I run tech at a digital marketing company. Dozens of active projects. A team that needs answers from me every day. SEO strategies, technical decisions, client histories, conversations that suddenly matter again weeks later.

I can’t hold all of it in my head. Nobody can.

Last week Andrej Karpathy posted something that got the tech world buzzing. I wouldn’t have seen it if our guy Business Walrus hadn’t flagged it for me. He’s the same person who got me into Obsidian in the first place. He’s got a nose for finding the stuff that actually matters. And he was right about this one.

Karpathy is one of the sharpest minds in AI. Co-founded OpenAI, led AI at Tesla, the whole resume. And he said something that caught my attention: he’s spending less time using AI to write code and more time using it to organize knowledge.

Not generate it. Organize it.

The Problem Everyone Has

Here’s what most people do with AI right now. They open ChatGPT or Claude, ask a question, get an answer, and close the tab. Next week they ask the same kind of question again. The AI starts from scratch every time. Nothing compounds. Nothing builds.

It’s like having a brilliant employee who gets amnesia at the end of every conversation.

Karpathy’s solution is simple. Instead of treating AI like a search engine, treat it like a librarian who never forgets. You feed it your raw material. Research, notes, articles, data. The AI reads it, organizes it, cross-references it, and maintains a living knowledge base in plain markdown files. He ended up with 100 articles and 400,000 words on a single research topic without writing any of it himself.

The AI did all the grunt work. The summarizing, the filing, the connecting dots between things. He just pointed it in the right direction.

Why This Matters If You Run a Business

I started doing a version of this before I even knew Karpathy was thinking the same way.

I recently started using Obsidian for note-taking, thanks to Business Walrus. Every project, every client, every decision gets logged. My CLAUDE.md files tell the AI what I’m working on so it has context when I pick something back up. Not just for the AI. For me. Because when you’re managing a team and running a business, you need to be able to jump back into any conversation and know where things stand. Even early on, I can already feel the difference.

Think about what this looks like in practice. You’re picking up a codebase you haven’t touched in two weeks. Instead of digging through Git logs and Slack messages and trying to remember what you decided and why, you’ve got a system that already knows. The context is there. The history is there. The reasoning behind past decisions is there.

That’s not fancy AI magic. That’s just good systems thinking applied with better tools.

This Isn’t New. The Tools Are.

People have been building knowledge management systems forever. Wikis, intranets, shared drives, Notion boards. The problem was always the same: someone has to maintain them. And nobody wants to do it. So they rot.

What changed is that AI can do the maintenance now. It can read a messy set of notes from a planning session and file the important stuff in the right places. It can notice when something you learned last month contradicts something from six months ago. It can keep the whole thing organized without you spending hours on housekeeping.

The knowledge base stays alive because the AI does the work nobody wants to do.

Keep It Simple

Here’s where I’ll push back on some of the hype around this. You don’t need a complicated setup. You don’t need vector databases or custom RAG pipelines or whatever the latest framework is. Karpathy himself said it: markdown files in folders. That’s it.

Obsidian on one side. Your AI agent on the other. Plain text files that any tool can read, that you own, that aren’t locked inside someone else’s platform.

The best technology is the technology that works. That hasn’t stopped being true.

What This Means for Developers

If you’re a developer, think about how much context you lose between projects. Why you chose one architecture over another. What you tried that didn’t work. The workaround for that weird bug in production that you’ll hit again in six months.

Every technical decision you make is knowledge. Every debugging session, every code review, every “oh right, we tried that and here’s why it broke” moment. Right now most of that lives in your head. Or it’s gone.

An AI-maintained knowledge base means your experience compounds instead of leaking out. New devs on your team get access to what you’ve learned. You get access to what you learned two years ago and forgot. Your codebase has version control. Your thinking should too.

The Real Point

Karpathy is one of the most technical people on the planet and his big insight wasn’t about a new model or a breakthrough algorithm. It was about organizing information so you can actually use it.

That’s not a tech insight. That’s a business insight.

AI didn’t make your brain bigger. It gave you a second one. Use it.