---
title: "How to Design Reliable Handoffs Between AI Agents"
description: "Use typed handoff packets, acceptance checks, and clear responsibility boundaries between specialist agents."
language: en
canonical: https://navinresearch.com/blog/agents/agent-handoffs.md
topics: ["AI agent handoff", "agent routing", "typed agent state"]
---

# How to Design Reliable Handoffs Between AI Agents

Use typed handoff packets, acceptance checks, and clear responsibility boundaries between specialist agents.

**Short answer:** A reliable handoff is a contract, not a conversational suggestion. Include the objective, relevant state, evidence, constraints, unresolved questions, and an explicit acceptance condition. The receiving agent should be able to reject malformed work.

## Implementation steps

1. Create a versioned handoff schema with required and optional fields.
2. Summarize decisions separately from observations and raw evidence.
3. Validate the packet before routing it to the next agent.
4. Record acceptance, rejection, or escalation as a trace event.

## Validation checklist

- Test missing fields and incompatible schema versions.
- Confirm secrets and unnecessary personal data are excluded.
- Require source links or tool-result identifiers for factual claims.

## Common mistakes

- Passing a huge transcript as state.
- Allowing two agents to believe they own the same side effect.
- Treating a handoff as successful before the receiver validates it.

## Practical decision

Ship the smallest design that passes the checks above. Record the model, prompt, tool, dataset, and runtime versions used in testing so later changes can be compared rather than guessed. Recheck the linked documentation before relying on provider-specific limits, model names, prices, or preview features; those details change more quickly than the engineering principles in this note.

## Official sources

- [OpenAI, New tools for building agents](https://openai.com/index/new-tools-for-building-agents/)
- [Anthropic, Effective context engineering for AI agents](https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents)

---

Reviewed: 2026-08-24. This concise engineering note is educational, not a claim that Navin Research created or independently verified the cited provider technology.