SKILL

find-your-margin

Help a knowledge worker find where their attention earns the fattest margin when combined with AI. Maps their skill stack against AI capabilities to identify high-surplus opportunities vs. commodity traps. Use when someone asks where to focus their AI efforts, how to avoid the allocation economy race-to-zero, or how to build a defensible position as an individual operator.

原文 · 译文尚未补齐

适用对象:对象待分类。自动收录 · 待核查。

原作者说明节选

从固定版本的 SKILL.md 提取,保留原文语言。以下内容属于作者说明,本站尚未验证安装、兼容或运行结果。

查看英文原文

原文涵盖的主题

  • Find Your Margin
  • When to Use
  • The Core Framework
  • Workflow
  • Step 1: The Skill Stack Audit
  • Step 2: The AI Commoditization Map
  • Step 3: The Margin Finder
  • Step 4: The Attention Allocation Portfolio

Full Production Studio note: this skill comes from another creator's own setup. Brand names, people and folder paths in it (for example OpenEd, Skill Stack, Howseen, /Desktop/...) are their examples. Replace them with the user's brand, voice and folders (use the arabic-voice Voice Card when available) and never write in that other brand's voice. Audit a knowledge worker's skill stack against AI capabilities to find the narrow lanes where their human judgment + AI throughput creates surplus nobody else can touch. Based on the marginalist insight that intelligence, like capital, flows to the area of highest return — and the counterpoint that individuals win not by competing on allocation efficiency, but by finding fat margins at human scale. -- "Where should I actually focus my AI efforts?" "I'm using AI for everything but nothing feels defensible" "How do I avoid being replaceable by someone with the same tools?" "What's my moat in the AI age?" The Marginal Intelligence Trap: In a competitive allocation economy, surplus converges toward zero. Everyone uses the same models, the same prompts, the same workflows. The marginal return on one more hour of AI allocation approaches $0. The

这里只展示节选,请以完整原文和当前要求为准。

来源仓库
alfaris/full-production-studio
源文件
skills/find-your-margin/SKILL.md
固定版本
223f74cc6dceb4c16858c4d58b5d066e7c5eeb83
阅读完整原作者说明 ↗

准备条件

  • 本条仅收录原作者的技能元数据;请阅读完整说明,确认依赖、许可与使用条件。

第一件可以尝试的小事

先阅读原作者说明,再决定是否在自己的 AI 工具中使用。

对应 AI 工具说明

作者有说明不等于本站实机验证。没有证据时,不自动标为兼容、安全或免费。

来源与内容状态

本条为自动发现的元数据,尚未完成人工文档核查;适用性与运行结果待核查。

原作者:alfaris/full-production-studio · 原作者仓库元数据。文档核查:未核查。最近来源检查:2026-11-10T12:01:33.853Z。

分类由名称、说明与路径规则生成,分类不代表已核实适配。

许可与权利归属

MIT。第三方内容及版权归原作者,使用条件以原文为准。

许可原文 ↗

本站没有因同步、复制或用户自报成功而将资源标为运行验证通过。

限制与注意事项

  • 元数据收录不代表本站已经安装、适配、实测或进行安全审查。