Show Notes
Code reviews are one of the most powerful tools teams have for maintaining quality — but they're also one of the most emotionally charged parts of the development process. With AI coding agents generating more code than ever, the review bottleneck is growing fast. But what if AI-assisted reviews could not only keep up with the volume, but actually be kinder about it? Scott talks with Nnenna Ndukwe, Developer Relations Lead at Qodo, about how AI code review is evolving beyond glorified linting into something that understands context, catches what matters, and delivers feedback developers actually want to read. They explore what happens when the same AI writes and reviews its own code, and whether thoughtful AI review can make code review culture healthier for everyone...not just faster.
More from Hanselminutes with Scott Hanselman
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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/