Variant Founder: Everything is a Market, the Endgame of Finance is 'Invisible'

marsbitPublished on 2026-02-23Last updated on 2026-02-23

Abstract

Jesse Walden, founder of Variant Fund, argues that crypto is fundamentally about finance—but in a radically expanded sense. He identifies three core drivers reshaping finance: mass participation, permissionless markets, and programmable endpoints. Mass participation is lowering barriers, intertwining finance with culture as trading becomes a form of expressive, accessible engagement. Permissionless innovation allows new markets to emerge outside traditional systems, forcing regulatory evolution—as seen with prediction markets, stablecoins, and ICOs. Programmable markets, combined with AI, are evolving from outputs into infrastructure. Markets generate real-time, hard-to-fake data that AI and applications can consume as APIs, enabling new products and automated decision-making. Ultimately, finance is transitioning from a vertical industry to a horizontal, invisible infrastructure layer embedded into the fabric of culture and technology.

Author: Jesse Walden, Founder of Variant

Compiled by: Yuliya, PANews

Editor's Note: Variant Fund founder Jesse Walden presents the forward-looking view that "everything is a market" in this article, arguing that cryptocurrency is expanding the boundaries of finance into the cultural realm, becoming a horizontal infrastructure layer. The article explores the three core drivers—mass participation, permissionless innovation, and market programmability—to discuss how finance is evolving into a ubiquitous infrastructure, and paints a future vision of finance becoming invisible as crypto technology integrates with artificial intelligence.

Full text below:

There has been much debate about whether cryptocurrency is purely for finance or has a grander purpose. My view is: yes, cryptocurrency is for finance. But the key point is that the connotation of finance is becoming much broader than commonly understood.

Behind this transformation lie three fundamental drivers:

  • Mass Participation: As market access barriers lower, finance is increasingly intertwining with and being deeply influenced by culture.

  • Permissionless Markets: This force acts as an agent of change, allowing global users to exhibit new behavioral patterns and, in the process, forcing regulators and traditional institutions to evolve.

  • Programmable Endpoints: Financial markets are evolving from discrete venues into APIs. They embed economic data, generate real-time information that other systems cannot produce and is extremely difficult to fake, and are seamlessly available for use by AI Agents.

Mass participation changes who uses markets; permissionless innovation changes which markets can exist; and the programmability of new markets opens up a new design space for how we (and AI agents) use them.

In summary, as value in the world becomes increasingly software-based, finance is undergoing a radical transformation, requiring us to adopt a more expansive perspective on its endgame.

Towards a Billion Traders

In 2020, Variant proposed the vision of the "Ownership Economy" at its inception, aiming to make a billion users become owners: owning their identity, funds, data, and the products and services they use daily. Today, user ownership has been realized in some important but vertical software areas, primarily focused on financial attributes: such as store-of-value assets (BTC/ETH), decentralized blockchains, and financial markets (Solana, Uniswap, Morpho, Hyperliquid)—we are fortunate to be investors in these projects.

In hindsight, the 2020 thesis was correct: people want economic upside in things they understand and care about. But I originally thought this would extend to all products users engage with daily, similar to employee stock options; however, the opportunity turned out to be making a "stake" in anything you have conviction in.

Today, "trading" has become a broader, non-skeuomorphic way for users to participate in economic upside (and downside). It turns out that trading provides more immediate and expressive feedback compared to owning digital identity, money, data, or platforms.

Trading is often the gateway to participating in broader markets. Many of the talented people I've met in crypto follow a similar growth trajectory:

  • Learning a lesson on a volatile altcoin;

  • Learning to manage risk like a trader;

  • Eventually becoming a more mature long-term investor.

Even failed experiences are meaningful: a gambler who loses everything becomes a trader if they decide to only bet on what they understand; a trader becomes an investor if they develop conviction and extend their time horizon.

We can view this continuum of risk-taking through the lens of Maslow's hierarchy of needs:

  • Gambling and trading satisfy lower-level needs: security (escaping economic hardship by making a big win), or a sense of belonging (like WallStreetBets trying to fight Citadel, or you and your friends betting on a team).

  • Investing is closer to self-actualization and purpose at the top. Owning a home is the American Dream; investing in a company is expressing belief in its future. But it's hard to achieve this conviction if your attention is still focused on lower-level needs.

PANews Note: WallStreetBets (WSB) is a famous subreddit known as a hub for retail investors famous for high-risk, aggressive investing, and meme stock trading. It is renowned for encouraging the use of leveraged options trading and pursuing short-term, high returns, gaining global financial notoriety in 2021 for orchestrating the GameStop (GME) short squeeze. Citadel is a top-tier hedge fund and financial services company, known for its rigorous risk control and high returns, and is one of the most influential financial giants on Wall Street.

