More AI Code, Less Certainty: Why Production Measurement Is the New Code Review | Harness Resource | Harness

AI coding tools are helping teams generate more code than ever, but the real bottleneck has moved downstream: review fatigue, brittle release processes, and uncertainty about whether AI-generated changes actually improve the product. Manual review still matters, but it cannot be the only line of defense when code volume keeps accelerating. In this webinar, we’ll explore why production measurement is becoming the new gold standard for validating AI-generated software. You’ll learn how progressive delivery, feature flags, guardrail metrics, experimentation, and automated rollback help teams release AI-assisted changes safely, observe real-world impact, and make decisions based on outcomes instead of reviewer confidence alone. We’ll also show how Harness Feature Management & Experimentation helps teams turn every release into a measurable, controlled experiment, so they can move faster without gambling on quality, reliability, or customer experience. Key Takeaways: 1. AI coding speeds up development, but creates new challenges in review, release safety, and validating quality at scale. 2. Production measurement is becoming the best way to evaluate AI-generated code using feature flags, experiments, guardrails, and automated rollback. 3. Harness Feature Management & Experimentation helps teams ship AI-assisted changes faster by turning every release into a controlled, measurable experiment.