What I do
My career started on the revenue side of marketing — channel work, demand generation, leading teams and owning budgets, with a fair bit of beating pipeline targets along the way. Over time, though, the work I gravitated toward changed. I found myself less interested in the campaigns and more interested in the systems underneath them.
There's a pattern to it: I notice where teams are quietly losing time and momentum — signals scattered across tools, work being done by hand that shouldn't be, no clear sense of what to tackle first — and I build something that closes the gap. Lately that's meant teaching myself AI-native tools like Claude, Cursor, and Gumloop and building go-to-market workflows on my own, without waiting on engineering.
What I care about now is the part of AI adoption that's less about the models and more about the people: how a team actually folds these tools into real work in a way that feels useful and earns trust. I do my best work where the playbook is still being written — and I care just as much about building teams people want to be on as I do about shipping the work.