The long game for crypto
Are non-financial use cases dead? Why this conclusion misunderstands the stage we’re in.
It’s fashionable right now to declare that “non-financial use cases of crypto are dead.” Some people also claim that read write own has failed. These conclusions misunderstand both the thesis and the stage we’re in.
We are clearly in the financial era of blockchains. But the core idea was never that every crypto application would emerge all at once, or that finance wouldn’t come first. The core idea was — and remains — that blockchains introduce a new primitive: the ability to coordinate people and capital at internet scale, with ownership embedded directly into the system. (And increasingly, to coordinate AI agents too.)
Finance is the most natural place for that primitive to prove itself, which is why we’ve often cited it first among examples for productive uses of tokens. Finance isn’t separate from the broader thesis; it’s part of it. It’s the foundation and proving ground for everything else.
This belief has informed our work at a16z crypto from the very beginning. Many of our investments have been explicitly financial: Coinbase, Maker, Compound, Uniswap, and Morpho among them. “Blockchain networks can make financial infrastructure a public good, upgrading the internet from handling bits to handling money,” as I wrote in my book. We expected finance to matter early and continue to expect, sooner or later, other categories to develop alongside it.
We play the long game at a16z and a16z crypto: Our funds are structured with 10+ year horizons because building new industries takes time.
The order of operations matters
So why haven’t non-financial use cases taken off yet?
First, the order of operations matters. Infrastructure and distribution tend to precede new categories of applications. The internet didn’t begin with social media, streaming, or online communities; it began with packet switching, TCP/IP, and basic connectivity. Only once hundreds of millions of people were online did entirely new cultural and economic categories emerge.
Crypto is likely no different. It’s plausible that we need hundreds of millions of people onchain through financial applications, such as payments, stablecoins, savings, and DeFi, before we see meaningful adoption in categories like media, gaming, AI, or other areas that may be further out. Many applications depend on wallets, identity, liquidity, and trust already being in place.
There are other factors too. One of crypto’s core benefits is the ability to give communities ownership via tokens. But years of scams, extractive behavior, and regulatory attacks severely eroded trust in tokens. This has likely contributed to the recent market downturn as well. It’s hard to build a genuine community of owners in an environment saturated with cynicism.
Policy as the missing piece
That’s why we’ve worked for 5+ years pushing for a clear regulatory framework around tokens. Good policy does two things at once: it gives builders a clear roadmap, and it establishes risk-based guardrails that protect consumers and build trust in the market. Market structure legislation like the CLARITY Act would introduce disclosure and transparency standards that guard against rug pulls and self-dealing — standards that are routine in other markets but have long been missing in crypto.
When it comes to emerging technologies, progress on the policy front is often slow and incremental…until, suddenly, it isn’t. Much of our work over the years, including my book, has been focused on contributing to that groundwork: explaining the benefits of crypto and blockchains to policymakers and broader audiences, and offering a grounded way to think about how this technology could evolve over time. We frequently hear that this framing has been useful to policymakers in DC. Years of education, debate, and refinement can accumulate quietly in the background, and then surface all at once when a political or institutional window opens.
The reaction to GENIUS strongly validated this theory. Almost overnight, stablecoins went from suspect to legitimate in the eyes of finance, technology, and government. That shift looked sudden, but it was the product of years of work by builders, policymakers, and advocates coming together at the right moment. I expected a positive response, but the speed and magnitude of the technology’s adoption surprised even me. It makes me optimistic about market structure legislation which, at a high level, does for other categories of tokens what GENIUS did for stablecoins.
What the long game looks like
Big things take time. The breakthroughs we’re seeing in AI today are due to the hard work of brilliant people over many decades. (The first paper on neural networks was published in 1943.) The internet dates back to the 1960s, and the commercial internet was only possible because of visionary builders and thoughtful policy actions in the 1990s. Building new technological systems is a long game, and this is what the long game looks like in practice: prolonged periods of groundwork followed by sharp inflection points.
If you want to work in a more mature industry, that’s fine. If you want to build a new one from scratch, it can be messy and frustrating, but it’s important work.
The messy years are what make the obvious years possible.
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This post nails why experiences like trying to ingest 10M+ Florida property records on-chain (as open, verifiable RWAs) ended up “breaking” a general-purpose chain—we became its largest data writer by far, gas costs skyrocketed, and artificial caps had to kick in. It wasn’t a flaw in the tech; it highlighted that we’re still in those messy foundational years where finance builds the onchain population, liquidity, and trust layers first. Non-financial (but deeply economic) use cases like massive-scale real-world asset data hit the current infrastructure’s limits hard because it wasn’t architected for that volume or pattern.
The order-of-operations point resonates strongly: overload the primitives before they’re ready for broader categories, and you get exactly these revealing “failures.” Treating them as groundwork rather than dead ends is what makes the obvious years possible. Curious how others see policy shifts (like market structure legislation) helping bridge from the financial proving ground to things like RWAs at true scale.
Grateful for the framing—it’s permission to keep building through the mess.
Soofi
I’ve spent more than 25 years operating inside decentralized communities. I’m living full-time in one right now. I’m not talking about theory. I’m talking about how these systems actually work when people have to live inside them every day.
What I’ve seen over and over is this: decentralized systems don’t fail because the technology isn’t powerful enough. They fail because they don’t have the basic cultural infrastructure people need to participate meaningfully and to coordinate without friction.
We keep building things in the wrong order.
In tech, we’re trained to build downstream. Downstream means apps, features, interfaces, things you can ship fast. That works when there’s already structure in place. It works when identity is clear, coordination is handled, and people already know how to participate.
In decentralized ecosystems, it’s the missing layer. And what you’re building isn’t the app. The thing you’re building is the environment people have to operate inside. If that environment doesn’t support participation and coordination, everything built on top of it stays fragile.
Upstream work is different from downstream work. It’s not about speed. It’s not about features. It’s about answering basic questions first. How do people enter the system? How do they know where they belong? How do they coordinate without a central authority? How does work continue when one person leaves? How do people stay involved without burning out?
These are not soft questions. They are design problems.
But builders are conditioned to work downstream. They’re rewarded for shipping, not for building the systems that make participation possible. So cultural infrastructure gets ignored. It doesn’t look like a product. It doesn’t have immediate payoff. It gets treated like overhead.
The result is predictable. Participation stays shallow. When incentives change, people leave. Context disappears. Trust breaks. The system has to start over.
This keeps happening because we don’t treat cultural infrastructure as real infrastructure.
As a creator, I don’t see technology as just a tool. I see it as a medium. And mediums need structure before expression. You can’t build culture on top of chaos and expect it to last.
If we want decentralized systems that actually work, we have to build upstream first. We have to design for participation and coordination before we scale anything. And we have to understand that culture isn’t decoration. It’s what makes systems usable, stable, and real for the people inside them.
Until that changes, we’re going to keep building the same systems that look exciting at first and fall apart later.