The current impact of AI on engineering velocity: What 400 companies are seeing

Recorded live at DX Annual, Abi Noda, co-founder and CEO of DX, joins Brian Houck of Microsoft to share an early look at DX’s new research on AI’s impact on engineering velocity. Drawing on data from a sample of DX customers, they discuss what companies are actually seeing as AI adoption matures. Most organizations in the study saw pull request throughput increase by 10 to 15 percent—far more modest than the 10x gains often promised in industry headlines. They explore why coding remains only a small part of developer work, where time saved by AI may be going, and the unintended consequences of moving faster, from shifting bottlenecks to “false velocity.” Abi also shares how engineering leaders are applying AI beyond coding and how DX is evolving its measurement framework to account for both human and agent productivity. — Where to find Brian Houck: • LinkedIn:   / brianhouck   Where to find Abi Noda: • LinkedIn:   / abinoda   — In this episode, we cover: (00:00) Intro (00:53) What motivated DX’s research into AI’s impact on engineering velocity (02:36) How DX designed the study and selected companies (04:54) What DX’s data reveals about AI’s impact on engineering throughput (06:31) Why PR throughput was the most practical metric to publish (08:21) Why AI productivity gains are lower than many leaders expected (10:24) How an all-in culture can amplify AI productivity gains (12:35) Why it’s hard to track where AI-generated time savings are going (15:04) Unintended consequences of AI-driven productivity gains (17:12) Why leaders should look beyond coding to the rest of the SDLC (19:43) Cognitive debt and the human costs of AI-assisted development (21:33) How DX’s AI measurement framework is evolving (24:42) How to make agents more effective