Practical resources adapted from AI evaluation, retrieval readiness, and knowledge systems work. Each is tied to a documented method or case study — not produced independently.
A structured process for diagnosing why AI responses fail in a specific workflow — and identifying where the knowledge layer is the root cause. Built from the AI Response Quality Scoring method applied across 949 evaluated responses.
Download →A structured rubric for scoring AI responses across correctness, completeness, and clarity. Adapted from the 3C scoring model used to evaluate 949 responses across seven product teams.
A topic-level checklist for assessing whether content is scoped, structured, and clear enough to support retrieval-augmented workflows. Based on the working group assessment framework.