Due to short timeframes and high volatility, trading can satisfy more urgent needs for more people. And, because permissionless markets can exist for almost anything—from derivatives to memes to political outcomes—the channels for people to access economic gains have never been broader.

In many of these markets, life experience can (at least briefly) become an advantage. A kid who understands TikTok trends understands memes better than Citadel; a player living in a virtual economy understands the game better than a game analyst.

The old adage "invest in what you know" is becoming increasingly feasible today. The result is that market participation is no longer a professional career but a mass-participation culture with its own status games, memes, heroes, villains, subcultures, and language. Due to this newfound expressiveness and accessibility, financial markets are increasingly intertwining with culture. And culture—from trends to political events—is increasingly expressed through markets.

(Image: Balenciaga S2023 fashion show at the New York Stock Exchange)

We are witnessing exponential expansion of global economic access through stablecoins; at the other end of the spectrum, financial risk-taking through trading and markets is also expanding, moving towards a scale of a billion daily active traders.

Markets as Agents of Change

In the 1960s, the average holding period for stocks was over 8 years. By 2020, this average had fallen to less than a year. This is the world we live in today: a mass-participation market where trading has become the main artery for people trying to capture economic gains.

This world hasn't entirely emerged within the boundaries of the traditional financial system. New markets have been built primarily outside, often intentionally and out of necessity. Leveraging new technology and free markets to pressure regulators and institutions is one of the most reliable patterns for the adaptation and evolution of traditional systems.

As I wrote in the original thesis:

"The history of protocol adoption follows a pattern: first, early adopters use the new protocol to do things that were impossible before the new technology enabled them. This new behavior often involves breaking the rules. Then, the winning strategy for founders is to build products that make these new patterns accessible to a broader audience."

A classic example is BitTorrent, invented in 2003. It enabled streaming, and at its peak, piracy via this protocol accounted for a third of total internet traffic. Later, Spotify productized streaming by striking compliant deals (and actually used BitTorrent technology underneath initially).

Cryptocurrency is doing to value what BitTorrent did to information: remaking it permissionlessly.

  • Prediction Markets: Polymarket operated for years on offshore crypto rails when prediction markets were banned in the US. Today, thanks to new regulatory clarity, they have a mobile app in the US (though not on-chain).

  • Stablecoins: Similarly survived in a regulatory gray area, initially bootstrapping liquidity on offshore exchanges. Last year, the GENIUS bill brought them inside the system.

  • ICOs & Fundraising: In 2017, ICOs enabled permissionless crowdfunding when early-stage venture investment was restricted. A hostile SEC subsequently cracked down, but this highlighted a problem: the returns from technological innovation and growth were captured privately, with diminishing opportunities for public participation in the upside. But this year, Congress is working on market structure legislation in the CLARITY Act, explicitly allowing founders to raise funds broadly via public token sales and share ownership.

Permissionless markets constantly try to "break the rules," allowing people to access the economic gains of private companies (wouldn't you want to own a piece of Claude or ChatGPT?). Robinhood recently tried to launch tokenized exposure to private companies like OpenAI and SpaceX on crypto rails in Europe and applied to the SEC to bring private market funds to US retail investors. Startups are trying to offer synthetic exposure to private companies through novel products.

This could be a path back to the original "Ownership Economy" thesis, where users actually get economic exposure to the products and services they use daily. But as we've seen with other markets, forcing regulatory change takes time and often relies on scaled and proven market demand.

More directly, I expect we will see many new, net-add markets take off, which raises the question: what is the full design space of these new markets? How are they different from previous ones? And who, or what, is trading and consuming them?

Markets as APIs

What makes this moment different from previous waves of financial innovation is the simultaneous expansion of two representations in software:

  • Cryptocurrency (Crypto): Provides the most powerful rails for new markets—permissionless creation, programmable settlement, composable liquidity, and global access, with costs rapidly approaching zero. Now, we can tokenize and trade things that were previously illiquid, inaccessible, or simply didn't exist.

  • Artificial Intelligence (AI): Makes it possible to build, model, and automate things that were previously unmanageable.

Crypto + AI creates a combinatorial design space: every price generated by a market is a signal an AI can act on, and every new thing an AI can model is an object a market can use to price.

Arguably, intelligence is the ability to predict or make informed decisions. Markets and crypto provide the best "prediction" mechanisms we know. AI can use these prices to understand and simulate the future and make decisions.

This design space is why markets are evolving from "outputs" to "infrastructure." The last decade, crypto built the underlying infrastructure enabling an explosion of new markets. The next decade, markets will increasingly become infrastructure themselves; endpoints consumed as inputs by applications and agents.

(Image: Central de Abasto food wholesale market in Mexico City)

Traditional APIs return stored data. As APIs, markets generate real-time data through adversarial competition between participants willing to risk capital on their convictions. This makes markets more expressive than ordinary APIs; they don't just provide information, they generate it. And because the information generated by markets is costly to produce, it is also harder to fake.

