AI Product Manager
Product direction that starts with people and proves itself in outcomes.
I help teams decide what AI should — and should not — do. My work turns community and customer insight into product requirements, quality standards, and measurement plans, so every release answers one question: did this make things better for the people it serves and the business behind it?
Product Strategy · Digital Health · Community-Centered Innovation
My primary focus is AI Product Manager roles. I’m also open to Senior Product Manager roles with an AI focus.
“I led a company-wide AI Gather & Learn at Acclinate, teaching employees practical ways to use AI in their everyday workflows—from better prompting and personalized AI assistants to more thoughtful, responsible use.”
The pitch in practice
What hiring me gets you.
Use-case judgment
I separate AI capabilities that create real value from ones that only sound impressive — grounded in customer interviews, community research, and business priorities. ACE began this way: community stories had clear buyer value, if they could become structured, trustworthy insight.
Requirements technical teams can build from
I write product definitions that engineers and data partners can act on — pipelines, acceptance criteria, and MVP roadmaps — while protecting scope from hype. My work spans voice-to-insight systems, instrumentation architecture, and multi-platform release processes.
Quality as a product decision
I define evaluation and responsible-use requirements as part of the product: human review, source traceability, consent, de-identification, bias review, and explicit boundaries on what AI output may claim. For ACE, these are documented requirements; completed evaluation and technical enforcement remain unverified.
Outcomes you can point to
Every product decision I make ties to a measurable outcome — engagement, activation, quality risk, partner value — so teams know whether the product is working, not just whether it shipped.
Education & professional development
Applied work, sharpened by study.
Professional development · Coursework
AI Product Management — Technomanagers
Ongoing coursework focused on AI product strategy, development, and evaluation — deepening the frameworks I already apply in my product work: identifying valuable AI use cases, defining requirements for technical teams, and evaluating model and product quality responsibly.
Applied experience
Product Lead / Product Manager — Acclinate
Leading product for digital health and community platforms — including ACE, a working AI demo that turns community stories into enterprise-ready insight, and the measurement systems that connect product decisions to user and business outcomes.
See the case studiesSee how this plays out in real work.
Three flagship case studies show the full arc — defining an AI product, building a measurable strategy, and creating the quality system that ships it safely.