A practical operating model for measuring AI coding tools beyond token spend, including workflow outcomes, review quality, and organizational capability growth.
A practical framework for measuring AI-assisted engineering productivity without rewarding noisy output or blind approvals.
A practical framework for measuring AI coding productivity beyond token volume, with quality, reliability, and delivery metrics that matter to engineering leaders.
Using PR throughput, review-assisted merge metrics, and cycle-time signals to run AI-supported software delivery as a measurable system.
How platform teams should redesign Copilot governance now that auto model usage is resolved to actual models in metrics.
How to operationalize GitHub Copilot’s resolved model metrics for cost controls, policy design, and developer productivity governance.
