Sense: finding valuable AI opportunities

Bansi outlines the 'Sense' step: research, map user problems, data access, model constraints, and risk boundaries.

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In this episode of the Future of UX Podcast, I’m speaking with Bansi Mehta, founder of Koru UX Design. We talk about one of the biggest challenges product teams face today:

Everyone wants to add AI to their product.
But very few teams know how to actually design AI features that create real value for users.

Bansi recently shared a framework her team uses internally to design AI-powered experiences. The framework is called Sense–Shape–Steer, and it helps teams move from vague ideas like “we should add AI” to well-designed AI features that solve real problems.

In this conversation we break down the framework step by step and talk about:

✨ why many AI projects fail before they even start
✨ how to identify real AI opportunities
✨ how to decide between copilot, conversational, or agentic experiences
✨ why storyboarding AI behavior matters more than pixel-perfect mockups
✨ and how teams can prototype and test AI features faster than ever

If you’re currently exploring AI features or designing AI-powered products, this episode will give you a practical way to think about it.

00:00 Intro
02:30 Bansi’s background in healthcare UX
06:50 Why most teams struggle with AI features
11:30 The Sense–Shape–Steer framework explained
20:00 Copilot vs agentic AI experiences
27:00 Storyboarding AI interactions
33:00 Rapid AI prototyping and experimentation
44:00 Why AI literacy matters for designers

Bansi Mehta (LinkedIn)
https://www.linkedin.com/in/bansi-mehta/

Koru UX Design
https://www.koruux.com/

Sense–Shape–Steer AI UX Framework
(Comment “SENSE” on Bansi’s LinkedIn post to get access)

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