# Self-contained agents that self-organize > Source: > Published: 2026-08-12 00:11:19+00:00 One install command. Pick a model. Start coding. No accounts, no configuration files, no setup guides. #### Go offline in one command Type /offline-mode — Ante installs a local inference engine. No API keys, no internet. #### Configure the model Choose your model, set context window, enable thinking mode. Tuned to your hardware. #### Agent does the work Give it a task. The agent reads your codebase and produces working output — fully offline. ## MEET ANTE ### AI-native, cloud-native, local-first agent runtime Built from the ground up in native Rust — a single self-contained binary with no external dependencies. Designed for cellular-native agents: lightweight enough to run by the thousands and reliable enough that the system self-heals when any one fails. #### Lightweight agent core A single lightweight binary with zero runtime dependencies. Built for minimal overhead and maximum throughput — the ideal runtime for orchestrating agents at cellular scale. #### Native local models Run models entirely on your machine with built-in llama.cpp integration. No API keys, no internet, no data leaving your device. #### Zero vendor lock-in Bring your own API key, subscription, or local model. Switch between providers freely — Anthropic, OpenAI, Gemini, Grok, Open Router, and more. No account required. ### Built on first principles Ante is designed for cellular-native agents — like cells in a living organism, tiny and expendable, massively replicated. Everything we build serves this thesis. #### Lightweight Hundreds of agent replicas can't each cost gigabytes. Every byte per instance matters at scale — so we maintain a tight, tiny core. #### Reliable The return on reliability is non-linear. There's a phase transition — and you need to be on the right side of it. #### Closed-loop Declarative intent, automatic reconciliation. Individual agents are expendable; the organism persists. #### Minimal cognitive load Fewer concepts to learn, fewer knobs to turn. If a feature needs a paragraph of explanation, it's probably too complex.