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One thing I can't help but noticing is that the majority of discussions regarding this talk are focusing on the examples presented.

I thought it was pretty clear that the talk wasn't about whether constraint-based solvers and visual programming environments were the "future of programming." It was a talk about dogma. Brent points out that none of the examples he's mentioned are inherently important to what he was trying to get across: they were just examples. The point he was trying to elucidate was that our collective body of knowledge limits our ability to see new ways of thinking about the problems we face.

It is at least somewhat related to the adage, when you have a hammer every problem looks like a nail. He's just taking a historical view and using irony to illustrate his point. When computer technology reached a certain level of power there was a blossoming garden of innovative ideas because the majority of people didn't know what you cannot do.

What I think he was trying to say, and this is partly coloured by my own beliefs, is that beginner's mind is important. Dogma has a way of narrowing your view of the world. Innovation is slow and incremental but there's also a very real need to be wild and creative as well. There's room for both and we've just been focusing on one rather than the other for the last 40 years.



In this discussion I've been trying to make the point that he's missed the mark even in the idea that developer attitude is the inherent barrier preventing these breakthroughs. I believe he's stealing bases here. At least with respect to visual programming, there is objective evidence (that is easily google-able) that this problem is actively being tackled but with very little success. Active and recently failed projects seem to be glaring counterexamples to his broader point, at least with respect to the visual programming domain.

I suspect that my point about presuming developer attitudes are the biggest problems here can more broadly applied though I do not have enough experience with constraint-based solvers and his other examples to do more than wildly speculate.




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