[marcinzm]

I agree.

For example, looking at the ChatGPT link the author has, the model loaded 5 pages besides the one the author wanted. That clearly is going to cause some issues but the author didn't modify the prompt to prevent it. It was also a misspelled five (?) word prompt.

I don't see how you can draw conclusions from a model not reading your mind when you give it basically no instructions.

You need to treat models like an new hire you're delegating to and not an omniscient being that reads your intent on it's own.

[gctwnl]

Why, if the author asks it to summarise a single webpage and gives the link should ChatGPT go out and load 5 more (one is the same page again, the others short overview pages, so won't have influenced the result much)

And why all this talk about trying to engineer a prompt so that in the end the result is good? Should an actual usable system not just handle "Please summarise [url/PDF]"? That is, I suspect, what people expect to be able to do.

[marcinzm]

Summarize clearly means something different to the author and the people who think the model results are good. Everyone expects different things. Most people are used to others knowing their preferences and adjusting over time. Models do not unless you tell them.

[spaceship__sun]

Exactly, 'ChatGPT can't do this that' is way too generic. We can't even be sure if GPT-5 is still the LLM architecture anymore.