What is a Multi-Agent System?
An architecture where multiple AI agents collaborate on a task, each with its own context window, tools, and responsibilities.
Multi-agent systems divide complex work across specialized agents (e.g., a planner, a researcher, a coder) that coordinate through structured handoffs. The main challenge is context management: how agents share information without leaking irrelevant state, duplicating tokens, or operating on stale data. Effective multi-agent architectures scope context per agent and summarize at handoff boundaries.
Related concepts
An autonomous software program that uses a large language model to plan and execute multi-step tasks.
The practice of deliberately designing, structuring, and managing the information provided to AI models to improve output quality and relevance.
An open protocol that standardizes how AI applications provide context and tools to language models.
Further reading
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