* 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.
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.
Comments
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.
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.