Martin Casado on the Demand Forces Behind AI

What's gonna 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. 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 permanent 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 SAS, but SAS 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 a 16 z general partner, Martine Casado, in conversation with Patrick Moorhead and Daniel Newman. 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 that 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, like, two days. …