The State of AI in Software Development: Data from 400+ Orgs — Justin Reock, DX

Justin Reock (Deputy CTO, DX) shares five trends from DX's data on about 200,000 engineers. Deployment frequency is rising, but change failure rate has become far more volatile. Maintainability is up while change confidence is down. PRs have grown from about 44 to 72 lines. Juniors use AI the most, but staff+ engineers save as much time while using fewer tokens. Median gains in PR throughput are around 7.7%, and even top performers didn't reach 2x, because code generation was never the bottleneck. Justin walks through the DX AI Measurement Framework (utilization, impact, cost), how to assess your platform's AI readiness, and "agent experience," which uses feedback from the agents themselves. He closes with case studies of AI applied across the whole SDLC: Morgan Stanley (300K hours saved a year), Zapier (15% more value per engineer, and hiring more) and Spotify (an SRE incident agent). Speaker info: Justin Reock LinkedIn: https://www.linkedin.com/in/justinreock/ Substack: https://substack.com/@jreock DX: https://getdx.com X: https://x.com/DeveloperXM LinkedIn: https://www.linkedin.com/company/developer-experience Timestamps: 0:00 Intro: DX research on AI's impact 1:27 Trend 1: velocity and deployment frequency 2:53 Regional differences 3:33 Perceived speed vs. reality 4:38 Trend 2: quality and change failure rate volatility 6:02 Maintainability up, change confidence down 7:02 PR size is growing and incremental delivery is suffering 8:42 Trend 3: juniors, staff+ engineers and company size 10:37 Trend 4: how to measure AI (utilization, impact, cost) 13:27 Platform AI readiness: good DX is good agent experience 14:17 Listening to feedback from agents 14:57 Trend 5: code generation was never the bottleneck 16:27 Case studies: Morgan Stanley, Zapier, Spotify 18:32 Get the Q2 report