A Vault That Rewrites Itself: obsidian-second-brain and the Karpathy LLM Wiki Pattern

Two tools most of us own ignore each other completely. An Obsidian vault with hundreds of notes nobody rereads. An AI agent in the terminal whose every session starts from zero, as if the past never happened. The obsidian-second-brain repository glues them together: 4.7k stars, MIT, authored by Eugeniu Ghelbur. The README's own formula: an evolution of Karpathy's LLM Wiki pattern, a vault that rewrites itself.
Here's a review, plus why I read the whole thing with deja vu: my business CRM runs on the same pattern.

The pattern first

Karpathy's LLM Wiki idea: a knowledge base in wiki form, maintained by an LLM. The model adds pages and links them, flags contradictions for manual resolution, surfaces patterns on request. The human owns the knowledge, the model maintains it.
The weak spot: it's passive. The wiki grows when you ask, and contradictions sit until you resolve them. This repo pushes the pattern into active form.

Four layers, 47 commands

The repo gives a CLI agent (Claude Code, Codex, Gemini CLI and four more) a command set that operates directly on your vault.

• Operations (30). Ingest URLs, PDFs, audio, screenshots into normalized notes. /obsidian-reconcile resolves contradictions. /obsidian-health lints the vault. /obsidian-architect documents a codebase into notes.
• Thinking tools (9). The part I care about most. /obsidian-challenge makes the vault argue with you from your own history. /obsidian-emerge hunts unnamed patterns. /obsidian-connect bridges knowledge domains.
• Context (1). /obsidian-world loads identity and state with token budgets, from a light L0 to a full L3.
• Research (7). Vault-first: /research-deep scans your notes first and researches only the gaps outside. Plus four scheduled agents: morning, night, a Friday review, a Sunday health check. The vault lives without you. That's the design goal. ## The part that's actually engineering Two rules separate this from "plug GPT into notes". Open Knowledge Metabolism. Every fact must be timeless, dated, or a pointer. Slow-changing knowledge lives in the note; fast-changing facts link to a live source with an "as of" date. There's a spec and a linter. Bi-temporal facts. The vault remembers when a fact was true and when it learned about it. It sounds academic until someone asks "when did this stop being true", and someone always asks. Add the inversion I like most: an AI-first note format, notes written for an agent to read, with frontmatter, recency markers and verbatim sources. For decades we adapted machines to documents. Here documents adapt to the machine. And the restraint: bounded recall through a hook, at most four notes of roughly 900 characters per prompt, so memory doesn't eat the context window. 763 tests in CI, eight builds per platform. It's built like infrastructure, not like a prompt collection. ## The principle to steal "Your vault outlives any CLI." Agents change every six months. Knowledge in markdown belongs to none of them. Switch the tool, keep the files. A rare case where the right architecture is also the cheapest one. ## The deja vu: our CRM runs on this pattern I've been building business automation for 14 years, and my company's CRM is a production implementation of the same idea, on business entities instead of notes. What exists today, not on a roadmap:
• The vault is the source of truth. Clients, deals, tasks, invoices, infrastructure and correspondence: markdown with frontmatter in an Obsidian vault. A task tagged urgent and important lands in the right quadrant of an Eisenhower matrix on the dashboard, automatically, like this:

---
title: "Connect payment webhook to the CRM"
urgent: true
important: true
hours: 3
---

• Agents read and write directly. A board of director roles works on the same files: a CEO holds the weekly plan, a CFO holds cash and price floors, a commercial director holds receivables. Decisions land in a shared journal, a human approves what matters.
• Panels read, the vault stays. A promotion dashboard compiles semantics, content coverage, five social networks and traffic into one JSON file that both the agent and the owner read. The vault never becomes a database you can't open.
• Data discipline. Sensitive client fields are encrypted in a vault that locks itself, and the company is a registered personal-data operator. ## How a business version differs The cost of an error. In a personal knowledge base a wrong note costs a reread. In business, an agent that records a payment wrong or leaks personal data costs money and reputation. So triple down on what the personal version treats as optional: human approval of critical actions, encrypted personal data, and a decision log that shows who did what and why. In about two years the pattern has traveled from a tweet to systems with hundreds of tests, and to CRMs companies actually run on, If you've got an Obsidian vault full of knowledge, this repo is the shortest path to giving your agents persistent memory. If you're running a business, the same pattern works there too, just bring the discipline along. --- This article was prepared with AI assistance (drafting and adaptation) and reviewed by the author before publishing. Originally published at https://automata.sale/en/blog/ai-automation/obsidian-second-brain-obzor/ tags: aiagents, obsidian, knowledgebase, productivity