How we work changes and the extra complexity buys us productivity. The vast majority of software will be AI generated, tools will exist to continuously test/refine it, and hand written code will be for artists, hobbyists, and an ever shrinking set of hard problems where a human still wins.
This to me looks like an analogy that would support what GP is saying. With modern farming practices you get problems like increased topsoil loss and decreased nutritional value of produce. It also leads to a loss of knowledge for those that practice those techniques of least resistance in short term.
This is not me saying big farming bad or something like that, just that your analogy, to me, seems perfectly in sync with what the GP is saying.
Truth is, for "AI" to get markedly better than it is now (0) will take vastly more money than anyone is willing to put into it.
(0) Markedly, meaning it will truly take over the majority of dev (and other "thought worker") roles.
Just about a week ago I launched a 100% AI generated project that shortcircuits a bunch of manual tasks. What before took 3+ weeks of manual work to produce, now takes us 1-2 days to verify instead. It generates revenue. It solved the problem of taking a workflow that was barely profitable and cutting costs by more than 90%. Half the remaining time is ongoing process optimization - we hope to fully automate away the reaming 1-2 days.
This was a problem that wasn't even tractable without AI, and there's no "explosion of AI generated code".
I fully agree that some places will drown in a deluge of AI generated code of poor quality, but that is an operator fault. In fact, one of my current clients retained me specifically to clean up after someone who dove head first into "AI first" without an understanding of proper guardrails.
People often say this when giving examples, but what specifically made the problem intractable?
Sometimes before beginning work on a problem, I dramatically overestimate how hard it will be (or underestimate how capable I am of solving it.)
