Phil Jacobson has published a detailed reflection on Vector and on why fomo managed to take a similar product thesis much further.
Jacobson wrote that his team built Vector several years ago as a mobile social trading app for onchain assets. The business scaled quickly from zero, eventually reaching peak daily trading volume of more than $20 million and roughly $1 billion in cumulative volume. In the first months after launch, as growth accelerated, retention looked more like that of a social network than a conventional trading app, which was exactly what the team had set out to build.
Still, the company was sold to Coinbase at the end of 2025. Since then, Jacobson said he has been watching how fomo took a product idea that resembled Vector’s and pushed it in another direction. He said fomo broke beyond CT, or Crypto Twitter, brought large numbers of new users into the onchain world, and has recently topped $100 million in daily volume.
He did not frame that outcome as something Vector should have owned. Instead, he described fomo’s achievement as impressive execution. In his view, the company adopted a product vision that Vector had strongly believed in, then focused it on a market Vector never truly entered and delivered that vision at a much larger scale.
From Tensor to the idea behind Vector
Jacobson said Vector’s origins can be traced back to Tensor, the Solana NFT trading platform.
Before joining Tensor as vice president of operations, he had participated in the project’s only financing round as an angel investor. At that point, Tensor had almost no market share. By the time he officially joined, it had become the dominant NFT marketplace on Solana, with market share at one point exceeding 80% and trading volume in the billions of dollars.
He recalled that around his second day on the job, Ilja approached him with a simple message: the team was not sure where the NFT market was headed, but it believed the next wave would be meme coins and wanted to build a product around that shift.
For Jacobson, the opportunity was not only that meme coins could become the next hot asset class. The larger opening, he wrote, was social trading.
His argument was that trading is already social by nature. The GameStop episode and the WallStreetBets community showed that clearly. More people are making their own investment decisions, and the triggers for those decisions increasingly come from trusted people online rather than traditional financial advisors or institutions.
Crypto makes that pattern easier to see. Jacobson pointed to people on X who catch trades early, naming Ansem as an example. When Solana was around $8, he wrote, Ansem was already strongly bullish and promoting the asset. Anyone who trusted that view and acted on it could have seen outsized returns.
The problem was that discovery and execution were split apart. A user might see a token call on X or in a Telegram group, decide whether to enter, and then start searching for the correct contract address. On mobile, the experience was clumsy: open Phantom, open a browser, find Jupiter, connect the wallet, paste the contract address, verify the token, set size, and then trade. In meme coins, speed matters, and by the time all of that is done, the opportunity may be gone.
That is why Vector believed social signal and trade execution needed to live inside the same product, with as little distance between them as possible.
Jacobson cited a well-known idea from a16z crypto founder Chris Dixon: all interesting products look like toys at the start. That was how his team saw meme coins, as the “toy” that could bootstrap a social trading network.
The long-term vision went beyond meme coins. He wrote that as more mainstream assets move onchain, that network could naturally expand. If a company already has users, a social graph built around trading and alpha, and a high-quality execution layer, then moving from meme coins into stocks or other assets becomes much easier, especially if those assets are also becoming more onchain over time.
Why he thinks social trading extends beyond meme coins
Jacobson argued that while stocks and meme coins differ in fundamentals, with stocks often tied to underlying businesses and meme coins often not, the way they are traded is becoming strikingly similar.
He described GameStop as an early and extreme case, then pointed to what he sees now in storage chip trades, next-generation cloud trades, and hyperscaler-related trades. In each case, he said, narrative and market momentum are central, and the information layer around those trades is deeply social.
He also named Leopold Aschenbrenner as a recent example. According to Jacobson, Aschenbrenner built strong credibility through his views on the direction of AI. Investors now watch and mirror his positions in names such as Bloom Energy, CoreWeave, and Micron. Reputation and conviction, he argued, have become part of how many people evaluate and execute trades.
Some of those theses will turn out to be right, some will not, and only hindsight can settle that. Even so, the social nature of investment information is already obvious in his telling.
That is why he sees meme-coin behavior not as an isolated corner case, but as an amplified version of a broader market trend.
