I Pulled 3 Months of Engineering Metrics on Our AI Tools - Here's the Dashboard Cell Nobody Built Last week our team got the same question I bet half of you got: "what's the ROI on the AI tools we adopted in Q1?" The CFO asked engineering. Engineering pointed at the PM retro. The PM retro had a row that said "team velocity feels higher" and a row that said "developers report subjective time savings." That was the data. Meanwhile a fresh enterprise survey out of ExcelMindCyber says 73% of companies will fail to deliver promised ROI on AI investments this year. I read that and thought: of course. The dashboard for the question doesn't exist. What the Repo Already Knows Pull request throughput. Time-to-first-review. Cycle time from open to merge. Build duration. CI flake rate. Incident count. Mean time to recovery. PR size distribution. We ship all of these. Most teams stream them into a Grafana board or a Linear analytics view or a custom dbt model on top of GitHub events. The data is in the repo.…