TechCrunch’s StrictlyVC evening in Los Angeles late last week brought together two of the more straight-talking investors working in AI right now. Carter Reum is co-founder of M13, an early-stage firm with $2.5 billion in assets under management that has been a seed or Series A investor in 17 unicorns, he says. Chang Xu is a partner at Basis Set Ventures, which launched in 2017 as one of the first early-stage funds focused exclusively on AI and is now investing out of its fourth fund, with nearly $1 billion in assets under management.
On stage, in a sun-filled room in El Segundo, the two were as entertaining as they were illuminating, covering how to price deals in a market that has never moved this fast, how to find companies that won’t get steamrolled by the hyperscalers, and what the SpaceX IPO is about to do to L.A. The conversation has been condensed and edited for clarity.
Is there an AI infrastructure bubble?
Chang Xu: There’s both a bubble and not a bubble. It’s not a bubble because we’ve never seen this type of growth curve before. ChatGPT goes from one to $40 billion in six months in terms of revenue — that’s just unprecedented growth at that scale. We have a portfolio company, Open Art, that went from $1 million to $10 million ARR in year one, and $10 million to $70 million in year two, [and it was] cash-flow positive most of that time with just 20 people. The bar for what is good growth has totally changed. When you have this possibility of compounding accelerant growth, the valuations don’t seem so crazy because you price that into the terminal value. On the other hand, if you price every single deal to that math, there’s no way that will work out well for a portfolio. So it is a paradoxical time.
Carter Reum: I always laugh because we pretend like this is the first time in venture capital land, but we’ve seen this before — with cloud, with the iPhone, with the car in the 1920s, when people were worried they’d lose their jobs, and they did, and life went on. This is steeper and faster, but the same dynamic. What’s different in this cycle is that past cycles had innovators competing with innovators — Zuck versus Evan, Travis versus John Zimmer. In this cycle you have innovators competing with innovators, competing with the largest, most well-funded innovators the planet has ever seen, and competing with the ten largest tech companies on the planet. And I would argue that for the first time in history, the incumbents actually do have the advantage — the tech, the capital, the data, the talent. So as quickly as some of these companies rise, they may potentially fall. I actually find it harder to invest in a market like this. But if you get it right, you look like a genius.
How do you price deals when startups are generating revenue faster than ever but it’s not clear how sustainable they are?
Reum: We always do the cocktail napkin math. We were looking at a business the other day — AI software for brands. I asked: how big were the winners last cycle? Are there going to be more brands in the world? Are they willing to pay double or triple for software in this cycle? We ended up not making the investment because we couldn’t make the math check out.
Xu: We stay very, very close to what is the defensible technical differentiation, because that frontier changes every quarter, maybe every month, sometimes every week. The framework we think about is investing below the AI and above the AI. Below the AI, you have all this infrastructure that’s getting rethought — databases, version control, deployment tools — because they were all built for humans. Now you have agents using all this infrastructure, and agents require fundamentally different things. Last year I would never have thought you’d need a new GitHub. This year I can count on two hands how many really strong teams are going after being the GitHub for agents. Above the AI, when things get super crowded, we always go back to: what is defensible, and what has long-term differentiation?
How do you invest in companies that aren’t going to get blown apart by OpenAI or Anthropic or Google?
Reum: We always try to think about where they’re going first and where they’re going last. It was obvious they’d go after marketing and the obvious places. So we have a thesis around friction as a moat — we love regulated industries. We had a just-shy-of-a-billion-dollar exit in a company disrupting 911 call centers with AI. The hyperscalers might go there eventually, but as a few-billion-dollar outcome, they’re not going there anytime soon. Healthcare — they will go there, but there’s a lot of regulation slowing them down.
What keeps all of us up at night is that it can change on a dime. You used to see them coming in the rearview mirror. I tell every founder: you need a microscope in one eye and a telescope in the other. The microscope is for the day-to-day — what do I have to do this week, execute. But you better have your telescope out, because the world is shifting so fast. You have to be a domino player and a chess player, because your board is changing constantly.
