The LLM wiki
Karpathy's pattern: the AI keeps a set of interlinked pages current as sources arrive, so knowledge is compiled once and maintained, not rebuilt on every question.
Most AI tools that work on your documents answer a question by reading the files afresh every time. The LLM wiki, a pattern Andrej Karpathy described in 2026, does something different. The model keeps a set of interlinked pages and maintains them as new material arrives, so the knowledge is compiled once and kept current rather than rebuilt on every question. You add the sources. The machine does the writing and the cross-referencing.
Two operations run it. Ingest: a new source is read against the schema and every page it touches, often ten or fifteen, is updated in one pass, with contradictions flagged rather than silently overwritten. Query: a question is answered from the pages, and any synthesis worth keeping is written back as a new, permanent page, so the next question starts further ahead. The living account plan is this pattern applied to one key customer, and the reason it beats RAG is that something accumulates.
Set out in full in: Karpathy (2026); Creating Customer Value Propositions with AI (Kogan Page, 2027), chapter 9.
Related terms
The living account plan
Something closer to a brain than a binder: an account plan an AI maintains from raw sources, against your methodology, so it is current when you open it.
Retrieval-augmented generation
The model reads your files afresh to answer each question. It works, but nothing accumulates. Each answer starts from a blank page.
The schema
The set of rules that turns a generic chatbot into a disciplined maintainer of your account plan. For a KAM, the schema is your sales methodology.
AI agent
Software that takes a goal, plans the steps, uses tools and keeps working until it is done. On the buyer's side it is the procurement of the future; on yours it maintains the plan.
See the method run on one real account in three days: the One Page Proposition.