LLM Wiki
An LLM Wiki is a persistent, structured knowledge base composed of Markdown files that is built and maintained by a large language model (LLM) agent rather than by humans directly. The concept was introduced by Andrej Karpathy in April 2026 as a pattern for personal knowledge management that shifts the role of the LLM from a passive retrieval-and-generation tool to an active knowledge compiler and curator[^c1]. The core insight is that knowledge should be compiled once at ingestion time and kept current, rather than being re-derived from scratch on every query as in traditional Retrieval-Augmented Generation (RAG) systems[^c2].
The architecture consists of three layers: an immutable raw sources layer containing original documents and materials, a wiki layer of LLM-generated and maintained Markdown pages with cross-references, and a schema layer (such as a CLAUDE.md file) that defines the conventions and workflows for the LLM to follow. Three core operations—ingest, query, and lint—govern the system's lifecycle, enabling knowledge to compound over time as each new source and query enriches the existing knowledge base.
The LLM Wiki pattern has generated widespread community adoption, with dozens of open-source implementations, commercial products, and academic papers emerging within weeks of its introduction[^c3]. Google Cloud formalized the underlying structure as the Open Knowledge Format (OKF) in June 2026, establishing a vendor-neutral specification for representing knowledge as Markdown files with YAML frontmatter[^c4]. The pattern has been compared to and contrasted with RAG and other knowledge management paradigms, with LLM Wiki positioned as a "knowledge compiler" paradigm suited for hundred-page-scale knowledge bases with depth and knowledge compounding as primary goals[^c5].