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AI engineering8 min read

A production-readiness checklist for AI features

A release review covering user value, data, evaluation, security, fallback, observability, and operational ownership.

Prove the workflow

Production readiness starts with the user decision or task the feature supports. Test representative inputs, edge cases, adversarial content, latency, integration failures, and the experience when confidence is insufficient.

Review controls as a system

Bring product, engineering, security, data, and operations together for one evidence-based review. Confirm data boundaries, permissions, evaluation results, human review, disclosure, monitoring, support, and recovery.

  • Purpose and users are explicit.
  • Evaluation data and thresholds are versioned.
  • Actions use least privilege and validation.
  • Fallback and disable paths have been exercised.
  • Dashboards, alerts, runbooks, and ownership exist.

Release narrowly and learn

Limit the first production scope, watch both technical and user outcomes, and define in advance which signals will pause or expand the release. Feed corrections and incidents back into evaluation and architecture decisions.