LLM Wiki
Dan PetersonSynopsis — AI-drafted from Dan's notes
Karpathy’s idea file proposes a different shape for personal knowledge bases. Rather than having a model search raw documents afresh every time you ask a question, you let it build and keep up a wiki: a set of interlinked Markdown pages that sits between you and your sources and grows with each one you add.
The design has three parts. The raw sources stay untouched. The wiki belongs to the model, which writes the summaries, the pages on people and concepts, and the links between them. A schema file sets the conventions. Three routines keep it going: ingesting a new source (a single source might touch ten or fifteen pages), answering questions from the wiki and filing the good answers back in, and linting for contradictions, stale claims and orphaned pages.
His argument for why it works is about maintenance. People abandon wikis because upkeep grows faster than value, and a model doesn’t get bored of upkeep. The human curates sources, directs the analysis, asks the questions and thinks about what it means. The model does everything else, and the human rarely writes the wiki at all.
Where I land
This works for well-cited material, or wherever the domain is easy to verify. Once you get into more abstract territory, like writing, philosophy or the kind of material in this garden, you need a viewpoint layer to guide your argument and the overall thesis of the wiki.
So the first question for anyone setting one up is the use case: technical documentation, or something more qualitative? For qualitative work I would add a verdict layer kept separate from the LLM, where you record in your own words and your own voice how you read each source. That is what shapes and refines your arguments.