資料來源#
- A Field Guide to Fable: Finding Your Unknowns
- Fable's judgement
- How I AI: Thariq Shihipar on Replacing Markdown with HTML for AI-Powered Development
- The new rules of context engineering for Claude 5 models
摘要#
他是 Anthropic Claude Code 團隊的工程師。「HTML 是新的 markdown」論點(參見 HTML as the New Markdown)以及將人的角色稱為 Compute Allocator 的說法,都源自他。兩人在舊金山的 Code with Claude 活動相識後,Claire Vo 邀請他參加「How I AI」系列訪談(該集於 2026 年 5 月發布)。個人網站為 thariq.io;X 帳號是 @trq212。
重要主張與立場#
- 「HTML 是新的 markdown。」 隨著模型能力提升、專案日益複雜,markdown 計畫會讓人類讀者不堪負荷;HTML 是更豐富的媒介,能讓人保持投入。瓶頸不在模型,而在人類的注意力。參見 HTML as the New Markdown。
- 我們都逐漸成為「compute allocators」。 人的工作是決定哪些事情值得投入運算資源;他產生的 token 約有 1% 進入正式環境,其餘 99% 都是支架(計畫、介面、狀態、設計系統),用來投入協作與溝通。參見 Compute Allocator。
- 豐裕思維。 生成成本低到足以負擔一次性工具——為單一編輯任務打造的 micro-apps(「建構在微型軟體之上的微型軟體」)。
- 提示中兼具限制與自由度。「提供足夠的限制,讓你得到想要的結果,但也要留點空間,讓模型帶給你驚喜」——「嘿,Claude,這部分我相信你的判斷。」
- 讓人重新回到核心位置。 他的工作流程明確不是要把開發者自動化取代掉,而是讓協作更清楚可見、更引人投入。
- 地圖不等於疆域。(2026 年 7 月的實作指南。)提示、技能與上下文是地圖;程式碼庫及其真實限制才是疆域;兩者之間的落差就是未知之處。「Fable 是第一個讓我覺得,工作品質的瓶頸在於我能否釐清它的未知之處的模型。」 減少未知並預先規劃「就是代理程式程式設計的技能」——而且可以學會。參見 Unknowns as the Agentic Bottleneck。
- 測驗關卡。「只有在我完美通過測驗後,我才會合併」——合併前,他會讓 Claude 就某項變更考問自己,因為若行為取決於既有程式碼路徑,只讀差異不足以充分理解。受驗證的是人,而不是代理程式。
- 原始碼是最好的參考。 如果你無法描述想要什麼,就指出能做到這件事的程式碼——即使它使用另一種語言。這就是 Claude Design 的運作方式:指向一個元件,它「讀取底層程式碼,而不只是看截圖」。
- 解除束縛。(2026 年 7 月的上下文工程文章。)Claude Code 團隊過度限制模型:他們刪除了 Claude 5 models 系統提示中超過 80% 的內容,評估結果沒有可測得的損失,並淘汰了一系列上下文工程「迷思」(規則→判斷、範例→介面設計、預先提供→漸進揭露、重複內容→工具描述、CLAUDE.md-memory→auto-memory、簡單規格→豐富參考資料)。以
claude doctor的形式提供給使用者。參見 Harness Shrinkage as Models Improve 與 Agent Context Files。他與 Cat Wu 在 AI Engineer World's Fair 的爐邊談話中,將規則→判斷這項原則作為面向使用者的建議:讓 Fable「運用自己的判斷,而不是指揮它該怎麼工作」,並以自動化測試為實際案例(2026-07-03;二手轉述於 Fable's judgement)。
他示範的三種工作流程#
- 互動式 HTML 腦力激盪與規劃 — 要求以 HTML 檔案而不是清單呈現計畫;內容具視覺性、可捲動,也方便分享。
- Disposable Micro-Apps — 產生一次性自訂介面,編輯計畫中的一個部分,並能複製回 markdown。
- Living Design System — 從程式碼庫擷取出
design_system.html,作為可攜、同時供人與機器讀取的真實資訊來源。
相關連結#
- Claude Code — 他在 Anthropic 的團隊
- Anthropic — 雇主
- Claire Vo — 邀請他參加「How I AI」訪談
- HTML as the New Markdown — 他的核心論點
- Compute Allocator — 他描述人類角色的說法
- Disposable Micro-Apps / Living Design System — 他的另外兩種工作流程
- Boris Cherny — Claude Code 團隊同事;「對我而言,程式設計已經解決」是 Thariq 提出運算資源分配者觀點的前提
- Harness Shrinkage as Models Improve — Thariq 關於 99% 支架的觀察,是面向人的說法,與團隊面向模型、精簡 harness 的做法形成互補
- Engineer PM Convergence — 他的運算資源分配者觀點,就是在呼叫尺度上實踐「決定要寫什麼」
- AI Native Product Cadence — 他看好更豐富的 HTML PRD,與 Cat Wu 看好更精簡的 PRD 形成對照
- Interaction Models — 兩者都以改善人與 AI 的協作為目標;他的 HTML 產物豐富了非同步管道,而 TML 則消解了即時介面
- Software 3.0 — 他的 HTML 優先工作流程與 Disposable Micro-Apps 都原生適用於 Software 3.0:根據提示為每項任務快速生成介面,而非手工打造應用程式
- Unknowns as the Agentic Bottleneck — 他在 2026 年 7 月提出的論點:使用 Fable 等級的模型時,主要限制在於人類能否說清楚自己從未寫下來的內容
- Context Advantage, Not Taste — 他所說的已知卻未明言之事,是從人的內在視角看 Andrew Ng 的上下文優勢;實作指南則是引出這些內容的方法
- Claude Fable 5 — 根據他的說法,這個模型讓瓶頸轉移到人身上
資料來源#
- How I AI: Thariq Shihipar on Replacing Markdown with HTML for AI-Powered Development — Claire Vo 在 ChatPRD 的「How I AI」訪談,2026 年 5 月
- A Field Guide to Fable: Finding Your Unknowns —「A Field Guide to Fable: Finding Your Unknowns」,發布於 X,2026-07-04(
practitioner-opinion) - Fable's judgement — Simon Willison,2026-07-03(
practitioner-opinion):AI Engineer World's Fair 爐邊談話的建議,經二手轉述,並共同歸於 Cat Wu,但未說明各自說了什麼;資料庫中沒有逐字稿或錄音
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