Okay, when that happens, then sure, you don't need to understand the codebase.

I have not seen any evidence that that is currently the case, so my observation that "Continue letting the LLM write your code for you, and soon you won't be able to spot errors in its output" is still applicable today.

When the situation changes, then we can ask if it is really that improtant to understand the code. Until that happens, you still need to understand the code.

What happens when your LLM provider goes down during an incident?

What happens when you have an incident on a distributed system so complex that no LLM can maintain a good enough understanding of the system as a whole in a single session to spot the problem?

What happens when the LLM providers stop offering loss leader subscriptions?

Natural language is not a good way to specify computer systems. This is a lesson we seem doomed to forget again and again. It's the curse of our profession: nobody wants to learn anything if it gets in the way of the latest fad. There's already a historical problem in software engineering: the people asking for stuff use plain language, and there's a need to convert it to a formal spec, and this takes time and is error prone. But it seems we are introducing a whole new layer of lossy interpretation to the whole mess, and we're doing this happily and open eyed because fuck the lessons of software engineering.

I could see LLMs being used to check/analyze natural language requirements and help turn them into formal requirements though.