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# Karpathy's LLM Wiki Pattern — Original Reference
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Source: https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f
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## Core Insight
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"The wiki is a persistent, compounding artifact. The knowledge is compiled once and then kept current, not re-derived on every query."
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Human curates sources and asks questions; LLM maintains the knowledge system. Obsidian becomes the IDE, the LLM becomes the programmer, and the wiki becomes the codebase.
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## Why This Beats RAG
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Traditional RAG rediscovers knowledge on every query — it searches raw sources, pulls relevant chunks, and synthesizes an answer from scratch. The LLM Wiki compiles knowledge once into maintained pages, so queries hit pre-synthesized, cross-referenced content.
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## Key Operations
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| Operation | What it does | When to use |
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|---|---|---|
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| **Ingest** | Read new sources, extract key information, update 10-15 wiki pages, maintain consistency | When new documents arrive |
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| **Query** | Answer questions against compiled wiki with citations | When the user asks something |
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| **Lint** | Identify contradictions, orphaned pages, stale claims, missing cross-references | Periodic maintenance |
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## Recommended Tools
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- **Obsidian** — IDE for browsing and exploring the wiki
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- **Web Clipper** — Browser extension for converting articles to markdown
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- **Marp** — Markdown-based slide decks from wiki content
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- **Dataview** — Obsidian plugin for querying page metadata
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- **qmd** — Local search engine with BM25/vector hybrid search
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## Applications
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- Personal tracking (goals, psychology, self-improvement)
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- Research (building comprehensive understanding over weeks/months)
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- Book annotation (companion wikis with characters, themes, plot connections)
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- Team/business (wikis from Slack threads, meeting transcripts)
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- Due diligence, competitive analysis, trip planning
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## Community Extensions Worth Knowing
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- **Provenance tracking** — Record which source files produced each claim, detect staleness through content hashing
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- **Hierarchical inheritance** — Parent-child page relationships instead of flat indexing
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- **Decision records** — Capture why the wiki evolved, not just what changed
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- **Two-tier LLMs** — Local models for sensitive data, cloud for the rest
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- **Graph databases** — Typed ontologies instead of markdown links
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