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    3. From Web3 to AI: Why This Group Always Hits the Next Trend

    From Web3 to AI: Why This Group Always Hits the Next Trend

    By: foresightnews.pro|2026/08/17 13:03:09
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    Understanding the right technological direction and making money from it are not the same thing. They are not good at predicting answers; rather, they are accustomed to placing bets before the answers emerge.


    On August 16, American payment giant Stripe announced the acquisition of AI model aggregation platform OpenRouter for over $7 billion—just three months ago, the company's financing valuation was only $1.3 billion, marking a fivefold increase in just one quarter.


    OpenRouter's founder, Alex Atallah, achieved something similar last time with the NFT trading platform OpenSea.


    This is not the first time he has hit the mark so accurately. When he co-founded OpenSea with Devin Finzer in 2018, the term NFT had not yet entered the public consciousness; by the time he founded OpenRouter in 2023, the issue of "too many AI models and developers needing a unified interface" had not yet been widely recognized in the industry. In both instances, he laid the groundwork before the market reached a consensus.


    Among this group of individuals emerging from Web3, nearly everyone is repeating the same action.


    Where Did They Get Ahead?


    The problem OpenSea addressed was the extreme fragmentation of NFT trading, scattered across various independent platforms without a unified entry point. This judgment was counter-consensus in 2018—at that time, the entire NFT market's daily trading volume might have been less than tens of thousands of dollars.


    The problem OpenRouter addresses is the explosive growth of AI models, with inconsistent interface standards locking developers into single suppliers. This judgment was also counter-consensus in 2023—most developers at that time assumed that "choosing a single model supplier to the end" was the normal state.


    In both cases, Atallah was not solving a problem that had already been validated; instead, he anticipated that "fragmentation would eventually be aggregated" and built the bridge in advance. When others realized they needed to cross the river, the bridge was already there. Stripe's willingness to pay $7 billion was not for an API gateway but for the validated foresight of having built the bridge ahead of time.


    They Excel at Securing Entry Points


    Kris Marszalek, co-founder and CEO of cryptocurrency exchange Crypto.com, took a different path, but the core remains the same.


    In April 2025, he spent $70 million to purchase the domain AI.com using cryptocurrency, setting a record for publicly disclosed domain transactions. On the surface, this appears to be an expensive domain transaction, but looking back at Crypto.com’s history, it aligns perfectly with Marszalek’s consistent approach—spending heavily on domain names, securing stadium naming rights, and buying Super Bowl ads, all fundamentally aimed at securing user entry points.


    In the past, users opened exchanges to buy coins; in the future, users may open AI Agents to book flights, manage emails, or complete payments. Marszalek is not betting on a URL but on who will become the new digital entry point once AI transitions from "answering questions" to "executing tasks for users"—this judgment was also ahead of the market, as most were still discussing the usability of chat boxes while he was already securing a nameplate for an unformed track.


    From Web3 to AI, he did not change his competitive approach; he simply shifted his experience of competing for wallets, exchanges, and traffic entry points to the Agent entry point.


    Not the First Time Doing This


    If Atallah and Marszalek represent this migration, then Emad Mostaque, founder of open-source AI company Stability AI, actually walked this path even earlier.


    Before entering AI, he had long focused on Bitcoin and Ethereum, and in 2019, he worked on a project called Symmitree, aiming to lower the barriers for impoverished areas to access digital technology through blockchain, but failed because hospitals, governments, and tech companies were unwilling to open their data. This failure did not deter him; instead, it led him to conclude that AI models would inevitably move towards an open-source versus closed-source route.


    When he released the open-source image generation model Stable Diffusion in 2022, the mainstream narrative in the industry was still that "top AI models must be controlled by a few giants," and this logic had not been truly broken. What Stable Diffusion did was highly similar to some early Web3 concepts: opening capabilities that were originally concentrated in a few institutions to developers and communities as much as possible. The model could be downloaded, developers could make secondary developments, and communities could continue to build around the model—he truly broke the moat of commercial closed-source models for the first time.


    This indicates that being "early to the scene" is not a coincidence that emerged only in this AI cycle; it is a behavioral pattern that this group has repeated at least twice. And this pattern soon will not only belong to the founders.


    -- Price

    --

    Two Types of People Emerging from the Same Disappeared Institution


    Avital Balwit, the current CEO office director at Anthropic, has a different version of the story.


