This checklist helps students understand that AI delivery quality depends on more than pushing code. The same logic applies to daily website automation: validation, traceability, and post-release checks must exist before users see the result.
What students can learn
- How evaluation thresholds can become release gates.
- Why automated output should be validated before deployment.
- How monitoring plans support safe AI adoption after release.
Recommended classroom use
- Use the checklist after an applied AI project sprint.
- Ask groups to justify each release gate they include.
- Compare operational risk between unsupervised automation and evidence-based release plans.