Multi-Agent Systems

Teams of specialist agents that collaborate

🔑 Key Concepts

When multi-agent helps — Single agent juggling too many responsibilities drops quality. Specialists outperform generalists.
Supervisor pattern — One agent delegates to specialists: researcher, writer, critic. Supervisor monitors and handles failures.
Frameworks — CrewAI (role-based teams), AutoGen (Microsoft, conversation-based), LangGraph (stateful orchestration).
Cost management — Use cheap models for routine agents (GPT-4o-mini), expensive models only for quality-critical roles.

💡 Practice: Try implementing each concept yourself before moving on. Reading about RAG and building RAG are very different things.