Can Today's AI Winner's Be Dethroned?

I've always felt round size is there's this weird circular logic that's been happening probably since 2010, which is that why round sizes get bigger? Is it because funds get bigger, or is it because founders need more capital?

If you're running around town saying that you are building the best AI fund in the market, or plan to, and you're not in one of the big names that have already been mentioned, how much will that matter?

If you're a big multi billion dollar venture fund and you're not an anthropic or OpenAI, it's probably going to be tough on a relative basis.

While near 10 years ago a sub $5 million seed round accounted for nearly 70% of all seed deals, recent data showed that we're sitting at nearly half of that figure today.

Welcome to the Learning Corner by Precursor. I'm Mia Farnam and I'm joined by our GP and Managing partner Charles Hudson, where we will be talking through the articles and good that caught our team's attention over the past week. Our first piece is a blog post written by Elon Gill, who claims that AI markets are the clearest they have been in a few years, with new markets finally ripe for disruption. Markets like Foundational Models, Code, Legal, Medical Scribing, CX and Search are specifically some of the markets where more likely winners have emerged. Elon cautions folks that just because some big players have come forth today doesn't mean that there won't be newer ones in the future. However, it will be rather difficult to fully dethrone some of the companies he mentioned. So, like the Anthropic squad Mistrals of the world, of course I agree with Elon saying that there will be many more successful AI companies to emerge, some within the more crystallized markets he spoke about in the piece. From your perspective, however, if you're running around town saying that you are building the best AI fund in the market or plan to, and you're not in one of the big names that have already been mentioned, how much will that matter? Was a question I had.

Yeah, first of all, Elon's obviously been super successful as an investor. When I read the post I was like the capital markets have decided the companies they want to support and a lot of wood has been put behind some of these arrows. I don't know that the capital market level of conviction and the customer level of conviction are the same because most of this technology is really new. And when I looked at that list I was like, okay, the foundation model piece I understand because capital is an essential input to those businesses. Like you cannot build the infrastructure you need to continually develop new models without large pools of capital. And I think most of the capital has coalesced around, as Elad said, you know, a couple of commercial players than others that are maybe being supported for nationalistic or strategic reasons for the more application level stuff. It's unclear to me. It's very clear to me that if you were to try to start a legal AI company today, two things are likely true. One, the first question people are going to ask you is what about Harvey? And second, if you started looking at what are the venture firms that could actually go pitch to raise money, you'd realize most of the venture firms you'd want to pitch have already made an investment of some sort in a company in that category, if not Harvey, one of the others. And so this is more I think one of the oddities of venture capital is once capital lines up behind certain companies, most funds are unlikely to invite a portfolio company conflict by investing in a similar company, and they're pretty much wedded to that company. And I've seen situations where sometimes the VC market gets it really right early and the company that's anointed ends up going on to be the winner. And I've also quite a few cases where the capital lines up behind a company that the VCs believe will be the winner. And you fast forward five to seven years and the world's different and there was a dark horse company or a bootstrap company or a company that wasn't as highly regarded that ends up being the winner. And I've just seen that play out. But usually by the time that happens, the attention has moved on to the new hot thing. So I think if you read that article through the lens of these are markets where large venture funds and private equity and sort of the capital markets have made a decision about who they're going to back. I think that's true. I think customers have something to say about this too.

In the end, I want to go back to that piece that you just mentioned about portfolio conflict and that typically being a reason why one company will not do another investment in an adjacent or direct area. I know you wrote a post about how you might predict this to shift and change in this new investing area. Can you elaborate a little bit about it for people who haven't read the piece?

