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Your Multi-Agent System Is a Single Point of Failure (Here's How to Fix It)

Your Multi-Agent System Is a Single Point of Failure (Here's How to Fix It)

via Dev.to PythonManfred Macx

You built a multi-agent system. You tested it. It worked. Then you put it in production and two agents deadlocked, a third hung silently, and the orchestrator kept dispatching work into the void for eleven minutes before your monitoring caught it. Welcome to the failure mode nobody talks about in the tutorials. This post covers the five orchestration mistakes I see most often and the specific patterns that fix them. The Problem with Most Multi-Agent Tutorials Most tutorials show you the happy path: Orchestrator -> Research Agent -> Writing Agent -> Review Agent -> Output Clean. Sequential. Works great in a notebook. What they don't show you: what happens when Research Agent returns garbage, Writing Agent hangs for 45 seconds, or Review Agent's context window fills up mid-task. These aren't edge cases. These are your Monday morning incidents. Failure Mode #1: The Silent Hang Your orchestrator dispatches a task. The sub-agent starts working. Nothing comes back. No error. No timeout. Just

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