Moving From One AI Agent to a Multi-Agent Team: A Production Roadmap

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A practical guide walks developers through building a multi-agent AI system for production, starting from a working single agent. It notes that single agents often struggle as prompts grow, tool counts rise, latency increases, and failures become hard to trace. The author argues that splitting into multiple agents should happen only when measurable failures justify it, such as tool overload, bloated prompts, differing risk levels, or parallelizable work. The roadmap proceeds in stages, covering baselining, hardening, splitting by responsibility, handoff contracts, observability, guardrails and budgets, evals in CI/CD, and deployment. Framework-agnostic Python examples are provided, applicable to tools like LangGraph, CrewAI, AG2, and the OpenAI Agents SDK.

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