Read the message
The full turn is classified by difficulty, risk, context, and intent.
AgentOS routes every turn, runs tools safely, and remembers what matters across CLI, Web UI, and chat.
A local signal pass and a small judge model choose the cheapest capable tier before execution starts.
The full turn is classified by difficulty, risk, context, and intent.
Local rules identify debug work, strict formats, long context, and agentic tasks.
A small model selects the lowest tier that can complete the work reliably.
The chosen tier maps to a concrete provider profile for that turn.
Greetings and one-liners
Routine edits and focused tasks
Refactors and non-trivial debugging
Production and cross-service work
Recent higher-tier turns stay warm, protecting continuity and model cache reuse.
Short follow-ups inherit the active workstream instead of dropping context.
A failed answer raises the next turn instead of repeating the same attempt.
CLI, Web UI, and chat share the same gateway, memory, tools, approvals, and usage accounting.
Configure a provider, start the gateway, and run full agent turns from the shell.
Run sessions, review approvals, publish artifacts, and inspect replay data.
Bring the same runtime into the messaging tools your team already uses.
Memory persists, tools stay controlled, and context remains focused across extended workstreams.
Large outputs stay useful without flooding model context. Full results remain available on disk.
Facts, notes, and task traces return through local keyword and semantic search.
File, shell, web, git, and media tools run behind policy and approval layers.
Package recurring work as reusable, composable routines.
Transcripts, summaries, artifacts, cost, and replay data persist.
Bring fresh external context into any turn through a configured provider.
Local ONNX embeddings power semantic recall without sending memory to a remote model.
Point AgentOS at the backend that fits the work. Switching never requires application code changes.
Windows, macOS, and Linux use the same setup path.
AgentOS installs into an isolated tool environment and manages its own Python, so you don't need Python first.
Pull the recommended profile — router plus the on-device memory stack — from the latest release wheel.
Run the onboarding wizard to pick a backend and set your key, or point it straight at one non-interactively.
Start the shared runtime that every surface connects to, then open the local control console in your browser.
Chat interactively, or fire a single one-shot turn. Smart routing sends each turn to the cheapest capable model.
A small crew at 404 Labs ships AgentOS end to end: routing, memory, sandbox, and the surfaces you run it through.
View the full teamRoute each turn to the lowest-cost model that can complete it reliably.
Install AgentOS