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待翻譯:The Sequence Opinion #909: Return on Token: The New Economics of AI-Native Engineering

文章摘要

AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:Token maxing was the adoption phase. Intelligence resource planning is what comes next.

來源TheSequence作者: Jesus Rodriguez
待翻譯:The Sequence Opinion #909: Return on Token: The New Economics of AI-Native Engineering
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AI 服務暫時不可用,以下為來源正文,待恢復後補全翻譯。

For most of software history, engineering capacity was easy to sketch on a whiteboard. You had a certain number of engineers. Each had a certain amount of time and talent. The basic equation held: Engineering capacity ≈ people × time × talent. AI breaks that equation. An engineer can now assign one agent to investigate a production bug, another to write tests, a third to prototype an architecture, and a fourth to document the result. The agents can run for hours and work in parallel. They do not appear on the org chart, ask for equity, or attend the planning offsite. They do, however, consume tokens. The modern engineering organization now has a second, elastic workforce. The human workforce is measured in headcount. The machine workforce is measured, imperfectly, in tokens. And because companies love measurable things—especially things that produce dashboards—we have entered the era of token maxing. Token Maxing Is the New Lines of Code Read more

展開要點與分析

文章情報

工程師進階

要點

  • AI 服務暫時不可用,系統已先保留來源內容與降級後設資料。
  • Token maxing was the adoption phase. Intelligence resource planning is what comes next.

技術影響

可能影響 Agent 架構、工具呼叫、工作流自動化和產品整合。

要點與分析由自動化流程生成,可能有誤,請結合原始來源核實。