Ciera Jaspan

This week we’re joined by Ciera Jaspan and Collin Green, who lead the Engineering Productivity Research team at Google. Ciera and Collin have written several papers from studies they’ve conducted, and this discussion covers the insights from their research as well as their work more broadly at Google. Discussion points:(1:19) About the Engineering Productivity Research team(3:57) How the team interacts with the rest of the organization(5:58) The different backgrounds included on the team(13:11) How Google measures developer productivity(18:54) Evaluating discrepancies between qualitative and quantitative data (28:40) Google’s quarterly developer survey(32:02) Distributing survey results back to the organization (40:25) Misunderstandings about surveys(43:51) Ciera and Collin’s paper on why measuring productivity is difficult(50:35) Reductionist metrics for measuring productivity(55:26) Examples of other fields that have struggled with measurement(59:00) Google’s study on measuring technical debt(1:08:05) Human judgment in measurementMentions and links: Follow Ciera and Collin on LinkedInA Human-Centered Approach to Measuring Developer Productivity - Paper, Abi’s summaryEnabling the Study of Software Development with Cross-Tool Logs - PaperDefining, Measuring, and Managing Tech Debt - Paper, Abi’s summaryGoogle’s Goals, Signals, Metrics framework - Paper, Abi’s summary

Join Brian Houck from Microsoft, Ciera Jaspan and Collin Green from Google, and Eirini Kalliamvakou from GitHub as they dive into the complexities of measuring AI's impact on software development. They discuss how traditional metrics like lines of code fall short, the potential for AI to reshape developer roles, and the importance of identifying genuine pain points for AI solutions. The conversation also explores how AI can foster creativity and accelerate junior engineers' growth, setting the stage for a more thoughtful approach to AI adoption in the industry.