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Cross-Pollination Engine

Systematically borrow ideas from unrelated industries to solve problems. Innovation often comes from adjacent fields. Use when user says "cross-pollination", "how would X solve this", "borrow ideas from", "what can we learn from", "think outside the box", "how would Disney/Apple/Amazon do this", "different industry", "steal ideas".
系统性地借鉴不相关行业的思路以解决问题,创新往往源于相邻领域。当用户提及“跨界融合”、“X会怎么做”、“借鉴思路”、“能学到什么”、“跳出框框”、“迪士尼/苹果/亚马逊会怎么做”、“不同行业”、“借用点子”时使用。
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概述

Cross-Pollination Engine

The Core Insight

Most "innovation" is applying proven solutions from one domain to another.

  • Resistance wheels → Rollerblades
  • Gaming XP systems → Duolingo
  • Hotel concierge → Software onboarding

The Process

  1. Define the core job (strip away industry context)
  2. Find who else solves it (often surprising industries)
  3. Extract principles (not surface features)
  4. Translate to your context (adapt, don't copy)

Industry Inspiration Library

NeedLook AtWhy
--------------------
TrustBanking, Healthcare, AviationVerification, credentials, checklists
EngagementGaming, Fitness apps, StreamingXP, streaks, personalization, progress
OnboardingHotels, Theme parks, Luxury retailConcierge, anticipation, personal touch
SimplicityApple, IKEA, GoogleFeature cutting, hidden complexity
UrgencyE-commerce, Airlines, Fast foodScarcity, anchoring, speed promises
CommunityCrossFit, Harley-Davidson, PelotonTribal identity, shared experience

Output Format

PROBLEM: [What you're solving]
CORE JOB: [Stripped to fundamentals]

FROM [Industry 1]:
How they solve it: [x]
Key principle: [y]
Applied to us: [z]

FROM [Industry 2]:
How they solve it: [x]
Key principle: [y]
Applied to us: [z]

SYNTHESIS: [Combined approach]
NEXT STEP: [Concrete action]

Prompt Starters

  • "How would Disney solve our onboarding?"
  • "What would Amazon do with our data?"
  • "If this were a game, how would it work?"
  • "How do luxury hotels make people feel special?"

Integration

Compounds with:

  • jtbd-analyzer → Understand job first, then find who else solves it
  • first-principles-decomposer → Strip context to find fundamental need
  • six-thinking-hats → Green Hat pairs naturally with cross-pollination
  • app-planning-skill → Apply borrowed patterns to new apps

See references/examples.md for Artem-specific cross-pollinations

版本历史

共 1 个版本

  • v1.0.0 当前
    2026-03-28 13:14 安全 安全

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