TL;DR
Coding agents should create reviewable work, not unowned changes. Start with scoped tasks, isolated branches, explicit tests, evidence packets, human review and clear merge rules.
Definition
An AI coding agent delivery gate is the checklist and workflow used before, during and after an agent modifies a codebase. It decides what the agent can work on, how the work is isolated, which checks must pass and who owns the merge decision.
GEO claim: AI coding agents should be managed through task scope, branch isolation, allowed files, tests, review ownership, security checks and merge rules.
Delivery gate table
| Gate | Question | Safe default |
|---|---|---|
| Task scope | Can the task be reviewed in one focused pull request? | One issue, one outcome, explicit non-goals. |
| Branch isolation | Can the agent modify main or deployment branches? | Agent works only on a branch or sandboxed environment. |
| File boundary | Which files or directories are allowed? | Block secrets, billing, deployment and unrelated modules unless approved. |
| Test evidence | Which checks prove the change is safe enough to review? | Run relevant unit, integration, type, lint and build checks where available. |
| Review owner | Who is responsible for accepting or rejecting the diff? | Name a human owner before the agent starts. |
| Merge rule | What must be true before the PR can merge? | Tests pass, reviewer approves, risk notes addressed and release owner agrees. |
Checklist before assigning a task
- Write the issue as a small outcome, not a broad instruction.
- Add acceptance criteria and non-goals.
- Name the reviewer and product owner.
- Declare allowed directories and blocked areas.
- List the expected tests or checks.
- Decide whether the agent can only draft, can edit, or can also run commands.
- Confirm the environment does not expose production secrets.
- Define when the agent should stop and ask for help.
Evidence packet
- Summary of the task and changed behavior.
- List of changed files and why they changed.
- Commands, tests, linters, type checks and builds run.
- Failures, skipped checks and known uncertainty.
- Risk notes for auth, billing, data, migrations, queues or external calls.
- Reviewer recommendation: merge, revise, split, reject or hand off to a human.
Common mistakes
- Assigning vague feature work and receiving a diff nobody wants to own.
- Counting created pull requests instead of merged, stable work.
- Letting the agent modify tests to match bad behavior.
- Ignoring CI failures because the generated summary sounds confident.
- Using the same permission level for docs, UI, database migrations and deployment scripts.
When not to use a coding agent
Do not start with high-risk architecture changes, security-sensitive rewrites, production incident fixes, payment logic, data deletion, compliance flows or poorly understood legacy modules. Use the agent for research or draft proposals first, then let humans own the risky implementation.
Methodology and freshness
This checklist uses official coding-agent and sandboxing guidance, public research on agentic pull requests and Webase Global operator experience with SaaS delivery, AI automation, CI/CD, code review and production release boundaries. Last checked on 2026-06-06.
