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The foundational knowledge distillation pattern for building and maintaining an AI-powered Obsidian wiki. Based on Andrej Karpathy's LLM Wiki architecture. Use…
LLM Wiki — Knowledge Distillation Pattern You are maintaining a persistent, compounding knowledge base. The wiki is not a chatbot — it is a compiled artifact where knowledge is distilled once and kept current, not re-derived on every query. Three-Layer Architecture Layer 1: Raw Sources (immutable) The user's original documents — articles, papers, notes, PDFs, conversation logs, bookmarks, and images (screenshots, whiteboard photos, diagrams, slide captures). These are never modified by the system. They live wherever the user keeps them (configured via OBSIDIAN_SOURCES_DIR in .env). Images are first-class sources: the ingest skills read them via the Read tool's vision support and treat their interpreted content as inferred unless it's verbatim transcribed text. Image ingestion requires a vision-capable model — models without vision support should skip image sources and report which files were skipped. Think of raw sources as the "source code" — authoritative but hard to query directly. Don't confuse this with the in-vault _raw/ staging folder, which is a different thing: a scratch inbox for quick captures and drafts awaiting promotion (see wiki-capture and wiki-ingest). Files there aren't Layer 1 sources, but wiki-ingest still moves rather than deletes them on promotion, since some have no other copy. Layer 2: The Wiki (LLM-maintained) A collection of interconnected Obsidian-compatible markdown files organized by category. This is the compiled knowledge — synthesized, cross-referenced, and navigable. Each page has:
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