A production AI checklist keeps launches honest. Accuracy, cost, privacy, and monitoring must be green before you remove the feature flag.
Accuracy
- Golden set pass rate above threshold
- Citations or "I don't know" for knowledge tasks
- Human review for customer-facing publish paths
Cost
- Model tier chosen by job, not habit
- Token budget and alerts configured
- Caching for safe repeated answers
- Per-tenant metering live
Privacy
- Written rules for what may leave your VPC to providers
- PII scrubbing where required
- Retention and deletion documented
- Keys rotated and scoped
Monitoring and rollback
- Latency, error, and spend dashboards
- Feature flag kill switch
- Prompt version rollback path
- Incident owner named
Summary
If any pillar is missing, the launch is a demo. Production AI is operability, not only a working prompt.
Related: AI SaaS Development, AI MVP Development, Hire AI Developer.
Prakash Tank
Full-Stack Architect & Tech Enthusiast. Passionate about building scalable applications and sharing knowledge with the community.
