About
Product-minded builder at the intersection of AI, cloud, and delivery.
Growing up, technology pulled me from gaming rigs to building my own PC — then into how software shapes real decisions. Shifting from pre-med to CS, I traded studying the human body for systems that still fail the same way when the feedback loop between user and product breaks. That lens — outcomes, trust, iteration — is what I bring to AI PM work.
I’m a Computer Science student at BYU–Idaho with hands-on experience across nonprofit and startup environments: modernizing financial audit infrastructure on AWS, utility billing and property management SaaS, standing up internal agentic AI programs, and prototyping a RAG-based campus support agent with clear escalation and evaluation criteria.
I am an incoming Digital Product Manager on Charles Schwab’s Conversational AI team and an AI Fellow with Cornell Tech × Break Through Tech, building fluency in applied ML and product leadership.
My take on AI product
The best AI products aren’t built around the model — they’re built around the moment of friction they remove. The hardest part usually isn’t the LLM; it’s defining what “good” looks like when every output is probabilistic.
I believe AI PMs need to be part designer, part translator between policy and engineering, and fully obsessed with trust: evaluation criteria, escalation when confidence is low, and human-in-the-loop paths that don’t feel like failure modes.
Ethan Trent
Education & Trajectory
Sep 2023 – Jul 2026
Brigham Young University–Idaho
B.S. Computer Science · Full Stack Web Development
May – Aug 2026
Cornell University
Machine Learning Certificate
Prospective · Fall 2030 – Spring 2032
Carnegie Mellon University — Tepper School of Business
Accelerate Online Hybrid MBA.
Targeting the Technology Strategy & Product Management track and concentrations in AI in Business, Business Technologies, Strategy, and Marketing.
Currently based in Dallas, TX.