LLM Wiki

An LLM Wiki is a modern design pattern for personal-knowledge (PKM). It treats a user's personal knowledge repository as a clean, interlinked, machine-readable "codebase" that growing AI agents can operate on over time.

This replaces fleeting AI chats and unstructured RAG databases with a persistent, compounding core of intelligence.

The LLM Wiki is a modern design pattern for personal knowledge management (PKM) popularized by Andrej Karpathy in early April 2026. It represents a paradigm shift from traditional Retrieval-Augmented Generation (RAG)—where an AI searches through unstructured files on the fly—to a compiled, persistent, and compounding knowledge base.

Karpathy's viral analogy

Karpathy summarized the ultimate relationship between the human, the AI, and the files with his famous analogy:

"Obsidian is the IDE; the LLM is the programmer; the wiki is the codebase."

He highlighted that traditional AI chat windows are "stateless" and fleeting, forcing you to reconstruct context every time you start a session. In contrast, an LLM Wiki compiles your unstructured raw inputs (diaries, PDFs, articles, research notes) into a clean, interlinked Markdown codebase ([slug]) that grows more intelligent and interconnected over time.

Farza's follow-up & Farzapedia

Developer Farza (founder of buildspace) created farzapedia as the definitive real-world proof of concept for the LLM Wiki pattern:

• The Input: Fed approximately 2,500 unstructured entries (comprising personal diary entries, Apple Notes, and raw iMessage histories) to an LLM agent.
• The Compilation: The LLM agent parsed, categorized, and synthesized the raw materials, outputting ~400 beautifully structured, clean, and heavily interlinked wiki articles.
• The Takeaway: Farzapedia demonstrated that an LLM can act as an objective, disciplined "gardener" of a human's mind, creating a private, local, and navigably explicit knowledge base that can be queried by any downstream AI.

Integrating the LLM Wiki in this vault

This llm-wiki-cli repository is built directly on the principles of the LLM Wiki design pattern. It enforces:

1. Declarative Frontmatter: Structuring YAML-LD metadata to make pages machine-readable.
2. Procedural Automation: Using subcommands like wiki check to validate shapes, and wiki render to execute SPARQL queries dynamically, compiling the graph's intelligence back into static Markdown.