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There has been a lot of debate about whether crypto is for finance, or more than that.
My view is that, yes, crypto is for finance.
But also, finance is becoming much more expansive than is commonly understood.
There are three fundamental drivers. First, mass accessibility and participation in markets means that finance is increasingly intertwined with, and influenced by, culture. Second, that dynamic is enabled and accelerated by permissionless markets, which act as change agents, enabling a global user base to express new behaviors, and, in the process, pull regulators and institutions forward. Third, financial markets are evolving from discrete venues into programmable endpoints; they are becoming APIs with embedded economic data that produce real-time information that no other system can generate, is costly to fake, and can be used seamlessly by intelligent agents.
Mass participation changes who uses markets; permissionless innovation changes which markets exist; and the programmability of new markets opens up new design space for how we (and our agents) will use them.
Taken together, as all the world’s value becomes software, finance is undergoing a radical transformation that demands a much more expansive view of its end state.
Share Dialog
There has been a lot of debate about whether crypto is for finance, or more than that.
My view is that, yes, crypto is for finance.
But also, finance is becoming much more expansive than is commonly understood.
There are three fundamental drivers. First, mass accessibility and participation in markets means that finance is increasingly intertwined with, and influenced by, culture. Second, that dynamic is enabled and accelerated by permissionless markets, which act as change agents, enabling a global user base to express new behaviors, and, in the process, pull regulators and institutions forward. Third, financial markets are evolving from discrete venues into programmable endpoints; they are becoming APIs with embedded economic data that produce real-time information that no other system can generate, is costly to fake, and can be used seamlessly by intelligent agents.
Mass participation changes who uses markets; permissionless innovation changes which markets exist; and the programmability of new markets opens up new design space for how we (and our agents) will use them.
Taken together, as all the world’s value becomes software, finance is undergoing a radical transformation that demands a much more expansive view of its end state.
Towards a Billion Traders
In 2020, the vision of Variant's founding thesis on the Ownership Economy was to make a billion users owners: owners of their identity, money, data, and of the products and services they used every day. Today, user-ownership has been realized in a significant, but narrow set of software verticals, mostly financial in nature: store-of-value assets (BTC/ETH), decentralized blockchains, and financial markets (Solana, Uniswap, Morpho, Hyperliquid)—all of which we’re lucky to be investors in.
In hindsight, the 2020 thesis was correct about people wanting economic upside in the things they know and care about. But whereas I thought it would expand to ownership in all of the products you use every day, skeuomorphic to employee stock options, in reality the opportunity turned out to be skin in the game on anything you have conviction about. Today, trading is the broader, non-skeuomorphic way that users are participating in economic upside (and downside), and it turns out to be more immediate and expressive than ownership of one's digital identity, money, data, and platforms, at least for now.
Trading is often a gateway to broader forms of participation in markets. Many of the talented people I've met and worked with in crypto have followed some version of a common trajectory: from getting humbled on a moonshot token, to learning to manage risk as a trader, to becoming a more sophisticated, long-term investor. Even in losing, a gambler who gets wiped out and decides to only place bets on things they know becomes a trader. A trader who believes in something and increases their time horizon becomes an investor.
It's useful to think of this continuum of risk taking within Maslow's Hierarchy of Needs. Gambling and trading address lower-rung needs: security (hit a big lick to escape your economic situation)—and maybe (just maybe) community, like when WallStreetBets tries to stick it to Citadel, or you bet on your team with friends. Investing maps closer to the top of the hierarchy: self-actualization and purpose. Owning a home is the American Dream. Investing in a company is expressing belief in its future. But it's difficult to actualize that belief if your focus is on the lower rungs of the ladder.
Because of its lower duration and high volatility, trading purports to satisfy more immediate needs for more people. And because permissionless markets can be expressed for nearly everything, from derivatives to memes to political outcomes, access to economic upside (and downside) has never been wider. In many of these markets, lived experience can, at least briefly, be an edge. A kid who understands TikTok trends knows memes better than Citadel. A gamer who lives in a virtual economy knows it better than a gaming analyst.
