My work brings together hands-on AI building, team leadership, and the operating decisions that turn individual experiments into a capability an organization can use.
Start with the actual work
I’ve led efforts to map workflows with the people doing them, looking at handoffs, systems, time, and friction. Those maps helped give teams real problems to work on. Removing unnecessary work was an acceptable outcome before introducing any new tool.
Build the capability, not just the first tool
I’ve combined hands-on build sessions, recurring training, and opportunities to share work with building agents myself. The aim was to help people develop the judgment and confidence to apply the tools to their own work.
Decide what deserves to scale
As participation grew, the operating problem changed: duplicated effort, competing ideas, and tools that needed support beyond their creators. I helped establish a model separating personal productivity, team solutions, and enterprise initiatives, with a path for deciding what needed engineering ownership.
Something you can inspect
I’ve published Chief of Staff agent instructions for meeting preparation, decisions, and work coordination. They’re a public example of how I translate a job into context and instructions someone else can adapt.
Connect investment to the work it improves
My approach considers time, cost, capacity, and delivery speed alongside the effort required to integrate, review, and maintain a solution. Expected benefits guide prioritization; measured outcomes require a baseline and evidence from use.
The foundation behind it
I joined Rivian in December 2020 as a Product Manager, helping design its capital projects platform and initial portfolio analytics. I became Manager of Tech & Strategy in February 2024, then Sr. Manager of Tech & Applied AI in February 2025. That systems and operating experience informs how I approach AI today.