Healthcare AI product & systems leader · Chicago, IL
I build the product systems that let AI move through healthcare at full speed — and stay answerable when it's wrong.
14 years shipping clinical products at Epic, Doximity, and Transcarent — HIPAA compliance architecture, identity verification at 35,000-physician scale, care-routing escalation paths — now generalized into open standards and deployed as the infrastructure that makes adoption possible.
Organizations I've worked with
Latest writing
The Official Record Is Late
A structure can be correct on paper and dangerous in practice — here is where that observation came from, and what I'm building now
Don't Let Reassurance Do Engineering's Job
Why 'we care' substitutes for obligation — and how delay gets disguised as kindness.
If Every User Is a Potential Threat
People are not becoming dishonest. They are becoming game-theoretically optimal for the environment they have been placed in.
Selected work
Scaling clinician communication through verified identity and workflow integration
Built the identity and verification layer for Doximity Dialer, solving the 'unknown caller' bottleneck that prevented mass telehealth adoption.
Read case study → Scaling specialty-care through unified clinical workflows and automated ownership
Led product work across value-based specialty-care and care-navigation programs (Surgery, everyday urgent care, Behavioral Health, and Oncology Care).
Read case study → Scaling trusted financial guidance through automated review and accountable sign-off
Co-founded Andwise and built the product and advisory infrastructure required to deliver trusted, fiduciary-aligned financial guidance to physicians at scale.
Read case study →Current work
One flagship: NextConsensus. Supporting it: Refract (verification), Ethotechnics (governance), Crumple Zone (analysis).
Powers NextConsensus — change detection
Refract
Reports what changed and when; deciding whether the change matters is the caller's job. Under the hood: an open-source engine (AGPL-3.0) that replays a source's revision history into deterministic, byte-reproducible change events with full provenance.
Published standards
Ethotechnics
Open standards for AI decision accountability — how to contest an automated decision, how to get recourse when it's wrong, and how to prove a system is safe before it ships.
Writing on institutional accountability
The Crumple Zone
Writing on how institutions absorb automated decisions — where accountability thins, and what keeps systems answerable.
Operating principle
Every AI system that influences a clinical decision makes a claim — this drug is safe, this guideline is current, this patient should be prioritized. The work is making those claims answerable: what evidence backs them, who can challenge them, what happens when they're wrong. I design those questions into the product, not as downstream compliance. Read the method →
Email me. I'm looking for VP Product or senior product leadership at healthcare AI companies — where the constraint is getting AI through clinical adoption, institutional security, and regulatory review.