PRODUCT LEADER · AUTHOR · PROFESSOR · SALEM, MA
Author of Delightful Intelligence (O'Reilly, 2027) and serial solver of unfamiliar problems — from genomics instruments to factory floors to data centers. The industries change. The toolkit doesn't.
// still a data nerd, design geek & product fanatic — now with footnotes
FIG. 01 — CAREER TRAJECTORY, 1996–2026
Adaptable is a career strategy.
Three decades, three domains, one repeating pattern: learn the customer's world fast, find the problem that matters most, build the team and the product that solve it — then do it again somewhere new.
NEW BOOK — EXPECTED 2027
Delightful Intelligence is a practical guide to closing that gap. Drawn from a decade of shipping machine-learning products in the real world, where models meet messy humans. It covers what actually makes AI feel trustworthy, useful, and worth returning to: the design decisions, not just the model choices.
I started building AI products in 2018, before it was a category. This book is everything I wish someone had handed me then.
FIG. 02 — SELECTED OUTCOMES
Find the high-value problem. Ship the solution. Measure honestly.
FIG. 03 — THE WORK
Life sciences, SaaS, industrial IoT, insurance, AI infrastructure. Every entry follows the same arc on purpose: the problem, what I did, what changed.
Data centers burn staggering energy on cooling, and the AI boom is making it worse. Deployed AI/LLM- and RAG-based control of airflow and cooling, translating facility constraints directly into the roadmap.
>40% energy savings for customersA product-led-growth pioneer in a crowding market, making decisions without data. Reset the product strategy against competitive analysis and founded the company's first data team.
Strategy the company could steer byA fast-growing insurtech with no product or design organization — and growth that wouldn't wait for one. Hired and built both teams from the ground up, with the processes to let them scale.
Supported 7× ARR growthFactory machine data was abundant; products manufacturers would actually use on the floor were not. Led product, design, and data science; translated customer roadmaps and machine data into shipped ML products.
2 ML products · 2.5× ARR · +20% CSATUX teams couldn't measure how users felt. Built a zero-to-one product analyzing user sentiment through facial expressions with RNN, CNN, and NLP models — AI product design before it was a category. Also served as interim VP of Product at Cobu, lifting its app-store rating from one star to four.
Seeded a decade of AI product workDesign and product strategy for FedEx, Spotify, TripAdvisor, Shopify, Genentech, LogMeIn, and BBVA — professional-grade practice at entering someone else's domain and finding the problem that matters.
Scaled a company-wide design-thinking practice inside a public company; co-led a startup accelerator mentoring SMB tech startups.
Led executive strategy sessions for Lowe's, Redbox, Harley-Davidson, Discover, Teradata, Coca-Cola, and VW — where I learned that a picture of a strategy beats a deck about one.
A scientist and research engineer turned product manager in life-science capital equipment. Global Product Manager at PerkinElmer Life Sciences; product roles at MJ Research (acquired by Bio-Rad) and US Genomics; Product Marketing Manager at Agencourt Bioscience (acquired by Beckman Coulter) through 3× ARR growth. Inventor on U.S. Patent 6,485,918. This is where "learn the customer's science, then build the product" became a habit.
FIG. 04 — TEACHING & SPEAKING
Fifteen years of teaching executives and graduate students how to make decisions with data — and to build products worth deciding about.
ADJUNCT FACULTY · 2024–PRESENT
Business Analytics · Business Intelligence & Insights · Data Science & Analytics · Complex Decision Making · Data Visualization
ADJUNCT FACULTY · 2010–PRESENT
Data-Driven Innovation (AI/ML for Business) · Design Sprints · Presentation Design · Creativity & Innovation
ADJUNCT FACULTY · 2017–2024
Information Visualization graduate program: Thesis Capstone · Applications in Data Visualization · Designing Information
Guest lectures: Harvard · MIT · Stanford · Columbia · Northeastern. Available for keynotes and workshops on AI product design, product roadmaps, and design sprints — invite me to speak.
FIG. 05 — PUBLISHED WORK
2027 · O'REILLY
How to create AI products users love. The design gap between AI capability and AI products people enjoy — and how to close it.
2020 · O'REILLY
Nine foundational rules for product teams to run accurate research that delivers actionable insights.
2017 · O'REILLY
How to set product direction while embracing uncertainty. A staple on product-team bookshelves ever since.
2015 · O'REILLY
A practical guidebook for building great digital products, fast.
Occasional, practical writing on AI product design, roadmaps, and decision-making — the working notes behind Delightful Intelligence. No spam, no filler. Subscribers hear first when the book ships.