Implementation Checklist for AI Projects
A lightweight checklist covering scope, data access, evaluation, monitoring, and fallback plans.
Before launch: define success metrics, create an eval set, decide on human-in-the-loop points, log key events, and implement graceful fallbacks. After launch: monitor, retrain, and expand.