The adage “invest in what you know” is increasingly possible today. As a result, market participation is no longer a specialized profession. It's a mass-participation culture with its own status games, memes, heroes, villains, subcultures and language. Because of their newfound expressivity and accessibility, financial markets are increasingly intertwined with culture. And culture, from trends to events to political outcomes, is increasingly expressed through markets.
We are seeing exponential expansion in global economic access through stablecoins, and on the other end of the spectrum, an expansion in financial risk-taking through trading and markets, towards one billion daily active traders.
Markets as Change Agents
In the 1960s, the average holding period for stocks was over 8 years. By 2020, that average had reduced to less than a year. The previous section describes where we are today: a world of mass market participation where trading has become a major artery for people trying to access economic upside. That world didn’t emerge entirely within the bounds of the legacy financial system. New markets have largely been built outside, often on purpose and out of necessity.
Leveraging new technology and free markets to force the hand of regulators and institutions is one of the most reliable patterns of how legacy systems adapt and evolve. As I wrote in the original thesis:
The history of protocol adoption fits a pattern: first, early adopters use new protocols to do things that were impossible before the new technology empowered them to do so. Very often, this new behavior involves breaking the rules. Then, a winning strategy for founders is to build products that make these new models more accessible to a wider audience.
A classic example I gave was BitTorrent, which was invented in 2003. It enabled streaming, and at its peak, piracy over the protocol represented one-third of all internet traffic. Later, Spotify productized streaming (and actually used BitTorrent under the hood, initially) by striking deals to offer the product compliantly.
Crypto has enabled the permissionless rewiring of value in the same way that BitTorrent rewired information. Polymarket ran offshore on crypto rails for years while prediction markets were banned in the U.S. Today, thanks to new regulatory clarity, they have a mobile app in the U.S. (and it's not onchain). Stablecoins similarly existed in regulatory limbo, first bootstrapping liquidity on offshore exchanges. Last year, the GENIUS Act brought them inside the system.
In 2017, ICOs enabled permissionless crowdfunding at a time when early-stage startup investment was off-limits. A hostile SEC then cracked down, exacerbating a problem that has only gotten worse: that the returns to technology innovation and growth are privately captured, with fewer opportunities for the public to participate in upside growth. But this year, Congress is working on market structure legislation in the CLARITY Act that would expressly allow founders to fundraise and share ownership broadly through public token sales.
Permissionless markets keep trying to “break the rules” to give people economic upside in privately owned companies. (Wouldn’t you like to own a piece of Claude or ChatGPT?)
Robinhood recently attempted to launch tokenized exposure to private companies like OpenAI and SpaceX on crypto rails in Europe, and filed with the SEC to bring a private market fund to U.S. retail investors. Startups are attempting to offer synthetic exposure to private companies through novel products.
This may be a path back to something more akin to the original Ownership Economy thesis, where users are, in fact, able to get economic exposure in the products and services they use every day. But as we’ve seen with other markets, forcing change in regulation can take time, and is often dependent on a scaled and proven market demand.
More immediately, I expect we will see many net-new markets take off, which begs the question of what the full design space of these new markets looks like. How are they different from what came before, and who, or what, are trading and consuming them?
Markets as APIs
What makes this moment different from prior waves of financial innovation is that two forms of expressivity in software are expanding simultaneously. Crypto provides the most powerful rails for new markets: permissionless creation, programmable settlement, composable liquidity, and global access, at a cost rapidly approaching zero. It is now possible to tokenize and trade things that were previously illiquid, inaccessible, or simply didn’t exist. At the same time, AI is making it possible to build, model, and automate things that were previously intractable. Together, they set up a combinatorial design space, where every price a market produces is something AI can act on, and every new thing AI can model is something a market can be used to price.
One could argue that intelligence is the ability to predict or make informed decisions. Markets and crypto provide the best mechanism for “prediction” that we know of. AI can use these prices to understand and model the future and to make decisions.
