Your approach of deciding on the overall framework yourself and then handing individual tasks over to AI as modules is really interesting. I can well imagine that this way of working will become increasingly important.
Perhaps programmers will actually be needed less often — at least those whose main task is writing code. At the same time, there will be an even greater need for people who understand what actually needs to be done, who can capture the requirements properly and recognize when the AI is heading in the wrong direction.
I find your point about newcomers almost even more interesting. If AI takes over a large part of the work from day one, where do they gain the experience they need to judge later whether the result is actually right?
I think this question will keep us busy for quite some time. And in two or three years, the answer will probably already look quite different from today.
Offloading implementation to AI misses a critical truth: writing code was never just execution, but the cognitive vehicle through which engineers stress-tested their architecture. By skipping the painful, hands-on debugging cycles where intuition is forged, we risk creating a dangerous junior talent debt - producing developers who lack the deep mental models required to spot subtle logic bugs or security flaws when AI output strays. In two or three years, the most valuable engineers won't be those who prompt fastest, but those with enough deep technical fundamentals to rigorously audit AI-generated code and call BS when the model inevitably goes off the rails.
Maybe this is actually the more fundamental question: What skills do humans need to retain as more and more of the execution becomes automated?
For me, that includes understanding, critical thinking, and above all the ability to properly understand a problem in the first place. But experience also matters enormously. You need to have experienced things yourself, tried them, and sometimes gotten them wrong to be able to judge whether a seemingly perfect solution actually works.
Perhaps this also changes the value of education. We may not need to train people to execute as much as possible themselves if AI can eventually do it faster. But we need to give them enough depth of understanding to guide, question and, when necessary, correct the AI.
And perhaps that is the real challenge: As we let AI take over more and more of our work, we must not simultaneously lose the skills we need to judge the AI.
Otherwise, we may eventually have increasingly capable and efficient systems, but fewer and fewer people who still know whether the result is actually right.
Exactly. It comes down to a simple question: do we still learn enough by doing the real work, or will we lose our ability to catch sneaky mistakes? We’ll see how things play out. Thanks for the great chat!