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Everything in GRID starts from the grid CLI — an interactive shell that onboards robots, starts simulator and robot sessions, and deploys programs.

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1. Install the CLI

Your organization’s GRID admin portal shows this same command on its Welcome screen, pre-filled with your cluster:
Prefer the portal variant — it registers your cluster so login connects to the right place immediately. (Windows support is coming soon; use WSL in the meantime.) The installer verifies a signed binary, installs it to ~/.grid/bin/grid, adds it to your PATH, and offers the GRID Studio VS Code extension. Open a new terminal and run:

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2. Log in

Inside the shell, authenticate with your browser:
Your tokens are stored per cluster; context use switches the active cluster if your organization has more than one (context list shows them).

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3. Get your Cortex API key

Cloud model inference (detection, depth, grasping, VLAs) is authenticated by a separate runtime key. Generate it in the admin portal (the same site that showed your install command — ask your org admin for its URL if you don’t have it), and paste it when robot add asks — the CLI persists it for every later session.

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4. Onboard a robot

The wizard walks you through connecting your robot to the GRID network. Once added, it shows up for everyone in your organization:

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5. Start working

sim start allocates a cloud simulator (it opens a browser workspace with a live scene). To work against your physical robot, run skill run --dev and choose an online robot. The CLI opens a VS Code workspace in the current folder with dev.ipynb and Python configured. You can start in the notebook or create a Python file in the editor.

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