the crimes he was committing."

The case has drawn over 200 victim impact statements, with one investor writing Mashinsky "devastated numerous lives, and there are those who have taken their own lives because of him." Many victims are demanding a life sentence similar to Bernie Madoff's 150 years.

Prosecutors said Mashinsky has shown a "lack of remorse" and "abandoned all pretense of acknowledging his sustained wrongdoing." They also claim he's shielded his assets in an "elaborate system of trusts" managed by his sister while his wife challenges government seizures meant for victim restitution.

The sentence hearing is scheduled for May 8.

The Crypto Comic 🎭

El Salvador President Nayib Bukele continues adding to the country's Bitcoin stash (now 6,163 BTC worth more than $585 million) despite IMF loan deal that restricted the nation from giving the cryptocurrency legal tender status.

The clever workaround? Using entities "outside the fiscal sector" while technically complying with the $1.4 billion agreement.

“’This all stops in April.’ ‘This all stops in June.’ ‘This all stops in December.’ No, it’s not stopping. If it didn’t stop when the world ostracised us and most “bitcoiners” abandoned us, it won’t stop now, and it won’t stop in the future. Proof of work > proof of whining,” Bukele tweeted.

Dispatch Decoder 👨🏽‍🏫

What are Liquid Staking and Restaking?

Liquid staking gives you flexibility with staked assets. Stake ETH, get stETH in return – a token you can trade or use in DeFi while still earning your base rewards. No more waiting through lock-up periods! This lets your crypto work double duty.

Restaking is crypto's way of squeezing extra juice from already-staked assets. Protocols like EigenLayer let you use your staked ETH (or its liquid version) to secure additional networks and earn extra rewards on top. It's essentially putting the same capital to work multiple times, potentially boosting yields while supporting the broader ecosystem.

Under the Radar 🔎

Chip giant NVIDIA has kicked crypto firms out of its Inception Accelerator Program as of April 24, formally adding "companies associated with cryptocurrency" to its no-fly list.

NVIDIA's CTO Michael Kagan didn't mince words back in 2023. "Crypto doesn't bring anything useful for society." Then the company went on to ride the mining boom to massive profits, only to now firmly pick Team AI over Team Crypto.

The biggest casualty? Arbitrum, a layer-2 platform which was about to be announced as NVIDIA's exclusive Ethereum partner until the chip giant got cold feet. Arbitrum promptly walked away, calling it a "sound business decision." Meanwhile, Aptos Foundation still has a seat at NVIDIA's table.

Well, some blockchains are more equal than others, perhaps?

That's it for this week's News Rollups. Until next Thursday, stay curious.

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. You can find all about us here 🙌

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, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

Broader and crypto markets swung in the last seven days as US President Donald Trump publicly attacked Federal Reserve Chair Jerome Powell, calling him a "major loser" and saying his "termination cannot come fast enough!" before suddenly backing down on Tuesday this week, stating he had no intentions of firing Powell.

In today's News Rollups edition, we look at:

• Why Trump backed down from firing Fed Chair Powell after threatening him

• The constitutional debate over whether a president can legally remove Powell

• Why Oregon is suing Coinbase even after the SEC dropped its charges

• Why Kraken is cutting jobs despite doing stable business

• Emerging of public companies building Solana treasuries

Got questions about a hot crypto topic that you want help understanding? Ask your question using the form and our crypto experts may answer it along with your name in our weekly News Rollups.

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Q: Why Trump won’t fire Powell? Legally, can he? What if he does?

President Trump’s U-turn of not intending to ask the Fed Chair to leave didn’t come out of nowhere. In meetings with top retail CEOs and advisers, the industry stakeholders painted a dire picture of empty store shelves and financial turmoil if the trade war with China and attacks on Fed independence continued.

Can a president legally fire the Fed chair, though?

The Federal Reserve Act states board members can only be removed "for cause" (meaning serious misconduct or violations), not policy disagreements. This is backed by a 1930s Supreme Court ruling commonly called Humphrey's Executor.

All good, then? Nah, Trump's Justice Department is still actively seeking to overturn this precedent as part of a broader legal fight regarding independent agencies. While Powell believes the Fed might receive special treatment from the courts, the uncertainty has kept markets on edge.