That design space is why markets are evolving from outputs to infrastructure. Over the last ten years, crypto built the underlying infrastructure to enable new markets to proliferate. Over the next ten years, markets will increasingly become infrastructure; endpoints for applications and agents to consume as inputs.
A conventional API returns stored data. As APIs, markets produce real-time data through adversarial competition among participants that are willing to risk capital on their beliefs. This makes markets more expressive than ordinary APIs; they don't just serve information, they also generate it. And as the information that markets generate is costly to produce, it’s also harder to fake.
Onchain markets are even better than traditional APIs because, by default, they are permissionless and composable (anyone can call them), global, and use a standardized interface.
Direct composition of markets into products is starting in the financial sector in what is known as the "DeFi mullet": fintech products with a familiar front-end built on DeFi back-end rails, like Morpho vaults.
Coinbase’s Borrow and Earn products give users a dynamic interest rate to pay or earn by pinging Morpho’s onchain lending market for quotes. Users get the utility without needing to see or understand the lending market dynamics underneath.
Further afield of financial services, Polymarket odds at the Golden Globes are a recent and literal example of this phenomena. The API serves real-time prices to be composed into an entertainment product (and the market correctly predicted 26 out of the 28 award winners).
As we tokenize more of the world's value and bring new markets onchain, this pattern can extend beyond fintech wrappers or odds on live events. While not onchain today, Apple's Clean Energy Charging is an illustrative mainstream example. In the U.S., when you plug in your phone, Apple uses real-time projections of grid carbon intensity to schedule charging for maximum energy and cost efficiency. You never see the underlying energy market, but Apple's product is calling an endpoint to get market data, consuming its signals as inputs to make a decision that makes the product better.
MetaDAO, a prediction-market powered crowdfunding platform, takes this idea further. When it faces a governance decision it creates two conditional markets: one that prices its token assuming a proposal passes, the other assuming the proposal fails. Whichever market prices higher determines the outcome: the proposal is automatically enacted or rejected. Instead of a vote, the DAO calls a market to make a decision, with participants risking capital on their beliefs about which future outcome is better. Here the underlying market isn’t just an input for decision making, but the decision mechanism itself.
If you assume all finance and markets are becoming programmable, in tandem with AI becoming more powerful, it's reasonable and exciting to entertain an expansionary view of what finance could look like in the end state. Price signals, prediction market outcomes, onchain flows, and more become inputs that any application or agent can read, interpret, and act on. And if an agent can earn one cent more than the cost of inference by creating or participating in a market, it's rational to do so. A billion active traders might be severely undershooting it when we count in agent consumption and participation in markets.
'Finance'
Finance is undergoing a transformation from a distinct vertical sector into a horizontal substrate. As markets become more expressive and accessible, finance is becoming embedded into culture, and culture itself is increasingly expressed through finance. Simultaneously, as markets become permissionless software, they accelerate their role as change agents, opening up even new opportunities for users to seek economic upside (and downside) in things they know and love. And, they'll want their agents to make their lives better by participating in markets too.
As markets become more programmable, finance is increasingly accessible as a new building block of information infrastructure. The most successful infrastructure becomes invisible, and finance is on the path to dissolve into the fabric of everything else.
That is why I am willing to entertain a hugely expansive view of what “finance” will look like in the end-state.
What calls will you make?
–
Thanks to Martti Kalliala, Emily Segal, Jake Chervinsky, Alana Levin, Daniel Barabander, Shreyas Hariharan, and Kayvon Tehranian for feedback.
