Researchers from Microsoft, Google, and GitHub discuss what has been learned about AI adoption in engineering organizations throughout 2025. They examine the challenges of measuring AI's impact on developer productivity, why simple metrics like lines of code are misleading, and how frameworks like SPACE and DORA provide better multidimensional approaches. The discussion covers how AI is reshaping developer roles from implementers to orchestrators, the implications for junior engineers, high-leverage use cases focused on reducing toil, and the importance of organizational culture in successful AI adoption. Looking ahead to 2026, they explore emerging trends like task parallelization and agentic workflows.
Sort: