This is why the chat interface is ultimately not the best option for non-expert users, because they require the user to bring knowledge with them. You can call this the “query” method: you have to know what to ask to get the answer you want.
A real world example might be: I can find any movie DVD you want from our warehouse, but you need to tell me the name of it. Don’t know the name? Tough luck.
Contrast this with a “browse” interface: the options available are presented to you, and you can pick from them. Relevant contextual information is already on-site. The DVD store has shelves of potential movies you can rent, and you don’t need to know their names ahead of time.
The interfaces of future AI will be more browse oriented, with a query viewer available in the settings for advanced users.
Picking a DVD to watch is a rather inconsequential decision. LLMs already do this sometimes, asking you to pick one of a few options, but without domain expertise you will invariably make worse decisions, but if all the n-th order consequences were first explained to you, that would result in you having built domain expertise, but also erasing most of the speed advantage LLMs give you. Moreover, you will never know about the options that are never presented.
Inevitably, this is the new tradeoff to make, above average quality comes from asking for more, and knowing what to ask for comes from expertise.