I'm Carlos. I design products where getting it wrong costs something: a missed regulation, a patient dropping out of therapy, a booking flow used by 152M passengers.
I like the dense, unglamorous problems: AI features that have to earn their place, design systems nobody wants to fund, and data-heavy tools built to scale.
1 Product-first: name the real problem, make the tradeoff out loud, measure what changed.
2 AI where it removes work, not where it adds a demo. Prototype it, test it with users, keep what holds up.
3 Systems so the next team builds on shared parts instead of starting from scratch.
4 Built to scale: it still makes sense at a million users, and to the team maintaining it.
Work
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DatamaranDatamaran design harnessA design harness that turns Datamaran's design judgment into rules AI agents and engineers can read: used to build production screens, and as the environment every prototype runs in.
DatamaranWhen the AI says "I don't know"Redesigning how an LLM's "unknown" becomes a short question the user can answer, with the legal source one click away.
DatamaranDatamaran architecture redesignRestructuring how a complex ESG platform reveals what matters — reorganizing navigation around jobs, not features.Writing
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AIDescribe FiltersA lab exploration on the oldest problem in table UI. You describe the rows you want in plain language, and the model hands back ordinary filter chips instead of an answer.
Product buildingHuecastA 2016 side project rebuilt ten years later. The idea held: colour carries the forecast, the numbers come second.
SystemGlyph SystemThree shapes, five relations, one glyph per post. I designed the grammar and a reference graph; AI turned them into a system that maps each post's idea to a shape, and keeps doing it for every new one.