
#1 PROPOSE
NOTHING APPLIES ITSELF.
No agent can change your files on its own. Every proposed change waits in one approval queue until you say yes — and it is checked again at the moment it is applied.
OPERATION ANTHILL · OPEN SOURCE · MIT · SELF-HOSTED
A colony of specialized agents that plans, builds, verifies, and remembers.
INSTALL VIA TERMINAL
curl -fsSL https://raw.githubusercontent.com/Formicaria/anthill/main/deploy/lxc/setup.sh | bash
ANTHILL is a self-hosted AI workspace for Windows and Linux — an AI assistant that lives on your own computer instead of someone else's cloud. Open it as a desktop app or in a browser tab and talk to it like any AI chat.
The difference: your request becomes a mission. The colony researches, drafts the change, tests it, and shows you exactly what it wants to do — and nothing happens until you approve it. Your history stays on your machine in a local SQLite database, and the easiest way to add a model is Ollama, which is free and runs locally too.
Pre-1.0 software under active development, with deliberate safety gates. The measured current state lives in the PLAN document.
DOWNLOAD THE APP
WHY IT IS DIFFERENT

#1 PROPOSE
No agent can change your files on its own. Every proposed change waits in one approval queue until you say yes — and it is checked again at the moment it is applied.

#2 VERIFY
An AI saying its own work looks good counts for nothing here. Only real proof — a compiler, a test run, a security scan — can mark work as verified.

#3 REMEMBER
The colony remembers what actually worked and forgets what did not. Only verified results strengthen its memory — confident-sounding words never do.

#4 BOUNDED
Everything runs on your hardware, inside boundaries you set. Internet access, file writing, and auto-apply all start switched off. Every agent has a kill switch.
HOW A MISSION MOVES
A chat request becomes a structured mission with a visible task trail.
The planner drafts a task graph from planner-eligible roles.
Researcher, Web, File, and UI Cartographer gather read-only context.
The Coder emits a patch set. Proposed code is data — nothing is applied.
Policy inserts Tester and Soldier on every state-changing patch set.
The Verifier reads stored evidence. Model prose is recorded, never decisive.
The operator approves before anything is applied. No role can apply patches.
The Archivist turns the canonical outcome into memory candidates and pheromones.
The safety checks are built into the flow itself — the system adds them automatically, so a forgetful plan can never skip them. See the full mission lifecycle.