There's a new kind of computer media in the enterprise: Write once, Read never. The docs are perpetually stale, constantly diverging from reality, and scattered across Confluence, SharePoint, GitHub, Webex (or Slack) threads, Notion, Obsidian - and in my personal life, add Apple Notes, Goodnotes, web clippings, and multiple Google Drives worth of docs and slides that nobody is ever going back to. Karpathy tweeted his LLM knowledge base wiki architecture which went viral last weekend and I decided to give it a run yesterday. Verdict: You *have* to try this out. Prediction: You won’t be able to live without it soon. There were a few mods and decisions I made to the base Karpathy provided. First, the vault / folder structure in Obsidian. I already use Obsidian as a human. Instead of creating separate vaults and dealing with the sync nightmare, I just have folders for Human and Agent, and a Raw folder. (1) The Human/ folder is where I write long form articles and notes independent of the knowledge base wiki. No LLM or agent touches this folder. (2) I do have Arnold Layne, my OpenClaw agent, doing background tasks for me. Raw/ is where both Arnold and I, dump raw snippets. Inclusive of diverse kinds of media. (3) The Agent/ folder is where the LLM (Claude in my case) synthesizes the wiki. No human touches this folder. Second, some customizations to CLAUDE.md for enterprise-like usage - (4) Domain extensions - the agent needs to know that quantum computing and agentic AI have different entity types and different provenance thresholds. (5) Primary source protection, when I drop in my own original work, secondary sources can extend it or raise questions against it, but they cannot overwrite it. It sounds like a small thing but its’s not, especially at enterprise scale where provenance actually matters. Karpathy is upfront that what he’s built is working memory for a single agent, and it’s truly remarkable at that. The jump to Shared Context across teams, reconciling conflicting beliefs at org scale, ontologies that don’t collapse under the weight of a hundred contributors - those are much harder problems and what we are exploring with the Internet of Cognition. PS: The screenshot shows my Obsidian vault after just two runs: one with Karpathy’s original tweet and gist file itself (so meta!) and one with our Internet of Cognition paper. Claude (Sonnet) read it, compiled it into structured summaries, entity pages, concept pages, backlinks, merged all the information cohesively, and keeps it all maintained from there. You just read the Wiki. It’s simply magical.
LLM Wiki v2 — extending Karpathy's LLM Wiki pattern with lessons from building agentmemory
LLM Wiki v2 — extending Karpathy's LLM Wiki pattern with lessons from building agentmemory · GitHub
How To Build LLM Wiki In Obsidian? 🧠 A Memory Layer For Any Agentic AI
I Built a Knowledge Base That Writes Itself. Here Is What Andrej Karpathy Got Right.
Andrej Karpathy posted about using LLMs to build personal knowledge bases. I took his workflow, wired it into my Obsidian vault with Claude Code, and within an hour had 21 cross-linked wiki articles compiled from YouTube transcripts. Here is how it works and why it matters.
Karpathy's LLM Wiki v2: What to Keep, What to Skip
I rebuilt it, ran it daily for months, and most of the v2 hype is overkill.
The REAL Second Brain: an autonomous, self-hosted knowledge wiki that runs on cheap local models
How I turned Karpathy's "LLM wiki" sketch into a system that actually maintains itself — no frontier API, no human in the loop, nothing leaving my LAN.
elvis on Twitter / X
Building a personal knowledge base for my agents is increasingly where I spend my time these days. Like @karpathy, I also use Obsidian for my MD vaults. What's different in my approach is that I curate research papers on a daily basis and have actually tuned a Skill for… https://t.co/4AQSFOv4PV pic.twitter.com/YI5cWUhqT3— elvis (@omarsar0) April 2, 2026
I Built a Digital Brain Upload Using Karpathy's LLM Knowledge Base
10 Easy Ways to Enhance Your LLM Wiki or Knowledge Base
Yuchen Jin on Twitter / X
Karpathy’s “LLM Wiki” pattern: stop using LLMs as search engines over your docs. Use them as tireless knowledge engineers who compile, cross-reference, and maintain a living wiki. Humans curate and think.Diagram generated by my Claude agent knowledge worker. https://t.co/5u5i1GeFK8 pic.twitter.com/NIaq3KlAok— Yuchen Jin (@Yuchenj_UW) April 4, 2026
Karpathy's LLM Wiki: What It Means & How to Build One
Karpathy's LLM Wiki as Agent Memory - Agentic AI Foundation (AAIF)
At work, I’m building agents to handle various operational tasks and have found Karpathy’s LLM Wiki design to be an excellent solution for implementing most ty…
Why LLM Wiki? 🧠 Future Of Knowledge For Agentic AI & Humans
Patina: Turning Karpathy’s LLM Wiki Pattern into a Rust CLI
Useful, local, and slightly fun. There is a simple but important idea behind Andrej Karpathy’s LLM Wiki pattern: useful synthesis should not disappear into chat history.
How I Write Blog Posts with Obsidian — Unattributed
You've probably run into some Obsidian evangelist espousing some convoluted system of organizing all their notes, and building some knowl...
I rebuilt Karpathy's LLM Wiki gist: what's missing
Karpathy's original LLM Wiki gist, explained and rebuilt as a working system. 44 open-source commands, plus the five things the gist leaves out.
Build an LLM Wiki for Your AI Agents
Build an LLM Wiki for Your AI Agents with myKG and Obsidian How to turn a folder of mixed format documents into a typed, interlinked knowledge graph your agents can actually read — using myKG and …
