Not Every Workflow Needs AI
The useful question is not where AI can help. It is where AI creates enough leverage to earn a durable place in the workflow.
I build products, systems, and experiments around the places where technology changes how people work. I use the skills I have developed along the way to give back, strengthen my community, and help the people around me grow.
These are the ones currently shaping what I build, test, and pay attention to. None of them feel finished.
Finding the boundary where automation creates leverage without hiding responsibility.
Protecting curiosity while the distance between an idea and a working thing keeps shrinking.
Designing environments where trying, getting stuck, and trying again all feel welcome.
A year-long shift from autocomplete to an engineering workflow where AI planned, reviewed, investigated, and prepared work across the delivery cycle.
An annual coding camp designed to help girls in grades 3–12 experience programming as something they can shape, share, and enjoy.
An internal system that gave operations teams AI-assisted prioritization and review while keeping consequential judgment with experienced people.
The useful question is not where AI can help. It is where AI creates enough leverage to earn a durable place in the workflow.
AI has made software feel playful and alive again. That same energy can quietly turn into burnout when engineers never stop using the muscles that make the moment exciting.
The old picture of engineering culture was a quiet room with headphones on and nobody talking. Ours looked nothing like that.
The longer version includes the career turns, the community work, and the principles that have stayed with me while the technology kept changing.
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