從 Context 流失到自我修復 CI：Anthropic 的工程實戰觀察
Anthropic 工程師在臺北 Meetup 分享：如何透過 hooks 與自動化機制，把 CI 的回饋迴路產品化，減少等待與人工重工。
CI/CD
From Context Loss to Self-Healing CI: Observations from Anthropic’s Engineering Practice
Anthropic engineers shared at a Taipei Meetup how hooks and automation can productize CI’s feedback loop, reducing waiting and manual rework.
DevOps 沒有取代 SDLC，AI 也不會
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。
DevOps Didn’t Replace SDLC. Neither Will AI.
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.
End-to-End Testing Guide: From Definitions to AI-Augmented Strategies
Master E2E Testing: Debunk the ‘Ice Cream Cone’ anti-pattern, leverage AI visual regression, and build reliable Playwright strategies for confident deployments.
E2E 測試完全指南：從基礎定義到 AI 賦能的現代化測試策略
E2E 測試完全指南。破解 200 個購物車測試案例的迷思，深入解析 AI 視覺回歸與自我修復技術。學習如何結合 Playwright 與單元測試，建立高信心的自動化防護網。