About
I've spent twenty years taking things that don't exist yet and making them work.
I'm open to the right Director or VP of Product role, remote, and I take on a small number of Origin partnerships alongside it. See the resume →
That's meant different things at different points: leading tech strategy inside Missouri state government, chairing the board of an $8B public pension fund, modernizing the technology at an insurance company, and, most recently, building the online rental business at a Nasdaq-listed construction technology company from the ground up: the design, the sign-up, the credit and insurance steps, and all the behind-the-scenes connections underneath it, grown to $12M+ a year across 400+ branches as the company went public.
State of Missouri
The state had no single source of record for the roughly 20,000 businesses it regulated. Its first enterprise master-data implementation changed that: 1,400 employees, a $12M budget, 14 projects running at once.
Missouri Employers Mutual
Quoting a workers' comp policy took ten minutes. A 40-person portal replacement and Lean process work cut it to three, and claims intake was rebuilt around the moment policyholders need the company most.
Construction tech
A construction technology company (on the Nasdaq) had no way to connect insurance to its equipment data. I led that build from scratch and rolled it out across the business, alongside early AI work: predicting breakdowns and recognizing equipment from photos.
The rental channel launches
In January, online revenue was $0 and not one customer email existed anywhere in the business. Two years later: $12M+ a year across 400+ branches, a real customer list built from nothing, and momentum the company carried into going public.
Origin
The pattern becomes the practice: growth strategy, digital channels, and applied AI, concept to market. Every build starts at the origin.
The through-line isn't the industry. It's the moment right before something becomes real, when there's a problem everyone agrees on but no system yet to solve it. That's where I do my best work, and the work I love most: translating ambiguity into architecture, and architecture into adoption.
The method underneath is Lean: find the pain point, simplify the process, then bring technology to what's left. And the belief on top is that AI is ending the era of one-size-fits-all software. It's finally affordable to build products shaped to how a business actually works, instead of bending the business to fit some off-the-shelf product.
The construction tech years were startup years, and they gave me range. I looked after the company's whole online reputation, built the kind of search visibility a company needs heading into going public, and used AI to grow both the traffic and what we understood about it. Through all of it I stayed data-driven without being data-only: the numbers showed me where customers got stuck, and the conversations told me why. Clear the way, improve it, repeat until it's excellent.
I've owned the revenue and the budget, led the AI work, run a federal-compliance project, and governed a public pension board: the same challenge at four different heights. And none of it was solo work. I led an in-house web team and an eight-person outside engineering firm, ran a $1.2M a year budget, and coordinated credit, marketing, fleet, billing, and insurance to deliver one seamless experience.
And I stay hands-on with the technical work, not above it. The image-recognition system that grew an online catalog from 5,000 items to 100,000 was mine to conceive, direct, and test into production.
I also run my own working life on an AI Chief-of-Staff system I built: a set of agents that handle my calendar, my search pipeline, my ventures, and my house, and report to one voice. It's how I stay hands-on with the tools I recommend, and it's why the ventures on the Proof page exist.
I work alongside your team, in the room and in the weeds, not from a slide deck. If you're building something that doesn't exist yet, that's exactly my kind of problem.