    She previously worked at the FTX Future Fund, funded by SBF, responsible for screening and evaluating long-term projects that had not yet been recognized by the mainstream but could impact the future of humanity. AI safety was one of the few areas that received significant attention at that time (FTX had invested $580 million in Anthropic). The fund ultimately disappeared with the collapse of FTX, but the training of "anticipating which fields will become the next key variables" did not vanish. Balwit later joined Anthropic, becoming an important decision-maker alongside CEO Dario Amodei.


    Leopold Aschenbrenner, also from the FTX Future Fund, took a different route.


    He joined OpenAI's "super alignment" team and subsequently became one of the most watched young researchers in the AI circle with his 165-page essay "Situational Awareness," being dubbed the "AI new stock god" in the investment circle for betting early on the AGI wave.


    One entered the highest levels of an AI company, another entered the AI investment market, and a once-bankrupt institution produced completely different types of people for the AI industry. The significance of this is greater than "FTX once invested in Anthropic"; it shows that the Web3 bull market left behind not only protocols, exchanges, and tokens but also a group of talents who have experienced rapid growth, capital frenzy, and industry collapse—they are familiar with an environment where technology is not yet mature, rules are not yet defined, but capital has already begun to bet. AI has just entered such a stage.


    Judged the Direction Correctly, but...


    Aschenbrenner used the fame of "Situational Awareness" to raise funds for a hedge fund of the same name, achieving a net return of over 439% from July 2024 to June this year, with the scale once soaring to $45 billion, proving that his judgment on the AGI direction was indeed early and correct.


    However, in July this year, the Situational Awareness fund, heavily leveraged at 400% in semiconductor and AI infrastructure stocks, fell over 35% in a single month. Goldman Sachs, JPMorgan Chase, and Bank of America simultaneously issued margin calls, forcing him to sell about $16 billion of public holdings at around a 10% discount to hedge fund giant Citadel (founded by Ken Griffin), with the $45 billion dropping to only about $10 billion within a month.


    A person who can accurately judge the long-term trends of AI may still encounter severe failures in the short-term capital market—this is not contradictory. Understanding the right technological direction and making money from it are not the same thing. Judgment is responsible for answering "what will happen," while leverage and position management are responsible for answering "how much to bet and whether one can hold out until verification day"—these are two completely independent abilities; the former is a shared talent of this group, while the latter is the real variable that determines winning or losing. The experience of Stability AI also illustrates the same principle: those who first saw the potential of open-source AI do not necessarily become the final commercial winners—Mostaque himself also left the CEO position in early 2024 due to internal disputes.


    Thus, they seem not to be better at predicting answers but rather more accustomed to placing bets before the answers have emerged.


    What Is Truly Being Transferred


    The real capabilities that this group brings from Web3 to AI can be broken down into three specific sensitivities:


    The first is sensitivity to infrastructure gaps—when NFTs exploded, Atallah saw the trading infrastructure; after the explosion of large models, he saw the routing and aggregation between models.


    The second is sensitivity to new entry points—Crypto.com is securing trading and user entry points, while AI.com is securing entry points for the Agent era.


    The third is sensitivity to opportunities before consensus formation—when the FTX Future Fund researched AI safety, AI had not yet become today’s mainstream capital narrative; when Stable Diffusion was launched, open-source models were far from being as popular as they are today.


    These three sensitivities point to the same thing: they are not predicting a specific trend but identifying what the next market will lack.


    Web3 has long placed this group in an environment where rules are not yet mature, business models are constantly rewritten, and technology and finance are highly intertwined, forcing them to repeatedly experience the same complete cycle—concept emergence, capital influx, infrastructure explosion, business model competition, bubble burst, and remaining talents seeking the next table. When AI enters a similar stage, they already know where to look.


    Aschenbrenner's liquidation precisely confirms the boundaries of this capability: it can tell you where the direction is but will not decide how much effort you should put into betting on that direction.


    AI has not yet completed its first round of reconstruction, and the real opportunities often do not appear after everyone sees them. The next batch of industry changers may have already begun to look for the next blank space that has not yet formed a consensus.

    This content is provided for general informational purposes only and doesn't constitute financial, investment, legal, or tax advice. Any events, rewards, online promotions, or related information mentioned herein should not be considered a recommendation, solicitation, or invitation to purchase, sell, trade, or otherwise deal in any crypto assets. Crypto assets are highly volatile and may result in loss. The availability of WEEX services, products, and related events may vary by region. You are responsible for ensuring that your participation is in accordance with applicable local laws and regulations.

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    Contents

    Where Did They Get Ahead?
    They Excel at Securing Entry Points
    Not the First Time Doing This
    ANTHROPIC
    Two Types of People Emerging from the Same Disappeared Institution
    What Is Truly Being Transferred

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