This argument can be applied to anything AI does. AI can do bad writing, bad code, bad graphics and bad music.

But AI cannot (yet?) do the job of a skilled writer, coder, graphical artist and musician.

And it is the same problem every time, LLMs lack intention. That's essentially what the article is about, writers choose every word because they have something to convey. Something complex, deliberate, that can't fit in a simple prompt, a LLM can't get these nuances, it is all in the writer's head, so you get something generic, the information to do it better simply isn't there.

But it apply to other arts as well, ChatGPT flyers, Suno music, etc.. they all look and sound the same, because there is no intention behind them, besides all the technical issues, like inconsistent images and instruments blending into each others, the model just can't work with information it doesn't have, so it just generate something generic that looks like its training dataset.

And it is the same with code. Coding is not about the programming language, it is about expressing with precision what the machine has to do, and programming languages are really good at that, that's why they exist. LLMs let you use English instead, but it doesn't change the fact that everything has to be intentional, otherwise, the LLM will just put something that may or may not be what you want.

Most success stories of LLM coding are ports. Because someone already did most of the job with the original code, sometime even twice if we count the tests.