The difficulty might be in that much like we partition our brains to prepare for low-effort tasks and high-effort tasks (have you ever hyped yourself up to "fin

The difficulty might be in that much like we partition our brains to prepare for low-effort tasks and high-effort tasks (have you ever hyped yourself up to "finally sit down and get this thing done?"), so too could LLMs partition their compute space. Basically memoizing the low-hanging, easy-to-answer fruit. The difficulty comes in when a system 2 task arises, it's not easily apparent at first what the requester is asking for. Some people are just fine with a single example being shit out, then they copy-and-paste it into their IDE and go from there. Others, want a step-by-step breakdown of the reasoning, which won't be apparent until 2+ prompts in. It's the same as your boss emailing you asking: "What about this report?" It could just be a one-off request for perspective, or it could spider web out into a multi-ticket JIRA epic for a new feature, but you can't really discern the intention from the initial ask. The difference is back-and-forth is more widly accepted, in my experience, interfacing human-to-human than human-to-LLM.