Do not keep every screen on by default. Protect only the local part of the workflow that actually depends on your device.
A long AI workflow may include remote inference, local preprocessing, uploads, tool calls, builds, browser automation, and result downloads. Each step reacts differently to screen-off, full sleep, and network loss.
Map the workflow before changing power settings. When local execution matters, use a temporary operating-system sleep inhibitor and add checkpoints, logs, retries, and resumable work where possible.
List which steps run in the browser, on your computer, and on a remote service.
Temporarily prevent system sleep for local agents, servers, uploads, builds, or scripts.
Save checkpoints and logs, use resumable transfers, and verify the result after the run.
Scope sleep prevention to local work, keep durable checkpoints, and rely on the product's documented background behavior for remote work.
Prefer a temporary, scoped setting for the task. Restore normal power behavior afterward.
Usually not for computation. Keep it on only if the workflow requires visible progress or interaction.
Often the remote computation can, but uploads, local tools, browser sessions, and confirmation steps may still depend on your laptop.