
The shortest path to a great product isn't a straight line — it's a conversation.
I didn't start in tech. Before I ever opened Figma, I spent years in real estate development and large-scale project operations, where zero-to-one meant turning an empty lot into a physical asset. The medium changed; the core challenge didn't: how do you take a messy, multi-stakeholder vision and give it enough structural logic to actually function?
Today I bring that same ownership to product systems. I'm the PM who leans into the messy middle — the ambiguous data models, the platform pivots, the backend constraints — and I use my design literacy to make sure what we build isn't just technically sound, but engineered to preserve user autonomy and trust.
Every case study on this site started with a question I couldn't answer yet. How does an agent actually take a home to market? What makes two strangers trust a countdown timer? Why does a seller abandon a form at step three and come back four days later? I stay in questions like these until the answers turn into product.
Storytelling is the other half of the craft. A spec, a user flow, a film — each one is the same job: making someone see a thing that doesn't exist yet, clearly enough to build it, fund it, or believe in it. It's why I write the way I prototype: rough version first, honest edits after.
Right now I'm taking on independent product work — discovery sprints, onboarding audits, and prototype-to-spec projects for small teams that need product thinking before they need a full-time hire. If that sounds like your problem, email me.
Email meI don't touch solutions until the problem holds still.
Everyone rowing in the same direction before anyone builds.
Prototype what I propose, instrument what we ship, iterate on what the data says.
IN PRACTICE — filtering stakeholder noise into sharper priorities, and anchoring teams through deliberate tradeoffs so execution stays protected.
Product taste is engineering clean system logic that executes the user's intent, securely.
Beyond feature building: writing the strict operational rules that govern human–AI interaction.
Automate the manual burden to surface clearer data for smarter human choices. Never to overwrite them.
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