Deployment

Deployment choices shape what an AI workspace can see, where its state lives and how much control a team retains. These guides explain the practical boundaries between browser-only tools, cloud services and local-first desktop environments. They look at file access, connected models, permissions, network dependencies, data movement, updates and the operational work required after installation. Local-first does not automatically mean offline or private, so each article separates product architecture from marketing shorthand and shows which questions still need an answer. Use this section when you are planning a rollout, reviewing security and maintenance responsibilities, or deciding whether recurring work with local files and human approval needs a desktop workspace rather than another browser tab. The aim is to make tradeoffs explicit before rollout, so product owners, engineers and operations teams can agree on the controls they need, the services they depend on and the parts of the workflow they are prepared to maintain.