AI Coding Tools Took Off.

Engineering Performance Didn’t.

New research reveals why AI adoption isn’t translating into engineering performance and what leaders can do to fix it.

We analyzed telemetry and workflow data from 10K devs across 1,255 enterprise engineering teams. Engineers are completing twice as many code changes, but company metrics remain flat.

This landmark report reveals the AI productivity paradox in software engineering and unpacks the three systemic barriers blocking real impact at scale.

  • Real-world engineering telemetry, not survey data
  • Deep analysis of adoption, friction, and outcomes
  • Actionable insights for leaders building AI-first orgs
Read the report
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