PR merge count doubled — and so did production rollbacks. After adopting AI tools, one team watched weekly merges climb from 32 to 71, while monthly rollbacks jumped from 2 to 5. Every rolled-back PR had passed CI. AI accelerated the coding part, but the feedback net of review and testing didn’t become denser to match. This post breaks down the three-layer architecture of SDLC, DevOps, and CI/CD, and looks at which layer AI should be placed in.
PR merge 速度翻倍，rollback 次數也跟著翻倍。AI 加速的是寫程式碼那一段,但 review 與測試的反饋網沒跟著加密。本文拆解 SDLC、DevOps、CI/CD 三層架構,看 AI 該被擺進哪一層。
Junior 提交了 PR，AI review 吐出一份 40 頁的報告。120 個標記中,Senior 看了 20 分鐘，發現 80% 是風格，15% 是誤報。當警告太多，高信賴度風險就被淹沒了。PR review 有兩個特殊結構，讓它特別吃多 Agent 交叉驗證的紅利。
A junior engineer submitted a PR, and the AI review returned a 40-page report. Among 120 flags, a senior engineer spent 20 minutes reviewing them and found that 80% were style comments and 15% were false positives. When there are too many warnings, high-confidence risks get buried. PR review has two special structural properties that make it especially benefit from multi-agent cross-validation.
AI can write 500 lines of code. But that senior engineer spent 10 minutes reviewing it and found the critical bug. Those 10 minutes—that is where your value lies in the AI era.
AI 可以寫 500 行代碼。但那個 Senior 花 10 分鐘 review，發現了關鍵問題。那 10 分鐘，就是 AI 時代工程師最值錢的東西。