Introduction
# 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