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Or a custom zeroshot graph based on your actual QA requirements
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Hey I'm Gabe (one of the engineers @Momentic). In general Mo's advantage is in the total amount of bugs found. In comparison to claude code we find roughly 5x as many bugs at 35% less per bug (for the 60 min session).
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Then stock claude code??? that's like... the lowest of bars.
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You're right stock CC was pretty terrible. Thats why we compared against CC && Codex with agent browser and playwright mcp as well as devin. Do you have any other agents / configurations you'd like to see?

We had someone recommend browser-use and are running it against the benchmark currently. We're hosting the results here if you'd like to see more: https://momentic.ai/qa-bench

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I think all of those are very naive approaches. What I currently do is script out screenshot + application state pipelines and then run those screenshots and states through clef with questionnaires. The scripts are deterministic, clef costs pennies or less and is also reliable, the questionnaires are derived from the script with escalation to stronger lmm's if necessary (historically very infrequent from my usage). It isn't a "drop in" solution, but it is fairly trivial to set up and you can attach it to CI. It isn't perfect, but I've found it to be more successful and way more cost effective than throwing Claude or GPT models at it regardless of harness.
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Thoughts on the bitter lesson? Eg what if models just keep getting better?
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Good question, in short our harness & e2e tests act as compliments with the frontier rather than competitors. Architectural choices and data you provide really matter for domain specific tasks. Mo will be working with harness specific tooling like: previous momentic test results, our KB, and eventually creating new Momentic regression. Having smarter/more capable models will improve the efficiency of AI generated tests (coverage/runtime) and ideally do less repetition in exploratory testing.
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