Remote AI Agent Workflows: Cloud Computer, Session and Client
A practical mental model for separating the remote cloud computer, persistent session and client when running AI coding agents away from your laptop.
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SHORT ANSWER
What does a remote AI-agent workflow actually require?
A reliable remote workflow has three separate pieces: a cloud computer that stays online, a persistent session for long-running terminal work, and one or more clients used to connect. Keeping those concerns separate makes it possible to start from one device and reconnect later from another.
Key takeaways
- The cloud computer provides the long-lived environment.
- Persistent Agent Sessions provide terminal-session persistence.
- Web Terminal, SSH and compatible Remote SSH desktop tools are access methods.
- The harness is a tool running on the cloud computer, not the cloud computer itself.
1. The cloud computer
The cloud computer holds repositories, dependencies, containers and the processes your agents use. If the goal is independence from a personal laptop, this machine needs to stay online on its own.
2. The persistent session
A Persistent Agent Session lets long-running terminal work survive a client disconnect. In TermSquad, this role belongs to the product session capability rather than the browser socket.
3. The client
The client is how you reach the machine. It might be a Web Terminal, a normal SSH client or an Any Desktop Harness that explicitly supports a remote SSH environment.
Harness-agnostic by design
The same remote cloud computer can run different CLI-based AI coding tools. The useful abstraction is the cloud computer: a harness can change while the environment beneath it stays stable.
Managed versus DIY
You can build this architecture yourself on a VPS. A managed product such as TermSquad removes much of the provisioning, access setup, baseline hardening and terminal setup while leaving the Linux environment under your control.