How AI Is Rewriting the Power Law of Venture Capital

Aram Verdiyan (0:00)

We've looked at the data of 3,000 venture capital firms in the US. Only 20 have achieved consistent 3x net returns over the last two decades.

David George (0:06)

Right now, clearly, the power law is more extreme than it has been in the last 10 to 20 years of technology investing. For the first time, you can take capital and throw it at a company, and it compounds their advantage.

Aram Verdiyan (0:18)

AI is attacking every facet of the GDP, transportation, labor, services, capital, coordination. There hasn't been a technology paradigm that hits on 30 trillion in GDP at the same time.

David George (0:28)

Elon has talked publicly about GrockBot on Sam's side. He's talked about Astra and some of the long-running capabilities that are going to come out soon.

Jen Kha (0:35)

What do you think is going to be the next 100 trillion dollars market cap company?

SPEAKER_4 (0:39)

It is possible that AI isn't just creating faster growing companies. It may be changing the power law itself. In this episode, A16z's Jen Kha and David George sit down with Accolade Partners Aram Verdiyan to unpack what that means for technology investing and portfolio construction. For most startups, too much capital can become a liability. But David argues that frontier AI is different. Dollars can be converted directly into compute, and compute can make the product better, reinforcing advantages of companies already at the frontier.

They discuss why AI's addressable market could extend far beyond software, why Aram believes AI is becoming a core rather than satellite allocation, and why access, selection, and position sizing matter even more as the power law becomes more extreme.

They also look at what comes next, from robotics and healthcare to energy, chips, and data centers, and why some of the biggest outcomes of the AI era may still be in categories that barely exist today.

Jen Kha (1:42)

Welcome back to the a16z podcast. Something fundamental has changed in how value gets created. Power law used to be just a feature of a cottage industry and venture capital, and now it's systemic throughout, and particularly the three frontier model companies, SpaceX, OpenAI, Anthropic, represent somewhere between three and a half to five trillion dollars of potential enterprise value. Shockingly, before SpaceX went public, a lot of our LPs and also the broader institutional allocator community didn't have a lot of exposure to it.

We'll talk about today why potentially portfolio construction and asset allocation may have changed, why power law is not just only in the venture capital industry, and then particularly where and how value actually compounds today. David George, Aram Verdiyan, thank you for joining me.

David George (2:29)

Great to be here. Thanks for hanging out.

Aram Verdiyan (2:30)

Thank you for having us here.

Jen Kha (2:32)

Awesome. Okay, so DG, so if you add up every venture-backed IPO for the last six years, all of them together, where does it go from here?

David George (2:41)

Right now, clearly, the power law is more extreme than it has been in the last 10 to 20 years of technology investing, probably going back to the emergence of network-effect-driven consumer companies. There are many reasons why that's the case. Increasing returns to scale have always been a dynamic in our business. Obviously, it's well covered how a network-effect business can have increasing returns to scale, but so can software businesses, right? And they can take different forms, but brand, reputation in the market, the accumulation of resources, all provide competitive advantages.

That all still is the case. But right now, especially with the labs, for the first time on my career, you can take capital and throw it at a company, and it compounds their advantage. And this is a thing, like, how do you screw up a startup? Well, throw too much money at it and have them hire a thousand people, and then you create all these coordination issues and overhead issues and dueling priorities, and it sort of gets messed up, because you can't hire enough people to do enough things fast enough. Now, that's not the case. You can throw dollars at Compute, and Compute can make products and the business better. And so to me, it's not terribly surprising that the power law is more extreme.

Right now, economies of scale are a very real thing in the AI market, and I think will continue to be the case.

Jen Kha (3:55)

So Ram, so first of all, you're not just one of our long-time LPs at Accolade, but incidentally, it's been exactly 10 years since you were actually an employee of a16z. And so for your 10-year anniversary since you were last year, I brought this gem back.