Complimentary report

What Stanford researchers found across 10,000+ engineers and 600+ companies

AI can boost productivity by up to 40% on simple greenfield tasks. But for complex work on existing applications, gains fall to just 0-10%. Stanford research reveals why, and how growing codebase complexity can turn more AI-generate code into more rework.

Readers will learn:

  • Where AI delivers meaningful productivity gains
  • Why those gains diminish as codebases grow
  • How software architecture limits AI’s impact

Download the Stanford study "Does AI Actually Boost Developer Productivity".

Yegor Denisov-BlanchStanford AI Lab
Yegor Denisov-Blanch

Research Scientist

Yegor Denisov-Blanch studies how artificial intelligence is changing software engineering. His research focuses on measuring real-world engineering productivity, AI adoption, code quality, and organizational outcomes across large populations of repositories and teams. He designs empirical methods and metrics that move beyond simple proxies to accurately quantify software output, rework, and AI-assisted development at scale.