Knowledge Supply Chain

Right now, somewhere in this loop, a fact is changing. Watch one.

  1. Somewhere in this loop, a fact is changing right now.
  2. A new fragment arrives: a changelog note reading, PostgreSQL 14 is no longer supported.
  3. The system reads it and recognises two things inside the sentence: PostgreSQL, and the version, 14.
  4. A human reviews it and marks it trustworthy. Nearby, a fact from a meeting — a Knowledge Session — gets the same review.
  5. The validated fact joins a corpus: a small, connected cluster of related facts about the same system.
  6. That corpus is one part of a much larger, connected whole: Graph Memory. An older fact, elsewhere in the graph, is now in question because of this new one.
  7. Activity converges on the Knowledge Compiler, which takes the connected facts and produces several different outputs at once.
  8. The outputs reach three different readers: a human gets documentation and support material, a developer gets OpenAPI, and an AI agent gets MCP, prompt recipes and runbooks — together, the Agent Kit. All of it passes through the same API.
  9. An agent tries to install the system on a real server, using the runbook it was given. Something doesn’t match, and the install fails.
  10. The failure itself becomes a new fact, and it travels back into the system instead of disappearing.
  11. It rejoins the same corpus it came from, slightly improving it. This is the Discovery / Publishing loop: the system doesn’t just store knowledge, it keeps it correct. The loop continues.
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