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The explore agent can dogfood your app for you: it walks the user journeys it discovers in a live browser and files a potential bug whenever the observed behavior does not match what a user would expect. Reach for this to bug bash a staging build before a release, to dogfood a feature branch, or to run a recurring automated bug bash across the whole product.
The explore agent is in beta and may change.

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What a bug report contains

Every potential bug the agent files includes:
  • A short title and a one-line summary of what is broken, from the user’s perspective.
  • The expected behavior and the actual behavior observed instead.
  • A severity: high when something is completely broken and blocks user progress, medium for broken non-essential functionality a user will still notice, low for minor UI/UX issues a user is unlikely to notice.
  • Ordered, concrete reproduction steps from a clear starting point.
  • A screen recording of the reproduction when one was captured.
The report describes observable behavior only; the agent never proposes code-level fixes.

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Run a bug bash

momentic ai bugbash latest reuses explore’s journey discovery, then verifies each discovered plan in a live browser and reports bugs instead of building tests:
The explorer maps the whole product, and each plan is checked by a dedicated agent that exercises the flow and files bugs for anything broken along the way. By default no tests are authored or edited, so nothing needs review or merge afterwards; the output is the bug list. To also build tests for the same discovered journeys, run momentic ai explore latest, which authors tests and reports any bugs it finds along the way. bugbash latest accepts the same flags as momentic ai explore latest: use --budget or --granularity to control how many plans are verified, --parallel to verify several plans at once, and --timeout to cap the run (60 minutes by default).

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Dogfood a change

To dogfood a specific change rather than the whole app, run momentic ai explore diff over the diff window. Bugs the agent finds while covering the changed journeys are included in the output alongside the proposed tests, so a PR or merge to main gets both coverage and a bug report in one run. Pass --dry-run to skip building tests and only report what it discovered. See Author tests from a diff in CI for the workflow setup.

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Steer the bash

The agent needs the same project context a new teammate would: which URL to target, how to sign in, and what to focus on. Keep that in a committed prompt file and pass it with --prompt-file:
--prompt-file and --prompt are repeatable and stack in order, so you can layer a bash-specific focus on top of a general repo overview:
Useful things to put in the bug-bash prompt file:
  • The environment to bash (a staging URL, not production) and the test account to sign in with.
  • Areas to focus on: a feature that just shipped, a flow customers reported problems with.
  • Areas to skip: admin screens, third-party embeds, destructive actions.
  • Data guardrails: do not send real emails, do not delete records.
See Write a good prompt file for the general guidance.

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Review the findings

The CLI prints each potential bug with its severity, summary, and reproduction steps; pass --json for a machine-readable result. Every run also appears on the Explorations page in the dashboard, where each bug’s reproduction steps and screen recording can be reviewed and shared. When Slack notifications are configured for explore, potential bugs are included in the org-channel notification and the author DM.

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Run it on a schedule

A recurring bug bash against staging catches regressions that no test asserts on yet. Run it nightly or before each release:
.github/workflows/momentic-bugbash.yml
Because a bug bash never opens a pull request, the job needs no contents: write or pull-requests: write permissions; only the MOMENTIC_API_KEY secret.