I see where you're coming from, and I agree with the implication that this is more of an issue for inexperienced devs. Having said that, I'd push back a bit on the "legacy" characterization.

For me, if I check in LLM-generated code, it means I've signed off on the final revision and feel comfortable maintaining it to a similar degree as though it were fully hand-written. I may not know every character as intimately as that of code I'd finished writing by hand a day ago, but it shouldn't be any more "legacy" to me than code I wrote by hand a year ago.

It's a bit of a meme that AI code is somehow an incomprehensible black box, but if that is ever the case, it's a failure of the user, not the tool. At the end of the day, a human needs to take responsibility for any code that ends up in a product. You can't just ship something that people will depend on not to harm them without any human ever having had the slightest idea of what it does under the hood.

Take responsibility by leaving a good documentation of your code and a beefy set of tests, future agents and humans will have a point to bootstrap from, not just plain code.