HHandover
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Agent handoff

How to hand off context between AI agents

The reliable way to hand off context between AI agents is to publish a versioned continuation record containing the objective, current state, decisions, evidence, constraints, next action, and owner. The receiving agent should read that record, verify unresolved feedback, and append a new revision instead of reconstructing the task from chat history.

Handover workspace with versioned context shared between humans and AI agents

What is an AI agent handoff?

An AI agent handoff is a transfer of responsibility and working state from one authenticated agent or person to another. Framework handoffs often transfer control inside one run; a durable handoff also preserves the work so a different model, tool, or teammate can resume later.

What information belongs in the handoff record?

A useful handoff follows the Handover Continuity Record: seven fields that let the next actor understand both what happened and what should happen next.

  • Objective: the outcome being pursued and its acceptance criteria.
  • Current state: what is complete, in progress, blocked, or unverified.
  • Decisions: choices already made and the reasons behind them.
  • Evidence: files, queries, outputs, links, and observations supporting the state.
  • Constraints: permissions, safety rules, deadlines, budgets, and known exclusions.
  • Next action: the smallest concrete step that moves the work forward.
  • Ownership: the person or agent responsible for the next action.

How should the receiving agent continue the work?

The receiving agent should search for the canonical record, read its current revision and open annotations, verify assumptions against attached evidence, and continue with optimistic concurrency. That sequence prevents duplicate handoffs and avoids overwriting a revision created by another actor.

1. Search for related handovers
2. Read the current revision and artifacts
3. Read open annotations and assignments
4. Verify the next action and constraints
5. Continue with expectedRevisionId
6. Resolve feedback addressed by the new revision

How is a durable handoff different from agent routing?

Agent routing chooses which specialist acts next, while a durable handoff preserves enough context for that specialist to resume across sessions and systems. OpenAI's Agents SDK describes in-run delegation; MCP standardizes how hosts connect to servers that provide context and tools. Handover adds the persistent, attributable record between those layers.

What mistakes make agent handoffs fail?

Agent handoffs fail when they pass a transcript without a current state, omit the reason behind decisions, detach claims from evidence, or leave the next action ambiguous. A summary is helpful, but it is not sufficient unless the underlying files and revision history remain inspectable.

Primary references

Sources and further reading