AI junior developer adoption

1. Publish AI partnership charter covering goals, responsibilities, and communication norms.
2. Document task categories suitable for Level 0 (docs/summaries) and Level 1 (tests/simple fixes); gain team agreement.
3. Create bot accounts, enforce least-privilege access, and enable audit logging for all AI-authored activity.
4. Provide mentors with dedicated time in sprint planning and clarify approval SLAs for AI-generated work.
5. Establish review checklist tailored to AI contributions (tests required, prompt context, security considerations).
6. Log each AI-generated change with outcome (accepted, edited, rejected) plus reason; review trends weekly.
7. Run sprint-level retrospectives focused on mentorship experience and developer sentiment.
8. Update the AI skill ladder when acceptance criteria are met; expand scope only after stability at current level.
9. Refresh onboarding docs and prompts whenever workflows change to keep new teams aligned.

Prerequisites

• Coding standards, branching strategy, and review process already documented.
• Mentors empowered by leadership to invest time in coaching automation.

Pitfalls

• Allowing AI to produce large changes without incremental review.
• Neglecting to communicate vision, leading to fear or resistance.
• Tracking metrics manually, which causes data to degrade.

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