AI-Friendly Code: The Missing Link for Speed with Quality
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 doesn’t just increase defects and costs. It also turns promising AI agents into legacy code generators rather than genuine help.
In this keynote, Adam Tornhill shows how teams 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 then look at a practical framework for driving and sustaining AI-friendly code at scale.
Zero fluff.