[munk-a]

It's funny - the problem with outsourcing is the same problem as AI and it's all a huge callback to the early 2000s. Companies are astonished by just how much money can be saved without realizing the damage to their product. Some will have extremely fastidious oversight from strong product/project leads that will become the new generation of developers and some will buy the pitch and just fail when their software becomes unmaintainable.

In ten years my prediction is that we have just as many developers as now building more products than they build now and AI is used for automation in isolated areas where it makes sense but most software development just happens at a higher level of abstraction where less text garbage is required to express the same concepts and the meat of code becomes even more focused on specifically encoding and highlighting the intricacies of the strange edge cases.

I started my journey in software development working on a MUD that had been passed down through a dozen hands and was extremely dirty software. I can't see anyone wanting to try and pick through the ball of mud and spaghetti that'd result of letting AI build software without severe oversight and corrections.

The core of software development has always been problem solving (or, more accurately, problem identification). As time has gone on we've gotten rid of more and more of the cruft to focus on that point. I suspect that trend line will continue and we'll evolve towards even leaner and more abstract languages to state problems and try and isolate the fiddly logical flow components, driver bits and math more and more into libraries and tools because for most daily work it is important but can be assumed to have been done by someone else better.

[dogcomplex]

I think this is a very reasonable middle-of-the-road AI take and our likely future. Just with the caveat that there's still a major threshold being hit here where we jump up to a new casual capabilities class where it becomes silly not to use AI for the majority of work, but there are still some high-intricacy problems which become much more load bearing than they ever were before and our new abstraction level doubles down on those.

I would like to submit that the high-intricacy work congregates in Protocols themselves, and we start seeing the cycles of development and all the ways to direct AIs, programs, inter-person/inter-company interactions, etc etc all as types of protocol design - and studying those rules of interaction themselves becomes the new job of a programmer (systems architecture). What used to be hard rules and deterministic programs becomes soft self-governing tendencies and probabilistic behavior that can nonetheless be managed and bounded with the right system, but it's new and weird and more akin to management or herding cats than architecture. This is still very different from what most of us were working on before AI, but it's still familiar - especially to those who worked on internet protocols, or defensive UX design around users, physical engineering systems, or team management. Less programming languages, more - control theory, flows and throttles, quality control, design theory, etc. And clearly the field is still wide open as everyone seems to be experimenting with their own take on the AI orchestrator.