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Multiple AI agents working together as a team, each with their own specialty, to solve problems that would be hard for one agent alone.
Architectures where multiple AI agents collaborate, each with specialized roles, to accomplish complex tasks.
Multi-agent systems coordinate multiple LLM-powered agents through communication protocols, task delegation, and result aggregation. Common patterns include supervisor-worker hierarchies, peer-to-peer collaboration, debate/critique loops, and pipeline architectures. Frameworks like CrewAI, AutoGen, and LangGraph facilitate multi-agent orchestration.