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Cross-Pollination Engine

这是一个跨行业创新思维框架:先剥离行业背景定义核心任务,再寻找其他行业如何解决同类问题,提取底层原则并迁移到自身场景,最后综合并给出下一步行动。适用于产品、运营和策略类头脑风暴。

artyomx33
artyomx33
热度 94.21
最近更新 2026-05-11 15:50:52
分类:创作依赖:纯提示词应用场景:研究 / 推荐 / 概念解释 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add cross-pollination-engine
Metadata
name
cross-pollination-engine
description
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".

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

Need Look At Why
Trust Banking, Healthcare, Aviation Verification, credentials, checklists
Engagement Gaming, Fitness apps, Streaming XP, streaks, personalization, progress
Onboarding Hotels, Theme parks, Luxury retail Concierge, anticipation, personal touch
Simplicity Apple, IKEA, Google Feature cutting, hidden complexity
Urgency E-commerce, Airlines, Fast food Scarcity, anchoring, speed promises
Community CrossFit, Harley-Davidson, Peloton Tribal 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