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.
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.