AI DevOps impact

AI is generating code faster than most engineering organizations can absorb it. Developer output is up 2–5x over baseline and 43% of that AI-generated code needs to be debugged in production, while the incidents-to-PR ratio across engineering orgs has jumped 242.7% as adoption scales. I call this the AI Velocity Paradox: teams are shipping faster and breaking more, at the same time, and the DORA dashboard leadership is watching doesn't show it. In my new report, I dig into the six places where that stress is already surfacing, source control, CI/CD pipelines, artifact storage, cloud and token costs, security gates, and the broken-deployment problem and lay out a governance framework for closing the gap before the bill comes due. Read the full analysis here.