Agent Handoff

Agent handoff is the structured transfer of an active task, along with its full context and intermediate state, from one AI agent to another within a multi-agent system. The handing-off agent passes control to a receiving agent – which may be a specialized sub-agent, a peer, or a supervising orchestrator – so the task can continue without loss of information or progress. A reliable agent handoff requires three key elements: first, complete context transfer, ensuring all relevant data, intermediate results, and task instructions are passed along; second, defined handoff protocols that specify the conditions, triggers, and responsibilities governing the transfer; third, robust error handling that detects a failed handoff and retries or escalates appropriately. In practice, agent handoffs appear in multi-step agentic pipelines where planning, implementation, review, and deployment are distributed across specialized agents. A planning agent might outline a task and hand it off to a coding agent, which then forwards the output to a validation agent. Each handoff is a critical transfer point where context loss or miscommunication can break the entire pipeline. For scaled agent architectures, well-defined handoffs enable parallelization, reduced per-agent context overhead, and clear accountability chains. Modern orchestration frameworks such as LangGraph, AutoGen, and the MCP protocol provide standardized handoff patterns as part of their orchestration layer. Teams building production multi-agent systems should treat handoff design as a first-class architectural concern.