| Honest question: Do you feel GenAI coding is substantially different from the lineage of 4GL to 'low code' approaches? Reason I'm asking is because despite all promises al suffered from what Spolsky coined the 'leaky abstraction' problem. Once something goes wrong, the user is left without recourse in a sea of additional complexity created by the tooling that was meant to not have to deal with it in the first place. My own opinion is that GenAI is different because of (a) its recursive reflexive potential (you can use the tool itself to help you past the failure) and (b) it shifts the input out of the necessity for algorithmic/systemic thinking (which may come as a surprise to the audience here but my experience has taught me is alien to dare I say the majority of people). Now don't get me wrong. We have not reached the point where (a)+(b) make it to where you don't need application layer devs, but we are definitely seeing some progress. As for going deeper into the stack to "escape" AI, I would venture that is probably a non starter as the deeper you go the more constrained the domain is, so your escape strategy relies on AI reasoning making little progress, where AI reasoning has always been more successful in smaller well defined spaces. |