Why does Fed independence matter?

The historical record is clear: When presidents successfully pressure the Fed to lower rates for political gain, inflation rises "strongly and persistently." One study found that presidential pressure at half the level Nixon applied to Fed Chair Arthur Burns in the 1970s raised prices by 8% over a decade.

What if Trump actually fired Powell?

• Traditional assets like bonds and the dollar would plummet

• US equity markets would crash on fears of political meddling

• Alternative assets like gold and Bitcoin could surge as safe havens

This is why both Wall Street and White House advisers reportedly persuaded Trump to back off.

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Q: Why is Oregon state suing Coinbase?

Oregon Attorney General Dan Rayfield filed a securities enforcement action against Coinbase last week, just months after the US Securities and Exchange Commission dropped similar charges against the exchange.

The lawsuit claims Coinbase "encouraged and helped the sale of unregistered cryptocurrencies to people in Oregon," listing XRP and 30 other tokens as unregistered securities.

Why counter SEC’s position?

"States must fill enforcement vacuum being left by federal regulators who are abandoning these cases under Trump administration," said Rayfield, positioning state authorities as a counterbalance to the SEC's dramatically shifted approach to crypto regulation post Trump’s relection.

Coinbase Chief Legal Officer Paul Grewal blasted the action as "Oregon's holdout campaign" and "obstruction for the sake of obstruction," arguing it "takes us a giant leap backwards from hard-won progress."

Legal experts note that even if Oregon wins, the ruling wouldn't create binding precedent beyond the state. However, it could provide ammunition for other state regulators or potential plaintiffs seeking to build similar cases.

Q: What's up with Kraken's layoffs?

The crypto exchange platform was reported to have trimmed hundreds of job ahead of a potential IPO, after it confirmed it's making "the difficult decision to eliminate certain roles and consolidate teams where redundancies exist."

This follows a previous 15% reduction (about 400 employees) in October 2024 when Silicon Valley investor Arjun Sethi joined as co-CEO alongside David Ripley.

Despite the cuts, Kraken maintains its "business is thriving" with strong revenue growth. The exchange currently handles more than $1 billion in daily trading volume.

If successful, Kraken would join Coinbase as only the second publicly traded US crypto exchange.

The Crypto Comic 🎭

$TRUMP, marketed as the official token of president Donald Trump, rallied about 70% on Wednesday as the official website posted an invitation to a dinner event with the US President for top 220 token holders.

Watch: Why Bitcoin's Moment Is Finally Here

Dispatch Decoder 👨🏽‍🏫

What's the Fed's "Dual Mandate"?

The Federal Reserve operates under what's called a "dual mandate" from Congress: maintain maximum employment while keeping prices stable (targeting 2% inflation).

This creates a dilemma when facing economic pressures like Trump's tariffs, which simultaneously threaten to:

1. Slow economic growth (pushing the Fed toward rate cuts)

2. Increase inflation (pushing the Fed toward higher rates)

This "stagflation" scenario puts the Fed's dual mandates in direct conflict, forcing what Powell recently described as a "difficult judgment" between competing goals.

The situation explains why the Fed is hesitant to cut rates despite Trump's demands. With inflation still at 2.4% in March (above the 2% target) and tariffs threatening to push prices higher, rate cuts could worsen inflation while only temporarily boosting growth.

Under the Radar 🔎

Companies race to build Solana treasuries

A wave of public companies rushed to stack Solana in the past week, mimicking Strategy's (formerly MicroStrategy) Bitcoin accumulation playbook.

DeFi Development Corp added $9.9 million worth of SOL on Wednesday, bringing its holdings to 317,273 tokens ($48 million). The former real estate data company, which was earlier known as Janover until its rebranding exercise last week, acquired discounted locked SOL through BitGo's OTC desk.

Canadian firm SOL Strategies, which has been a pioneer in building Solana treasury, secured a $500 million convertible note facility to accelerate its Solana purchases.

Nasdaq-listed Upexi saw its stock surge 335% in a single day after announcing a $100 million raise with 95% dedicated to establishing a Solana treasury.

