In my company some people are using LLMs to generate some of their code, but more are using them to get a first code review, before requesting a review by their colleagues.
This helps getting the easy/nitpicky stuff out of the way and thereby often saves us one feedback+fix cycle.
Examples would be "you changed this unit test, but didn't update the unit test name", "you changed this function but not the doc string", or "if you reorder these if statements you can avoid deep nesting". Nothing groundbreaking, but nice things.
We still review like we did before, but can often focus a little more on the "what" instead of the "how".
In this application, the LLM is kind of like a linter with fuzzy rules. We didn't stop reviewing code just because many languages come with standard formatters nowadays, either.
While the whole code generation aspect of AI is all the rage right now (and to quote the article):
> Focus on tangible changes in areas that you care about that really do seem connected to AI