Yeah. So my argument is, in the past, a lot of firms were hesitant to do portfolio company conflicts for a bunch of reasons. One, you know, most multistage Funds take board seats and you can't have the same person on. We'll say, for example, you probably couldn't be on the Google board and be on the OpenAI board without it being a little awkward given how important AI is to both of those companies. So most venture firms had a policy, hey, we're only going to invest in one company in the category and once we have our bet, that's our bet. And it has this nice two sided property in that as the company receiving the money, you have some assurances that that investor is not going to go back your biggest competitor. And as a venture fund it forces you to be honest and say if we make this investment, we're foreclosing the right to make another investment in this category. So we better be sure that we're excited about this company before we say yes. And that's been a norm, not, not a rule, but a norm in most venture funds. And in my article I was like, well look, venture funds are so big now. This might not be a sustainable norm because the need to be in the biggest, best, most important companies is becoming existential. If you're a big multi billion dollar venture fund and you're not an anthropic or OpenAI, it's probably going tough on a relative basis to keep up with your peers. And so if the norm of non competition holds, everything Elad said is probably true. If people are willing to break that, there could be companies that come out of nowhere or are funded differently that become interesting. And venture firms might say, hey, I know I'm already in company X in this category, but we need to be in company Y from a return standpoint. I'm very curious to see if this norm persists.

I can't think of any companies off the top of my head right now. But you think about, I don't know, Facebook to MySpace, Webvan and Instagram. The timeline horizons are a little bit stretched out. So maybe if there is a same investor wanted to hop into that one, like maybe that could be it. But I feel like the difference here is that the timelines are a little bit compressed. So folks who maybe are in some of the big winners, if something happens and a big shift occurs, they could in like two years later create an entire rationale that jumping into the next big winner in the same category is worth it if it's going to return fund.

Or they'll just say hey, we have partner X is on that deal, Partner Y is on this deal. We promise, promise, promise that they don't talk and Share and that we have some kind of like ability to firewall the data and you can trust us. I mean firms already, some firms already have this. They have a series A and B firm that does, you know, early stage investments and then the growth fund that has the ability to both invest in portfolio companies and non portfolio companies. And that growth fund presumably has access to the information at the fund about their own portfolio but is also meeting other late stage companies. And so you know, there are some venture funds who go, oh, our growth team is a different set of people and yeah, you know, you can trust us. The growth team can do different stuff than the main. So I think the norm of no conflicts is of part probably going to look like a relic of the past in a few years.

Yeah. Elon mentioned some other emerging markets like financial tools, sales, tooling, security and looks forward to seeing more winners emerge across those industries. We talk a lot about the possible reasons why there hasn't been complete clarity on major players in every industry. And Elon says a lot of that has to do with things like go to market buyer behavior, which we've dissected a lot teams and simply the time to build and ship products. Anything else you feel like could be a possible reason here that's preventing the anointing of key AI winners across every industry.

I also think people have to remember this stuff as fluid. I think there was a period of time where people like, well, Anthropic isn't really that competitive with OpenAI. OpenAI is like the clear front runner. And I think that's changed. At least my sense is the perception. And some of that I think is Claude code. I think some of that's mcp. But my sense is people's perception that Anthropic is destined to be the number two player. Like that is not the case anymore. And even if I look at the, the coding tools market we've seen even in the last five years, Copilot is obviously going to win because it's got Microsoft and it's got GitHub. That's not going to work. Oh, ChatGPT is really good at code. Oh no. There's Cursor and Windsurf and Replit. And then lately everyone's like, you know what's really good? Cloud code. Cloud code's really good. And so I think when I read the piece I was like, I think we know the circle of companies that have the resources and brand to be competitive in all these categories. I don't think we know who's going to win. And I'd say a lot of people have counted Google out in search, and depending on what you believe about the numbers they put out recently, I don't think Google's going to roll over and seed the search market to AI upstarts. It's just not going to happen. But I think this is an interesting time because these capital allocation decisions are sticky because you can't trade out of these positions. But we're in a very dynamic market where the facts on the ground change every day. And I wouldn't be surprised if later this year we're talking about companies we haven't heard of that have broken through in some of these categories that appeared to be settled.

