Thinking
A curated set, not a feed. The pieces I'd point you to on leading design through the AI transition, on how AI systems behave with people, and on how trust is earned and repaired. Each links out to where it lives.
Essays
Ranked · 10The Biggest AI Mistake Design Leaders Are Making Right Now →
Plus-AI versus AI-plus: bolting intelligence onto a product versus building around it, and what a design leader has to decide first.
AI Products Have a Behavioral Layer. Almost No One Owns It. →
The layer that decides how an AI signals confidence, escalates, and recovers, and why it needs an owner on the product team.
The Hidden Logic Layer: Where AI Design Actually Happens →
The real design work moved below the interface, into the logic that governs how a system behaves. This names where it went.
My Second Brain Can Fix a Mistake. But It Still Needs Me to Notice One. →
A month of logged failures in a memory system I run myself, and what each one taught about where a person has to stay in the loop. Evidence, not framework.
The Agentic Interface Has Two Faces. We're Building the Easy One. →
An agentic product serves people and machines at once; this is about designing for both.
How to Design Trust Into AI Systems (It's Not What You Think) →
Trust isn't a feeling you hope for. It's engineered across five vectors: clarity, control, consistency, disclosure, repair.
Designing for Trust: Why Explainability Alone Falls Short in AI →
The research says explainability barely moves trust. Consistency and repair are what earn it.
Neuro-Symbolic AI: Why Behavioral Contracts Work When Prompting Fails →
Why prompting alone can't make an agent behave, and what a testable behavioral contract does instead.
The Self-Maintaining Framework: What AI-Native Operations Actually Look Like →
How written standards can carry human judgment through an AI-assisted workflow.
When Regulators Design Better Than We Do →
A Chinese AI law specified behavior precisely enough to enforce, and what product designers can take from that.