I started in marketing. I ended up building AI systems.

I've spent my career at the intersection of product, growth, and strategy. I've led growth at startups. Built products from zero. Advised established companies on what to build and how to take it to market.

What I learned: the best marketing is a better product, and the best product strategy starts with understanding what people actually need — not what technology makes possible.

When AI capabilities started accelerating, most people in my position did one of two things: they ignored it, or they hired someone technical to “figure it out.”

I did neither. I started building.

The turning point was watching an AI work through a genuinely hard problem for an extended stretch. Not autocompleting an answer: reasoning. Holding context, weighing tradeoffs, changing its mind. It didn't feel like a tool I was using. It felt like a thinking partner and a build partner at the same time.

That reframed the work for me. If someone who isn't an engineer could direct that kind of reasoning into real, working software, then the constraint was never the code. It was knowing which problem to point it at, and what “good” looks like when it ships. That had been my job for years.

So I stopped advising from the outside and started shipping from the inside. A year in, it's the thing I think about most. The marketer who learned to build turned out to be the right shape for this moment: close enough to the business to know what matters, close enough to the machine to make it. You can see the result in the Build Log.

Marketing instincts. I know what makes people care, what makes them buy, and what makes them stay. Every system I build starts with a human outcome, not a technical architecture.

Product discipline. I've built products from zero. I know the difference between a prototype and a production system — and when each one is the right tool.

Building speed. 6 tools. 3 businesses. One weekend. I don't plan in quarters. I build in days.

Integration judgment. The hardest part of AI isn't the technology. It's knowing where it creates real leverage versus where it creates expensive complexity. That judgment comes from building across enterprise, retail, media, and my own operations.

• Claude / Claude Code (primary reasoning engine)
• Python and TypeScript
• LLM orchestration patterns
• Process design + systems thinking

I don't use a hundred tools. I use a few tools deeply. That's the point.

I travel. I work with clients. I work from wherever I am. Right now, I work.