AI infrastructure is becoming a platform-team problem.
Once agents move into production, the hard work is routing, cost control, observability, identity, and rollout safety.
The pattern is familiar from earlier platform shifts. At first, teams focus on the new capability. Then the real work moves into the operating layer. AI is following the same curve. Inference routers choose models by cost and latency. Agentic NetOps needs trusted inventory before it acts. Endpoint privilege management matters because agents touch real machines. Observability matters because regulated teams need shared telemetry and audit trails.
AI does not remove DevOps and platform work. It expands the surface area that platform work has to cover.
The companies that scale AI safely will treat it as infrastructure, not as a feature toggle with a model behind it.