Martin Casado on the Demand Forces Behind AI

**Martin Casado** (0:00)
What's going to happen to central buyers and platform teams and IT teams if agents are making the decision? It's very clear that coding is pretty much dead, but engineering is very much not. Every time you have a technical epoch, you have to redo everything, and we forget that every time. I don't think people even have a common definition of a bubble.

**Derrick Harris** (0:28)
If AI demand is real and accelerating, why does everything still feel constrained? Why does a technology that's clearly delivering value also feel harder to scale than expected? We've seen this pattern before. In early technology shifts, it was easy to assume the hard problems were solved. Infrastructure was treated as finished, then usage surged. Systems built for a smaller world began to fail. Networks strained, power, physical footprint and coordination became first order constraints again.
Each new technical epoch forced a rebuilding of the stack. AI is creating that moment now. The demand is not speculative. Companies are deploying models, budgets are moving. Real productivity gains are already showing up, and yet nearly every part of the system feels tight. Compute is scarce, data centers take years to permanently build, power is difficult to secure. Regulation moves far more slowly than the technology itself. This has led to two dominant stories. One says we're in an AI bubble. The other assumes scale will smooth everything out. Neither fully explains what's happening. Demand continues to outpace supply, and the biggest bottlenecks increasingly sit outside the models themselves. This is especially visible in enterprise software. AI is often framed as a threat to SaaS, but SaaS was never hard because of the interface. It was hard because it encodes business processes, compliance and operational reality. Those needs do not disappear. What changes is how humans and increasingly agents interact with those systems and how software is priced, bought and controlled? That shift raises a deeper question. If agents are writing code, provisioning infrastructure and selecting tools, who's actually making the decision? And what happens when that decision-making layer becomes less visible? This conversation helps clarify where the real constraints are and why infrastructure is not fading into the background, but moving back to the center of the story. This is a feed drop from The Six Five Podcast featuring a16z general partner Martin Casado in conversation with Patrick Moorhead and Daniel Newman.

**Daniel Newman** (2:30)
Let's go off the record. I know we don't do these as often as we probably like, but when we have the opportunity to bring someone in, it can really change the trajectory of the conversation here, Pat, or just someone that's got really interesting ideas and things to talk about. I know we love to do that, and we got one today that you met when you were doing your professional modeling and hosting. That was fun. It was really fun for me to sit there and watch you, because I saw you working and sweating at GTC for two days. Let's have you introduce our guest, which I'm super excited to have here today on the pod.

**Patrick Moorhead** (3:04)
That's great. I'm proud to introduce here, Martin Casado, General Partner at a16z, joining us today. Martin, it's great to see you.

**Martin Casado** (3:14)
Great to be here. Thanks so much for the insight. Yeah.

**Patrick Moorhead** (3:16)
The lights aren't as hot, but the audience is actually bigger than the in-person audience that we had in Washington DC for GTC. I really appreciated it. But hey, why don't we start off just to make sure we know who we're talking to. We know you're famous, but for those who don't know who you are, what do you do and what does your portfolio, what do you focus on?

**Martin Casado** (3:42)
Yeah.
I'm a General Partner at a16z. I run the Infrastructure Fund. The Infrastructure Fund, our definition of infrastructure, this is computer science infrastructure. This is anything with a technical buyer, so think compute, network storage, databases, of course, any of the low-level AI stuff, DevTools, that sort of thing, security. So I run the team. I've been here for 10 years and then prior to that, I was actually portfolio founder for a16z.

**Patrick Moorhead** (4:10)
Now, that's wonderful. Isn't it funny how infrastructure was pretty much left for dead about five years ago, and the meme of hardware was a hardware is an undifferentiated commodity. And look at us now. And I know infrastructure spans not just hardware, but also software.

**Martin Casado** (4:32)
Yeah, for sure. So listen, it's been an evolving tale. I mean, hardware has historically actually been pretty boring, like networking, silicon. Now, software infrastructure, especially in data has been pretty exciting, things like Snowflake or Databricks. And so like there has been a lot of exciting, you know, GitHub. But AI has blown everything up. Like, I don't remember the last time you had a lot of excitement around, you know, a silicon chip and, you know, NVIDIA just bought Grok for, or didn't buy Grok. They hired the Grok team.