Our next topic is a post by Oren Hoffman titled Data is actually Not a Great VC Backed Business where he shares how his entire tune around investing in pure play data businesses has completely shifted over the last few years. Most of his original hypothesis was rooted in the prediction that data buyers would grow in number and enlist the support of companies whose main value add was data lakes and data scientists. Turns out while there were plenty of hedge funds that purchased alternative data, it wasn't done at the scale that he predicted. And other industries he assumed would be clear buyers like real estate retailers, they just never really invested at the rate he anticipated. He goes on to conclude that data businesses are good businesses, perhaps for private equity just given the predictable revenue and high trading multiples, but not venture backed businesses as they don't need tens of millions of dollars in equity financing to be fully stood up. I felt like this post really landed specifically because Oren has spent so much of his career in this DAS space. From an investor and builder perspective, how many investors do you think are optimistically choosing to disagree with this article, especially with the added layer of AI right now?

You know, there are very few people I know who've spent more time on data businesses than Oren, and he has no incentive to say this. He's made a lot of money and been very successful in these businesses. He has no reason to say this other than that he believes that. And the number of companies I've met who are like, well, we're going to have this data and we're going to sell it to a bunch of people. And I'm always like well how confident are you that the pool of buyers is as deep as you say it is? And in many cases it isn't. And there have been a bunch of other reasons too. I found some of this data doesn't change that often. What's the value of subscribing to it. In a lot of cases there's a couple of providers. But to Oren's point, my sense has been a lot of data entrepreneurs end up being overly optimistic about the universe of people who will see value in their data. And some of it feels very like an ex post rationalization. It's like, well, because I've gone through all this effort to collect this data, there must be people who will find it valuable. And if I think about what is what appears to be valuable today, it's the ability to transform data into some other useful input. Whether that's, hey, we have a bunch of training data that you can use to train your LLM. We have a bunch of data we can use to train your self driving car. It appears that data that enables some other business process is valuable as an input, but as an input to another business, not as a business in and of itself.

And somewhat of a commodity.

And somewhat of a commodity. Like I have a friend who used to be in the sports score business and he's like, yeah, at one point it was really hard to get sports scores, then it was pretty easy and then you had box scores. And he's like, the incremental things you can do to differentiate yourself other than for gambling. It's like at some point you get to the asymptote of this is good enough for most use cases. And I still hear people tell me, oh, we're going to build this data business. We're going to accumulate this data asset and we're going to license it. I'm like, to Oren's point, I'm like, you probably won't build a big business unless this data is going to dramatically increase the market size. And I just think about when all the payment for order flow stuff happened with Robinhood and people were really upset about it. And I'm like, well, this isn't a new thing, right? But like the existence of Robinhood expanded the sort of aperture for selling that payment for order flow data because you brought a bunch of new traders into the market and Robinhood users who hadn't been present before. So occasionally, yes, you can have a data business that gets where like something else happened and it expands. That just hasn't been my experience.

Yeah, I mean, I think Oren shared it. There are only 60 publicly traded DAs companies in the world and most of them were started 40 years ago. And so not, not like founders who want to build in data can wake up the next day and within a year amass so much Data that's automatically useful for multiple use cases. Again, there are exceptions. And I think that was my last question I was going to ask you, which I think you were half answering. What is that bar of which a company can surpass, which makes it very applicable to the needs of businesses today? I think Scale AI has done this. We did an investment in a company called secludi. Anything else that comes in mind for you?

I'd say, like, I've met a bunch of people who are trying to build either custom underwriting or, like, a new credit score. And I'm like, well, we can all have qualms with transunion or experience the big three. And I'm like, part of the reason those businesses are valuable is because other people put faith in the score.

Yeah.

And because there's an economy built around credit scores. If you're going to build a more accurate credit score based on data you collect, collecting the data isn't the hard part. Convincing other people that your score has value and merit and that they should care about it is actually a much harder problem to solve. And so I would say, like, one of the fallacies I see in a lot of data businesses. People like, oh, there's this data source. If we use this and mix it with this other thing, you can make more accurate predictions. I'm like, great. Who's going to trust you enough to actually run their business based on the data that you provide?

Yep.

And they're like, oh. I'm like, well, if it's.