Foundations as a Feature: How Dev Teams Are Approaching AI Modernization
Data Scientist & AI Lead
The Research Lab
Aaron Tellis is a Grand Rapids, Michigan-based data professional with 7 years of experience spanning data engineering and data science, currently serving as AI Lead within a large healthcare system's Development Center of Excellence. He leads AI initiatives by equipping developers with AI tools that improve development and DevOps workflows. Outside of his day job, he writes about machine learning systems, AI tooling, and enterprise adoption.
Most organizations treat AI modernization like a single initiative, one strategy, expected to work the same way for every developer. In practice, data developers and application developers work fundamentally differently, and treating them the same creates friction before adoption even starts.
This session offers a firsthand look at a persona-first approach to AI modernization: breaking developer personas into their own lanes, solidifying foundations before layering on intelligence, and building toward software/analytic factories and self-service tooling that meet each persona where they are. The bigger shift is in the developer's role as AI takes on more of the execution, and developers shift toward bridging business problems and technical solutions. This is an honest look at the problem, the approach, and what's being learned along the way.