IMO: One idea I've been pondering is this idea of contextual continuity in programming, or really any task you may ask an AI to do. If I code a system, then th

IMO: One idea I've been pondering is this idea of contextual continuity in programming, or really any task you may ask an AI to do. If I code a system, then that system has a bug; or if I use Illustrator to make a drawing, then the stakeholder says they want the tree a different shade of green; correcting that error after delivery is reasonably easy. If I ask an AI to do either of these things, even if I'm still being paid to be in the room (many supporters would argue this system has replaced me, and thus I'm not even in the room anymore): How does this correction happen? The operator has to take off the vibehat, dig in to the inevitable machine-generated mess the AI has created, and learn everything its done in order to diagnose it (or, keep prompt-praying it comes up with a solution on its own). Getting past this feels like a fundamental issue with the proposed process. AIs are trained on human data, and prompted by humans, who are imperfect. I don't think its reasonable to assume that AI will ever be able to generate perfect solutions, if only because we will never be able to engineer prompts that adequately encapsulate what the prompter wanted, let alone if the AI makes no errors in its generation. If we can't get to that, its obvious to me simply knowing how much of my time is spent every day [writing code] versus [debugging existing code] versus [gathering requirements] that AI is doing any significant amount of any of that unsupervised will not result in a more productive system. It will always be most productive for me to leverage (or tightly supervise) AI in its generation, intercepting errors before they compound, directing the flow of output. I do think the roles and responsibilities of devs is going to change a lot over the next ten years; from crafters to soothsayers or oracles one might say. But I am still very comfortable betting my career on: 1. Someone (meaning: human) needs to do the soothsaying. 2. Those classically trained in software engineering will be the most effective people to do this. 3. The amount of stuff one individual can output will be amplified, but there will still be a reasonable per-capita maximum of output, and thus the industry, in its ever-increasing desire for code and ever-increasing need to manage the output of AI, will continue to demand more soothsayers.