Ben Holmes (Developer Relations Lead at Warp) walks through his personal LLM knowledge-base pipeline: raw voice-dictated notes → agent-enriched markdown → generated wikis → nightly background automation → agent-built graph visualizations. 21 minutes, AI Engineer conference talk.

The pipeline: from scattered thoughts to browsable knowledge

  • Goal: turn a jumbled Apple Notes folder into something navigable, interconnected, and discoverable — by you AND your agents
  • Four stages: raw capture → enrichment → wikis → visualization
  • Notes stay plain markdown; his demo app is Hubble (hub.md) — free, open-source, agent-accessible

Stage 1 — raw capture: voice dictation wins

  • Dictation is ~200 wpm — the fastest way to get thoughts down, no formatting, no polish
  • Local options now: Handy (open-source, on-device model) or Voice Inc. ($20 lifetime; hotkey + mobile app — his pick)
  • Scrappy, rambly notes are fine — volume of raw material is what LLMs need to work with later

Stage 2 — enrich notes with an agent skill

  • An “enrich note” skill: timestamp (so later passes skip already-enriched files), tags, source research, related-note search → backlinks
  • Tags come from a controlled vocabulary in a reference file — instruct the agent to be reluctant to invent new ones (Claude “loves to get creative”)
  • Runs in any harness — he demos Warp, notes open-weight models (GLM 5.2) work just as well; batch mode finds every un-enriched note and processes them all

Stage 3 — generate wikis (the Karpathy idea)

  • The concept comes from Andrej Karpathy’s “LLM knowledge base” gist: raw directory + focus area → generated wiki
  • Example: an AI-news wiki grouping people, concepts, sources, and organizations (e.g. jazz musician Adam Neely on AI in music)
  • Workspace use case: meeting notes → generated people/organizations section with backlinks to every related meeting

Stage 4 — automate: run it on a cadence

  • Enrichment and wiki generation take time — run them nightly/weekly in the background instead of on demand
  • oz.dev (Warp’s cloud automation): a sandbox syncs your markdown via the Obsidian headless CLI (or git), runs the skill, syncs back
  • Codex automations work too, but they need the laptop open — cloud runs while you sleep

Stage 5 — visualizations: just ask an agent

  • No tool to install — tell an agent to build an HTML/Tailwind graph view of your notes
  • Clickable nodes, cluster view of what you actually care about, a “constellation” mode, habit/burndown charts
  • Good for spotting gaps in your thinking, not just browsing

“I wake up to a perfectly fresh wiki that I can review. It’s like the daily paper, but it’s your own.”