I've recently been trying to write a paper with an application in a field that I'm not an expert at. I gave the LLM agents to analyze the methods, the data, the outputs, plus some explanations from me what I want to say and show, and told it to write a section of the paper. It did. Then I asked like 3-4 more different frontiers to do the same.

They all do.. something[1]. They write visually great looking papers. Even good on a quick read.

But once I try porting their proposed Section ideas into the paper, I notice that for each sentence I either need to do a complete rewrite, or a deep dive into it (plus the literature), to confirm or delete that idea/sentence.

If it were my field, it would be much simpler to just write everything directly, rather than attack every sentence of LLMs. As it's not my field, it's a decent way to understand the nuances and learn, but I get increasingly disillusioned by AI writing skills.

[1]: Old and new Gemini models are too categorical, everything is a breakthrough and a marvel; Sol/Astra gets bogged down with too many details, and "it's X, not Y" garbage. For some reason, it's very defending against potential referee questions which don't add anything to the main idea; Opus 5.5 or Fable are basically the same. Maybe it's their way of anti-hallucination..

You almost have to treat these models as a monkey paw, or a maliciously compliant genie. They grant you your wish, but rarely the way you intended. You must be incredibly diligent, or accept the consequences.