These small-cap stocks (both Upexi and DeFi Development Corp with market caps under $7 million each before their crypto pivots) have found new life by offering investors regulated exposure to Solana.

Only time will tell if this will help them taste the kind of success that Saylor’s Strategy is enjoying.

That’s it for this week’s News Rollups.

Until next Thursday, stay curious.

PS: Got some questions about the world of crypto from this week? Fill this form here and get a chance to have your question featured and answered by our experts in the next edition.

Disclaimer: This newsletter contains analysis and opinions, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. You can find all about us here 🙌

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, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

Global markets felt tremors for the past two weeks with US President Donald Trump's tariff announcements. Bitcoin slumped, recovered a bit and is now stuck in a range. Altcoins are living through a forgettable nightmare.

One unlikely asset defied gravity, though. And it’s a memecoin.

Fartcoin rallied more than 2x in a month. No, you are not dreaming. A flatulence-themed token is leading the crypto recovery.

In today's News Rollups edition, we tackle:

• Why are traders betting on Fartcoin while other memecoins struggle?

• Why Pakistan suddenly tapped former crypto exile CZ as advisor

• How tariffs might fund America's Bitcoin reserve

• How a DeFi CEO plans to burn $236 million of his team's tokens

Got questions about a hot crypto topic that you want help understanding? Ask your question using the form and our crypto experts may answer it along with your name in our weekly News Rollups.

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Q: Why are traders betting on Fartcoin while other memecoins struggle?

Fartcoin rose about 220% over the past month and nearly 100% in a little over a week. While Bitcoin remained flat, FART blasted past other memecoins, including TRUMP (down ~30%), DOGE, PEPE, and WIF.

It’s not some random whales swinging the price for Fartcoin.

Heavy trading volume is driving the rise - more than $300 million in the last 24 hours. That’s exceeding the combined volume of Bonk's $92 million and even Shiba Inu's $146 million, both of which boast of higher market caps than Fartcoin.

There’s no solid fundamentals though driving this activity in Fartcoin.

“Fartcoin’s absurd outperformance is the perfect metaphor for this market. A joke wrapped in volatility, where escalating US-China tariffs make 'rational' trading a fantasy," said Kirill Kretov.

For those invested in the Solana and memecoin ecosystem, it also makes sense to move their funds into a memecoin themed around flatulence that’s giving more than 2x returns in a week, than letting the value erode by holding the funds in Solana.

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Q: Why is Pakistan suddenly talking crypto with CZ?

The South-east Asian country last week appointed former Binance CEO Changpeng "CZ" Zhao as advisor to its newly formed Crypto Council.

The move aligns with Pakistan positioning itself to become a crypto hub, with plans to use its surplus electricity to power Bitcoin mining and AI data centres. Council CEO Bilal Bin Saqib made it clear: "Pakistan is done sitting on the sidelines."

Why CZ? His global connections and exchange-building expertise could help Pakistan attract international investment. The collaboration also aligns with US President Donald Trump's pro-crypto stance, as Saqib noted: "Every country will have to follow suit or risk getting left behind."

Q: US wants to fund its Bitcoin reserve with tariffs. Can it?

The numbers suggest it's feasible. Current tariffs are projected to generate between $220-460 billion annually, while acquiring 800,000 Bitcoin (to reach the proposed 1 million BTC goal) would cost about $66 billion at current prices.

Bo Hines, a crypto advisor to Trump, said in a recent interview with Professional Capital Management CEO Anthony Pompliano, that the US is exploring “…many creative ways, whether it be from tariffs,…” to fund its BTC reserve without using taxpayers’ money.

Another proposal: revaluing Treasury gold certificates (more on this later) from $43 per ounce to the current $3,200 market price, creating a paper surplus to fund Bitcoin purchases without selling gold.

The administration needs "budget-neutral" strategies that impose "no incremental costs on American taxpayers," making tariff revenue an attractive option.

What’s the catch, then? Economic concerns loom large. Tariffs are predicted to reduce GDP growth by 0.6% in 2025, with JPMorgan warning of potential recession. The 90-day tariff pause announced April 9 also complicates immediate funding plans.

