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You're right, I'm not arguing against the article so much as trying to continue its thought. I agree that generative models are useful. Among people who use the

You're right, I'm not arguing against the article so much as trying to continue its thought. I agree that generative models are useful. Among people who use them, I suspect that the next major predictor of success would be adaptability. Confirmation bias is the opposing force: once we form a model, we are biased towards it, and tend to overlook contradictory evidence. One tactic that increases adaptability is not forming a model until you actually have to; this avoids confirmation bias. You're also right about the nature of the test: as an experiment, it does show that presence of generative models predicts success. I'm interested in education, so I'm voicing the reason why this wouldn't be a practical test of qualification.

shevertalov 18y ago
The bias point is well made. I don't remember the quote exactly, but i think it's something like "...when all you know are hammers, everything looks like a nail...". Though I think his point is that you have to at least be able to form models about the problems you tackle and stick to those models. I feel like you need some commitment or vision to be able to move on. Development tends to have two phases, exploration and exploitation. Balancing the two is a real problem. If you exploit too soon you may miss a much better solution, but if you do too much exploring you may just be wasting time. Balancing the two contributes to writing good code it seems.