What is an Agent Handoff?

2 min read Updated

An agent handoff is the transfer of control, context, and responsibility from one AI agent to another during a workflow — enabling specialized agents to handle different phases of a complex task.

WHY IT MATTERS

Handoffs are a core primitive in multi-agent systems. A customer service agent might hand off to a billing agent when the conversation turns to payments. A research agent hands off to a trading agent when it's time to execute. The OpenAI Agents SDK makes handoffs a first-class concept.

The quality of a handoff depends on context transfer. The receiving agent needs enough context to continue effectively — conversation history, task state, relevant data — without being overwhelmed by irrelevant information. Poor handoffs lead to agents repeating questions or losing important context.

For financial operations, handoffs carry additional complexity. If a research agent identified a trade and hands off to a trading agent, the financial authority and spending limits must transfer correctly. The trading agent should only have the authority needed for this specific operation.

HOW POLICYLAYER USES THIS

PolicyLayer manages financial context during agent handoffs — ensuring spending authority is properly scoped when control transfers between agents. The receiving agent inherits only the financial permissions needed for its specific task.

FREQUENTLY ASKED QUESTIONS

What context should be transferred during a handoff?
Transfer task-relevant context (what needs to be done), conversation history (if customer-facing), relevant data (research findings, analysis results), and authority scope (what the receiving agent is allowed to do).
How do you handle failed handoffs?
Implement fallbacks: retry the handoff, return control to the original agent, or escalate to a human. For financial handoffs, ensure no transactions are left in a pending state during the failure.
Can handoffs be bidirectional?
Yes. Agent A can hand off to Agent B, which can hand back to Agent A (or to Agent C). OpenAI's Agents SDK and similar frameworks support this natively.

FURTHER READING

Enforce policies on every tool call

Intercept is the open-source MCP proxy that enforces YAML policies on AI agent tool calls. No code changes needed.

npx -y @policylayer/intercept
github.com/policylayer/intercept →
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