All information contained herein is for general information purposes only. It does not constitute investment advice or a recommendation or solicitation to buy or sell any investment and should not be used in the evaluation of the merits of making any investment decision. It should not be relied upon for accounting, legal or tax advice or investment recommendations. You should consult your own advisers as to legal, business, tax, and other related matters concerning any investment. None of the opinions or positions provided herein are intended to be treated as legal advice or to create an attorney-client relationship. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by Variant. While taken from sources believed to be reliable, Variant has not independently verified such information. Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by Variant, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Variant (excluding investments for which the issuer has not provided permission for Variant to disclose publicly as well as unannounced investments in publicly traded digital assets) is available at https://variant.fund/portfolio. Variant makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. This post reflects the current opinions of the authors and is not made on behalf of Variant or its Clients and does not necessarily reflect the opinions of Variant, its General Partners, its affiliates, advisors or individuals associated with Variant. The opinions reflected herein are subject to change without being updated. All liability with respect to actions taken or not taken based on the contents of the information contained herein are hereby expressly disclaimed. The content of this post is provided “as is;” no representations are made that the content is error-free.
Towards a Billion Traders
In 2020, the vision of Variant's founding thesis on the Ownership Economy was to make a billion users owners: owners of their identity, money, data, and of the products and services they used every day. Today, user-ownership has been realized in a significant, but narrow set of software verticals, mostly financial in nature: store-of-value assets (BTC/ETH), decentralized blockchains, and financial markets (Solana, Uniswap, Morpho, Hyperliquid)—all of which we’re lucky to be investors in.
In hindsight, the 2020 thesis was correct about people wanting economic upside in the things they know and care about. But whereas I thought it would expand to ownership in all of the products you use every day, skeuomorphic to employee stock options, in reality the opportunity turned out to be skin in the game on anything you have conviction about. Today, trading is the broader, non-skeuomorphic way that users are participating in economic upside (and downside), and it turns out to be more immediate and expressive than ownership of one's digital identity, money, data, and platforms, at least for now.
Trading is often a gateway to broader forms of participation in markets. Many of the talented people I've met and worked with in crypto have followed some version of a common trajectory: from getting humbled on a moonshot token, to learning to manage risk as a trader, to becoming a more sophisticated, long-term investor. Even in losing, a gambler who gets wiped out and decides to only place bets on things they know becomes a trader. A trader who believes in something and increases their time horizon becomes an investor.
It's useful to think of this continuum of risk taking within Maslow's Hierarchy of Needs. Gambling and trading address lower-rung needs: security (hit a big lick to escape your economic situation)—and maybe (just maybe) community, like when WallStreetBets tries to stick it to Citadel, or you bet on your team with friends. Investing maps closer to the top of the hierarchy: self-actualization and purpose. Owning a home is the American Dream. Investing in a company is expressing belief in its future. But it's difficult to actualize that belief if your focus is on the lower rungs of the ladder.
Because of its lower duration and high volatility, trading purports to satisfy more immediate needs for more people. And because permissionless markets can be expressed for nearly everything, from derivatives to memes to political outcomes, access to economic upside (and downside) has never been wider. In many of these markets, lived experience can, at least briefly, be an edge. A kid who understands TikTok trends knows memes better than Citadel. A gamer who lives in a virtual economy knows it better than a gaming analyst.
The adage “invest in what you know” is increasingly possible today. As a result, market participation is no longer a specialized profession. It's a mass-participation culture with its own status games, memes, heroes, villains, subcultures and language. Because of their newfound expressivity and accessibility, financial markets are increasingly intertwined with culture. And culture, from trends to events to political outcomes, is increasingly expressed through markets.
We are seeing exponential expansion in global economic access through stablecoins, and on the other end of the spectrum, an expansion in financial risk-taking through trading and markets, towards one billion daily active traders.
Markets as Change Agents
In the 1960s, the average holding period for stocks was over 8 years. By 2020, that average had reduced to less than a year. The previous section describes where we are today: a world of mass market participation where trading has become a major artery for people trying to access economic upside. That world didn’t emerge entirely within the bounds of the legacy financial system. New markets have largely been built outside, often on purpose and out of necessity.
Leveraging new technology and free markets to force the hand of regulators and institutions is one of the most reliable patterns of how legacy systems adapt and evolve. As I wrote in the original thesis:
The history of protocol adoption fits a pattern: first, early adopters use new protocols to do things that were impossible before the new technology empowered them to do so. Very often, this new behavior involves breaking the rules. Then, a winning strategy for founders is to build products that make these new models more accessible to a wider audience.
