AI Agents Are Distributed Systems

AI agents aren’t magic. They’re distributed systems — with better marketing.

Behind every impressive demo is a messy reality: multiple tools, remote services, auth boundaries, latency, retries, side effects, and deployment trade-offs. When I took a seemingly simple multi-tool agent built with MCP and Gemini ADK and pushed it into production, I stopped thinking about prompts — and started thinking about architecture.

In this talk, I’ll share what changed when the agent left localhost.

We’ll explore what happens when tools become independently deployed services, when stdio orchestration meets HTTP in the real world, and when generating an image, storing it, and emailing it turns into a reliability problem — not just a feature.

You’ll see how treating the agent as a control plane — and exposing it as a service — transforms it from a demo into infrastructure.

This isn’t a code walkthrough. It’s a systems story.

If you’re building AI agents meant to survive outside a notebook, this talk is about the parts no one shows in the demo.