“Token-maxing” inflates code volume — not productivity: what AI-agent data shows

Colleagues, a brief insight from the AI trenches: widespread code generation has increased the volume of generated code, but not necessarily its value.
- Analytics (Waydev, GitClear, Jellyfish, etc.) report more accepted PRs but also rising code churn: portions of code are being rewritten weeks later.
- Engineers with large token budgets open more PRs, yet effectiveness doesn’t scale — token costs often outweigh gains.
- Junior engineers accept AI-generated code more frequently and then spend more time reworking it.
Why this matters: measure code quality and longevity, not token consumption.
How do you evaluate AI-tool effectiveness in your team?
#AI #development #productivity #engineering