A classic example I gave was BitTorrent, which was invented in 2003. It enabled streaming, and at its peak, piracy over the protocol represented one-third of all internet traffic. Later, Spotify productized streaming (and actually used BitTorrent under the hood, initially) by striking deals to offer the product compliantly.
Crypto has enabled the permissionless rewiring of value in the same way that BitTorrent rewired information. Polymarket ran offshore on crypto rails for years while prediction markets were banned in the U.S. Today, thanks to new regulatory clarity, they have a mobile app in the U.S. (and it's not onchain). Stablecoins similarly existed in regulatory limbo, first bootstrapping liquidity on offshore exchanges. Last year, the GENIUS Act brought them inside the system.
In 2017, ICOs enabled permissionless crowdfunding at a time when early-stage startup investment was off-limits. A hostile SEC then cracked down, exacerbating a problem that has only gotten worse: that the returns to technology innovation and growth are privately captured, with fewer opportunities for the public to participate in upside growth. But this year, Congress is working on market structure legislation in the CLARITY Act that would expressly allow founders to fundraise and share ownership broadly through public token sales.
Permissionless markets keep trying to “break the rules” to give people economic upside in privately owned companies. (Wouldn’t you like to own a piece of Claude or ChatGPT?)
Robinhood recently attempted to launch tokenized exposure to private companies like OpenAI and SpaceX on crypto rails in Europe, and filed with the SEC to bring a private market fund to U.S. retail investors. Startups are attempting to offer synthetic exposure to private companies through novel products.
This may be a path back to something more akin to the original Ownership Economy thesis, where users are, in fact, able to get economic exposure in the products and services they use every day. But as we’ve seen with other markets, forcing change in regulation can take time, and is often dependent on a scaled and proven market demand.
More immediately, I expect we will see many net-new markets take off, which begs the question of what the full design space of these new markets looks like. How are they different from what came before, and who, or what, are trading and consuming them?
Markets as APIs
What makes this moment different from prior waves of financial innovation is that two forms of expressivity in software are expanding simultaneously. Crypto provides the most powerful rails for new markets: permissionless creation, programmable settlement, composable liquidity, and global access, at a cost rapidly approaching zero. It is now possible to tokenize and trade things that were previously illiquid, inaccessible, or simply didn’t exist. At the same time, AI is making it possible to build, model, and automate things that were previously intractable. Together, they set up a combinatorial design space, where every price a market produces is something AI can act on, and every new thing AI can model is something a market can be used to price.
One could argue that intelligence is the ability to predict or make informed decisions. Markets and crypto provide the best mechanism for “prediction” that we know of. AI can use these prices to understand and model the future and to make decisions.
That design space is why markets are evolving from outputs to infrastructure. Over the last ten years, crypto built the underlying infrastructure to enable new markets to proliferate. Over the next ten years, markets will increasingly become infrastructure; endpoints for applications and agents to consume as inputs.
A conventional API returns stored data. As APIs, markets produce real-time data through adversarial competition among participants that are willing to risk capital on their beliefs. This makes markets more expressive than ordinary APIs; they don't just serve information, they also generate it. And as the information that markets generate is costly to produce, it’s also harder to fake.
Onchain markets are even better than traditional APIs because, by default, they are permissionless and composable (anyone can call them), global, and use a standardized interface.
Direct composition of markets into products is starting in the financial sector in what is known as the "DeFi mullet": fintech products with a familiar front-end built on DeFi back-end rails, like Morpho vaults.
Coinbase’s Borrow and Earn products give users a dynamic interest rate to pay or earn by pinging Morpho’s onchain lending market for quotes. Users get the utility without needing to see or understand the lending market dynamics underneath.
Further afield of financial services, Polymarket odds at the Golden Globes are a recent and literal example of this phenomena. The API serves real-time prices to be composed into an entertainment product (and the market correctly predicted 26 out of the 28 award winners).
