working-with-instances-manager

Managing AI workspace instances across runtimes requires an orchestration API that handles creating, starting, stopping, and deleting workspaces. This approach integrates with runtime registries to control multiple isolated environments from a single interface.

Automatic project detection for AI workspaces is a mechanism that integrates with git-based sources to identify project configurations. It merges workspace, project, and agent settings automatically to streamline onboarding and ensure reproducible environments.

To start and connect to isolated workspace instances, you apply start lifecycle operations through the management API. Once running, you can establish interactive terminal sessions to directly interface with the orchestrated AI workspace environment.

Yes, you can merge agent settings automatically when onboarding new workspace instances. The onboarding integration automatically merges workspace, project, and agent configurations to streamline multi-workspace workflows without manual setup.

The best way to orchestrate multiple AI workspace lifecycles is using a dedicated instances manager. It provides a comprehensive API for listing, querying, and managing state transitions across one or more runtimes, ensuring reproducible environments.

You do not strictly need git-based project detection, but it is required for automatic configuration. By supplying a source directory, git-based project detection merges configurations automatically, streamlining the setup of isolated AI workspaces.