How I Use Multi-Agent AI to Debug Production Errors in My Laravel App

Production bugs have a predictable, exhausting rhythm. Sentry fires. You open the issue, read the stack trace, try to orient yourself. Then you jump to the code. Then you open TablePlus to check the database record. Then you check git to see what changed recently. Then you open Telescope to look at the queries that ran during that request. You're holding five mental contexts simultaneously, cross-referencing them by hand, and trying to reason about what went wrong. It works. But it's slow, and the context-switching is brutal. I got tired of it. So I built a multi-agent debugging system using Claude Code that does all of that investigation in parallel and hands me back a diagnosis and a ready-to-review fix. This is how it works. The Architecture The system has five parts: investigate — the orchestrator. This is the command you actually run. It receives the error context, dispatches four specialist subagents in parallel, waits for their findings, synthesises everything, and produces the