Arpy Dragffy Guerrero

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627 appearances 7 recordings 1 series first heard May 2026 last heard 6 Aug

Arpy Dragffy Guerrero’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 7 in all, peaking in Jun 2026 with 3.

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Product Impact Podcast | Secrets to unlocking the value of AI · 17. Your AI Product is Failing — Microsoft's UXR Team Knows Why · 20 Jul 2026 podcast

Every industry, every archetype.

Regulated environments, hundreds of millions of interactions.

And where this team is taking UX research next, the new methods they're developing that the rest of the field will eventually follow.

This conversation is essential for anyone building with AI, because LLMs have made every business believe that it's possible to build an agent that can handle any use case.

That belief becomes immensely difficult to act on the moment it meets real users.

So to develop, scale, measure, and manage in a way that actually serves people rather than just impressing them in a demo.

We're gonna have three different perspectives coming from Microsoft Copilot.

And so let's jump into it.

Copilot is the most used AI product in the world by

Yeah.

What is the hardest part of existing under the weight of so many different user expectations and restrictions and regulated environments?

So we're gonna talk a little bit more about evolves in a a couple minutes.

So I won't get into that much right now, but when you say side by side experience, can you define that for us?

The average person would probably look at that method of saying, We just have people come and bring their own prompts and go through their own experiences.

I think in research you would typically be like, Well, you can't really control for that then and you have so many different experiences that people are bringing and how do you then get enough um responses that you feel like you can actually act on all those different experiences?

But it sounds like what you're saying is that was actually probably

one of the best reasons that it allowed you or one of the secrets to building an AI product that can do everything and work for everyone because you have a wider breadth of cases.

Is that true or is there some other secret about how to build for everything for everyone?

Fabulous.

Thank you.

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