Citing Godhart’s Law, they stressed that AI code-generation metrics are a “terrible choice” because they incentivize more code where less would do. Instead, they suggest evaluating AI coding tools through engineer qualitative self-assessments and throughput metrics attached to the wider engineering organization rather than individuals. This includes: on-time delivery, and SPACE and DORA frameworks.
“It’s outcomes, not activities, that get results,” he said.
Couldn’t agree more. we HAVE good metrics. Delivery of solutions. Why muddy that with how many lines of code were written by AI vs a Human.
Quote Citation: Sage Lazzaro, “AI coding trackers are here. Proceed with caution - LeadDev”, 2025-06-18, https://leaddev.com/reporting/ai-coding-tool-trackers-proceed-with-caution