Show Notes
From wrist‑mounted CD launchers to rope‑driven quadrupeds, Purdue engineering student and YouTuber Aaed Musa turns wild ideas into precision‑crafted reality. On Hanselminutes, he joins Scott Hanselman to share the art, grit, and storytelling behind his most ambitious projects — and why iteration is his superpower.
More from Hanselminutes with Scott Hanselman
AI isn't just changing how we write code. It's changing how we build software, structure teams, and think about what it means to be a software engineer. In this episode of Hanselminutes, Scott Hanselman sits down with Sunita Verma, CTO at Ironclad and a longtime Google engineering veteran, to explore why simply adding AI tools to existing development workflows isn't enough.
What happens when the laws of quantum physics meet computer science? In this special crossover episode of Hanselminutes and ACM ByteCast, Scott Hanselman sits down with Charles H. Bennett and Gilles Brassard, recipients of the 2025 ACM A.M. Turing Award, often called the "Nobel Prize of Computing."
A young man who's a sophomore in high school emailed me to come on his podcast that he does with his friend, and I had so much fun. I decided to make it a crossover episode. Check out "Compile after Class" on this week's episode!
Maynard Holliday spent 30+ years at the intersection of robotics, nuclear security, and defense technology, most recently serving as the Assistant Secretary of Defense for Critical Technologies. He's worked on everything from helping remediate Three Mile Island to securing tons of Soviet nuclear material in post-Cold War Ukraine to overseeing the Pentagon's critical technology portfolio including AI, hypersonics, and microelectronics. He shares what "trusted AI" really means, why he co-founded Black in Robotics, and how T'Challa and Tony Stark shaped his career more than you'd expect.
Felix Rieseberg came to computing through poetry, and that background gives him a unique lens for explaining language models. A longtime engineer, Felix now gets to watch AI evolve from the inside. In this episode, Scott and Felix explore why language models are surprisingly easy to understand despite feeling magical, what it's like to train a model from noise to coherence, and the bigger philosophical questions about intelligence that AI keeps surfacing. You can learn how AI really works by making your own in a weekend with his free https://languagemodelbuilder.com/