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Cursor, Claude Code, Codex, and Devin can open a browser and check the change they just made. That works for one diff in one session, and the check disappears with the session. Momentic keeps the check as a YAML test in your repo, runs it on managed browsers, emulators, and simulators, and returns the evidence from a failing step to the agent over its MCP server. For a running app with no test suite, see Mo.

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What each one is for

Agentic steps are non-deterministic. Keep critical paths step-based and wrap each agentic step in an assertion. See agentic testing.

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Read a failing run

When a coding agent maintains the suite, it also debugs the runner. It re-runs a flaky spec, reads a stack trace, and guesses which selector moved. Each of those turns costs wall time before the agent reaches the product bug. The test adapts as it runs, so that work does not reach your agent. Auto-heal re-resolves a moved locator mid-run, failure recovery clears a transient obstruction and retries the step, and classification triages what broke. When a run does fail, it produces artifacts per step, and the agent reads them through the MCP server:
  • Screenshots before and after each step.
  • A trace with the DOM, the network requests, and the console output.
  • The step execution order with each step’s status and duration.
  • Video, when recordVideo is on.
See run artifacts for where each one is stored, and request visual evidence for the prompts that make an agent display them. A typical loop:
1

CI runs the suite

npx momentic run fails on a step and uploads the run.
2

The agent reads the failing step

With the momentic-maintain skill, the agent finds the run for the branch, reads the saved classification, and opens the artifacts for the first step that changed behavior.
3

The agent decides what broke

A product bug goes back into the code. A stale locator or an intended behavior change goes into the test file, in the same pull request as the code.
Devin can drive this loop with no extra setup beyond the MCP entry. See Devin.

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What a repeat run costs

A coding agent that maintains a Playwright suite calls a model on every failure, and again on every rerun of a flaky spec. Because the run adapts itself, your agent is called for a product change and not for a test change, so the loop runs less often and each cycle is shorter.
  • Each run reports its duration and cost in the dashboard. See run results.
  • Hosted browsers run the suite off your CI machines, so the runners can be lower-spec.

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Product context between runs

An agent session starts with no memory of your product. The knowledge base holds your terminology, per-agent rules, and known flows, and Momentic retrieves the relevant entries on every AI-assisted step. A decision you record, such as marking a finding expected behavior, becomes an entry that later runs retrieve.

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When the coding agent is the better tool

  • The check only covers the diff you are writing right now. Use momentic-spec so the affected tests land with the change; see spec-driven development.
  • The task is a one-off inspection you do not want to keep, such as reading a staging page to confirm a deploy.
  • The work is a code change. Momentic does not read or write your product code.
Momentic is the right call if the check must outlive the session, run on every merge, and cover flows nobody touched in this diff, and if you want the failing step handed back to your agent with its evidence instead of a stack trace.