multi-agent-patterns

Multi-agent patterns distribute complex tasks across specialized agents to overcome single-agent context limits. You need them when tasks can be decomposed into subtasks, require different toolsets, or demand parallel exploration across domains.

You coordinate multiple agents by configuring supervisor, swarm, or hierarchical multi-agent workflows. These patterns apply explicit coordination protocols, context isolation, and robust failure handling to delegate subtasks to specialized agents.

Yes, hierarchical orchestration supports complex, domain-spanning tasks like research synthesis and system design. It distributes workload across specialized agents to achieve scalable coordination for multi-domain exploration.

The best way to decompose tasks requiring different toolsets is applying multi-agent patterns with explicit handoff protocols. This isolates context for each specialized agent while maintaining robust failure handling across the workflow.

A single agent fails due to context limits when tasks demand parallel exploration across domains. Multi-agent patterns overcome this by distributing workload across specialized agents with explicit coordination protocols.

Yes, explicit handoff protocols are required to isolate context and ensure robust failure handling in multi-agent systems. They enable seamless subtask delegation across supervisor, swarm, and hierarchical coordination patterns.