The same coding assistant can shorten feedback on one team and lengthen the review queue on another. Small batches, fast tests, and clear user outcomes turn generated code into learning. Weak version control, stale context, and large pull requests create more work nobody fully understands. Both teams can still report a successful rollout.

DORA's research helps explain why: AI amplifies the delivery system it enters. This session turns seven researched capabilities into signals a team can recognize in daily work, from growing pull requests and slow rollbacks to shadow use and disagreement about whether a change helped a user. We use a lightweight team assessment to reveal where engineers, leaders, and platform teams see the system differently, then choose the first condition worth improving. If you lead a team, or you're the engineer everyone asks whether the AI investment is working, you'll leave able to run that conversation with evidence and choose a practical next step before anyone buys another tool.