AI Knowledge Operations

Launching AI is a project. Running AI is operations. AI knowledge operations covers the recurring work: review queues, source diffs, failed tests, owner escalations, and release coordination. Teams that skip ops inherit a bot that rots quietly until a customer posts a screenshot on social media.

Knowledge ops is where accountability lives. Someone must answer why last week's policy change is not reflected in answers yet. Ops rhythms make that question boring and answerable.

Define cadences: weekly review sweeps, monthly coverage audits, immediate gates on high-risk collection changes. Assign operators who sit between support, docs, and engineering.

Tooling connects monitoring alerts to tickets, failed tests to release blocks, and feedback thumbs-down to doc updates. Metrics track stale collection percentage, test pass rates, and citation completeness.

Runbooks document how to handle source removals, emergency takedowns, and cross-app consistency checks after major launches.

Nintendo knowledge ops runs a Monday queue: expired review dates on Help Center articles, open alerts from Refund Policy changes, and failed chatbot tests from the prior deploy. Operators assign owners before any release train moves. A single blocked refund test stops the Wednesday chatbot update until fixed.