Xu: The framework we use is: is this a depth market or a velocity market? In velocity markets, fast followers are faster than ever — it’s all about speed of execution. In depth markets, hard things are still hard. We actually have a portfolio company using transgenic chickens as an alternative to manufacturing drugs, because it’s very expensive to manufacture complex proteins. It’s cheaper, apparently, if you have chickens do it. Chickens still take this long to hatch — for today [laughs]. Those are depth markets, and we invest accordingly.
Chickens notwithstanding, are you seeing genuinely novel ideas right now, or mostly new versions of old companies?
Xu: Both. The consensus categories — agents applied to finance, agents applied to healthcare — you see a lot of really strong founders going after them, and a lot of them are going to win. But the most interesting ideas are the ones where you think, ‘Huh, I don’t know if that can even be a business.’ OpenArt, when we first backed them — shortly after, Dall-E came out, Stable Diffusion came out, they started a discovery page of prompts you could type to get certain types of generative images. How is that a business? Absolutely no idea. They went from $1 million to $70 million in two years and have been accelerating ever since. There’s so much depth in that market that we just couldn’t tell from the outside. But from the very beginning these were young founders experimenting at the cusp of something they found exciting, and they kept iterating until they found a business. If they’d started a year later, they would have missed the window.
The story of VC is that it’s constantly a story of bad ideas becoming good again. Four or five years ago you would have said it’s a bad idea to invest in anything selling to Hollywood. Then we did a bunch of deals in creative AI, generative AI, which led to the current wave of companies doing incredibly well — generative images first, then video, now world models. That world has been way bigger than we could have ever estimated looking at the prior generation of software that sold to Hollywood. And then you have Cursor, which everyone said was just an AI wrapper. A $60 billion exit. And researchers — when my husband was doing his PhD at MIT, his pay was barely above the poverty line. Now researchers are who everyone follows on Twitter.
Reum: I think we’re still in the early innings. The first wave of any technological cycle, even one this steep and fast, is usually the most obvious — more competition, crowded. The second and third ripples are where it gets interesting. Think about when you were a kid: if you take a heavy rock and throw it as hard as you can and get it to skip across water, the heavier the rock and the faster you throw it, the longer the ripples. That’s what we’re going to have here. I get excited about two, three, four years from now, because there are going to be business models and companies that we can’t imagine today. As a VC, those second and third ripple bets are the hardest ones to get right — but if you do, fewer people are thinking about it, you pay more reasonable valuations, and the ROIs tend to be much better.
The SpaceX IPO is going to put a lot of money into the hands of people who live here in L.A. — employees especially. What does that mean for this ecosystem?
Reum: When Anthropic and OpenAI eventually IPO, it’ll be a bunch of VCs and institutional investors. Never has this much money come back and been so widely spread out as what’s going to happen with SpaceX. If anyone [in this room] has a house to sell, a boat, a plane — definitely take advantage of that ride. But more importantly, every major liquidity event generates a second wave. The previous L.A. cycle produced things like Riot Games, Tinder, Snap. This is a different order of magnitude.
Three years ago everyone said San Francisco was dead. Turns out it’s a little less dead than people expected. I think the same would be true of anyone who writes off L.A. There are too many smart people here — technically, but also people who understand brand, content, creators, influence. This first wave is a technical wave, and the technical talent is concentrated elsewhere. But what comes after technical waves? New business models, creative thinking, understanding culture. That’s going to be the next wave, and I think high likelihood it’s centered in L.A.
Xu: The thing that’s interesting is that the next frontier in AI isn’t more compute — it’s taste. It’s making films, making videos, making things that resonate emotionally, making things that connect with specific cultures. San Francisco has extraordinary technical talent, and that’s also exactly what the models are getting very good at automating and accelerating. L.A. has taste in spades.
