AI agents don’t escalate uncertainty. They just answer. One outdated document can reach thousands of users and downstream systems before anyone notices, and every new agent you deploy becomes another channel distributing it. The first instinct is to build more review capacity, fast. It doesn’t work. A knowledge manager can thoroughly review 350 to 600 pieces of content. The organization needs 5,000 to 15,000. Coverage stays at 8 to 12% no matter how many reviewers you add, while AI-assisted development runs 1.5 to 2.5x faster and cuts the half-life of documentation in half. The second instinct is to engineer around it. One CTO in the ebook describes six months building a context graph that worked perfectly on content that was already wrong. The Knowledge Accuracy Gap, a new ebook from Guru’s Rick Nucci and Hillary Curran, covers what works instead. Inside: Why one policy question returns six conflicting answers, all of them retrievable The two-layer architecture that puts a verified buffer between raw sources and every AI consumer How automated verification lifts coverage from 8 to 12% up to 60 to 80% without new headcount Why you cannot defend an AI answer you cannot explain
