skills/clawdbot/skills/cross-pollination-engine

cross-pollination-engine

SKILL.md

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

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