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。
Claude Code
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.
AI 寫的 UI 為什麼總差一點？因為沒人告訴它什麼算好
AI 生成的 UI 品質參差不齊，因為缺乏具體約束。UI Skills 將模糊的最佳實踐轉化為可驗證的規則。解析其設計模式，教你建立團隊專屬的 Skill 約束系統。
Why Does AI-Written UI Always Fall a Little Short? Because Nobody Told It What Counts as Good
AI-generated UI quality is inconsistent because it lacks concrete constraints. UI Skills turns vague best practices into verifiable rules. This post analyzes its design patterns and shows you how to build a team-specific Skill constraint system.
Why Can’t a Skill with 91 Components Generate an Order Page?
Developers often set a Skill’s responsibility scope too broadly, leading to overcomplicated architectures. This post breaks down the five levels of Skill capability boundaries and points out that its nature is a “knowledge base,” not an “automation engine.”
91 個組件的 Skill 為什麼生不出一個訂單頁面？
開發者常把 Skill 責任範圍設得過大，導致設計出過度複雜的架構。本文拆解 Skill 的 5 層能力邊界,指出其本質是「知識庫」而非「自動化引擎」。
CI Broke Again Over a Lint Error—Can AI Just Fix It?
Most CI failures are lint errors, typos, and formatting issues—anyone can fix them, but each round costs 10 minutes of waiting. Anthropic’s internal YOLO Push concept lets Claude auto-fix these mechanical failures, with a complete GitHub Action YAML example and safety boundary design.
CI 失敗→複製錯誤→手動修→再等 10 分鐘——這個循環可以自動化嗎？
CI 失敗最常見的原因是 lint error、typo、格式問題——任何人都能修，卻要等 10 分鐘。Anthropic 內部的 YOLO Push 概念讓 Claude 自動修復這類機械性失敗，含官方 GitHub Action YAML 範例和安全邊界設計。
Intent-driven Development: Lessons from Claude Code
The shift from Spec-driven to Intent-driven isn’t just about new tools—it’s a fundamental change in how we approach software development.
Intent-driven Development：我用 Claude Code 後的體悟
從 Spec-driven 到 Intent-driven，不只是工具的改變，而是開發思維的典範轉移。