# knowledge-management

There are hundreds of videos out there on how to remember everything you read, with millions of views between them. Dan Koe says the whole premise is pointed the wrong way: memory is not an input problem, it is a feedback-system problem. This one covers the four parts of helmsman-style learning, why the second brain turns into a graveyard for ideas, and a note-taking and writing workflow you can actually pull from.

Karpathy turned a viral tweet into a GitHub Gist idea file: a structured blueprint for an LLM-maintained Wiki. In the agent era, plain-text ideas can be more valuable than finished code because the recipient's agent can rebuild them.

Karpathy shared his experience building a personal knowledge base with LLMs, earning 29,000 bookmarks. Huryn argues the real killer feature isn't reading — it's writing back. When your LLM automatically updates your knowledge base, your personal wiki becomes a personal research team.

Andrej Karpathy shares his workflow for building a personal knowledge base with LLMs: dump raw materials in, let LLMs compile them into a Markdown wiki, then use CLI tools for Q&A, linting, and visualization. He thinks there's room for an incredible new product here.

rodspeed lays out six ways to use Claude Code as general automation, not just a code editor: fresh eyes, meta-skills, freshness-aware search, conversation harvests, structured memory, and handoffs. The deeper pattern is read, filter, decide, present.

Chapter 4 of Simon Willison's Agentic Engineering Patterns: Hoard Things You Know How to Do. Core thesis: every problem you've solved should leave behind working code, because coding agents can recombine your old solutions into things you never imagined.

Obsidian v1.12 ships an official CLI that lets you control your entire vault from the terminal. On the surface it's a power user tool — underneath, it's paving the road for AI agents. This article covers the full CLI command reference and demonstrates real Claude Code + Obsidian CLI workflows.

The original article builds a personal AI content factory with Obsidian + Claude. We rewrite it from a Tech Lead's perspective — managing a 6-person backend team with an AI-native doc system called orion-dev-doc.

The key to going from 'AI user' to 'AI master': turn fragmented AI usage into a systematic workflow. Build a complete system with Claude Code for memory, content reuse, and methodology accumulation.

When AI processes your notes by just 'reorganizing' without 'transforming,' it's expensive copy-paste. The Cornell Notes methodology pointed this out long ago: passive copying isn't the same as learning. Your AI summarizer falls into the same trap.

Meetings used to be overhead. Now yapping is work. Record a project chat, process the transcript, and suddenly you have docs, backlog ideas, captured decisions, reasoning, and updated status. Yapping has become production input.

Humans have Tools for Thought like Obsidian. Claude needs an AI-native version. Build a knowledge graph using markdown, wiki links, hooks, and subagents where agents can actually think.

Heinrich's six-part tutorial series: Building an AI agent thinking infrastructure with Claude Code + Obsidian. From vault basics to context engineering to meta layers — a complete knowledge management system.

Heinrich spent a year building an 'OS for thinking with AI': let Claude Code operate your Obsidian vault, extract concepts, link ideas, and build a living representation of your thinking. You don't take notes anymore — you command a system that takes notes.