What Coding Agents Teach Us About AI Agent Concurrency, Webhooks, and Design Architecture
I have spent the last few months reading source code of real coding agents — not the model, the scaffolding around it. What I found surprised me: the most interesting engineering is not the brain; it is the nervous system.
This post is what I learned from that source-code dive. We look at the code that wraps the model—the control loops, concurrency primitives, state management, and event plumbing—to understand what makes a coding agent usable in production. Building a coding agent is not just about calling an API; it is a distributed systems problem. You have to manage long-running state, coordinate multiple sub-agents, and ensure that a thought process that takes 30 seconds does not freeze your entire environment. The runtime that wires these pieces together is what separates a demo from a production-grade agent.