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Luotsi Luotsi

AI Agent Android Automation

If you searched for AI agent Android automation, the practical question is whether your agent can inspect real device state, act through a host-side control loop, and recover with replay artifacts. That is exactly the slice Luotsi is built to cover.

What Luotsi gives an agent loop

Section titled “What Luotsi gives an agent loop”
  • inspect for structured JSONL exploration of the current screen.
  • view when a human still wants the mirrored device while the agent consumes stream state.
  • run when the flow is stable enough to codify as a JSON scenario.
  • replay when the device session is over and the next question is summarization, search, or triage.
Section titled “Recommended starting path”
Terminal window
luotsi doctor --device <serial> --fix
luotsi inspect --device <serial>
luotsi scenario-validate --path scenarios
luotsi run --path scenarios --device <serial>
luotsi replay packet --artifacts ./artifacts/<run>
luotsi replay packet --artifacts ./artifacts/<run> --check

This progression keeps the agent loop on the host machine: explore first, codify second, replay after the run. Start replay with packet and packet --check so the agent gets the At a Glance summary, failure snapshot, primary failure, recommended next action, and first-minute checklist before deciding whether to open, summarize, search, draft, or rerun.

When the starting point is Android CLI Journey-style intent, use Evidence-Backed Android Journeys to keep natural-language flow authoring separate from Luotsi’s reviewed scenario and replay evidence path.

Strong fit when

Section titled “Strong fit when”
  • The agent needs real-device Android state rather than browser DOM state.
  • You want machine-readable JSONL sessions instead of a window-only control path.
  • You want the same runtime to support human debugging, agent exploration, and CI scenarios.
  • You need artifacts after the run, not just a final pass or fail.

Weaker fit when

Section titled “Weaker fit when”
  • The workflow never leaves a browser automation surface.
  • You need a cloud platform to supply both the devices and the orchestration model.
  • You only care about scripted end-to-end runs and not agent-driven exploration.

Open these next

Section titled “Open these next”