The Crypto Comic 🎭

Mantra CEO John Mullin pledged to burn his entire team's token allocation – worth $236 million – following OM token's catastrophic 92% crash on April 13. Why? To win back community trust.

Watch: Mantra Co-Founder Explains $5 Bn OM Token Collapse

Dispatch Decoder: What are Treasury Gold Certificates? 👨🏽‍🏫

Remember how Trump’s crypto adviser Hines was suggesting the Treasury gold certificates revaluation route to fund the Bitcoin reserve? Well, these certificates are claims the Federal Reserve holds on the US Treasury’s gold. These claims are valued at an outdated $43 per ounce from the 1970s, not the current $3,200 market price.

Revaluing them to today’s price creates a “paper surplus” on the Treasury’s balance sheet without selling gold. This surplus could fund a Bitcoin reserve without new taxes or debt, as it’s budget-neutral. Economically, this boosts the Treasury’s assets on paper but risks inflation or market distortions if perceived as money printing. It’s a creative way to fund Bitcoin without physical gold sales.

Under the Radar 🔎

Panama City became the newest addition to the list of growing cities that accept crypto for municipal payments. Mayor Mayer Mizrachi on Wednesday announced that the city will accept Bitcoin, alongside other cryptocurrencies including stablecoins, for taxes, permits and fines.

Unlike previous attempts requiring new legislation, they partnered with a bank to instantly convert crypto to USD, making implementation immediate. Panama joins a growing list of crypto-friendly municipalities worldwide.

That’s it for this week’s News Rollups.

Until next Thursday, stay curious.

PS: Got some questions about the world of crypto from this week? Fill this form here and get a chance to have your question featured and answered by our experts in the next edition.

Disclaimer: This newsletter contains analysis and opinions, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. You can find all about us here 🙌

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, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

A weekly direct line connecting our readers with us to get your pressing questions on the latest crypto trends and news answered, every Thursday.

Submit your crypto queries through our form and our experts might take a shot at them in our upcoming editions.

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Global and crypto markets dumped and pumped in the last 72 hours as Trump's tariff showdown with China intensified just as he hit a 90-day pause on tariffs against other negotiating nations.

In the inaugural edition of News Rollups, we answer the top questions on our readers’ mind:

• Has Bitcoin really decoupled from traditional markets?

• Why Justin Sun feels First Digital Trust is a worse scandal than FTX?

• What to make of the Nigeria’s $81 billion court battle against Binance?

• How amid all the market chaos $30 million were dumped in $MELANIA memecoin?

• How Pump.Fun secretly restarted one of its most controversial features?

Let's dive into what matters and why.

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Q: Has Bitcoin truly decoupled from traditional markets yet?

Bitcoin as "digital gold" and an uncorrelated asset sounds compelling, but recent price action shows there’s room for a nuanced understanding.

While Bitcoin appeared to move independently during US President Donald Trump's Liberation Day tariff announcements, it subsequently followed the broader market's trajectory with each fall and rise, albeit with a slight delay.

Bitcoin held its range longer than Wall Street amid the announcements, leading to the narrative of it decoupling from the broader markets. But when it did crash, it slumped all the way below $75,000 - the level last seen only before Trump’s re-election.

Bitcoin did retrace back to above $82,000 temporarily, but when China retaliated with 84% tariffs on US goods on Tuesday, Bitcoin dropped again.

When Treasury yields spiked to 4.5% on April 8, suggesting a potential unwinding of the basis trade, Bitcoin suffered alongside other risk assets.

Bitcoin's correlation with traditional markets remains strong during crisis periods but shows increasing independence during calmer intervals - like it outperformed broader markets (+21% vs +1%) between November 6, 2024, and February 28, 2025.

The verdict - claims of decoupling are premature, despite occasional divergence, and maturation of an asset such as Bitcoin takes time.

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Q: Should you worry about Justin Sun's battle with First Digital Trust?

Tron founder Justin Sun last week accused First Digital Trust (FDT) of misappropriating $456 million from TUSD's custodial funds without client authorisation or knowledge. This rapidly devolved into a high-stakes battle with Sun declaring the case "ten times worse" than FTX and launching a $50 million bounty for whistleblowers.

