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by brettcooke
547 days ago
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Andrew Ng made another point about AI product management in a previous piece [1] that I found both thought-provoking and a bit contrarian, and I’m surprised he didn’t mention it here. In that earlier piece, he went beyond just advocating for concrete specs and explicitly challenged the traditional design-thinking approach, arguing that teams should pick a fully formed idea and run with it rather than spending too long on broad problem exploration and multiple potential solutions. It’s a stance that favors speed and specificity over the more open-ended, iterative nature of design thinking. Curious what others think about forgoing design thinking in AI product development in favor of this more direct, concrete approach. [1] https://www.deeplearning.ai/the-batch/concrete-ideas-make-st... |
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Not every product can be totally designed and spec’d out from the outset. Especially when time to market is important.
Maybe this works at the individual feature scale, but at any reasonably large product, designing _everything_ from the outset would result in brittle design.