multi-agent-patterns

Multi-agent orchestration patterns coordinate specialized AI agents to improve collaboration and reliability across tasks. Common patterns include orchestrator-workers, router, plan-and-execute, debate, and swarm architectures for complex workflows.

Apply the orchestrator-workers pattern for centralized coordination of specialized agents, or use the router pattern for complex workflows. These provide clear interfaces and guardrails for reliable agent coordination and task delegation.

Use the debate pattern when you need critic-executor quality control and collaborative decision-making. Choose swarm patterns for complex workflows requiring distributed coordination and autonomous agent interactions.

Yes, you can manage agent lifecycle and memory sharing through governance patterns. These include fault handling, error handling, and lifecycle management guidance for production-grade multi-agent coordination.

Implement governance patterns with dedicated fault handling and error handling mechanisms. These guardrails ensure production-grade reliability and maintain agent coordination during failures across complex workflows.

A critic-executor pattern provides quality control and collaboration in multi-agent systems. It works alongside tool-use patterns to improve reliability and throughput when coordinating specialized agents across complex tasks.