FDT has denied these allegations. Calling them a "smear campaign" designed to damage a competing stablecoin issuer. The company announced plans to sue Sun for defamation and has filed an injunction with the Hong Kong High Court to prevent further statements.

First Digital CEO Vincent Chok defended his firm's actions, stating they acted purely as a custodian following client instructions, not as a fiduciary with independent decision-making power. "We're not asset managers and we don't claim to be," said Chok.

After Sun urged users to secure their assets from FDT, the company's FDUSD stablecoin briefly lost its dollar peg, falling to as low as $0.95. Meanwhile, TrueUSD's peg was only maintained after Sun provided a $500 million loan to Techteryx, TUSD's operator.

Why worry? If a dispute between business partners can threaten the stability of multiple stablecoins representing hundreds of millions in market value, how secure is the broader stablecoin ecosystem? As Congress advances legislation to regulate this critical market, this calls for clear standards for custody, reserves, and transparency.

The Crypto Comic 🎭

Dispatch Decoder: What is Basis Trade? 👨🏽‍🏫

The basis trade is a sophisticated arbitrage strategy used by hedge funds to profit from tiny price differences between Treasury bonds and futures contracts. Traders buy Treasury securities and simultaneously sell corresponding futures contracts, locking in a small profit from the price discrepancy.

Because the profit margins are minimal, funds typically use significant leverage, borrowing heavily to multiply their returns. This strategy is normally low-risk, but when many participants try to exit simultaneously — as happened this week when the 10-year Treasury yield spiked above 4.5% — it can create a cascading effect.

As yields rise (meaning bond prices fall), traders face margin calls, forcing them to sell their Treasury holdings. This additional selling drives yields even higher, triggering more margin calls in a dangerous feedback loop. A similar unwinding occurred in March 2020, requiring Federal Reserve intervention to stabilise markets.

This week's basis trade unwinding signals severe market stress as investors reassess risk amid escalating trade tensions.

Q: Why did Nigeria's $81-Bn legal battle with Binance get postponed?

Nigeria's tax evasion case against Binance hit a procedural roadblock last week for a comical reason. The exchange's attorney challenged the government's method of serving legal documents via email to Binance, which is headquartered abroad.

The Abuja federal high court adjourned the trial until April 30. Chukwuka Ikwuazom, a Binance attorney, argued that authorities must obtain formal permission to serve official documents abroad.

The government alleges the exchange owes $79 billion in damages and $2 billion in back taxes for operating without proper registration.

Why is Nigeria determined to recover the sum? The amount is roughly 20% of Nigeria's entire GDP.

When Binance dispatched executives Nadeem Anjarwalla and Tigran Gambaryan to negotiate crypto deals in the country last year, Nigerian authorities detained both men at Kuje prison, a maximum security facility typically reserved for terrorism and money laundering suspects. While Gambaryan was eventually released after nine months when his health deteriorated, Anjarwalla managed to escape the country and remains wanted by Nigerian authorities.

Under the Radar 🔎

Solana-based memecoin launchpad Pump.Fun quietly reintroduced its controversial livestreaming feature after pet threats and on-air chaos forced it to shut down last November.

Read: When Pump.fun Is No Longer Fun 🥵

The situation reached a tragic climax in February when a trader known as "MistaFuccYou" fatally shot himself during a livestream on X after losing money to a rug pull involving a Pump.Fun token. Now, the platform has reinstated the feature with a new moderation policy prohibiting content involving violence, harassment, and illegal activity.

Pump.Fun co-founder Alon Cohen announced the feature is being rolled out to just 5% of users with "industry standard moderation systems."

The platform’s attempt to reignite engagement through the feature that caused its greatest controversies at a time when the memecoin space and overall crypto market are going through a relative cool-down suggests a desperate play for survival.

That’s it for this week’s News Rollups.

Until next Thursday, stay curious.

PS: Got some questions about the world of crypto from this week? Fill this form here and get a chance to have your question featured and answered by our experts in the next edition.

Disclaimer: This newsletter contains analysis and opinions, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.

Token Dispatch is a daily crypto newsletter handpicked and crafted with love by human bots. You can find all about us here 🙌

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, not financial advice. Trading crypto involves substantial risk - your capital is at risk. Do your own research.