This is no different from reviewing code from actual humans: someone could have written great looking code with excellent test coverage and still have missed a crucial edge case or obvious requirement. In the case of humans, there's obvious limits and approaches to scaling up. With LLMs, who knows where they will go in the next couple of years.

Even that screenshot is bogus. When there's no understanding there can be no misunderstanding either. It's misleading to treat the LLM like there is understanding (and for the LLMs themselves to claim they do, although this anthropomorphization is part of their success). It's like asking the LLM "do you know about X?" It just makes no sense.

In order to get the full benefit of AI we must apply it irresponsibly.

That’s what it boils down to.