chore: clean repo for public distribution
- Remove verbatim Nate Herk transcript from .raw/ (copyright) - Rewrite wiki/sources page as synthesis + attribution + link to original - Keeps all original concept/entity pages (our synthesis, not third-party content) - .raw/ folder preserved for users to add their own sources - This repo is now safe to share publicly as a plugin/skill library
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Daniel
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---
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type: source
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title: "Nate Herk LLM Wiki Transcript"
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title: "Nate Herk — Obsidian + Karpathy Just 10x'd Claude Code Projects"
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source_type: transcript
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author: "Nate Herk"
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date_published: 2026-04-07
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@@ -9,10 +9,10 @@ confidence: high
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key_claims:
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- "LLM wiki makes knowledge compound like interest — nothing is re-derived on every query"
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- "Hot cache (~500 words) enables cross-project context without crawling the full wiki"
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- "One article can generate 15-25 wiki pages with full cross-references"
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- "One user dropped token usage by 95% switching from inline context files to wiki"
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- "One article generates 15-25 wiki pages with full cross-references"
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- "One user dropped token usage by 95% switching from inline context files to a wiki"
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- "Obsidian is the IDE, Claude is the programmer, the wiki is the codebase"
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- "Index file is enough at small scale (~100 sources) — no RAG infrastructure needed"
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- "Index file is sufficient at small scale (~100 sources) — no RAG infrastructure needed"
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created: 2026-04-07
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updated: 2026-04-07
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tags:
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@@ -26,69 +26,70 @@ related:
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- "[[Hot Cache]]"
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- "[[Compounding Knowledge]]"
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- "[[Andrej Karpathy]]"
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- "[[index]]"
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- "[[sources/_index]]"
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sources:
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- "[[.raw/nate-herk-llm-wiki-transcript.md]]"
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- "[[index]]"
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sources: []
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---
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# Nate Herk LLM Wiki Transcript
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# Nate Herk — Obsidian + Karpathy Just 10x'd Claude Code Projects
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Raw source: [[.raw/nate-herk-llm-wiki-transcript.md]]
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**Original:** [Watch on YouTube →](https://youtube.com/@nateherk)
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**Credit:** All ideas in this summary belong to Nate Herk and Andrej Karpathy.
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Nate Herk demonstrates the [[LLM Wiki Pattern]] in practice. He shows two live vaults: one for his YouTube transcript archive (36 videos) and one personal second brain. He breaks down Andrej Karpathy's original post and shows a 5-minute setup workflow.
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> This page is a wiki-style synthesis of the source — an example of what cosmic-brain produces after ingesting a video/transcript. The raw source is not included in the repo.
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---
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## Key Takeaways
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## What This Source Is
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**The core insight**: normal AI chats are ephemeral. The wiki makes knowledge compound. Every source ingested, every question answered, every analysis filed — all of it stays and grows richer over time.
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Nate Herk demonstrates the [[LLM Wiki Pattern]] in practice using Claude Code and Obsidian. He shows two live vaults: a YouTube transcript archive (36 videos) and a personal second brain. He breaks down [[Andrej Karpathy]]'s original post and walks through a 5-minute setup.
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**The stack is simple**: Claude Code + Obsidian + a folder of markdown files. No vector databases, no embeddings, no infrastructure. Just files and Claude.
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---
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**The hot cache**: a ~500-word file (`wiki/hot.md`) that captures recent context. In an executive assistant setup, this prevented having to crawl dozens of wiki pages at the start of each session. See [[Hot Cache]].
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## Key Insights
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**Cross-project referencing**: other Claude Code projects can read this vault by pointing at it in their CLAUDE.md. Nate's executive assistant reads from his herk-brain vault. Token usage dropped significantly compared to inline context files.
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**The wiki compounds.** Normal AI chat is ephemeral — knowledge disappears when the session ends. The wiki pattern changes this: every source ingested, every answer filed back, every connection made persists permanently. See [[Compounding Knowledge]].
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**At scale**: the index file alone is sufficient for hundreds of pages. Vector RAG only becomes necessary at millions of documents.
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**The hot cache is the force multiplier.** A ~500-word file (`wiki/hot.md`) captures what happened recently. New sessions read it first. Cross-project references read it first. It saves crawling dozens of wiki pages just to answer "where were we?" See [[Hot Cache]].
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**The stack is intentionally simple.** Claude Code + Obsidian + a folder of markdown files. No vector databases, no embeddings, no infrastructure. The index file alone navigates hundreds of pages.
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**Cross-project power.** Other Claude Code projects can reference this vault via their CLAUDE.md. Nate's executive assistant reads from his personal brain vault. Token usage dropped significantly vs inline context files.
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**95% token reduction.** One X user turned 383 scattered files and 100+ meeting transcripts into a compact wiki and dropped token usage by 95% when querying with Claude.
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**At scale.** The index file alone is sufficient for hundreds of pages. Vector RAG only becomes necessary at millions of documents.
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---
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## The Live Demo
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Nate ingested one article (AI 2027) and Claude produced 23 wiki pages in ~10 minutes:
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- 1 source summary
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- 6 entity pages (people)
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- 5 organization pages
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- 1 AI systems page
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- Multiple concept pages
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- 1 analysis
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- Open questions
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This is what one ingest looks like when the wiki pattern is applied correctly.
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---
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## Obsidian as IDE
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Obsidian is just a markdown viewer with graph visualization. The graph view shows which pages are hubs (many connections) and which are orphans (none). Real-time — you can watch the wiki grow as Claude creates pages.
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The key Obsidian features used:
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- Graph view — visualize the knowledge structure
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- Backlinks — follow connections between pages
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- Dataview — query pages by frontmatter
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- Web Clipper — send articles directly to `.raw/` from any browser
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---
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## Workflow Demonstrated
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1. Install Obsidian, create a vault
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2. Paste Karpathy's LLM wiki idea into Claude Code
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3. Claude scaffolds the structure (raw/, wiki/, CLAUDE.md, index, log)
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4. Drop a source into `.raw/` using Web Clipper
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5. Tell Claude: "ingest this"
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6. Claude reads, creates 15-25 wiki pages, cross-references everything
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7. Query the wiki for insights
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The ingest for one article (AI 2027) took 10 minutes and created 23 pages: 1 source, 6 people, 5 organizations, 1 AI systems page, multiple concepts, plus an analysis.
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---
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## Entities Mentioned
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- [[Andrej Karpathy]] — originated the LLM wiki pattern
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- Nate Herk — demonstrated the pattern in this video
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Obsidian serves as the visual layer. Key features used:
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- **Graph view** — see which pages are hubs and which are orphans
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- **Backlinks** — follow relationships between pages
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- **Dataview** — query pages by frontmatter
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- **Web Clipper** — send articles to `.raw/` from any browser in one click
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---
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## Connections
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See [[LLM Wiki Pattern]] for the full architecture.
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See [[Compounding Knowledge]] for the core insight on why this works.
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See [[Hot Cache]] for the session context mechanism.
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- [[LLM Wiki Pattern]] — the full architecture this source demonstrates
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- [[Compounding Knowledge]] — why the pattern produces increasing returns
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- [[Hot Cache]] — the session context mechanism Nate added to his executive assistant vault
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- [[Andrej Karpathy]] — originated the LLM wiki pattern that this video explains
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