My Journey in UX, Design Systems, & Life

Everyone's arguing about which AI tool writes the best code or generates the best images. Meanwhile, the companies building these systems are racing to ship faster, raise more, and consolidate more power than any tech cycle before them. And a small group of researchers, journalists, and engineers have been trying to get your attention about…

It's 4 pm on a Friday. I've approved my last PR of the week. I've reviewed more code today than I wrote. I got a lot done, or at least, the dashboard says I did. But I'm sitting here, and I can't think straight. Not in the dramatic, existential-crisis way. Just... tired. A kind of…

At some point, I stopped knowing what was on my Mac. A tool here, a dependency my agent dropped in there. Collectively, a mystery. I was losing track. To help, I created stockpile.

Everyone's building custom skills for their AI coding assistants right now. Commit helpers, linting rules, project scaffolding. Little markdown files that make Claude Code do things your way instead of the default way. I've been doing the same thing. But the more skills I wrote, the more I wanted them to follow me between machines…

I had done everything right. Or at least, everything the current playbook says to do. Used AI to fill the gaps, reviewed it myself, then handed it off to more AI.

After years of building, maintaining, and supporting in-house design systems with real tokens, governance, versioning, support, and contribution models, I recently found myself building with Tailwind and shadcn. Thanks, AI!

In software, a dependency is a risk you accept. It's a package you didn't write, maintained by someone you've never met, that can break your entire application if it disappears. Good engineering means knowing which dependencies are worth the risk and which ones aren't. Right now, I'm watching our industry decide that people aren't worth…

I came across a Medium post titled "AI Will Replace 70% of Design System Work." The premise is that most design system work, documentation, component building, token management, accessibility audits, is "structurally automatable," and that the real value lies in governance. The author argues that teams need to move "upward from execution to orchestration" or…

I've been tinkering with something lately that I think more design system teams should pay attention to. I'm trying to teach AI how my design system works through Claude skills and Cursor rules.

I came across a post by Cassidy Williams a few weeks ago about LLM discoverability. The gist: she asked ChatGPT some tech discovery questions, noticed it didn't recommend her, then asked why. The AI gave her a list of things to fix. She fixed them. It worked.