Self(StreetLight::Red)
The most controversial and highest-leverage constraint I’ve seen is a 100-line soft cap on PRs. Review effectiveness drops off a cliff above 200-400 lines. No matter how I look at the heaps and heaps of data, smaller PRs and clear PR descriptions are the only combination that consistently moves through review at a reasonable rate. This matters doubly for AI-generated contributions. The tools will happily produce 500 lines when 60 would do, and because agentic coding generates work asynchronously, those PRs tend to pile up in the queue without the natural back-and-forth that keeps human-authored changes in scope. The moment you start treating AI-authored PRs as a separate class with different standards, the lower standard wins. Treat every review the same regardless of who or what wrote it.，详情可参考line 下載
is never computed entirely, except for the initial values: only the changes are。谷歌对此有专业解读
The system will reboot now!
The incentive structure is clear: cap overhead to look responsible, underreport to stay funded, and close the gap by cutting the things donors never see. Maintenance, training, and long-term monitoring.