Why Multi-Agent Workflows Break in Production (And How to Build Predictable Loops)
Why Multi-Agent Workflows Break in Production (And How to Build Predictable Loops) Most multi-agent demos fail the moment you put them in front of real production traffic. They look impressive in five-minute screencasts: an orchestrator agent receives a user prompt, sketches a plan, delegates sub-tasks to three specialized agents, and returns a tidy response. When you deploy that architecture into production, reality hits quickly: An upstream API returns an unexpected 429 Too Many Requests , and the planning agent assumes the endpoint no longer exists. A research agent writes an 8,000-token summary of an API response into shared history, diluting system prompt instructions for subsequent steps. Two agents enter an agreeable loop where Agent A asks Agent B for clarification, Agent B reframes the question, and both report that progress is underway while burning through token budgets. These failures do not stem from bad prompt engineering or weak base models. They stem from a f...