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Most of the mentioned issues wouldn't be catched by a test loop unless you have 100% automated tests (unit tests, ...)

Which isn't always plausible ( time ). The AI makes makes different mistakes than humans that are sometimes harder to catch.



It's a lot more plausible now you can get LLMs to help write those tests in the first place.


Most of these examples build ( shallow test in my LLM on the end of the task ) and produced new edge cases




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