AI’s Capital Flywheel: Models, Money, and the Future of Power

**Sarah Wang** (0:00)
I mean, every industry has talent wars, but not at this magnitude. Very rarely can you see someone get poached for $5 billion, that's hard to compete with.

**Martin Casado** (0:07)
It's almost become a meme, right? Which is like, if you're not basically growing from zero to 100 in a year, you're not interesting, which is the silliest thing to say.

**Sarah Wang** (0:14)
When there's a real capability breakthrough, the demand is there, and so the revenue growth is much faster than we've ever seen once it's turned on.

**Martin Casado** (0:22)
There could be a systemic situation where the soda models can raise so much money that they can outpay anybody that bills on top of them, which would be something I don't think we've ever seen before, just because we were so bottlenecked in engineering.

**SPEAKER_3** (0:36)
During the internet buildout, investors put money into fiber that nobody used. Four years of supply overhang followed. This time, there are no dark GPUs. Every dollar going into compute has demand on the other side. But something else is different. A model company can raise capital, drop a model in a year with a team of 20, and produce something with immediate demand. If Frontier Labs can raise three times more than the aggregate of every company built on top of them, they may consume the entire application layer. Or the market fragments and value accrues to the company's closest to the end user. Nobody knows which path wins. In this conversation previously aired on the Latent Space podcast, Martin Casado and Sarah Wang, general partners at a16z, speak with Alessio Fanelli and Shawn Wang about the capital flywheel, talent wars, and why boring software is under-invested and whether every task is AGI complete.

**Alessio Fanelli** (1:28)
Hey everyone, welcome to the Latent Space podcast live from a16z. This is Alessio, Founder of Kernelance, and I'm joined by Swyx, editor of Latent Space.

**Swyx** (1:36)
Hey, hey, hey. And we're so glad to be on with you guys. Also a top AI podcast, Martin Casado and Sarah Wang, welcome.

**Martin Casado** (1:44)
Very happy to be here, and welcome.

**Swyx** (1:45)
Yes. We love this office. We love what you've done with the place. The new logo is everywhere now. It's still getting, it takes a while to get used to, but it reminds me of like sort of a callback to a more ambitious age, which I think is kind of.

**Martin Casado** (1:59)
Definitely makes a statement.

**Swyx** (2:01)
Yeah.

**Martin Casado** (2:02)
Not quite sure what that statement is, but it makes a statement.

**Swyx** (2:06)
Martin, I go back with you to Netlify, and you create a software defined networking and all that stuff people can read up on your background. Sarah, newer to you, you sort of started working together on AI infrastructure stuff.

**Sarah Wang** (2:19)
That's right. Yeah, seven years ago now.

**Martin Casado** (2:21)
Best growth investor in the entire industry.

**Swyx** (2:23)
Oh, say more.

**Martin Casado** (2:24)
Hands down. Yeah, Sarah is. I mean, when it comes to AI companies, Sarah, I think, has done the most kind of aggressive investment thesis around AI models. And I sort of worked with Noam Chazir, Mira, Ilya, Feifei. And so just these frontier kind of like large AI models, I think, you know, Sarah has been the broadest investor. Is that fair?

**Sarah Wang** (2:48)
No, I, well, I was going to say, I think it's been a really interesting tag team, actually, just because the, a lot of these big C deals, not only are they raising a lot of money, it's still a tech founder bet, which obviously is inherently early stage, but the resource is, so many, it's like all. One, they just grow really quickly, but then two, the resources that they need day one are kind of growth scale. So I think the hybrid tag team that we have is quite effective, I think.

**Swyx** (3:14)
What is growth these days? You don't wake up if it's less than a billion or like.

**Martin Casado** (3:20)
It's actually very, it's a very interesting time in investing because take the character around, these tend to be pre-monetization, but the dollars are large enough that you need to have a larger fund and the analysis because you've got lots of users because this stuff has such high demand requires more of a number of sophistication. Most of these deals, whether it's us or other firms on these large model companies are like this hybrid between venture and growth.

**Sarah Wang** (3:46)
Yeah, totally. I think stuff like BD, for example, you wouldn't usually need BD when you were seed stage trying to get product management. BizDev, exactly.