Start with the people who own the work
Every project begins with the team’s real problem, a named owner and an executive stakeholder, not with the technology.
I lead AI programs from the first idea to company-wide adoption.
AI Process Engineer running a company-wide AI program across every department: 70+ projects, the agents and automations behind them, and the training that gets people using them. I’m completing a Master of Science in Artificial Intelligence in Business at Arizona State University’s W. P. Carey School of Business, graduating in December 2026, and hold a BA in Digital Computational Studies and Sociology from Bowdoin College.
Master of Science
Bowdoin CollegeBachelor of ArtsEvery project begins with the team’s real problem, a named owner and an executive stakeholder, not with the technology.
A minimum viable product in front of a test group beats a perfect plan, and adoption is earned one team at a time.
Governance comes first, every project is documented and reviewed, and everyone can see what AI is doing and what it costs.
Start with the team’s problem and the people who own it: who uses the work, who signs off, and what good looks like.
Define the project as deeply as I can. I write the project spec and the instruction set an AI agent will work from, with milestones toward a minimum viable product.
Build the agent, skill, automation or app. Depending on the team, I’m the primary builder, a collaborator, or dedicated support.
Put the first working version in front of a small test group, the project owner and an executive sponsor, and refine it from what they find.
Release it to the people it was built for, and train them until it’s part of how they work.
AI projects overseen
employees supported as their AI resource
Claude skills and automations shared company-wide
employees trained hands-on
How I take AI from one team’s idea to company-wide use, plus the machine learning and governance case studies from my master’s program.