The best NLP interfaces will be asking questions to the users, in order to figure out what their real problem is. This is similar to what teachers and therapists do. It is not a lazy interface, but a natural one. The chatbot will step the user through a decision tree in situations where the user doesn't know how to ask questions or frame the problem.
Blog post on the initial idea: An inquisitive code editor: Overcome bugs before you know you have them https://austinhenley.com/blog/inquisitivecodeeditor.html
Grant proposal on the bigger idea: Inquisitive Programming Environments as Learning Environments for Novices and Experts https://austinhenley.com/pubs/Henley2021NSFCAREER.pdf
We all gather information in order to recognize complex patterns and make decisions.
Some of those decision flows are extremely deep, with complex inputs to determine the ultimate decision.
Skilled teachers and therapists develop pattern recognition skills that allow them to tailor a response to the state of their interlocutor. That process is analogous to a decision tree, but feel free to apply another word to it if you like. Whatever we call it, I think chatbots will be able to do that, and I think that will be a good thing.
Everybody's thinking about chatbots as a black box that answers our questions.
That's not the real value. The real value is to give those bots much large multi-modal prompts about whatever problem we seek to solve, and let the LLM ask us the questions to ferret out features that are not superficially visible, so that it can give us better guidance.