[hiq]

There are roughly two cases:

1. you don't know the answer, but you can check yourself and easily whether a given answer is roughly correct

2. you don't know the answer and wouldn't be able to check how valid a potential answer is

LLM-based tools are great for 1 to synthesize various sources into one coherent answer, since in this case, you won't become a victim of their hallucination. E.g. "write a one-off Python script to do this": you can quickly check if it does the job, even though you couldn't say whether that's idiomatic Python.

[ghaff]

When I'm writing (English text) about something I'm passably familiar with, it can be useful for generating some straightforward descriptions and background. Nothing I'd just cut and paste out of the box wholesale but it can be a timesaver, especially if it's somewhat boilerplate.

I would say it is not good at giving a sophisticated answer to anything that requires a lot of nuance. And I've also asked it questions with fairly objective factual answers that it gets hilariously wrong.