I'll need to work on the diagram to make it clearer next time. What it's trying to communicate is, in general, a human operating a computer has to turn their i

I'll need to work on the diagram to make it clearer next time. What it's trying to communicate is, in general, a human operating a computer has to turn their imprecise thinking into "specific and exact commands", and subsequently, understand the "specific and exact output" in whatever terms they're thinking off, prioritizing and filtering out data based on situational context. LLMs enter the picture in two places: 1) In many situations, they can do the "imprecise thinking" -> "specific and exact commands" step for the user; 2) In many situations, they can do the "specific and exact output" -> contextualized output step for the user; In such scenarios, LLMs are not replacing software, they're being slotted as intermediary between user and classical software, so the user can operate closer to what's natural for them, vs. translating between it and rigid computer language. This is not applicable everywhere, but then, this is also not the only way LLMs are useful - it's just one broad class of scenarios in which they are.