資料來源#
- Fable's judgement
- How Anthropic's product team moves faster than anyone else | Cat Wu (Head of Product, Claude Code)
摘要#
她是 Anthropic 的 Claude Code 與 Cowork 產品主管。她當了多年工程師，短暫進入創投業後加入 Anthropic。她訪談「數百位想進入 AI 領域的產品經理」，並將這些經驗轉化為鮮明觀點：產品經理的職責正處於重整之中（見 Engineer PM Convergence）。
重要主張與立場#
- 節奏轉變。 Anthropic 的功能開發時程從 6 個月縮短到 1 個月，有時甚至只要 1 天。做法包括移除流程阻力、將大多數發布標示為 research preview 以降低承諾，並先在公司內部推出，再對外發布。
- 使命優先於協調。「如果有兩個相互競爭的優先事項，我們會討論哪一個對 Anthropic 的使命更重要。」這才是規模擴大後消除摩擦的關鍵，而不是人數或流程。
- 直接動手做。 這是她的人生座右銘。「工作都是假的。只要你了解限制，就能找出自己能做什麼，然後試著趕快去做。」她認為，主動性是新創公司應該聘用的罕見能力。
- 為當前模型打造產品。 為超級 AGI 稻草人打造產品很容易；難的是激發當前模型的最大能力。產品經理最難的技能，是定義一個月後產品應該是什麼樣子。
- 請模型自我剖析。 這是個被低估的除錯技巧：Claude 做出意料之外的事時，問它原因。「很多時候，只要對模型為什麼做出那個決定保持好奇，就能看出是什麼誤導了它，進而修正 harness」（見 Model Introspection Feedback）。
- 判斷重於規則。 在 AI Engineer World's Fair 的爐邊談話中，她與 Thariq Shihipar 對談，由 Simon Willison 主持（2026-07-03；此內容由 Fable's judgement 轉述）：讓 Fable「運用自己的判斷，而不是指示他們該如何工作」。具體例子是測試：使用者可以寫「只有大型功能才使用自動化測試；小型文案或設計變更就不要更新並執行測試」，但「最好還是直接告訴 Fable，讓它自行判斷是否要寫測試」。她精簡提示詞的做法，指向的是使用者的提示詞，而不是供應商的提示詞；而且採取委派的方式，而不是刪除的方式（見 Harness Shrinkage as Models Improve）。
- 建立 evals。 十個出色的 evals 勝過一百個平庸的 evals；撰寫 evals「受到低估」，應該由更多產品經理與工程師投入。
- 95% 自動化不算自動化。 要嘛做到 100%，要嘛就別做。最後的 5% 佔了大部分工作，卻也是讓工作流程值得信賴的關鍵。
- 打造每天會用的應用程式，而非原型。 過度客製化設定會變成分心的事——「我認為簡單的設定實際上效果更好。」
- 性格就是產品。 Claude 的個性（低自我、積極、輕鬆愉快、偏向行動）是產品成功的核心——Amanda 塑造性格的工作「比寫程式更難」，因為這項任務實在太模糊。
訪談中的營運細節#
- Anthropic 約有 30–40 位產品經理，分布於研究產品經理、Claude Developer Platform、Claude Code、企業業務與成長等領域。
- 優先聘用產品品味出色的工程師，而不是工程能力不足的產品經理——團隊裡許多工程師能直接從 Twitter 上的回饋一路做到產品上線，全程不需產品經理參與。
- 團隊中的設計師都有前端工程背景。
- 每晚使用 Cowork，根據 Slack、Drive 與 Twitter 的脈絡草擬 20 頁簡報（預先載入 Anthropic 設計系統）。
- 內部技術堆疊：大量使用 Claude Code 與 Cowork、Slack（「我們公司的作業系統」），以及團隊為個人化工作流程打造的自訂內部應用程式。
- 「Applied AI」團隊的 token 用量僅次於工程團隊——這是個技術型市場拓展職務，負責為客戶製作原型。
重要引言#
- 「為超級 AGI 強大模型打造產品很容易。真正困難的是，針對當前模型，要怎麼激發它的最大能力？」
- 「隨著撰寫程式碼的成本大幅降低，決定要寫什麼就變得更有價值。」
- 「只要產品沒有阻礙核心使用情境，即使不成功也沒關係。」
- 「每當模型變得更聰明，我們就能移除許多提示詞介入。我們每次推出新模型時都會這麼做。」
關聯項目#
- Claude Code — 共同領導產品
- Cowork — 共同領導產品
- Boris Cherny — 技術主管合作夥伴
- Anthropic — 任職公司
- Engineer PM Convergence — 核心觀點
- Harness Shrinkage as Models Improve — Opus 4 移除待辦清單拐杖，是她的代表性案例
- Model Introspection Feedback — 她提出的除錯技巧
- AI Native Product Cadence — 體現這些做法
- Claude Character as Product — 闡明性格為何是產品的承重支柱
- Fiona Fung — 同一批產品的資深領導者，與她互補（Fung 描述工程組織；Wu 是產品主管）
- Dogfooding as Product Discipline — 她在午餐時做的氛圍檢查，是同一種 dogfooding 的 eval 形式；Fiona Fung 稱之為「ant food」
- Verification as the New Bottleneck — 她提出的「十個出色的 evals」與「推進到 100%」立場，從產品角度反映驗證成為瓶頸
資料來源#
- How Anthropic's product team moves faster than anyone else | Cat Wu (Head of Product, Claude Code) — Lenny's Podcast，2026-04-23
- Fable's judgement — Simon Willison，2026-07-03（
practitioner-opinion）：關於判斷重於規則的建議，來自 AI Engineer World's Fair 爐邊談話的二手轉述——資料集中沒有逐字稿或錄影，而且該觀點共同歸於 Thariq Shihipar，未說明各自說了什麼
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