Concepts

Autonomy docs use a small set of terms across web, mobile, API, and message checks. The same model applies whether a run starts from the dashboard, a pull request, an integration, or an AI assistant.

Plans

A plan describes the user journey Autonomy should verify. A good plan starts with user intent and expected outcomes, then adds test data, environment notes, and assertions only where they make the run more reliable.

Plans can cover browser steps, mobile sessions, direct API checks, inbox waits, SMS checks, visual assertions, and generated checks.

Runs

A run is one execution of a plan against one target environment. Each run has a status, timeline, artifacts, trace data, generated checks, and a review link.

Runs are the unit you attach to pull requests, Slack messages, release notes, and incident follow-up.

Environments

An environment tells Autonomy where to run: a preview URL, staging app, production smoke surface, mobile artifact, or private target reachable through your infrastructure.

Use explicit environment names so reviewers know whether evidence came from preview, staging, production, or a private execution environment.

Evidence

Evidence is the review surface for a run. It connects replay video, screenshots, API responses, network timing, inbox messages, SMS messages, logs, generated checks, and trace pivots into one timeline.

Evidence should answer three questions quickly:

• What did Autonomy try to do?
• Where did the journey pass or fail?
• Which artifact proves the result?

Checks

Checks are the assertions Autonomy evaluates during or after execution. Some checks come from the plan. Others are generated from observed behavior, network responses, messages, or visual state.

Execution environments

Autonomy can execute against public preview URLs, staging apps, uploaded mobile artifacts, and private environments. Use the simplest reachable environment for the first run, then move private or compliance-sensitive flows into your own infrastructure when needed.