Coding Agent Rollout Playbook

Start with tasks that are common enough to matter but bounded enough to review: dependency upgrades, test fixes, documentation updates, small refactors, migration prep, and exploratory bug analysis.

Avoid beginning with high-risk areas such as authentication, payment logic, destructive database migrations, or production incident response. Those workflows can come later after the team understands the agent's behavior.

The key metric is not how much code the agent writes. Track accepted diffs, reviewer corrections, reverted changes, tests added, and time from prompt to merged pull request.

Ask reviewers to tag agent-created changes for the first month. That creates a lightweight feedback loop and gives engineering leads evidence before expanding usage.

Agents should run with least privilege. Use branch protection, secret scanning, scoped tokens, and command approval for destructive operations. If a tool can read secrets or push changes, treat it as production automation.

Write rules for when agents can run commands, install dependencies, modify lockfiles, change infrastructure, or open pull requests. Clear rules reduce fear and reduce accidental misuse.

Agent output should be reviewed as seriously as human output. Require tests for behavior changes, explain large diffs in plain language, and check whether generated code follows local architecture rather than generic patterns.

The strongest teams use agents to improve review quality too: summarize diffs, list edge cases, generate regression tests, and compare implementation against the ticket's acceptance criteria.