On-chain markets are even superior to traditional APIs because, by default, they are permissionless and composable (anyone can call them), globalized, and use standardized interfaces.

Composing markets directly into products has already begun in finance, known as the "DeFi Mullet": fintech products with familiar front-end experiences built on DeFi back-end rails, like Morpho vaults. Coinbase's borrow and earn products offer users dynamic interest rates, which are paid or earned by querying Morpho's on-chain lending markets. Users enjoy these features without needing to understand the underlying lending market dynamics.

Beyond financial services, Polymarket's odds for the Golden Globes are a recent intuitive example of this phenomenon. The API provides real-time prices, composed into entertainment products (the market accurately predicted 26 out of 27 winners).

As we tokenize more of the world's value and bring new markets on-chain, this pattern will expand beyond fintech wrappers or live event odds. Although not currently on-chain, Apple's "Clean Energy Charging" is an illustrative mainstream example. In the US, when you plug in your phone to charge, Apple uses real-time predictions of grid carbon intensity to schedule charging times for maximum energy and cost efficiency. You never see the underlying energy market, but Apple's product is calling an endpoint for market data, using its signal as an input to make decisions and optimize the product.

MetaDAO, a crowdfunding platform powered by prediction markets, takes this idea further. When faced with a governance decision, it creates two conditional markets: one assuming the token price if the proposal passes, another if it fails. Whichever market price is higher determines the outcome: the proposal automatically takes effect or is rejected. The DAO no longer decides by voting but calls upon markets to make decisions, with participants betting real money on the future outcome they believe is better. Here, the underlying market is not just an input to the decision but the decision mechanism itself.

If you assume all finance and markets are becoming programmable while AI is becoming more powerful, then holding an expansive view of finance's endgame is reasonable and exciting. Price signals, prediction market outcomes, on-chain capital flows, etc., will become inputs that any application or agent can read, interpret, and act upon. If an agent can earn a penny more than its inference cost by creating or participating in a market, it becomes rational to do so.

When we factor in the consumption and market participation of AI agents, "a billion active traders" might be a severe underestimate of the scale of the future.

The Endgame of Finance

Finance is undergoing a transformation from a unique vertical industry into a horizontal foundational layer.

As markets become more expressive and accessible, finance is embedding itself into culture, and culture itself is increasingly expressed through finance. Simultaneously, as markets become permissionless software, they accelerate their role as agents of change, opening new opportunities for users seeking economic upside (and downside) in things they understand and love. And users will also want their AI agents to participate in markets to improve their lives.

As markets become more programmable, finance is becoming increasingly ubiquitous as a new building block of information infrastructure. The most successful infrastructure is often invisible, and finance is on a path to being woven into the fabric of everything.

This is why I'm willing to hold an extremely grand, expansive perspective on the endgame of "finance."

Related Questions

QWhat are the three fundamental drivers behind the expansion of finance's meaning according to Jesse Walden?

AThe three fundamental drivers are: 1) Mass participation, as lower market access barriers intertwine finance with culture; 2) Permissionless markets, which act as change agents allowing global users to exhibit new behaviors; 3) Programmable endpoints, where financial markets evolve from discrete venues into APIs embedded with economic data.

QHow does the author describe the evolution of a participant's journey in the crypto space?

AThe author describes a common trajectory: starting with a lesson from a volatile altcoin, learning to manage risk like a trader, and eventually maturing into a long-term investor. Even failed experiences are meaningful, transforming a gambler into a trader who bets on what they know, and then into an investor with conviction and a longer time horizon.

QWhat role do permissionless markets play in driving regulatory and institutional change?

APermissionless markets, often built outside traditional financial systems, act as change agents by allowing new behaviors that 'break the rules.' This forces regulators and traditional institutions to adapt and evolve. Examples include prediction markets (Polymarket), stablecoins, and ICOs, which eventually lead to new legislation and regulatory clarity after demonstrating proven market demand.

QHow does the combination of Crypto and AI create a new design space for markets?

ACrypto provides the infrastructure for permissionless, programmable, and globally accessible markets, while AI enables the modeling and automation of previously unmanageable things. This combination creates a design space where every price generated by a market becomes actionable data for AI, and every new thing AI can model becomes an object that markets can price. Markets evolve from outputs to infrastructure, serving as APIs that applications and AI agents can consume.

QWhat is the ultimate vision for the future of finance as presented in the article?

AThe ultimate vision is that finance is transitioning from a distinct vertical industry into a horizontal infrastructure layer that becomes 'invisible.' It is increasingly embedded into culture and expressed through it, driven by mass participation and permissionless innovation. As markets become more accessible and programmable, finance will integrate into the fabric of everything, serving as a universal information infrastructure for both humans and AI agents to consume and act upon.

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Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

304 Total ViewsPublished 2025.01.14Updated 2025.01.14

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