Claude Code agent loops with handoffs and proof

Overview
Agent Engineering
June 20, 2026Updated June 28, 2026Agent EngineeringClaude Code handoff loop

Rework prompt-heavy Claude Code workflows into handoff-driven agent loops that plan, act, review, and preserve proof across each development cycle.

Claude CodeAgent loopsHandoffsProof-driven development

What you will build

This guide builds a handoff-driven Claude Code loop. The loop is intentionally simple: a planner writes the next slice, a worker executes it, a reviewer checks it, and a handoff file preserves what happened.

Use this when a project needs repeated agent work but the risk is too high for blind autonomy.

Workflow

Handoff-driven agent loop

  1. 1

    Plan the next slice

    Write the smallest useful task and the proof it requires.

    Why: The worker should not infer scope from a vague wish.

  2. 2

    Execute in bounds

    Let the worker inspect and edit only what the slice needs.

    Why: Bounded work keeps review possible.

  3. 3

    Review before continuing

    A reviewer checks behavior, tests, and unrelated changes.

    Why: Loops need friction at the right place.

  4. 4

    Write the handoff

    Capture files changed, evidence, unresolved risks, and next action.

    Why: The next cycle starts with facts.

  5. 5

    Continue or stop

    Proceed only if the reviewer passes and proof exists.

    Why: This prevents momentum from outrunning correctness.

Setup
3

Before you start

  • A coding-agent workflow with at least one worker and one reviewer role
  • A repository with repeatable verification commands
  • A handoff file path such as .agent/handoffs/current.md

Step 1 - Create the handoff template

# Agent handoff

Goal:

Current slice:

Files inspected:

Files changed:

Verification run:

Reviewer result:

Risks:

Next action:

This file should be updated after every meaningful cycle. Keep it short enough that the next agent will actually read it.

Step 2 - Define the planner role

The planner chooses the next slice. It should not edit code. Its output is a task card:

Task: Add the DB-GPT BM25 article.
Files likely needed:
- content/tutorials/dbgpt-bm25-elasticsearch-rag-guide.md
- src/lib/site-content.ts
Proof:
- article route builds
- blog card links to article
- lint passes
Stop if:
- content renderer cannot parse required Markdown

Good planner output makes the worker boring.

Step 3 - Define the worker role

The worker executes one task card. It should finish by updating the handoff:

Files changed:
- content/tutorials/dbgpt-bm25-elasticsearch-rag-guide.md

Verification run:
- pending

Risks:
- Need final lint after blog card updates.

Next action:
- Add blog card and run npm run lint.

The worker should not claim final success before verification.

Step 4 - Define the reviewer role

The reviewer has a narrow job:

  • check the task card against the diff;
  • identify missing proof;
  • catch unrelated changes;
  • request fixes;
  • pass only when evidence exists.

Reviewer output should be blunt:

Result: fail
Reason: Article exists, but no blog card links to it.
Required fix: Add BLOG.posts entry and rerun lint.

The reviewer is not there to be encouraging. It is there to protect the loop.

Step 5 - Keep proof attached to each cycle

A handoff without proof is only a status update. Add the exact command or artifact:

Verification run:
- npm run lint: passed
- npm run build: passed

Evidence:
- /tutorials/dbgpt-bm25-elasticsearch-rag-guide generated by getTutorialEntries
- BLOG.posts links to /tutorials/dbgpt-bm25-elasticsearch-rag-guide

For UI work, include screenshots or route checks. For data work, include sampled query outputs. For code work, include tests.

Step 6 - Avoid the two common failure modes

First failure mode: every agent reads every document. Fix it by putting only the current contract and handoff in the default context.

Second failure mode: agents produce reports but nobody merges the reports into the next action. Fix it by making the handoff file the only active run state.

Step 7 - Scale the loop

After the simple loop works, add:

  • a registry for multiple active tasks;
  • agent-specific report folders;
  • a script that checks handoff freshness;
  • a final synthesis step;
  • a policy that blocks finish when proof is missing.

Do not start with the large system. Start with one handoff file and one honest reviewer gate.

Tutorial
Guide

Answer Engine Summary

Rework prompt-heavy Claude Code workflows into handoff-driven agent loops that plan, act, review, and preserve proof across each development cycle. Use this tutorial to turn Claude Code agent loop handoffs into a buildable workflow with prerequisites, source citations, implementation examples, review boundaries, and proof artifacts.

For AI search, the extractable answer is direct: Claude Code agent loop handoffs should be implemented as a bounded workflow with clear setup, source-grounded behavior, human review for risky actions, and a verification artifact before it is reused or scaled. The supporting keywords are Claude Code, Agent loops, Handoffs, Proof-driven development, Agent Engineering.

Source-Backed Guidance

This guide uses source article, source article, and Claude Code documentation as its source baseline. Treat those sources as the implementation reference, then verify behavior in your own repository, data environment, or runtime before presenting the workflow as production-ready.

SEO elementRecommendation
Primary queryClaude Code agent loop handoffs
Search intentimplementation guide
AudienceAI engineering teams using Claude Code loops, handoffs, and proof artifacts.
Citation angleExplain the build path, cite the source behavior, and show the verification artifact
Related internal pathsUse adjacent tutorials with matching tags.

Implementation Examples and Checks

ExampleHow to use itProof to capture
First setup passStart with a coding-agent workflow with at least one worker and one reviewer role.Command output, config diff, or local route evidence showing the environment is ready.
Controlled implementationUse a repository with repeatable verification commands for one narrow, reviewable case.A small artifact, report, test, retrieval result, or code diff that a reviewer can inspect.
Source-grounded reviewCompare the result against source article.A reference link plus notes on what changed from the source example.
Expansion decisionUse a handoff file path such as .agent/handoffs/current.md as the owner, approval input, or readiness check for the next scope.A written pass/fail decision with owner, limitation, and next action.

FAQ

FAQ

FAQ for Claude Code agent loop handoffs

What does this tutorial help me build?

It helps you build or evaluate Claude Code agent loop handoffs as a bounded workflow with setup steps, implementation examples, source citations, and verification evidence instead of a loose prompt or concept note.

Which keywords should this page target?

Target Claude Code agent loop handoffs as the primary phrase, then support it with Claude Code, Agent loops, Handoffs, Proof-driven development, Agent Engineering. Use those phrases in natural headings, examples, metadata, and related links rather than repeating them mechanically.

How should I validate the implementation?

Run the smallest command, route check, retrieval test, or code review that proves the workflow works in your environment. Capture the output and keep it next to the source references.

What should stay human-reviewed?

Keep data access, customer-facing output, regulated decisions, production code changes, financial actions, and destructive operations behind human review until logs, approvals, and recovery paths are proven.

How often should I refresh this tutorial?

Refresh it when the linked source docs, SDK behavior, model interfaces, or deployment target changes. AI-agent and RAG tutorials should be rechecked at least quarterly because platform behavior moves quickly.

References
3

References

The source articles discuss loop engineering and agent coordination from different angles. This guide combines those themes into a handoff loop that fits day-to-day repository work.

Stefan Creadore · @Eldergenix - generated and hand-seeded tutorials for governed agent systems