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

• DX data on about 200,000 engineers shows deployment frequency rising while change failure rate has become far more volatile, and maintainability is up while change confidence is down.
• PRs grew from about 44 to 72 lines, and Reock says incremental delivery is suffering as PR size grows.
• Juniors use AI the most, but staff+ engineers save as much time while using fewer tokens, according to DX's data.
• Median PR throughput gains are around 7.7% and even top performers did not reach 2x, which Reock attributes to code generation never having been the bottleneck.
• Case studies Reock cites: Morgan Stanley saving 300K hours a year, Zapier getting 15% more value per engineer while still hiring, and Spotify running an SRE incident agent.

• token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
• AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.

Shows measured gains are modest and quality risks rising, since code generation was never the bottleneck. Gives a utilization, impact and cost framework for measuring your own rollout.

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