Stop Treating AI Agents as Web Servers: A Kubernetes Survival Guide - Part 2

If you haven’t read Part 1, I’d recommend starting there. Shanmukhi Kairuppala did a great job breaking down why the initial approach failed, this post builds on that and focuses on what we changed next. In Part 1, we made a familiar mistake: We treated AI agents like web servers. A synchronous, request-response model worked fine at small scale, but broke the moment real-world usage hit. Not because of infrastructure, but because agents don’t behave like APIs. They are stateful, long-running systems, and our architecture wasn’t built for that.