Designing for Failure: When AI Gets It Wrong
AI 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 UX
• How to design graceful fallback states and undo flows
• Ways to signal uncertainty and build trust
• Real-world product examples and design tips

🎙️ Tune in, and start designing for the messy, human side of AI.