> What if in the future it will be easier (and maybe even more natural) to ask an LLM to "imagine" tons of possible inputs and correct outputs for a tool that you are making and then train a tiny model, without writing or generating any code?

This seems to assume you're okay with whatever you're building being a black box that will break in the future and require you to re-train the model for every scenario that comes up. I can't think of a problem I've solved recently where that would pass the bar for me. Maybe for one-off problems like 'I have all this data and I want to classify it' where you could hand-classify say 5-10% of your dataset and train a model to deal with the rest of it?