Summary: Large AI models can quickly generate product documentation that looks complete. But whether that content matches real user paths, has been verified, and is safe to publish for external users is still a high-certainty problem. This post records a real documentation engineering practice: how we moved from one-off AI chat generation plus manual patching to a verifiable and reusable documentation production flow built around Rules, Skills, validation Harnesses, and human review. Through this workflow, the documentation team improved the customer-facing quality of complex software docs and moved its focus further upstream, from content writing to documentation platform engineering, knowledge architecture design, and developer experience.