Uxtopian

Experiments

Building is cheap now. Knowing what's worth building is the whole game.

It's never been a better time to be a builder. Innovation, foundation, and production all happen simultaneously. Below you'll find some works inspired by intellectual curiosity, a kids' coach request and a friend's story of unemployment.

Multi-agent debate

The AI Symposium

What would Ray Kurzweil and Shoshana Zuboff make of your question? The Symposium is a room where AI versions of the field's sharpest thinkers actually disagree, and you can put a live question to them.

The hard part wasn't the models. It was writing personas sharp enough to disagree the way the real people would.

The AI Symposium — the thinker constellation beside the panel that tunes how a thinker responds
AI Face-off — a live matchup with the crowd's vote split between two tools

Head-to-head voting

AI Face-off

Every day there is a new AI tool hitting the market and remarkable claims of quality and velocity. Face-off turns that into a game: two tools enter, you call the winner, the crowd builds a live scoreboard.

The judgment call: let the crowd be wrong. No expert override, just taste, recorded honestly.

Consumer app

AccountaBALL

Kids' sports apps reward showing up, not getting better. AccountaBALL logs real reps, challenges, and keeps the coach and athlete grounded by reps.

The voice feature and court reps are getting the most positive feedback.

AccountaBALL — the weekly dashboard: progress ring, today's workout, and skill tracking
Still Looking — the anonymized public record of what the job market costs people

Anonymous testimony

Still Looking

The job market's human cost never gets counted. Still Looking is an anonymous, collective record of what it takes from the people moving through it: a witness project, not a job board.

This was a good branding and design exercise for working with AI.

Designing an AI product means holding the whole system at once: the model's behavior, the interface's promise, and the person on the other side deciding whether to trust it.

These experiments are where I work that out. The tech is the agentic tooling, but it keeps coming back to communication and constraints: how do you tell a system, AI or human, what to build, why, and for whom?

That's the design leadership I bring to every product I work on, and how I fold AI into a team's craft.