I was standing in the hardware store holding a dead coin cell, squinting at it, trying to remember if the Lutron dimmer in my hallway takes a CR2032 or one of the other fourteen round silver batteries that all look exactly the same. So I guessed. I bought two of the wrong one. Classic.

Here is the thing about a house. You slowly learn a thousand tiny facts about it. The vent sizes. The filter part numbers. The spa was installed in some year you’ll never remember. The good info is scattered across manuals in a junk drawer, an email from the installer, a photo of a model plate you took and never looked at again. By the time you actually need a fact, it’s gone.

I finally fixed it. Not with an app. With a folder.

The idea I borrowed

Earlier this year Andrej Karpathy posted a little pattern he called an “LLM wiki.” Instead of the usual retrieval setup where you chop documents into chunks and stuff them in a vector database, you just keep a folder of Markdown files that the AI itself writes and maintains. The model builds the connections once, when it learns something, instead of re-deriving them every single time you ask. The internet looked at it and went “wait, it’s just a folder? why did we ever do the other thing.”

Then Google Cloud made it official. On June 12 they published the Open Knowledge Format, or OKF. It’s a tiny, vendor-neutral spec: a directory of Markdown files, one concept per file, a bit of YAML at the top, an index, links between them. No database. No SDK. Readable by a human and by any agent. That’s the whole thing.

So I pointed it at my house. The project is called Abode 101.

What I actually built

Abode 101 is an OKF folder about my home. There’s a file for the Lutron dimmer, one for the swim spa, one for the HVAC vents, one for the smoke alarms. There’s an index.md the AI reads first so it knows where to look. To use it, I don’t open an app. I just talk to it in Claude Code.

you ▸ what's the battery for the Lutron dimmer?
abode ▸ Panasonic CR2032, per the install guide (page 10).

That’s the fact I drove to the store without. Now it’s one question away, and it tells me where it got the answer.

But a folder of files just sitting there is a filing cabinet. The magic is in two things the bare spec leaves out.

Thing one: the loop

OKF standardizes the files. It says nothing about keeping them fresh. Karpathy’s original idea had the AI do the maintaining, and that’s the part I cared about most, so I built it back in as a set of playbooks.

I capture a thing by telling it “I bought X,” or by dropping a manual, a receipt, or a photo of a label into an inbox folder. It reads whatever I throw at it, pulls out the real specs, and files them. Then overnight it does the boring homework I never do. It looks up the filter I just bought, finds the replacement part, figures out how often it needs changing, and adds a reminder. I wake up and my house knows more than it did when I went to bed.

Thing two: it refuses to guess

This is the part I’m proud of. Every exact fact carries its source and a confidence level. A battery type from the manufacturer’s manual is “verified” and it gets cited. A spec from a random Amazon listing is “reported” and ranked lower. And when I ask something it doesn’t actually know, it says so.

you ▸ what size is the kitchen toe-kick vent?
abode ▸ Not recorded. It's marked TODO, needs measuring. I won't guess.

An AI that says “I don’t know” instead of inventing a confident wrong number. For house facts, where the wrong answer means a second trip to the store or a part that doesn’t fit, that refusal is the feature.

I ran a little eval suite over it to make sure. Twenty-one questions, answered cold. It got the exact facts right, with sources, and on the three questions it shouldn’t know, it refused all three. That’s the behavior I want from something I’m going to trust with my house.

Why a folder beats an app

I could have built a slick app with a database. I’m glad I didn’t. The folder is portable, it diffs in version control, it works with any model, and I own it. There’s no service to shut down, no export button I’ll go hunting for in five years. When the next better model comes out, I point it at the same folder and it just works. Try that with your smart-home app from 2014.

Get it

I open-sourced the framework. The structure, the agent instructions, the playbooks, even the eval harness are all in the repo. My actual house data stays on my machine, gitignored, because you do not need to know my spa’s gallon count. You fork it and fill it with your own home.

→ github.com/nothans/abode101

Go give your house a memory. And maybe check what battery your dimmer takes before you drive to the store. Just a thought…