Multi-Agent Systems in Production: When One Agent Isn't Enough and How We Coordinate Them

Short summary

Breaking a monolithic AI agent into coordinated multi-agent systems avoids context-window overload and enables error isolation. From production experience, three patterns work: supervisor (orchestrator + workers), chain (sequential), and event-driven. Use Pydantic schemas as data contracts between agents to reduce token waste and implement per-step checkpointing for resilience.

• •Multi-agent systems solve context-window and persona-separation problems compared to monolithic agents
• •Three coordination patterns: supervisor (orchestrator + workers), sequential chain, event-driven async
• •Use structured output schemas as contracts between agents; checkpoint results per step for fault tolerance

Generated with AI, which can make mistakes.