Stop Measuring AI Coding Tools by Lines of Code Written

Vendors love to quote suggestion acceptance rates and lines generated, because those numbers only ever go up. They also tell you almost nothing about whether your team is shipping better software faster. A developer can accept a hundred lines and spend an hour untangling them.

The metric that matters is cycle time: how long an idea takes to reach production, safely. If AI assistance is working, pull requests should merge sooner and rework should drop, not rise. Track review comments per PR and post-merge revert rates alongside speed.

Code that is fast to write and slow to review is a net loss, and acceptance rate will never show you that.

Watch for the subtle failure mode where output volume climbs while defect escape rate creeps up with it. That is the signature of a tool generating plausible code that reviewers rubber-stamp under pressure. Faster typing is not the same as faster engineering.

Run a real baseline before rollout, segment by task type, and be willing to conclude the tool helps for boilerplate but not for gnarly domain logic. An honest, narrow win beats an inflated headline number every time.