Post

The AI-native operating system for every device, from your computer to embodied AI. Local-first, federated, OpenAI-compatible.

The most capable AI now lives inside a handful of organisations that can put enough compute in one building. That concentration is an architectural choice rather than a law of physics, and it decides what the models will refuse, what they cost, and who gets to read what you type.

To be precise, because this is the obvious thing to attack: you cannot train a frontier model without a datacenter, and we are not claiming you can. What we are claiming is that the intelligence people actually use does not have to be delivered from one. HART OS runs models on the device, and when a node cannot handle something it recruits a peer directly, with no broker and no company in the middle.

We do not shard a model across the network either. Layer-level parallelism over consumer links is a bad idea and we do not attempt it. A peer serves a whole request instead, so a machine with a bigger model answers what a smaller one could not, which tolerates latency in a way tensor parallelism does not.

The things we have not solved are written down in OPEN_PROBLEMS.md , each naming the file that implements today's inadequate answer.

HART = the bare engine (run from this repo, listens on :6777 ). There is no published PyPI package yet, so install it from source as shown below. HART OS = the full AI-native OS. It boots on a laptop, server, or edge node, runs on phones, and reaches into embodied AI, and it ships the agentic Liquid Shell, Model Bus, model catalog, channel pairing, agent dashboard, and hive view. Nunba = the consumer companion app, one signed client across Windows / macOS / Linux.