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The three basic guidelines are:

* Specify the product as concretely as possible

* Use existing applications to test feasibility

* Get non-engineer user feedback on early prototypes

These all obviously apply to product management more generally, but Andrew gives some examples/ways in which they apply specifically to AI products. Still, I feel like they're talking more generally about complex/abstract software engineering rather than simply AI.



> Specify the product as concretely as possible

This is no small task.


Indeed. I've seen people blind to how vague their specs were — I'm sure we all have a similar story, mine was someone wanting to know how much it would cost to make "uber for airlines" but it really was that vague a description even after I questioned them for more specifics, because their attempt at specifics was still vague.




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