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The Smartest Way To Approach AI Prototyping
The Deep View
May 02, 2026
Hello, friends. Teams building AI are running into the same problem: they cannot align on what to build until it is visible, and by then, time is lost. Prototyping fixes that. This guide offers a framework to choose where to invest before planning cycles begin. Thanks for tuning into this special weekend edition, presented in partnership with Miro. Let us know what you think! —Jason Hiner
The Smartest Way To Approach AI Prototyping
If you've ever been part of shipping an AI feature, you've probably hit the same wall most teams hit:
Nobody can agree on what you're actually building until they can see it, and…
By the time engineering has built something to look at, you've already burned weeks going in the wrong direction.
That's the problem prototyping solves. A prototype is just a fast, clickable version of your idea that the whole team can react to before anyone writes real code. Done well, it kills bad ideas early and gets everyone aligned on the right ones.
The trouble is, the AI prototyping tool landscape is changing weekly, and most teams have no real framework for picking what to use.
That's exactly why Miro put together this free guide. Inside you'll get a question set to lock in your requirements, a clear overview of the AI prototyping landscape today, and a tooling evaluation framework and scorecard so you know where to actually invest.
If you want to get in front of an audience of 750,000+ developers, business leaders and tech enthusiasts, get in touch with us here.