The seven steps that turn a raw note into knowledge a company can actually use, and the four-beat loop that makes the system better every time it runs.
In the previous piece, we described the metabolism of an AI-native company as five mechanisms: Capture, Storage, Distribution, Transformation, Feedback. Two of them decide whether the rest works, and both are usually botched: Capture, and the Feedback loops that make a system learn from itself.
Capture is the step we get wrong most often. We capture everything raw, and we file it badly. Most of the "knowledge bases" we see inside companies — Notion, a Drive folder, an Obsidian vault — are landfills more than brains. For a piece of information to become knowledge, it has to be digested, not merely dropped somewhere.