Product and systems leadership for clinical AI
Accountability infrastructure for high-stakes healthcare and AI.
I design and scale products where software decisions carry real-world consequences — turning complex clinical workflows, regulatory friction, and non-deterministic AI into systems that remain explainable, challengeable, and correctable in production.
Strategic engagement VP Product / CPO / Founding Product Lead — I selectively partner with executive teams in healthtech and regulated AI infrastructure. A small number of advisory engagements on production AI accountability, governance, and evaluation operations.
Case studies
Product methodology: Ethotechnics
I deploy Ethotechnics as an operating system for building and scaling product organizations — making automated and AI-driven decisions explainable, challengeable, and correctable in production. Read the framework →
Organizations I've worked with
Current work
Methods and research
Governance operating systems for AI safety — making decisions explainable, challengeable, and correctable in production.
Operating method
Ethotechnics
The governance method behind NextConsensus: explicit ownership, escalation, and correction paths for consequential AI decisions.
Explore method →
Specification
Mechanized Auditability Protocols for Algorithmic Systems
Technical specification for verifying non-deterministic model decisions through immutable ledgers, authorization states, and reconsideration loops.
Read specification →
Writing and analysis
The Crumple Zone
Essays on institutional burden, delay, and the gap between what systems recommend and what people can actually do.
Read essays →
Open-source infrastructure
If you're building AI systems that need accountability, evaluation, or correction infrastructure — I'd like to hear about it.