Hm, I think the author has got the causality wrong here. The direction of the tech industry is not a result of learning style. Rather, the tech industry goes

Hm, I think the author has got the causality wrong here. The direction of the tech industry is not a result of learning style. Rather, the tech industry goes in the direction of the incentives presented to it, which are largely capitalist in nature, and secondarily due to aggregate preferences and tastes of the various practitioners (which include UX, domain interest, taste in technology, etc). I believe on-demand learning naturally dominates in this environment because the goals are very pragmatic and short-term go-to-market concerns. Of course, when expand beyond the narrowly defined "tech industry", goals could be completely different. For example, pushing the boundaries of mathematics or astrophysics obviously requires a huge amount of preliminary learning to even start to make a dent. But this brings me to where I really disagree with the article: > Putting it bluntly, on-demand learning is excellent for learning tools, but it sucks at learning concepts. I could not disagree more about this, in fact I think it's borderline gibberish. First of all, you can absolutely learn concepts on-demand, and in fact a concrete use case can often make the concept much clearer than if you learned it from first principles. Secondly, of course tools are easy to learn this way, since a tool is a thing which was already thoughtfully designed for a purpose—if your goal is to quickly get something done, and a tool is available, of course that is likely going to be your first choice. Overall preliminary vs on-demand is just about time horizons and they are not mutually exclusive. For example, I don't see any shortage of programmers continuing to learn over the long-haul and develop new concepts and practices inductively based on years of short-term focused work.