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Multi-agent

Architecture where multiple specialised AI agents collaborate to handle a workflow. One agent plans, another researches, another writes, another reviews. More complex than single-agent but powerful when the task naturally splits.

How it works

Multi-agent systems define agents with specialised roles and tools. Communication happens via shared state, message passing, or A2A protocol in 2026. Orchestration patterns include hierarchical (manager-and-workers), sequential (pipeline), and free-form collaboration.

Example

A research agent system: a Manager agent decomposes a research question into sub-questions, dispatches them to Researcher agents (each scoped to a different source: web, internal docs, news), gathers responses, hands off to a Writer agent for synthesis.

Related terms

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