Product leader · hands-on builder · Chicago · US and Australian citizen, open to relocation
I turn new AI capabilities into products that hospitals and other cautious institutions will deploy
- calls on an average workday
- 300,000+
- health systems using it
- 250+
- since I left, still running
- 9 years
Doximity Dialer, which I originated as founding product lead. Doximity’s own figures, February 2026.
14 years as a product leader and hands-on builder, making products in clinical care, oncology and AI, after training in biomedical engineering and molecular-biology research. See where I’d fit →
Organizations I’ve worked with
Where to start
- Hiring a product leader Five healthcare products, in order What decided each one, and the rule it left. Epic to Andwise.
- Evaluating NextConsensus What it tracks, and what it does not claim How far medical evidence has moved ahead of a guideline, a coverage decision, or a label.
- Building with AI agents One change traced from start to finish Three failures, the redesign that held, and where I stopped trusting the agent.
Current work
The two products deal with one problem: records that go out of date while people still rely on them, like a guideline that no longer matches the evidence.
- Refract Change tracking: records every edit to a source, such as a Wikipedia article, and what each edit changed. A published test set of 16,146 recorded edits, reproducible from the same source.
- Fast Harm, Slow Repair Agent error evaluation: a draft benchmark protocol for measuring how far AI mistakes propagate through tools and what remains wrong after correction. No results yet.
Where I come in
I come in before there’s a roadmap, build an unproven idea far enough to see whether it holds, and then decide what to scale, what to cut, and who should own it.
I originated Doximity Dialer, led R&D at CancerCompass, and co-founded Andwise. Andwise showed in year one that physicians wanted it; I did not work out who would pay until year two, and by then every path that could fund the company made someone other than the physician the paying customer. In 2024, with funding and engagement short, I shut it down rather than rebuild it around the physician’s employer or financial advisor as the customer. Since then I have built systems myself: NextConsensus, Ambit and the tools under them.
Selected work
Decided by approval
The patient sees the office, not the cell phone
A physician calling a patient had two bad options: the hospital desk phone, or a personal cell that showed “Unknown Caller” and gave the number away for good. As founding product lead, I originated the identity layer that let the call come from their own phone while the patient saw the office number — so it got answered, and the cell stayed private.
Read case study → Decided by accountability
Four specialty programs on one routing architecture
High-acuity cases across Surgery, Oncology, and Behavioral Health were stalling in exception queues, and the default was a separate product for each of four programs. I put all four, Everyday Urgent Care included, on one routing architecture tied to clinical accountability, so a nurse and a navigator worked from the same facts and every case had an owner. It took longer to build than four products would have, and all four launched on it.
Read case study → Decided by who pays
Reading the contract before the physician signed it
Early-career physicians were signing employment contracts with no unbiased read of what was in them. Andwise’s software read the contract, flagged the clauses worth arguing about, and gave no advice. A named reviewer checked every analysis, on a deadline, before the physician acted.
Read case study →Revised