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AI Coding Agent Pilot Checklist
Free checklist from our AI coding agents guide
Plan a structured rollout for AI coding agents with clear readiness criteria, permissions, review gates, and success metrics.
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Instructions
Use this checklist to plan and evaluate an AI coding agent pilot. Complete each section before expanding from pilot to broader adoption. Share with engineering leads and security teams for alignment.
1. Pilot Scope
Pilot team:
Pilot duration:
Pilot sponsor:
Approved task categories (pick 3-5)
- Bug fixes in well-tested codebases
- Unit and integration test generation
- Code refactoring with existing test coverage
- Documentation and comment generation
- Boilerplate and scaffolding generation
- Dependency updates and migration scripts
- Data transformation and pipeline scripts
- Infrastructure-as-code templates
2. Tool and Agent Selection
- AI coding tools evaluated against security, privacy, and compliance requirements
- MCP server connections inventoried and scoped
- Agent model and version pinned for the pilot duration
- License and IP terms reviewed for AI-generated code
- Data handling policy confirmed (does code leave the environment?)
- On-prem vs. cloud hosting decision documented
3. Permissions and Access Controls
- File system access restricted to pilot repositories only
- No access to production environments or secrets
- Network access limited to required endpoints
- Git permissions scoped (branch creation, no direct main push)
- Tool invocations logged and auditable
- Agent cannot install packages or modify CI/CD without approval
4. Review and Approval Gates
- All AI-generated code goes through standard code review
- AI-generated PRs labeled or tagged for identification
- Security-sensitive changes require additional reviewer
- AI-suggested dependency additions require manual approval
- Generated tests validated for correctness (not just coverage)
- Review checklist updated to include AI-specific items
5. Success Metrics
Define measurable outcomes before the pilot starts.
| Metric | Baseline | Target | Actual |
|---|---|---|---|
| Time to complete approved task types | |||
| Code review pass rate (first review) | |||
| Bugs introduced per sprint | |||
| Developer satisfaction (survey) | |||
| Security findings in AI-generated code | |||
| Test coverage delta |
6. Risk Register
- Risk: AI generates insecure code | Mitigation: _____
- Risk: Over-reliance reduces code understanding | Mitigation: _____
- Risk: Sensitive data leaks to AI provider | Mitigation: _____
- Risk: AI introduces subtle logic errors | Mitigation: _____
- Risk: License/IP contamination | Mitigation: _____
7. Go / No-Go Decision
Decision:
Conditions for expansion:
Next review date:
Decision maker:
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Read: AI Coding Agents in 2026: How MCP Is Changing Software Development →