@Asteri_eth: Karpathy found a way to reduce token consumption by 90% The problem is that the LLM re-reads the same files over and ov…

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Summary

Karpathy's 'Wiki Layer' method reduces LLM token usage by up to 90% by having the model clean, structure, and link data into a local Markdown knowledge base, eliminating repeated reading of raw files.

Karpathy found a way to reduce token consumption by 90% The problem is that the LLM re-reads the same files over and over again, loses context between documents, and provides less accurate answers as a result The solution is called Wiki Layer the LLM cleans, structures, and links all your data once, after which it never works with raw files again Three folders `raw/` for originals, `wiki/` for a clean knowledge base in Markdown, and files with rules for the agent Result up to 90% token savings on repeat queries, automatic links between documents, and a visual knowledge graph in Obsidian Everything stays on your local machine nothing goes to the cloud
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