About
I'm a builder, data product manager, and leader from the back of the room.
I work at the intersection of social impact and technology, building the kind of data infrastructure that moves capital and capability toward mission-driven work.
Right now I lead data products and partnerships at Candid, cofound Roost with Josie Moss, and author Valet: an agentic operating system with 25 production skills running my PM work daily inside Claude Code.
How I got here
I started my first "company" at six. I lived near a golf course and turned lost balls into renewed chances by selling them back to the Bogeymen. I learned about customer problems, customer preferences, and pricing. I was hooked.
Twenty years later I started my professional career through service: chairing a climate non-profit chapter, ushering refugees through resettlement, teaching English to primary school children. From there I worked in international policy and federal elections. Across all of it, social systems thinking kept turning into the same question: where's the leverage?
Technology was the answer. It still is. Most of my career has been in data products: analytics, pipelines, machine learning, and natural language search. Those are the mechanisms that close the gap between what stakeholders need and the insight, process, or clarity that gets them there.
Where I've worked
- Candid · Senior Data Product Manager · Jun 2024 – present. Data acquisition for the social sector. Multi-vendor partnership strategy, AI prototyping, and a fiscal-sponsorship product surface that brought hundreds of previously-invisible projects into sector data.
- Classy / GoFundMe · Product Manager II → Sr Program Manager → Associate PM · Jun 2020 – Jan 2024. Led a 0-to-1 data migration and payments product driving $15M+ in transactions and 4–10% retention. Spearheaded a stealth post-merger AI/ML initiative shipping an LLM search alpha to 4,000+ customers in six months. Earlier, supported 200+ customers through SaaS onboarding and productization, with $10s of millions in revenue realization. → Case study.
- Achieve Internet · Associate PM & Technical Program Manager · May 2019 – Feb 2020. Founded the PMO. Took an API developer portal MVP to market in three months for customers including Moody's Analytics and Experian. Productized services for $90k MRR.
- Fairfield Residential · Technical Project Manager · Jun 2017 – May 2019. Stood up the first analytics suite optimizing a $10B real estate asset portfolio. Designed an accounting software migration that cut process time by 46%.
Education
- University of Utah, Master's, Information Systems (Dec 2016).
- University of Utah, Bachelor's, Political Science & Sociology (May 2013).
What I'm optimizing for
Three tracks running in parallel, on purpose:
- Career. Staying sharp at the data PM craft, especially at scale and in mission-driven contexts. Open to builder-track roles in social-sector AI tooling and philanthropic infrastructure.
- Entrepreneurship. Roost is the active venture. Future ventures in the philanthropic-infrastructure space are on deck.
- Craft. Getting better at the agentic tooling layer: the orchestration, the memory systems, the places where AI genuinely augments judgment rather than simulates it. Valet is the testbed. The methodology essays are the output.
How I work
- Frame, then draft. Figure out what I think before AI helps me say it. The reverse produces work that sounds smooth and doesn't hold up.
- Source every claim. Numbers, costs, timelines, legal points. When I'm uncertain, I say so.
- Ship infrastructure, not slideware. Decks are downstream of decisions. The leverage is in the systems that produce the decisions.
- External scaffolding over internal willpower. Systems beat motivation. If a thing has to happen reliably, the system holds it, not me.
- The trade-off is the design. The interesting questions are usually not "how do we do this?" but "which of these costs are we choosing to accept?"
Why I work this way
I built Valet because the AI tools I was supposed to use assumed I had reliable internal scaffolding: that I'd remember to check, hold context across sessions, and catch what the model got wrong before it shipped. That assumption doesn't hold for me the way it might for other operators.
So I designed around the inversion. The system holds the structure. I hold the narrative. That's the principle the whole framework is built on, and it comes from a pretty specific place: organizational psychology, behavioral design, and a decade of watching smart people fail at execution not because they lacked intelligence but because their operating environment didn't support how they actually think.
The same principle runs through everything I build. Roost routes around expert critique because critique stalls people who already doubt themselves. Floodplain makes the trade-off visible instead of issuing a verdict. Observatory gets quieter when markets get loud. The design is always about which way to point the friction.
What I read / who I learn from
- Daniel Pink. Drive, When, To Sell Is Human.
- Bridgewater. Principles. Systematized decision-making.
- Annie Duke. Thinking in Bets. Decision quality vs. outcome quality.
- Don Norman. The Design of Everyday Things.
- Howard Marks. Memos on behavioral discipline in the dark.
- Linear, Vercel, Stripe Press. The public writing on craft sets the bar.