We’re joined by Louise Macfadyen, author of Designing AI Interfaces, to talk about how we actually design for AI, and why most companies are getting it wrong.
We unpack “algorithmic transference” (why one bad AI experience makes you distrust all of them), the limits of the chat interface, and whether the text box is here to stay. Louise walks us through the history from command line → Google search → LLMs, and why designing for ambiguity is still one of the hardest problems in product.
We also get into generative UI (and why it might be a trap), how large companies should actually integrate AI without breaking user trust, and why understanding user intent matters more than ever. Plus: vibe coding, personal AI “jigs,” and the tension between personalization and privacy.
If you build products, or just use AI, this will change how you think about interfaces.
📘 Designing AI Interfaces · 🧠 Algorithmic Transference · 🛠️ Claude Code
