American Code is an independent AI lab — the kind the open models in your Ollama library come from, aimed at the layer around them: distributed AI, on‑device intelligence, hardware, and developer tools. A lot is already shipped. A lot more is coming.
Hardware, apps, distributed AI, developer tools — a slice of what we’ve shipped. It’s a running list, not a finished one.
A global inference fabric made of consumer Macs.
An Apple MLX–based mesh network that turns idle Apple Silicon into a distributed AI inference grid. No cluster to rent, no queue to wait in — the machines find each other and get to work. Open source, open protocol, AGPL.
mlxmesh.net ↗A physical control surface for your AI agents.
A custom RP2040 hardware macropad paired with a Tauri/Rust desktop app that orchestrates coding agents across Claude, Cursor, Windsurf, and VS Code. Auto‑commits, codebase analysis, security checks, multi‑agent monitoring — and a real red emergency‑stop key.
ai-vibedeck.com ↗An IDE that runs your models, not the cloud’s.
An open‑source Ollama model IDE built on the VS Code platform: multi‑model orchestration, device‑specific model recommendations, and Ralph‑based code / test / repair loops that keep grinding until it’s green. Local by default. AGPL.
github.com/american-code ↗An NVIDIA DGX cluster, in your pocket.
A native iOS app for monitoring and commanding an on‑prem NVIDIA DGX GPU cluster — live utilization, job control, and anomaly checks routed through an on‑prem LLM. The whole rack, from your phone.
Native iOS · on-premCore ML models for anyone, from raw data.
A native macOS app that let anyone build Core ML models straight from their own data — vision, semantics, and numeric prediction — no ML degree, no pipeline, no data science team. Train on your machine, ship on your machine.
Foundational work · c. macOSNew hardware, new apps, new models — there’s always something in the forge. This list keeps growing.
Follow along ↗The same kind of lab the open models in your Ollama library come from — pointed at the layer around the model. Distributed inference on consumer silicon. A hardware deck for driving AI agents. An IDE that runs your own models. A DGX cluster you command from your phone. Different problems, same instinct: pull it apart, understand it, and wire it up in a way no one bothered to before.
We like hard problems and people who’d rather build the future than wait for it. The channel is always open.