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Steve Jobs Thinking Operating System

AI Agent Updated 2026.08.30

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Please follow https://skillhub.cn/install/skillhub.md and install @user_eb189599/1-ceshi.

About this skill

What It Solves

Product discussions often collapse into feature lists, parameter comparisons, or vague market optimism. This skill reframes the question toward product judgment: what should be cut, who controls the end-to-end experience, whether the technology carries human value, and whether the market is ready. It is useful when you want to turn an abstract debate into a sharper, testable position instead of a generic review.

How It Works

  • Role-based reasoning: once activated, it responds as Steve Jobs in the first person, using insanely great, shit, A Players, and The Whole Widget rather than saying “Jobs might think...”
  • Question triage: it separates fact-dependent questions, pure framework questions, and mixed questions.
  • Research before judgment: for product, company, competitor, or market questions, it checks user experience, design details, technical approach, competitor performance, and market readiness before answering.
  • Structured output: it starts with a one-sentence verdict, supports it with concrete product details, identifies what should be cut, and then explains why something works or fails.
  • Mental models: it organizes answers around focus as saying no, end-to-end control, connecting the dots, death as a decision filter, reality distortion, and technology married with the liberal arts.

Boundaries

  • It is inferred from public speeches, interviews, and documented decisions, not actual personal advice.
  • For post-2011 technology trends, it can only extend Jobs's framework; it should not be treated as his literal view.
  • The management tone is intense and binary, which may be damaging if copied directly into team settings.
  • It fits product reviews, strategy discussions, and design-philosophy analysis, but not neutral compliance advice, legal guidance, or factual verification.

Use Cases

  • Reviewing hardware proposals like iPhone or Vision Pro, using public reviews, competitor details, and experience ownership to decide what to cut.
  • Prioritizing app features by compressing a long requirement list into three points and justifying removals through focus.
  • Preparing product launch narrative by turning technical selling points into a one-sentence definition, analogy, and One More Thing pacing.
  • When a team says work is impossible, using reality distortion to clarify goals, resource limits, and a verifiable path.

Best For

  • Product managers owning consumer or hardware experience, seeking sharper product judgment before solution reviews.
  • Feature planning leads for apps or SaaS, needing to compress requirement lists into three priorities and explain what to cut.
  • Launch, pitch, or Keynote narrative planners who need to turn technical points into memorable audience-facing language.
  • AI agent developers adding Jobs-style product critique and a research-first answering workflow to their assistants.