I think there is something here with the DAG exploration graph that systematically increase the surface area of exploration when the agents QA's an app. And I've definitely noticed in my own experience that Playwright QA steps in a coding agent will catch certain bug classes very reliably but some edge cases will slip through from time to time. So catching more bugs (even at a higher cost per bug) is quite useful.
But i suppose that this DAG approach is only useful for codebase-wide bug sweeps? If one actually integrates it into a feature-by-feature agent loop, then the QA following each change is already narrow (since it only needs to test 1 changed feature), so this kind of exploration thoroughness optimization (in author's own words "recall") is less important.
But i suppose that this DAG approach is only useful for codebase-wide bug sweeps? If one actually integrates it into a feature-by-feature agent loop, then the QA following each change is already narrow (since it only needs to test 1 changed feature), so this kind of exploration thoroughness optimization (in author's own words "recall") is less important.