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AI Models & Assistants / Knowledge library
Agent Handoff Loop
Transfers active control and relevant context from one agent to another specialist
Why learn Agent Handoff Loop?
It lets the selected specialist respond directly with a focused role and capability set.
The problem it solves
It routes ownership, not merely a subtask, when another agent should continue the interaction.
Where it came from
A handoff changes which agent owns the next turn, often replacing instructions and available tools. Context filters and clear target descriptions matter because irrelevant or sensitive history should not automatically cross every boundary.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Define Agent Handoff Loop and identify its place in an agent architecture.
- Choose a task where Agent Handoff Loop improves an agent system.
- Diagnose one failure caused by misusing Agent Handoff Loop.
- Interpret a trace or state transition involving Agent Handoff Loop.
- Explain one operational tradeoff of Agent Handoff Loop.
Documentation and sources
- OpenAI Agents SDK: Agent orchestration (openai.github.io)
Connect the ideas
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Real World Example
Automated Technical Support Routing
Enterprise SaaS providers managing complex, multi-tiered customer support queues.
The business problem
Generalist triage agents often struggle to resolve deep technical queries, leading to prolonged resolution times and inconsistent user experiences when context is lost during manual escalations.
How this topic solves it
The Agent Handoff Loop enables a triage agent to transfer both the active conversation control and the accumulated context to a specialized technical agent, ensuring the specialist owns the remainder of the turn without requiring the triage agent to narrate the result.
- Define a triage agent with instructions to identify technical intent.
- Configure the specialist agent with specific tools for database diagnostics.
- Implement the handoff trigger within the triage agent's logic to initiate the transfer.
- Verify that the specialist agent receives the full conversation history and state.
- Monitor the handoff transition to ensure the specialist assumes direct user interaction.
The flow shows how a user request moves from a triage agent to a specialist agent.
Initial intent classifier
Deep diagnostic agent
System logs and state
- User → submits query → Triage Agent
- Triage Agent → handoffs context → Technical Specialist
- Technical Specialist → queries logs → Database
- Technical Specialist → provides resolution → User
Expected business outcome
Improved resolution efficiency by reducing the need for users to repeat information, as the specialist agent inherits the full context of the triage phase.
Limitations and checks
The primary tradeoff is the potential for context bloat; as the handoff chain grows, the conversation history passed to the specialist can become excessively large, which should be checked by monitoring token usage and response latency.