Software quality and engineering metrics is a big topic in the industry right now, as companies seek to become more effective and competitive, and better understand how their engineering teams are performing. In this conversation Emilio Salvador, VP of Development at GitLab, and James Governor from RedMonk talk about the impact on generative AI on these topics, and take a look at GitLab's own framework for better understanding productivity - focusing on Task, Team, and Time dynamics. What is developer productivity, after all? What is team productivity? What does writing code 25% faster actually mean? What if you save an engineer an hour a week - what is that worth? What is breakthrough productivity? What if we could build 10 times as many things as we could before. What are the implications? Measuring, managing and understanding developer productivity requires us to consider these kinds of questions. The discussion delves into the complexities of measuring developer productivity, emphasizing that it cannot be reduced to a single number. The conversation explores the challenges in measuring performance, including the need for a combination of data sources and addressing cultural differences within teams. Emilio argues that we must recognise development as a team sport, with a focus on matching skill sets to internal transformations, always fostering collaboration within development teams.
This RedMonk Conversation was originally published in video form on February 6, 2024.
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