You bring the raw material; the AI agent files it.
This vault follows the Karpathy three-layer LLM-wiki pattern. raw/ holds your
immutable sources — interview notes, transcripts, specs — which you drop in and
never edit. wiki/ holds the structured, interlinked requirements knowledge
(glossary, stakeholders, use cases, stories, and more) that the AI agent reads
sources into and keeps current. A schema layer — CLAUDE.md, _templates/,
_system/anchors/ — defines the content types and conventions both layers share,
and evolves with you over time.
- Run
./dashboard.shto start the live dashboard (Docker) athttp://localhost:8080— a browsable view of the wiki, useful even while it's still empty. No Docker on this machine?./dashboard.sh localruns it directly with Python athttp://localhost:8000. - Open this folder in Obsidian (Open folder as vault) to navigate and graph-view the wiki directly.
- Point Claude Code at this same folder — it reads
CLAUDE.mdautomatically and discovers the bundled skills in.claude/skills/.
For a full walkthrough, see docs/GETTING-STARTED.md.
If you're running this as a workshop, see docs/WORKSHOP.md.