Pre-release guide

Design a recoverable desktop run.

Plan a computer-use workflow around application readiness, bounded control, durable artifacts, and deliberate recovery.

Planning a pilot? Share the workload
This is a design guide, not a live SDK reference.

Adept AI is pre-release. Final methods, limits, supported images, retention, and commercial terms are confirmed only in a written pilot scope.

01

Define the workload

Describe the application version, input artifacts, desired output, expected run length, and the evidence an operator needs to review.

02

Confirm capabilities

A pilot environment should report the controls, limits, application image, and recovery features actually available before an agent begins work.

03

Create the environment

Provision a clean application-ready desktop with a bounded workspace and an idempotent request identifier.

from adept import Client

client = Client()
environment = client.environments.create(
    "kicad",
    name="Board review",
    idempotency_key="board-review-v1",
)

environment.wait_until_ready()
capabilities = environment.capabilities()
print(capabilities)
04

Connect the control loop

Observe the screen, send pointer and keyboard input, and move approved files through explicit operations.

05

Checkpoint useful progress

Save inside the application, create a checkpoint, and verify that persistence succeeded before a risky step.

  1. Save the active document in the application.
  2. Create the checkpoint request.
  3. Wait for a durable success response.
  4. Record the checkpoint identifier with the agent trace.
06

Stop, inspect, or recover

Collect the intended artifact, preserve the run record required by the pilot, and either stop cleanly or restore a verified checkpoint.

Proposed control groups

One environment, explicit responsibilities.

ObservationScreenshot and structured application state
InputPointer and keyboard operations
ArtifactsApproved uploads, downloads, and checkpoints
LifecycleCreate, inspect, stop, resume, recover, and destroy