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Kora – An AI-native OS layer written in 370k lines of Rust

Kora – An AI-native OS layer written in 370k lines of Rust

by jwatters·Mar 26, 2026·4 points·0 comments

AI Analysis

●●●BangerBold BetWizardryZero to One

Local AI OS layer in Rust that replaces your window manager.

Strengths
  • 370k lines of Rust suggests production-grade depth beyond typical wrappers.
  • Wayland and Metal integration enables true system-level control and compositing.
  • Completely local execution eliminates API costs and privacy concerns for data.
Weaknesses
  • High complexity creates a large security surface area for this tool.
  • AI OS category has a poor history of delivering real utility.
Category
Target Audience

Privacy-focused power users and developers

Similar To

Raycast · Open Interpreter · Humane AI

Post Description

We've been building this for ourselves over the last year. We wanted the computer from Star Trek, something you just talk to, that knows your context, controls your environment, and runs locally.

Our core belief is digital sovereignty in that you should own your context. Your conversations, files, voice, memory, and identity never leave your machine unless you explicitly choose to route through a cloud provider. No telemetry, no accounts, no data collection. The AI that knows the most about you should be the one you control completely.

Kora is an operating system layer built around an AI agent. On Linux it runs as the GUI directly in Wayland (OpenGL via femtovg). On macOS it's a native app with a Metal compositor.

It's not a chatbot wrapper, it's closer to a full OS where the AI is a first-class service. The stack is ~8 services running locally:

- UI: custom window manager with guest app compositing. Apps are standalone Rust binaries that communicate with the host over IPC.

- Multi-device: one main machine runs the services and models. Thin clients on other devices connect over QUIC and get the full UI, voice, and tool access. The graph service tracks which clients host which apps and MCP servers. Add a screen in the kitchen, a terminal in the workshop, same agent, same context.

- Speech pipeline: real-time ASR, TTS, VAD, wake word detection, barge-in interruption. All on-device.

- Tool system: MCP servers and CLI for native OS automation, file management, browser control, calendar, email, terminal, music, messages. The AI doesn't need to simulate clicks it calls native OS APIs.

- Chat routing: you can talk to it from Slack or Signal. It's the same agent with the same context, just a different transport. It can still use all its tools from a chat message.

- Skills, workflows, and missions. Skills are reusable prompt templates that declare which tools they need. Chain them into workflows. Assign the agent a role (personality, permissions, context) and schedule it on a cron — we call these missions. The agent can run tasks overnight, check in on things, or maintain a recurring process without you touching it.

- Context service: identity hierarchy (directives → roles → learnings), semantic search over local files, per-session memory.

- Cognition service: background "dream state" that processes and connects information when idle.

- App framework: guest apps (browser, terminal, text editor, Doom (yes it runs Doom)) run as isolated processes. The host composites their rendered output. Think Wayland but the compositor is AI-aware. The system can generate its own applications on the fly and they automatically show up in the UI when completed. "please build me a magic 8 ball"

Nearly everything is Rust. ~370k lines across the workspace. Multi-user — each person gets their own identity, memory, and permissions. No cloud dependency. runs on local LLMs (Apple Silicon / your own inference) or connects to cloud providers via OpenRouter if you want.

Happy to answer questions about the architecture, the pitfalls of one device speech pipelines, CLI / MCP integrations, building a window manager in Rust, or anything else.

Demo: https://www.youtube.com/watch?v=40TyKAKNvJc

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