One of the big impacts of AI on product management is a blurring of the lines between product, design and engineering.
Just because you can use AI to spin up a prototype of your idea, though, it doesn’t mean you always should—you need to let the experts own the “how.”
Just because you can use AI to spin up a prototype of your idea, though, it doesn’t mean you always should—you need to let the experts own the “how.”
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The "let the experts own the "how" is the classic default answer to anything that tries to challenge overspecialisation.
We build prototypes to run experiments, so shouldn't the feedback come from what we observe?
- Shouldn't we learn to be objective?
- I guess we can still ask for feedback to a 3rd party to get feedback?
The point I was trying to make was that while AI empowers PMs, we need to be careful.
PMs building prototypes is great if it’s part of a collaborative process. Not so much if it’s at the expense of involving designers and engineers upfront in discovery.