An app that basically reimplements a well documented and tested api is the best possible use case for ai development.

I have nothing against a skilled maintainer with attention to detail using AI tools for assistance.

The important part is the human who will do more than just try to get the LLM to do the hard work for them, though. Once software matures the bugs and edge cases become more obscure and require more thoughtful input. AI is great at getting things to some high percentage of completeness, but it takes a skilled human to keep it all moving in the right direction.

I would cite this blog post as an example of lazy LLM use: It's over-dramatic, long, retains all of the poor LLM output styling that most human editors remove, and suggests that the maintainer isn't afraid to outsource everything to the LLM.