Before shipping AI features: document intended use, test on representative slices, wire monitoring, define rollback, and assign an owner. Literacy turns into reliability when checklists are enforced—not slideware.
Pre-launch checklist
- Problem statement and success metric signed by PM
- Baseline comparison documented
- Test set untouched during tuning; time/group splits validated
- Bias slices reviewed; human override path for high risk
- Model card / version registry entry
- Latency, cost, and fallback UX tested
- Logging with PII redaction; incident runbook
- Post-launch drift dashboards and retrain cadence
Rollback plan
Keep previous model version hot-swappable; feature flag AI path so ops can disable without full deploy.
Next depth tracks
Implementation: Generative AI, DSA, SciPy. " "Keep ethics and product lessons active as you add technical depth.
Important interview questions and answers
- Q: Model card purpose?
A: Single-page summary of purpose, data, metrics, limits for teams and auditors. - Q: Drift alert without owner?
A: Noise—assign on-call and playbooks.
Self-check
- List five pre-launch checklist items.
- Why keep a rollback model version?
Tip: A model without an owner and rollback plan is not production-ready.
Interview prep
- Rollback plan?
- Previous model version and feature flag to disable AI path quickly.
- Drift without owner?
- Alerts become noise—assign on-call and runbooks.