multi-agent-patterns

To overcome single-agent context window limits, design a multi-agent system using architectural patterns like supervisor or peer-to-peer to partition context and distribute complex tasks across specialized agents.

The supervisor pattern is an architectural design where a central orchestrator coordinates specialized agents, managing communication, task handoffs, and decision-making to produce a unified output for complex research systems.

Implement context isolation in a hierarchical agent architecture by partitioning state and context across subordinate agents, preventing individual context window limits from bottlenecking the distributed problem-solving process.

Use peer-to-peer swarm intelligence for decentralized consensus and distributed problem-solving, whereas a hierarchical agent structure suits tasks requiring a central orchestrator for strict coordination and specialized handoffs.

Building a swarm intelligence architecture requires an understanding of agent communication, state management, and distributed problem-solving to effectively implement coordination protocols and mitigate failure modes.

Mitigate failure modes in multi-agent coordination protocols by implementing robust consensus mechanisms and leveraging hierarchical structures or supervisor patterns to manage agent handoffs and state recovery.