Feed Drop from The Generalist: Why a16z's Martin Casado believes the AI boom still has years to run

**SPEAKER_1** (0:00)
Today, we're replaying a conversation from The Generalist with a16z general partner, Martin Casado. Martin shares his perspective on the AI boom, why he believes we're still in the 1996 moment of the cycle, how a market-first lens shapes his investing, and why he's skeptical of AGI-centric framing. He also reflects on his path from game engines and simulations to pioneering software-defined networking and investing at the frontier of AI and infrastructure. They close with why AI coding could be a multi-trillion dollar opportunity, how a16z evolved from a small generalist firm into a specialized organization, concerns about Chinese dominance in open-source AI models, and how World Labs is tackling the 3D representation problem with implications for robotics and VR.

**Martin Casado** (0:41)
If you ask me, what is the one area that AI has surprised you? It's encoding. I've been developing my whole life, and I would never have guessed it'd be this good.

**Mario Gabriele** (0:49)
You have mentioned that some of the energy that you're seeing in AI really reminds you of the 90s dot-com boom.

**Martin Casado** (0:56)
This feels a lot like early 96, but I don't think we're anywhere close to a late 90s level bubble. No, I think that could come. The current technology wave is you can actually deploy capital and you can get revenue on the other side of it. And I think that is what the market is trying to normalize. But there's a true value being created in this AI, and I think that if money's not following it, it's going to miss the greatest super cycle in the last 20 years.

**Mario Gabriele** (1:18)
How would you describe your investing style today? What is your filter?

**Martin Casado** (1:23)
I used to think from company out. I've stopped that. Now I think only from markets in. The reality is the market creates the company, in most cases, not the other way around. And so I always start with, what is the market? And then I ask the question, is just the right founder for this market? It's clearly not perfect. And in fact, you'll be wrong a lot of the time, but I would submit that if you invest in this way, you will be right in a way that's better than market norm.

**Mario Gabriele** (1:54)
Hey, I'm Mario, and this is The Generalist Podcast. As the saying goes, the future is already here. It's just not evenly distributed. Each week, I sit down with the founders, investors and visionaries living in the future to help you see what's coming, understand it more clearly and capitalize on it. Today, I'm speaking with Martin Casado, a general partner at Andreessen Horowitz and leader of the firm's infrastructure practice. Martin has had one of the most fascinating journeys in Silicon Valley, from writing game engines for budget video games in the 90s, to selling his startup for approximately 1.3 billion in 2012, and now investing in the next generation of AI companies like Cursor and World Labs. In our conversation, we explore why Martin believes the AI boom has room to run, how he identifies market leaders before consensus forms, and what China's dominance in open-source models means for American technological sovereignty. If you like today's discussion, I hope you'll consider subscribing and joining us for some of the incredible episodes we have coming up. Now, here's my conversation with Martin. Awesome. Well, I've really been looking forward to this a ton. You have such an interesting background and have sort of charted a lot of these different cycles in technology as both the founder and investor. So excited to get into AI today in particular. But to start, I wanted to maybe begin with a part of your history that intrigued me, which is that in the early 2000s, as far as I could tell, you were spending a little bit of time at the Department of Defense working on simulations. Tell me about that.

**Martin Casado** (3:30)
Actually, it was Department of Energy. So I worked at Lawrence Livermore National Lab. So actually, I'm going to rewind it just a couple of years. So I actually paid for a lot of undergrad writing game engines for video games. So back in the 90s, you only really got into computers if you wanted to hack or make video games. That was it. It wasn't what it is now. And I took the video game route. And so I did a lot of game development. And in college, I did a lot of engine development. And so what I was interested in was things like 3D engines and game physics and game mechanics. And that pushed me towards computational physics, like simulation. So the game industry is a very tough industry to do. And I was actually quite interested in science and I was quite interested in physics. And so that pushed me towards the national labs. And so yeah, so my first job was doing basically computational physics, working on these large simulations at Lawrence Livermore National Labs. And I started interning in like 97-98 time frame, and then I took a full time role in 2000