intelligence being available on tap has killed the expert - before LLMs if you wanted to do something, you would do research for that goal, while attempting to accomplish your task you would learn all kinds of related ways on getting to your goal that later on would somehow be useful across the domain, or would help you recognize patterns now, you have your agentic workflow, you set the direction and you get the output, while it is true that you can and will learn things, the accelerated process doesn't imbued you with witness, patience, hardens you - what you solve today, you just hope your workflow will work for the task of tomorrow i recognize this as the death of expertise and craft, and while anyone could argue that you can always learn the ins and outs and do things the older way, it's a disingenuous argument, the stakes to build and how to build right now are too high to ponder on why something is working or why something is made; you are the vector and you damn better get the output then it just becomes a question of, are the new workflows and harness knowledge the creation of new expertise and craft? well, yes, however if evolving as an expert in your domain is no longer a needed option to create great things, i guess that domain is solved, but what if it's not? that's what's happening with software right now, more code will be generated, until code disappears - perhaps not now, but it's coming, the discipline of software engineering was never about code the same logic, however, can be applied to any other domain being consumed by LLMs right now, even if it's just automating without real intelligence, how much is it left of that domain outside of the training data, and if we no longer become experts to extend and evolve the domain, are we stalled? maybe my premise is wrong and we will get people who keep digging and evolving anything, everything, even if they have to take pause from the insane acceleration - but this makes me wonder if there were the same questions during the industrial revolution