80% AI-Written Code: How 1KOMMA5 Measured the Real Impact of AI on Engineering

AI coding tools are everywhere, but how do you prove they're actually making engineers more productive? In this episode of PurePerformance, hosts Brian Wilson and Andi Grabner welcome Michael Reichenbach, Platform Engineer at 1KOMMA5°, to discuss the company's journey toward more than 80% AI-written code. Rather than relying on anecdotes or hype, Michael shares how his team designed a real experiment to measure the impact of AI-assisted development. We explore the metrics they chose, why traditional DORA metrics such as deployment frequency and change failure rate were not the right indicators, and how they instead focused on "Time to Code" from ticket creation and first commit to merged pull request. Michael also explains how AI lowered the barrier for contribution across the organization, enabling even non-engineering teams to prototype and build solutions faster. The conversation also dives into the operational side of AI adoption, including AI observability dashboards, budget controls, Slack alerts, usage monitoring, and the surprising decision to intentionally limit AI spending during their proof of concept. Whether you're evaluating Cursor, GitHub Copilot, or other AI coding tools, this episode offers practical lessons on measuring value, maintaining quality, and scaling AI adoption responsibly. Links we discussed Michael's LinkedIn: https://www.linkedin.com/in/michael-reichenbach/ Klaus's LinkedIn: https://www.linkedin.com/in/langenheldt/ Talk at Cloud Native Munich: https://www.youtube.com/watch?v=Ntf0h0vFuMQ 1Komm5 Website: https://1komma5.com/ Kenote from KubeCon: https://youtu.be/P1phxZHJGrA?t=570&is=9DYnbK8VGorMmaXo Michael's YouTube Playlist: https://youtube.com/playlist?list=PLn-u2xOcMlXlVweZ0aB4pu6VM6Xv6895i&si=MZ6jzF-VwIAY3HFF