multi-agent-patterns

Design multi-agent architectures by applying coordination patterns like Supervisor, Swarm, or Hierarchical. This enforces explicit context isolation and coordination protocols to manage sub-agent reasoning, enabling distributed task execution when scaling beyond a single context window.

Use swarm coordination for peer-to-peer task execution where agents operate autonomously, and use supervisor patterns when a central orchestrator must explicitly manage sub-agent handoffs, context isolation, and failure handling across different domains.

Context isolation separates the reasoning and data flow of individual sub-agents within a multi-agent architecture. It is needed to prevent context window saturation, ensure specialized toolsets operate independently, and maintain robust failure handling across complex workflows.

Handle failures in a hierarchical multi-agent workflow by implementing explicit handoff rules, timeouts, and circuit breakers. These mechanisms ensure robust failure handling and allow the orchestrator to manage consensus or reassign subtasks if an agent fails.

Yes, you can coordinate specialized subagents for cross-domain automation without external dependencies. The architecture relies on internal scripts and references to define coordination protocols, consensus mechanisms, and data flow for complex enterprise workflows.

The best way to decompose complex research tasks is to assign specialized roles like Researcher, Analyzer, and Synthesizer. Define a coordination pattern, establish explicit handoff rules, and outline a failure-handling strategy to manage the distributed reasoning.