A guide to choosing where to run
AI workspaces
Explore AI workspaces in the runtime catalogue and check how code execution, workspace state and agent access are handled.
What to check before choosing
An AI workspace is useful only if its execution environment fits the work you need to do. Check where code runs, what the agent can access, and whether you can inspect commands, files and results. A conversational interface alone says little about those boundaries.
Follow a project through its lifecycle: importing code, installing dependencies, retaining files between sessions, supplying credentials and exporting the result. Check whether the workspace is also a deployment destination or whether the finished application must be hosted elsewhere.
This is the narrow AI-workspace category in our run-destination catalogue, not a directory of all AI coding assistants, IDEs or no-code builders. Membership does not verify compatibility with a particular agent harness. The list may be small; consult the profiles for assessed evidence and use sandboxes or application hosting when those better match your execution needs.
