AI & Technology / Background
Four conditions behind skipping individual PR reviews
After recounting an AI-coding interview October 4, Bao Yu examined whether skipping individual PR reviews is reproducible. This article reports his own conditions. We read both posts, but have not watched the interview or verified its productivity figures.
First, he treats capable models and adequate token budgets as prerequisites; his personal multi-account practice is not a universal purchasing prescription. Second, AI-assisted checking still needs product observation and human judgment. Repeated deterministic checks belong in scripts.
Third, engineering direction should divide work into small, tested milestones. His marketplace example separates listings, browsing, user roles, payments and security before scaling. Fourth, derive tools and skills from repeated corrections and interventions in one’s own conversations, rather than copying another person’s setup.
The argument moves responsibility toward decomposition, verification and acceptance; it does not remove responsibility. These are practical recommendations, not a controlled demonstration that skipping PR reviews is safer. Risk and testability still shape the appropriate review process.
Sources and further reading
Edited report · Sources and limitations in the text
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