I agree. Since I'm recently retired and no longer code much, I don't have much need for LLMs but refining a complex, niche web search is the one thing where they're uniquely useful to me. It's usually when targeting the specific topic involves several keywords which have multiple plain English meanings that return a flood of erroneous results. Because LLMs abstract keywords to tokens based on underlying meaning, you can specify the domain in the prompt it'll usually select the relevant meanings of multi-meaning terms - which isn't possible in general purpose web search engines. So it helps narrow down closer to the specific needle I want in the haystack.

As other posters said, relying on LLMs for factual answers to challenging questions is error prone. I just want the LLM to give me the links and I'll then assess veracity like a normal web search. I think a web search interface allowed disambiguating multi-meaning keywords might be even better.

I’ll give you another use: LLMs are really good at unearthing the “unknown unknowns.” If I’m learning a new topic (coding or not) summarizing my own knowledge to an LLM and then asking “what important things am I missing” almost always turns up something I hadn’t considered.

You’ll still want to fact check it, and there’s no guarantee it’s comprehensive, but I can’t think of another tool that provides anything close without hours of research.