資料來源#
摘要#
在 Anthropic 領導 Claude Code 與 Cowork 的工程及產品;先前曾在 Meta 和 Microsoft 建立並領導團隊(她在 2000 年代初期參與了 Visual Studio 的開發)。她 2026 年 5 月的演講「Running an AI-Native Engineering Org」是組織領導層面的觀點,與 Cat Wu 的產品敘述和 Boris Cherny 的 IC 敘述互為補充:她描述了當 agentic coding 成為全組織預設後,團隊流程如何被重寫。她的核心主軸:「過去有效的方法未必繼續有效」("what served you prior may no longer") — 審視每個流程是否仍然達成其目的,因為瓶頸已經轉移了。
注意:Fiona Fung 和 Cat Wu 都被描述為領導 Claude Code + Cowork 的產品。她們是互補的資深領導者 — Fung 將自己定位在工程組織(管理者即 IC、審查、招聘、規範);Wu 是產品負責人(節奏、evals、與 Boris 的願景轉譯)。將職稱重疊視為共享範疇,而非矛盾。
五個改變#
她的演講圍繞五個組織轉變展開,這些轉變發生在寫程式不再是瓶頸之後:
- 瓶頸轉移了 — 從工程產能轉移到驗證、審查和維護(Verification as the New Bottleneck)。
- 規範自行重寫了 — TDD 不再是負擔;重構不再是預算之爭;設計文件縮短了(Building Is Cheap, Arguing Is Expensive)。
- 真實來源轉移了 — 從文件轉移到簽入 repo 的程式碼/skills(Code as Source of Truth)。
- 組織結構扁平化了 — 每位 Claude Code 管理者都從 IC 做起(Managers as ICs)。
- 產品感成為稀缺技能 — 透過不斷的 dogfooding 來培養(Dogfooding as Product Discipline)。
她引用的歷史類比#
她將此框架化為並非第一次的瓶頸轉移:在 2000 年代初期的 Microsoft,*建置(builds)*是瓶頸 — 一間伺服器機房、值班週、「一次六個 PR」的合併佇列、除錯哪個 PR 破壞了建置。雲端 + 持續建置消除了那個瓶頸。Agentic coding「只是同類型的又一次轉移」。這個紀律是永恆的:流程「悄悄地停止運作」,而人們不會主動刪除流程 — 它們會堆積起來(她的 SLA 堆疊戰爭故事)。因此「明確允許砍掉舊流程」成為團隊原則。
團隊原則(「必做事項」)+ 由下而上#
她讓團隊對齊的強制機制:每位隊友都使用 Claude Code 和 Cowork;「Claudify everything we can」(如果 Claude 能做,就該讓 Claude 做);明確允許砍掉舊流程。 在此之下的一切 — Claude 如何出現在分類、站會中,哪些工作流程優先被 Claudify — 則由各 pod 自下而上決定。平衡:在文化上對齊,留出適應空間。
關鍵語錄#
- "What served you prior may no longer."
- "Building is cheap, argument is expensive."
- "[TDD] kind of took the tax out… it was actually so much more fun."(先寫失敗的測試,搭配 Claude)
- "Dog food, dog food, dog food — or as we call it at Anthropic, ant food."
- "Our code is our source of truth."
相關連結#
- Claude Code — 領導工程及產品
- Cowork — 領導工程及產品(姊妹產品)
- Anthropic — 雇主
- Cat Wu — 同產品的互補產品領導者
- Boris Cherny — 透過產生三個 PR 而非白板討論來辯論重構方法
- Verification as the New Bottleneck — 她的核心論點
- Code as Source of Truth — 她的入職/知識分享重寫
- Managers as ICs — 她「辛辣的」組織變革
- Dogfooding as Product Discipline — 她的產品感引擎(「ant food」)
- Harness Shrinkage as Models Improve — 「Claudify everything / kill old processes」是 harness shrinkage 的組織流程面
資料來源#
- Running an AI-native engineering org — "Running an AI-Native Engineering Org" talk, May 2026
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