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To keep an AI coding agent working after you close your laptop, run the agent and its project on an always-on remote host, then connect to that host from your laptop. Disconnecting a laptop does not move an agent that is already running locally to a VPS; start a separate session in the remote workspace instead.
What actually persists when you disconnect?
The machine running the agent owns the work. In VS Code, the Agent Host owns agent sessions; while that host remains running, an active turn can continue even when no client is connected. The remote machine must also stay powered on and reachable over the network. See VS Code’s remote agent session documentation and its explanation of the Agent Host (page marked September 30, 2026; the feature is under active development).
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That is different from transferring an in-progress local turn. OpenAI’s guidance on local work sync says a turn running locally does not automatically switch to cloud execution when the computer goes offline. If the laptop is the host and it sleeps, loses connectivity, or stops the relevant process, remote access or execution may stop too.
Choose where the agent and project should live
| Setup | Where execution happens | What disconnecting means | Best fit |
|---|---|---|---|
| Remote workspace session | On the SSH host or dev-tunnel machine, alongside its selected project folder | A session owned by a still-running remote host can continue without the laptop client | You want the project and agent to keep working while the laptop is unavailable |
| Self-hosted agent sandbox | In a user-managed environment such as a container or remote sandbox, through an executor connected to an agent session | The executor must remain running; if its connection drops, it is designed to reconnect | You are building an application around the agent API and can operate the environment |
| Remote into a laptop | On the laptop, using its local workspace and tools | Remote access and execution still depend on the laptop staying awake, connected, and running the host process | You need access to an existing local project and can keep the laptop available |
For most people seeking laptop-to-VPS continuity, the remote workspace is the direct route: put the repository and required tools on the machine where the agent will run. VS Code documents remote sessions over SSH and dev tunnels, with a remote folder selected before starting a prompt. A self-hosted sandbox is an API architecture, not a one-click consumer VPS feature; OpenAI’s self-hosted sandbox guide describes the environment and executor responsibilities.
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Start a session on a remote host in VS Code
- Prepare the host. Make sure the remote machine is powered on and reachable. Put or clone the project on it, and install the dependencies and agent tools the project needs. A remote session uses the remote folder; do not assume your laptop’s files or installed tools have moved there.
- Connect using a supported route. Use an SSH host or a dev tunnel as described in VS Code’s remote-session instructions. For a tunnel, require account authentication. Anonymous access can expose the ability to start sessions.
- Select the remote project folder. Create the agent session against the folder on the remote host, rather than continuing to treat a local session as if it had migrated.
- Start the prompt in that remote session. The agent now runs in the environment that owns the workspace. You can disconnect the client, provided the host, network, and agent host remain available.
- Reconnect to the same host and session. Use the same authenticated remote route and account. If the host is unavailable, check power and network reachability before diagnosing the agent itself.
What a self-hosted sandbox requires
In OpenAI’s self-hosted sandbox model, an executor runs in an environment you manage and handles shell and file operations requested by the agent harness. It must stay running while the agent works and is designed to reconnect if its connection drops. This approach gives you control over the execution environment but also makes you responsible for preparing its files, dependencies, and runtime.
- Keep the executor running for the duration of the work.
- Protect the environment key: OpenAI says to restrict it and keep it out of source code, container images, and logs.
- Make sure the environment contains the repository, dependencies, and tools needed for the requested work.
These requirements are described in the OpenAI self-hosted sandbox guide. They should not be confused with moving a local ChatGPT or coding-agent session onto a VPS with a single handoff action.
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Secure the connection and the remote environment
A remote coding host can hold source code, credentials, and permission to run commands. Treat access to it as access to your development environment, not just as a way to view a screen.
- For SSH, use trusted keys and a least-privilege account; avoid exposing app-server transports directly on a public or shared network.
- For dev tunnels, require authentication. Avoid anonymous tunnels that let unauthenticated users start sessions.
- Restrict stored credentials and environment keys, and do not put secrets in source code, container images, or logs.
- Check which files, credentials, browser sessions, plugins, and computer-use features are actually available on the remote host. Do not assume laptop-specific state transfers with the project.
VS Code documents tunnel authentication and its associated risks in its remote agent session guidance. Codex’s remote-connection guidance also describes SSH security practices; the available source is a third-party documentation mirror, so treat it as general guidance rather than confirmation of a current official Codex workflow.
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Troubleshoot a session that stops or cannot be resumed
- The remote session will not connect: verify the host is powered on and reachable, then check the SSH or authenticated tunnel connection.
- The agent cannot find files or commands: confirm the remote folder is the intended repository and that its dependencies and required tools are installed on that host.
- The local turn stopped when the laptop went offline: that is not a remote handoff. Start a new session against the remote workspace; local execution does not automatically become cloud execution when the computer disconnects.
- A tunnel is reachable by the wrong people: require account authentication and review who has access; do not use anonymous access for a coding environment.
- A self-hosted executor has disconnected: check that the executor is still running and that its environment key remains valid and protected.
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