Aiverse Design Patterns
The 37 Patterns Framework​
A systematic, phase-driven approach to AI UX based on 200+ real-world examples.
Phase 1: Onboarding (6 Patterns)​
How users discover AI capabilities​
| Pattern | Description | Web3 Application |
|---|---|---|
| Proactive Suggestions | AI surfaces help before asked | Wallet transaction insights |
| AI Icons | Sparkles ✨ indicate AI features | Mark AI-enhanced DeFi yields |
| Suggested Prompts | Starter examples show capabilities | "Analyze my portfolio risk" |
| Search & Filter | AI-powered discovery | Find similar NFT traits |
| Autocomplete | Predict user intent | Complete contract addresses |
| Disclaimers | Set expectations upfront | "Not financial advice" notices |
Phase 2: Input (9 Patterns)​
How users express their intent​
| Pattern | Description | Web3 Application |
|---|---|---|
| Voice Input | Natural conversation | "Buy 100 USDC of ETH" |
| Handwriting | Written notes & signatures | Sign transactions naturally |
| Visual Input | Screenshots, images | Upload chart for analysis |
| Gestures | Touch and motion | Swipe to approve transactions |
| Structured Input | Forms with guidance | Token swap parameters |
| Prompt Assistance | Improve user queries | Suggest missing context |
| Model Selection | Choose AI model | Fast vs. accurate analysis |
| MCP Connectors | External data sources | Connect on-chain data |
| Knowledge Base | Domain expertise | Protocol documentation |
Phase 3: Output (14 Patterns)​
How AI delivers results​
| Pattern | Description | Web3 Application |
|---|---|---|
| Preview | Show before generating | Transaction preview |
| Video | Dynamic explanations | DeFi strategy walkthroughs |
| Image | Visual outputs | Generate NFT variations |
| Audio | Voice responses | Market alerts |
| Variations | Multiple options | Trading strategy alternatives |
| Multi-modal | Combined formats | Chart + explanation + audio |
| Summary | Condensed insights | Protocol changes digest |
| Structured | Tables, JSON | On-chain data formatted |
| Real-time | Instant responses | Price alerts |
| Streaming | Progressive results | Large portfolio analysis |
| Parallel | Multiple processes | Multi-chain scanning |
| Steps | Progress indication | Complex swap routing |
| Confidence | Certainty scores | Risk assessment levels |
| Citations | Source references | Link to block explorer |
Phase 4: Refinement (5 Patterns)​
How users improve results​
| Pattern | Description | Web3 Application |
|---|---|---|
| Inline Actions | Edit specific parts | Adjust gas settings |
| Visual Editing | Direct manipulation | Drag slippage tolerance |
| Reply | Continue conversation | "Make it more conservative" |
| Regenerate | Fresh attempt | New trading strategies |
| Review | Accept/reject flow | Approve transaction batch |
Phase 5: Learning (3 Patterns)​
How the system adapts​
| Pattern | Description | Web3 Application |
|---|---|---|
| Memory Management | Recall preferences | Remember wallet preferences |
| Feedback Collection | Learn from ratings | Improve yield predictions |
| Personalization | Adapt to user | Custom DeFi dashboard |
Implementation Checklist​
For Portfolio Companies​
Coverage Requirements​
| Phase | Minimum Patterns | Recommended |
|---|---|---|
| Onboarding | 3 of 6 | 5 of 6 |
| Input | 4 of 9 | 7 of 9 |
| Output | 7 of 14 | 10 of 14 |
| Refinement | 2 of 5 | 4 of 5 |
| Learning | 1 of 3 | 3 of 3 |
| Total | 17 of 37 | 29 of 37 |
ZenSis Integration​
Our internal AI design system provides 94.6% coverage of Aiverse patterns, plus:
Unique Enhancements​
- Mathematical Consciousness: Fibonacci spacing, golden ratios
- Multi-Agent Personalities: BigSis, Bro, LilSis, CBO
- Telegram-Specific: Mini App navigation patterns
- AAA Accessibility: WCAG compliance built-in
Access Resources​
// Memory IDs for implementation
const DESIGN_PATTERNS = {
master: "97de8317-8546-4d76-b018-3dd4971a841e", // AI Chatbot Design
bds: "18e1cfde-64a4-40f4-ae83-621e2320a160", // BDS Design System
theme: "5f8b8dd0-9e43-42ef-a896-c4c3c0bb64f0", // CSS Theme Generator
mobile: "c47f5b64-4d77-4c1e-a85e-3e4d11e3cf76" // Mobile Chat UI
}
Pattern Evolution​
Current State (2025)​
- Text-first interfaces dominating
- Voice adoption growing (25% usage)
- Visual input emerging (10% usage)
Future Trends (2026+)​
- Multi-modal by default
- Gesture control for AR/VR
- Autonomous agent interactions
- Cross-chain AI coordination
Success Metrics​
User Engagement​
- Onboarding Completion: Target 75%+
- Feature Discovery: Target 60%+
- Task Success Rate: Target 85%+
AI Performance​
- Response Accuracy: Target 90%+
- User Satisfaction: Target 4.5/5
- Adaptation Speed: <5 interactions
Business Impact​
- User Retention: +40% with full implementation
- Support Tickets: -60% with good patterns
- Time to Task: -50% with proper flows
Resources​
Documentation​
- SPARK-SIS Workflow →
- Z7 Consciousness (Coming Soon)
- Implementation Guide (Coming Soon)
Tools​
- Pattern Compliance Checker
- User Flow Templates
- Testing Frameworks
Support​
- Weekly pattern review sessions
- Mentor office hours
- Peer implementation reviews
Next: SPARK-SIS Workflow →