As we tokenize more of the world's value and bring new markets onchain, this pattern can extend beyond fintech wrappers or odds on live events. While not onchain today, Apple's Clean Energy Charging is an illustrative mainstream example. In the U.S., when you plug in your phone, Apple uses real-time projections of grid carbon intensity to schedule charging for maximum energy and cost efficiency. You never see the underlying energy market, but Apple's product is calling an endpoint to get market data, consuming its signals as inputs to make a decision that makes the product better.
MetaDAO, a prediction-market powered crowdfunding platform, takes this idea further. When it faces a governance decision it creates two conditional markets: one that prices its token assuming a proposal passes, the other assuming the proposal fails. Whichever market prices higher determines the outcome: the proposal is automatically enacted or rejected. Instead of a vote, the DAO calls a market to make a decision, with participants risking capital on their beliefs about which future outcome is better. Here the underlying market isn’t just an input for decision making, but the decision mechanism itself.
If you assume all finance and markets are becoming programmable, in tandem with AI becoming more powerful, it's reasonable and exciting to entertain an expansionary view of what finance could look like in the end state. Price signals, prediction market outcomes, onchain flows, and more become inputs that any application or agent can read, interpret, and act on. And if an agent can earn one cent more than the cost of inference by creating or participating in a market, it's rational to do so. A billion active traders might be severely undershooting it when we count in agent consumption and participation in markets.
'Finance'
Finance is undergoing a transformation from a distinct vertical sector into a horizontal substrate. As markets become more expressive and accessible, finance is becoming embedded into culture, and culture itself is increasingly expressed through finance. Simultaneously, as markets become permissionless software, they accelerate their role as change agents, opening up even new opportunities for users to seek economic upside (and downside) in things they know and love. And, they'll want their agents to make their lives better by participating in markets too.
As markets become more programmable, finance is increasingly accessible as a new building block of information infrastructure. The most successful infrastructure becomes invisible, and finance is on the path to dissolve into the fabric of everything else.
That is why I am willing to entertain a hugely expansive view of what “finance” will look like in the end-state.
What calls will you make?
–
Thanks to Martti Kalliala, Emily Segal, Jake Chervinsky, Alana Levin, Daniel Barabander, Shreyas Hariharan, and Kayvon Tehranian for feedback.
All information contained herein is for general information purposes only. It does not constitute investment advice or a recommendation or solicitation to buy or sell any investment and should not be used in the evaluation of the merits of making any investment decision. It should not be relied upon for accounting, legal or tax advice or investment recommendations. You should consult your own advisers as to legal, business, tax, and other related matters concerning any investment. None of the opinions or positions provided herein are intended to be treated as legal advice or to create an attorney-client relationship. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by Variant. While taken from sources believed to be reliable, Variant has not independently verified such information. Any investments or portfolio companies mentioned, referred to, or described are not representative of all investments in vehicles managed by Variant, and there can be no assurance that the investments will be profitable or that other investments made in the future will have similar characteristics or results. A list of investments made by funds managed by Variant (excluding investments for which the issuer has not provided permission for Variant to disclose publicly as well as unannounced investments in publicly traded digital assets) is available at https://variant.fund/portfolio. Variant makes no representations about the enduring accuracy of the information or its appropriateness for a given situation. This post reflects the current opinions of the authors and is not made on behalf of Variant or its Clients and does not necessarily reflect the opinions of Variant, its General Partners, its affiliates, advisors or individuals associated with Variant. The opinions reflected herein are subject to change without being updated. All liability with respect to actions taken or not taken based on the contents of the information contained herein are hereby expressly disclaimed. The content of this post is provided “as is;” no representations are made that the content is error-free.
DAOs 2.0
In 2014, Vitalik defined a DAO as follows:"an entity that lives on the internet and exists autonomously, but also heavily relies on hiring individuals to perform certain tasks that the automaton itself cannot do…"
DAOs 2.0
In 2014, Vitalik defined a DAO as follows:"an entity that lives on the internet and exists autonomously, but also heavily relies on hiring individuals to perform certain tasks that the automaton itself cannot do…"
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