Your AI gets its own computer
Your AI gets its own computer in the cloud, and you get a workspace built for both of you.
You've been babysitting your AI
The models are ready to do real work. But the tools around them aren't — so you're stuck managing permissions, fighting setup, and working around limitations instead of just building.
Your machine, your risk
Your agent runs on your personal computer, so you either approve every action or let it loose on your files, your credentials, your environment. Either way, it's your problem.
A terminal or a chat window
Your options are a command line with no UI, or a chat window that can't actually do anything. No workspace where you and the agent work side by side.
Close your laptop, lose your agent
Your AI lives on your machine. Walk away and it stops. The "remote access" drops half the time. The "cloud mode" barely exists. You shouldn't have to babysit your computer so your computer can work.
You're debugging the framework
Permission prompts that don't stick. Cron jobs that stop firing. Connectors you toggle off and on every session. You signed up to build things, not troubleshoot your AI's infrastructure.
What it actually looks like when AI has no limits
01
Its own machine
Your AI runs on its own computer in the cloud. It installs what it needs, builds what it needs, does what it needs without you holding its hand. Come back two weeks later and everything's exactly where you left it. Nothing resets.
02
A workspace for both of you
The agent creates a file and it appears in your file explorer. It finds what you're looking for and links you to the exact line — click and you're there, scrolled and highlighted. You edit something and the agent sees your changes. Not a black box you delegate to. A shared space you work in together.
03
Zero setup
Sign up and your agent is running. No Docker, no hardware, no config files, no weekend lost to setup.
04
Runs while you sleep
Your agent works whether your laptop is open or not. Schedule tasks, kick off long jobs, come back in the morning to finished work.
05
Yours to shape
Channels organize your workspace like Slack — #eng, #career, #strategy — each with its own context and instructions. Skills extend what the agent can do. Connected apps give it access to your tools. It gets better the longer you use it.
06
Nothing to maintain
No servers to patch, no updates that break your setup, no dependencies to untangle. The platform handles the infrastructure. You just use it.
Everything you need, nothing you don't
File explorer with live rendering
Browse, edit, and preview files alongside the chat. HTML renders live. Markdown renders with syntax highlighting. Images, PDFs, spreadsheets, audio, video — all native. The agent creates a file and you see it immediately.
Integrated terminal
Same machine the agent runs on. Full shell access. You're never locked out of what's happening under the hood.
Connected apps
Gmail, GitHub, Notion, Slack, Google Calendar, and dozens more. One-click OAuth. Your agent reads, writes, and acts across your services — without ever seeing your credentials.
Skills & marketplace
Skills are reusable instruction sets — just markdown files — that extend what the agent can do. Invoke them with slash commands. Browse and install community skills from the marketplace, or write your own. No code changes needed.
Scheduled tasks
Cron jobs, intervals, one-shots. Not just reminders — full agent capabilities on a schedule. Your agent triages email every morning before you wake up.
Model switching
Anthropic, OpenAI, DeepSeek, Kimi. Switch models mid-conversation. Connect your ChatGPT subscription and OpenAI models run through it instead of your usage balance. Cheaper that way.
Object links
The agent links you to specific lines of code, channels, tasks, and past conversations. Click and you're there. Ask it to find a conversation from last week — it links you to the exact message.
Security that doesn't require trust
Giving an AI agent access to your tools is a bold move. Here's why it's not a reckless one.
Your keys never touch the agent
A sidecar proxy intercepts every outbound request. The agent works with dummy placeholder keys. The proxy swaps them for real credentials at the network level. Your agent literally cannot access your API keys — they only exist in the proxy's memory.
Isolated containers
Each workspace runs in gVisor — the same container runtime Google uses for Cloud Run. Process-level isolation, not just namespace separation. Your environment is yours alone.
Network access controls
Lock the agent to only the services you've connected. If you didn't authorize it, the request gets blocked. You decide what your agent can reach.