AI-Friendly Code: The Missing Link for Speed with Quality • Adam Tornhill • GOTO Copenhagen 2026

Adam Tornhill examines why AI coding agents deliver early speed gains that often vanish under growing complexity, production incidents, and technical debt. Drawing on large-scale research, he introduces the code health metric as an objective measure of AI-friendliness, shows how agents can safeguard and refactor code within an agentic loop, and describes a Street Fighter 3 case study where agents uplifted 300,000 lines of legacy C code to a perfect score. He closes with how behavioral code analysis reveals architectural hotspots behind recurring merge conflicts.