Measuring and rolling out AI coding assistants | Eirini Kalliamvakou (GitHub)

This week's guest is Eirini Kalliamvakou, a staff researcher at GitHub focused on AI and developer experience. Eirini sits at the forefront of research into GitHub Copilot. Abi and Eirini discuss recent research on how AI coding assistance impacts developer productivity. They talk about how leaders should build business cases for AI tools. They also preview what's to come with AI tools and implications for how developer productivity is measured.Discussion points:(1:49) Overview of GitHub’s research on AI(2:59) The research study on Copilot(4:48) Defining and measuring productivity for this study(7:44) Exact measures and factors studied(8:16) Key findings from the study(9:45) How the study was conducted (11:17) Most surprising findings for the researchers(14:01) The motivation for conducting a follow-up study(15:34) How the follow-up study was conducted(18:42) Findings from the follow-up study(21:13) Is AI just hype? (26:34) How to begin advocating for AI tools(34:44) How to translate data into dollars(37:06) How to roll out AI tools to an organization(38:47) The impact of AI on developer experience(43:24) Implications of AI on how we measure productivityMentions and links:Eirini Kalliamvakou on LinkedInResearch on the impact of Copilot Crossing the Chasm by Geoffrey Moore

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