What PMF looked like inside Vector
Jacobson said the easiest way to explain Vector, or fomo, is to think of it as a hybrid of Instagram and Robinhood. Photos are the core unit on Instagram, short videos are the core unit on TikTok, and for Vector the core unit was the chart.
When users opened the app, they first saw a social feed. If someone shared a trade, other users could see the token’s live chart. If the trade happened through Vector, the buy or sell would appear directly on the chart at the relevant point.
The feed was algorithmic and designed to surface the most valuable trading signals in the network. Once users saw a signal, they could act on it almost instantly. The goal, he wrote, was to shrink the path from social signal to execution from minutes to seconds, ideally even milliseconds, in sharp contrast to the poor state of mobile trading at the time.
One product concept Vector introduced early was putting user avatars and trade activity directly on charts. Jacobson said nobody was doing that then, and when he first saw the design internally he thought it was brilliant. He noted that the interface pattern has since become common across trading apps.
His team had a plain definition of product-market fit. PMF, he wrote, is when demand is so strong that users are effectively pulling the product out of your hands faster than you can supply it. Vector felt that before public launch. During beta, users kept asking for invite codes so they could bring in friends.
The app launched in late November 2024 and quickly spread across crypto Twitter, now X. Daily trading volume soon reached about $1 million. By late January, during the release of Trump-related meme coins, peak daily volume rose above $20 million.
Retention stood out as well. Jacobson said he did not remember the exact figures, but recalled day-7 retention in the 60% to 70% range and day-30 retention around 40% to 50%. Users opened Vector frequently to trade, follow one another, share views, invite friends, and copy the people they watched.
The company had fewer than 25 people at the time. Hypergrowth showed up everywhere: repeated system failures, trades that sometimes would not go through, a support team under pressure, and a product roadmap that always exceeded available headcount. For Jacobson, that was the clearest lesson he had seen in real PMF. Demand creates pressure in every part of the company and drags the organization forward faster than it can comfortably handle.
It also reinforced one of his core beliefs about building companies: a small group of highly talented people can achieve a great deal, and nothing is more important than staying close to customers. Customer focus, he wrote, is a culture that has to be modeled from the top. If leadership is not talking directly to users, handling support, and learning where the product breaks, it is easy to lose touch with actual needs.
The strategic turn toward professional traders
As the meme-coin market cooled, Jacobson said a structural issue became harder to ignore.
Retail users often lost most of their capital, then traded less or left entirely. Professional traders were different. They could make money, keep trading, and generate huge volume. In his description, the economics were highly concentrated, with roughly 5% of users accounting for about 95% of trading volume.
From that starting point, Vector made what he still considers a rational choice: go after the professional trader market.
Those users had different needs. They often sat in front of multiple screens, watched many charts at once, and entered and exited positions rapidly. Vector was built for mobile, and many professionals did use it, but mobile was usually a supplement to their main setup rather than their primary venue.
Competition was also intensifying. Jacobson said Axiom had built a strong product, while Photon, BullX, and others were chasing the same users. Since professionals were contributing most of the volume, Vector started building a desktop product. At the time, becoming the preferred trading interface for professionals seemed like the clearest path to winning the market.
Even now, he said, he still sees that as a viable strategy. The desktop product was strong, early beta users responded well, and the company had prepared a confident go-to-market plan. But it was never released publicly, so the strategy was never fully tested in market conditions.
Looking back, Jacobson said he now sees another layer to that decision. The team was trying to win share in the market that already existed, not expand the market itself. It spent too little time on a different question: could a social trading product bring in people who had never traded onchain before and make the addressable market much larger?
In his telling, that is exactly what fomo chose to pursue.
What fomo got right, in his view
The most interesting part of fomo’s story, Jacobson wrote, is where it placed strategic emphasis.
When Vector was building its desktop product, the obvious opportunity was serving professional traders. Axiom was growing quickly, professionals dominated the economics, and many products were competing for the same segment. That was where the industry’s attention sat at the time.
fomo chose something else.
Rather than fight for veteran onchain traders, Jacobson said, the company looked to TikTok, Instagram, and audiences outside CT, including many people who had never made an onchain trade. It went after a large consumer market that much of the industry had largely ignored.
