AI-Assisted Engineering: Measure Outcomes, Not Activity

Measuring AI-assisted engineering by activity alone misses the point. Active users, token usage, generated lines of code, and agent sessions are useful signals, but they do not tell you whether the work was reviewable, trusted, safe, or worth the cost. This post looks at what platform teams should measure instead: workflow success, review effort, guardrail failures, context reuse, cost per useful…