一龍馬/AI 情報站讀懂消息背後的脈絡
星期二
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Addy Osmani 認為 Agent 會跳過新人原本靠嘗試、除錯、讀 diff 與 review 累積的練習,因此學習者必須刻意先形成假設、預測失敗並偶爾手動解題

中文摘要

他把優秀 Agent 工作濃縮成深度專業與應用判斷,並要求計畫能被測試與驗證。

一龍馬判讀

這比「學會下 prompt」更接近長期能力建設:沒有領域理解,就無法定義好結果;沒有判斷,就無法辨認 Agent 何時偏離。培訓應評量規格、驗證與取捨,而不只看交付速度。

原文節錄

Addy Osmani · @addyosmani

Mastery still comes from doing the reps.…

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Mastery still comes from doing the reps. Before agents, I got my reps as part of writing code: try different approaches out, debug what went wrong, review other’s code, read a lot. Agents can skip much of that work, so building your reps has to be deliberate. If I was new to the industry, I'd try to form a hypothesis before prompting. Ask "why" a lot, read the diffs, try to predict what might fail. Occasionally try to work through the problem myself manually. In my experience, good agent work depends on two abilities: 1. Deep expertise: you understand the problem domain well enough to define a good outcome. Understanding your user/product/business is part of this. 2. Applied judgment: use your taste to turn this into a clear, testable plan by choosing the right context, constraints, tests and verification. To build these the skills I'd practice are decision making, specifying, steering and verifying.

收錄日期
2026-09-01
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2026/09/01 06:13(台北)