Just wrapped two days at Auburn University for an Industrial Advisory Board meeting with the College of Electrical and Computer Engineering, the department where I earned my Computer Engineering degree in 2014.
The IAB brings together industry alumni twice a year to share workforce insights with the department, hear directly from students on their experience, and help evaluate whether graduates are coming out prepared for where industry actually is.
These meetings are always productive and insightful. I assumed AI would come up, but it was even more pervasive than I anticipated. Some of the more senior board members reflected on how the definition of what it means to be an engineer and how students are evaluated has shifted with every major technology transition. Slide rule to handheld calculator, to computer lab access, to the personal computer, to programming languages and computational tools. Each one forced a real reckoning about what foundational skills still matter and what competency actually looks like.
AI is a similar reckoning. The difference is the scope and speed of the shift feels categorically larger than anything that came before it.
Six months ago I was using ChatGPT as a productivity tool, drafting emails and streamlining my calendar. Today I’m using Claude Code, Cursor, Kiro, and ChatGPT across entirely different dimensions of my work - technical, strategic, productivity, and communication. At Built, AI isn’t optional. It’s embedded in how we build, how we work, and how we measure what we can accomplish, and even with that level of organizational support behind it, the pace of what’s becoming possible is still a lot to absorb.
Which is what makes this question so hard for academia. AI is producing a fundamental shift in how work gets done and the pace is only accelerating. But universities operate on a different clock. Curriculum is sequenced and budgets are scrutinized. There’s no moving fast and failing fast when the cost of getting it wrong is a graduating class that isn’t prepared. So how does an engineering program keep pace with an industry that is itself still figuring it out, without losing the foundational elements that make a strong engineer? I don’t think there’s a universal answer, and I’d expect that conversation to look different across each engineering discipline.
I’m grateful for the opportunity to participate in these conversations and give back to the program that shaped me. My career may have evolved from embedded development up the stack to a SaaS platform, but that computer engineering foundation is what made that journey possible. Glad I get to keep bringing that perspective to the table! #WarEagle
