The Great Engineering Reshuffle

AI is reshuffling software engineering: widening performance gaps, changing who the top performers are, and shifting the bottleneck from writing code to directing and reviewing it.

Drawing on research from Stanford’s Software Engineering Productivity Research Group, this talk explores why similar teams achieve dramatically different results with AI. We examine how committed project context, structured agent workflows, and codebase quality relate to productivity and maintainability, alongside a case study following AI adoption across approximately 600 engineers.

Attendees will leave with a clearer understanding of why AI productivity gains vary so widely, how structured AI practices and codebase quality influence results, and why faster coding does not automatically translate into better organizational performance.