Measuring the ROI of GenAI in Engineering: The Cody Experiment

The article explores how to measure the ROI of Cody, a GenAI-powered coding assistant, in engineering. It discusses the challenges of quantifying productivity gains, the importance of adoption rates, and the impact on code delivery speed. Key metrics include hours saved, usage percentage, and speed to merge request. The findings reveal enhanced productivity, cleaner code, and increased developer satisfaction, but also highlight the need for tailored onboarding and cultural alignment. The journey is ongoing, with a focus on refining metrics and maximizing GenAI’s potential.