Have you seen early productivity gains from AI, only to watch them disappear under growing complexity and production incidents? You're not alone. There's a common reason. Many production systems already struggle with technical debt. When AI agents enter the development loop, that debt becomes a multiplier. Poor-quality code not only increases defects and costs. It dramatically raises AI risk by driving high breakage rates and turning promising AI agents into legacy code generators rather than genuine help.
Fortunately, there's hope on the horizon. In this talk, Adam Tornhill builds on the ideas from Your Code as a Crime Scene to show how organizations can achieve both speed and quality with AI. Backed by large-scale empirical studies on AI coding and developer productivity, we separate what works from what doesn't in real-world systems. Building on these findings, we look at a practical framework for driving and sustaining AI-friendly code at scale.
The AI revolution is here. Is your code ready? The evidence is already there.
Adam Tornhill is a programmer who combines degrees in engineering and psychology. He's the founder of CodeScene, where he designs tools for software analysis. He's also the author of the best-selling Your Code as a Crime Scene, and three more technical books. Adam is an award-winning software researcher, focusing on code quality and AI. His other interests include music, retro computers, and marti...