Comment by dspillett

> To some degree, traditional coding and AI coding are not the same thing

LLM-based¹ coding, at least beyond simple auto-complete enhancements (using it directly & interactively as what it is: Glorified Predictive Text) is more akin to managing a junior or outsourcing your work. You give a definition/prompt, some work is done, you refine the prompt and repeat (or fix any issues yourself), much like you would with an external human. The key differences are turnaround time (in favour of LLMs), reliability (in favour of humans, though that is mitigated largely by the quick turnaround), and (though I suspect this is a limit that will go away with time, possibly not much time) lack of usefulness for "bigger picture" work.

This is one of my (several) objections to using it: I want to deal with and understand the minutia of what I am doing, I got into programming, database bothering, and infrastructure kicking, because I enjoyed it, enjoyed learning it, and wanted to do it. For years I've avoided managing people at all, at the known expense of reduced salary potential, for similar reasons: I want to be a tinkerer, not a manager of tinkerers. Perhaps call me back when you have an AGI that I can work alongside.

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[1] Yes, I'm a bit of a stick-in-the-mud about calling these things AI. Next decade they won't generally be considered AI like many things previously called AI are not now. I'll call something AI when it is, or very closely approaches, AGI.