Designing for Failure: When AI Gets It WrongAI might be impressive—but it’s not always right. And when it fails, your UX design can make or break user trust. In this episode, Kate dives into one of the most overlooked aspects of designing with AI: what happens when the system makes a mistake.From fallback states and recovery paths to confidence indicators and transparency, you’ll learn practical strategies for turning AI errors into opportunities to build trust—not break it. Whether you're designing chatbots, generative tools, or recommendation engines, this episode gives you a UX-first lens on human-AI collaboration, especially when things go wrong.Why AI errors require intentional UXHow to design graceful fallback states and undo flowsWays to signal uncertainty and build trustReal-world product examples and design tips🎙️ Tune in, and start designing for the messy, human side of AI.This podcast reflects my personal opinions and is not associated with my current or past employers.

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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