# Agentic engineering delivery loop

> Use coding agents to move a scoped feature from ticket to tested change, while retaining review, security checks, and release accountability.

- Canonical: https://gptnavi.com/workflows/agentic-engineering-delivery-loop
- Category: Coding
- Difficulty: Advanced
- Setup time: 3 hours
- Estimated time saved: 5-15 hours
- Last materially updated: 2026-08-19
- Best for: Engineering teams, Technical founders, Product engineers, Startups
- Tools: Linear, Codex, Windsurf, Devin, GitHub Copilot

## Quick answer

This workflow treats coding agents as implementation partners, not autonomous release owners. The team scopes a change, keeps tests and review visible, and signs off before deployment.

## When to use it

- Feature delivery
- Bug fix
- Refactor
- Test coverage improvement

## Steps

1. **Write an implementation-ready ticket** — Define the user outcome, scope, acceptance criteria, non-goals, affected systems, risks, and test cases. Tool: Linear. Expected output: A bounded engineering ticket.
2. **Ask for a plan before edits** — Have an agent inspect the codebase and propose a file-level plan, assumptions, and tests; a human approves scope. Tool: Codex. Expected output: A reviewed implementation plan.
3. **Implement in a contained branch** — Use an AI development environment to make small, reviewable changes and keep the original acceptance criteria visible. Tool: Windsurf. Expected output: A focused change set.
4. **Run a second-pass implementation** — Use a second agent for clearly scoped tests, migrations, or repetitive changes, then compare its output against the plan. Tool: Devin. Expected output: Additional implementation and test evidence.
5. **Review and release** — Use AI assistance for review suggestions, but require a responsible engineer to validate tests, security, behavior, and release notes. Tool: GitHub Copilot. Expected output: A human-approved release candidate.

## Prompt templates

### Feature implementation plan

Inspect this codebase request and propose a minimal implementation plan. Include affected files, data changes, acceptance criteria mapping, tests, rollout risk, and rollback plan. Do not edit yet. Ticket: [paste]

### PR review brief

Review this change against the ticket and tests. Find behavior regressions, security issues, edge cases, missing tests, migration risk, and scope creep. Give only actionable findings with evidence. Diff and ticket: [paste]

## Common mistakes

- Giving agents unbounded repository access
- Starting edits without accepted criteria
- Treating green tests as complete product validation

## Related workflows

- https://gptnavi.com/workflows/product-idea-to-coding-feature-spec
- https://gptnavi.com/workflows/ai-product-release-control-plane
- https://gptnavi.com/workflows/api-to-ai-operations-workflow