Karpathy's hand-curated LLM wiki, without the hand-curation

The shape of a personal knowledge base for the AI era, with the AI doing 80% of the upkeep.

The pain

Andrej Karpathy described the problem: keep a personal LLM wiki of the answers worth remembering. Three layers (raw transcripts, distilled wiki pages, structured schema) and three operations (ingest, query, lint). He maintains his by hand because no consumer surface offers the right shape.

That works for Karpathy. For most people, the hand-curation tax is too high. So they don't do it, and the answers leak away.

What Memory.Wiki does

Same shape as Karpathy's. Different effort:

Layer His way Memory.Wiki way
Raw Manual transcript copy + folder organization One-click capture from any AI tool, automatic permanent URL
Wiki Hand-write distilled pages Auto-synthesis with diff/accept. New captures generate proposed wiki updates, you accept or skip
Schema Hand-tag entities + relationships Embeddings + semantic graph + cross-ref rollup, all automatic
Ingest Manual /memory.wiki capture from any coding agent + paste/file drop
Query grep + read /recall API: vector + BM25 hybrid, paragraph-level chunks
Lint Periodic manual review Hub lint runs automatically and surfaces gaps, conflicts, orphans

The architecture is the same. The maintenance burden drops by roughly 80%. You stay in the loop on what enters the wiki layer (the diff/accept UI is intentional friction); everything else is handled.

What this case actually replaces

If you're already running a personal Notion, Obsidian, or DEVONthink for AI outputs and feel the hand-curation tax, Memory.Wiki is the lower-effort version of the same thing. If you're not running anything because the tax was too high, Memory.Wiki is what makes it possible.

See it in shape