3 posts tagged with "engineering-metrics"

Your dashboard has never looked better. Pull requests merged are up almost double. Commits per engineer are climbing. Lines of code are pouring in. Every activity chart points up and to the right, and the AI coding tool you rolled out six months ago looks like the best money the org has spent all year.

Then you check the one number nobody puts on a slide: how long it takes for a customer to actually get something they asked for. It hasn't moved. In some quarters it's worse. The team is producing more of everything except the thing the business buys.

This is the velocity mirage. The metrics that are easy to count went up, and the outcome that matters quietly went the other way. It is one of the most expensive measurement failures in engineering right now, because it looks exactly like success.

A head of engineering opens the velocity dashboard on a Monday morning. PRs merged per week, flat. Story points completed, flat. Lines changed, suspiciously low. The AI team is having a quiet quarter, the chart says. Two floors away, that team has rewritten the system prompt seven times in three weeks, swapped a tool description that doubled tool-call accuracy, added six new few-shot examples, and tuned the rerank instruction until the product feels like a different application. None of that work shows up in the PR graph. None of it is invisible to users.

The asymmetry between what AI teams change and what engineering dashboards measure has become the load-bearing misdiagnosis of 2026. Behavior change in an AI-heavy product is increasingly decoupled from code change, and the metrics that have governed software organizations for fifteen years — PR throughput, commit volume, lines touched — measure code change. A team can be reshaping production response distributions weekly and look idle on every chart leadership trusts.

Here is a number that should unsettle you: according to the 2025 DORA State of AI-Assisted Software Development report, developer PRs merged per person rose 98% while incidents per PR rose 242.7%. Deployment frequency looks elite. The system is breaking more often per unit of change than at any point DORA has measured.

Your dashboard is green. Your on-call engineers are exhausted. Something is wrong with the measuring tape.