Multi-Agent Orchestration
An architecture where multiple specialized AI agents collaborate to complete a complex objective, each with defined roles, tools, and communication protocols. An orchestrator agent decomposes the goal and dispatches subtasks to worker agents. Unlike single-agent loops, multi-agent systems enable parallelism, specialization, and fault isolation. The main patterns are: hierarchical (orchestrator→workers), sequential pipeline, and debate/critique among agents.
In practice
A developer building a complex RAG system can use an orchestrator (AutoGen, CrewAI, Magentic-One) to route queries to specialized agents — one for web search, one for the vector database, one for final synthesis. Debugging requires tracing inter-agent communication: tools like LangSmith or Phoenix show which agent received which input and what it produced, making bottlenecks and infinite loops visible.
Related terms
Seen in the wild
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