Cross-Pollination Engine: AI & Machine Learning for Claude Code | AI Skill Market | AI Skill Market

Cross-Pollination Engine: AI & Machine Learning for Claude Code | AI Skill Market | AI Skill Market

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

Define the core job (strip away industry context)
Find who else solves it (often surprising industries)
Extract principles (not surface features)
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