GoKawiilTechCrunch’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.
... continue reading