Timing mattered too. fomo emerged after the meme-coin mania had cooled. The market was no longer as frenzied or purely speculative as it had been when Vector was operating. Jacobson said he is not sure the same strategy would have worked as well at the peak of the craze, but he believes fomo targeted a different user base at the right moment and executed very well.
What the company solved, in his account, was hard. It found ways to reach users outside the traditional crypto circle, guide them into the product, and help them make a first onchain trade. That required strong distribution paired with a product good enough to make an unfamiliar activity feel simple, convert users successfully, and then give them reasons to keep coming back.
He added that fomo also captured the product details that matter to that audience. If Vector had simply been pushed through the same distribution channels without being adapted for those users, he said, it would not have produced the same result.
Even so, Jacobson did not call Vector’s professional-trader focus a mistake. He said he still believes the desktop strategy could have worked well. The more useful lesson, in his view, is that a much larger market existed outside the one Vector knew best, and his team did not spend enough time exploring it. fomo did, and it broke through.
That led him to a broader startup conclusion: the market that gives a company its first real PMF may not be the market that supports breakout scale.
An initial target segment may be the perfect beachhead, but it may still represent only a small part of the eventual opportunity. Once a team knows users genuinely want the product, the next question becomes where else that product can work.
Hindsight makes that logic look easy. Operating inside a company does not. The data a team sees usually comes from the market it already serves. That data can tell you how to win the market in front of you, but not necessarily what will happen with users you have not reached or distribution channels you have not really tested.
In Vector’s case, the data showed clearly that professional traders dominated the economics of onchain meme-coin trading. What it could not show was what might happen if a social trading product were placed in front of a completely new audience with no history of trading onchain.
Jacobson said fomo has now answered that question.
His larger thesis on social trading
The rise of fomo, Jacobson wrote, has made him even more confident that the early case for social trading was directionally right, and that the growth rate and scale of the opportunity may be much larger than his team first expected.
He argued that the world is becoming more financialized, with more people investing and trading on their own, market narratives becoming topics of public conversation, and investment ideas spreading through social networks. People build trust in particular traders, investors, and creators, and capital flows along those information and consensus networks.
For that reason, he sees trading and investing as fundamentally social activities now. He said the pattern applies not only to meme coins and crypto, but also to prediction markets and stocks.
He expects the trend to accelerate. The world is becoming more connected, information moves faster, and AI will strengthen the discovery and synthesis of information. At the same time, more assets are moving onchain: stocks, prediction markets, options, real-world assets, or RWA, and financial products that may not yet have been imagined, all converging on a more global financial infrastructure that runs around the clock.
If a company can build a strong social graph around trading and alpha while pairing it with strong execution, he argued, it will occupy an unusually advantaged position. Meme coins can be the entry point, but not the end state. As more of finance moves onchain, asset classes themselves will become more modular.
Jacobson said that had always been part of Vector’s vision. What fomo has done is make the timing and the scale of that vision feel more concrete. In his view, people are ready to trade onchain, and they are also ready for a more social financial experience. fomo, he wrote, has shown that this experience can reach far beyond crypto-native users.
He added that fomo has already started moving into perpetuals, pushing past a pure meme-coin focus. If execution remains strong, he sees a very large opportunity ahead. The closest comparison he offered was Robinhood, with the distinction that fomo began with an embedded social graph and an onchain asset system from day one.
Looking back at what Vector might have become
Jacobson closed by returning to a question that naturally follows from the whole story: if Vector had kept going, could it have become a multi-billion-dollar company?
His answer was yes, absolutely possible, and perhaps more than that.
He wrote that Vector had a strong product, a talented team, and a strategy he still believes had real potential. Perhaps the company would have started there and moved into a larger consumer market. Perhaps fomo still would have beaten it. Perhaps it could even have become larger than fomo is today. None of that can be proven.
What interests him most now is watching another strong team explore the path Vector never truly took. He said fomo opened a market that Vector did not really enter and pushed the social trading model much further than his own company did, and he expressed respect for what the team has built.
For Jacobson, the most important point is the one that keeps returning throughout his reflection: financial markets are deeply social by nature, and that trait should become even stronger as more global assets move onchain.
Vector, he wrote, was an early sketch of that future. The trajectory of fomo is showing what the eventual size of that future could look like.