Consequential moves queue for your approval instead of happening. Everything else is reviewable afterwards against the evidence, in real time or in a durable record.
Finished work, budget overruns, risky steps and proposed automations land in one approval queue on the dashboard, each with the evidence behind it. Approve, decline, or approve with edits in a click.
What that gets you. One place where the agent asks permission, so autonomy has a gate rather than a hope.
A running readout of events off the live system: tool calls, worker activity, navigations and lifecycle signals, timestamped as they happen.
What that gets you. You can watch exactly what it is doing right now, at the level of individual calls.
A 3D room where the agents are visible as characters, animated from real activity: live goals, actual memory recall, real worker state streamed as it happens.
What that gets you. A glanceable read on whether anything is working, driven by real events rather than decoration.
Each project opens into a workspace with a dashboard and a working view: key facts, people, documents with a built-in viewer, notes, and live task status.
What that gets you. Memory, files and work organised per project instead of pooled into one undifferentiated history.
You name the agent, choose its voice, and hear an audition before committing.
What that gets you. It is yours, and it answers to a name you chose.
It tracks which capabilities you have actually used, read from work you were doing anyway, and works out what you have not touched yet.
What that gets you. You find the useful parts without reading a manual, and it stops mentioning the ones you already use.
Everything on this page describes behaviour that ships today. The facts come from the runtime’s own capability brief, the same one the agent reads about itself on every turn, so nothing here is a roadmap item wearing a present tense.
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Can an AI agent run without sending your data to the cloud?
Can an AI agent work while you sleep?
What can an AI agent actually do on your computer?
What stops an AI agent from going off the rails?
Which AI models can you use, and who pays for them?