Turning AI-product skeptics into confident customers
Your customers are not buying AI. They are buying a safer way to change.
For seven years, I researched why people resist change. Now I help AI companies make change worth it.
My first enablement project wasn't called enablement. I studied why laid-off workers skipped the free job training that could have helped them start over. The barrier was almost never the training itself — it was fear. Will I be any good at this? Will this change how I see myself? Your customers ask the same questions the first time they try your product.
I design enablement programs that address those questions head-on. I've done the work under different titles: teaching in Ivy League classrooms, shipping production AI at early-stage startups, and running change management as a Chief of Staff. Enablement is where they converge. I bring a teacher's empathy and a salesperson's hunger to one job: clearing the way for people to adopt AI, at scale.
How I Work
I don’t rely on an outdated playbook.
I have a set of tools and a method for every situation.
I'm not running enablement from another company's playbook, and that's an advantage with AI products where every user is new to the idea. Whether I'm drawing on my experience as a teacher, data scientist, or operations leader, I use the set of tools the job calls for. It's not haphazard. It's a method that works.
01
Learn the product cold.
I get fluent at an expert level before I advise anyone. At Clairity, I walked in with no background in medicine and left as the person who wrote the statistics behind the first FDA-authorized AI breast cancer risk model.
02
Bring hypotheses, then let the data lead.
I'm battle-tested at three early-stage startups, and I have hypotheses about where both pre- and post-sales fall apart. I test my hypotheses with real customers and let the data prove me wrong.
03
Listen for the Question Behind the Question.
When someone hesitates over a feature, the QBQ is usually a fear about their competence, their job, or their judgment. That fear, not the feature, is what enablement needs to address.
04
Ship it.
I’ve shipped AI agents into production, taught hundreds of professionals to trust their judgment with AI, and built Circuit when the tool I needed didn’t exist. Even this website would not be possible without Claude as my copilot. Enablement isn't a strategy, it's a product, and products ship.
Roles
Where I fit on your org chart.
Customer Enablement
Enablement is a conversation, not a content library. I sit with customers one on one, listen the way the best teachers and chiefs of staff do, and figure out what they are really asking. Then I close that gap in the moment. Since 2020, I've taught data and AI to 675+ working professionals and helped three AI startups earn the one thing that actually drives adoption: trust.
Customer Onboarding
Onboarding is a journey, and I own every step of it, from a customer’s first login to the moment the product finally clicks. I don't guess where people stall; I watch. I've lived in PostHog tracking real customer journeys through new features, finding where the friction actually is and how to design it out. I build the path around the work people came to do, and I do not stop until they get there.
Customer Education
Education should happen in community, not in a stale documentation library. I run the webinars, workshops, and events that turn a customer base into a network that teaches itself. At Keywell, I created the webinars and intro videos that were a customer's first lesson in the product. On Maven, I teach live Lightning Lessons that put me in front of practitioners in real time, fielding the questions a recorded course never could.
Experience
The titles changed. The job didn’t.
“Enablement” has never been on my business card, but it’s been the work the whole time: the C-suite I taught what the numbers meant, the customers I walked through a brand-new AI product, and the seven years I spent studying why people don’t use tools designed to help them.
2025 – present
Founder
Bootstrapped an AI-native application that takes the fear out of data by stripping out the code and math and focusing on the intuitions that create confident data users.
2025 – 2026
Chief of Staff & CS Lead
The voice of the customer for Keywell’s AI product launch. Oversaw Keywell’s enablement assets and secured new SOWs with existing accounts that grew revenue by over 40%.
2022 – 2025
Founding Director of Data Science
I designed the analysis that won the first FDA authorization of an AI device to predict breast cancer risk. I taught our C-suite what the numbers meant, so they could close our Series B.
2020 – 2026
Data Science Instructor
University of Pennsylvania; George Washington Univ.
I started teaching before ChatGPT, and finished as an evangelist for AI. Proud to be one of the first faculty to treat AI as a learning objective, not a tool to be shunned.
2015 – 2022
PhD, Political Science
University of Pennsylvania
Spent years digging deeply into why a job training program with gold-tier benefits went almost entirely unused. It was my first enablement problem, and I’ve been working on versions of it ever since.
In Action
I've shipped the work.
Enablement is about creating a safer way for people to change how they work. I didn’t leave that as an argument. I built Circuit: responsible AI for data analysis, a tool that lets anyone, with no code or statistics, apply an analyst's judgment to AI-generated analysis. Here's the announcement, live from posit::conf(2026).