Developer productivity metrics are measuring you, not your team (dougrathbone.com)

Recent insights into developer productivity metrics reveal a paradigm shift in how performance is assessed within engineering teams. Traditionally, organizations relied on various metrics to gauge team performance while allowing leadership to coast behind the complexities of software development. However, with advancements in AI tools like Claude and Copilot enabling engineers to generate features rapidly, the longer cycle times and deployment delays now reflect managerial shortcomings rather than developer inefficiencies. The metrics, particularly DORA (DevOps Research and Assessment) indicators, serve as a scoreboard for leadership effectiveness, highlighting failures in establishing efficient systems for code review, deployment, and accountability. As AI elevates the potential output of engineers, it becomes crucial for leaders to actively remove obstacles and foster a high-performance culture. The responsibility lies in creating systems that facilitate quick code reviews, streamlined deployment pipelines, and clear decision-making ownership. Moreover, leaders must be vigilant in holding team members accountable for their commitments and addressing inefficiencies promptly. Ultimately, the narrative encourages engineering managers to view productivity metrics not as developer evaluations, but as reflections of their own leadership and organizational health, emphasizing the need for continuous improvement in managerial practices.