ai-hedge-fundVibe Coding GuideVibecoding Handbook

Vibecoding Development Handbook

🎯 What You Can Build (User-Focused Ideas)

🚀 Quick Wins

  • Test Investment Legends - Compare Warren Buffett vs Michael Burry on your favorite stocks
  • Create Strategy Combos - Mix growth + value approaches for balanced portfolios
  • Backtest Market Crashes - See how different strategies performed in 2008, 2020
  • Build Sector-Specific Strategies - Tech-focused with Cathie Wood + risk management

🔥 Power User Projects

  • Your Personal Investment Style - Create an AI agent that thinks like you
  • Market Timing Strategies - Combine technical analysis with fundamental insights
  • Risk-Adjusted Portfolios - Build conservative strategies for different risk levels
  • Multi-Timeframe Analysis - Short-term momentum + long-term value combinations

🎨 Creative Applications

  • Investment Education Tool - Show students how different approaches work
  • Strategy Competitions - Compare multiple approaches on the same dataset
  • What-If Scenarios - “What if Buffett focused on tech stocks?”
  • Custom Risk Models - Build strategies for specific market conditions

💡 Advanced Customizations

  • New Investment Philosophies - Add Ray Dalio, Joel Greenblatt, or your own approach
  • Alternative Data Sources - Integrate ESG scores, social sentiment, macro indicators
  • Custom Performance Metrics - Beyond Sharpe ratio - add your own success measures
  • Interactive Dashboards - Build real-time strategy monitoring interfaces

📋 Complete Case Study: Adding a New Investment Agent

Task: Create a “Ray Dalio” Diversification-Focused Agent

What Ray Dalio is known for: All-weather portfolio strategy, risk parity, diversification across asset classes and economic environments.

Task Description

We’ll create an AI agent that embodies Ray Dalio’s investment philosophy, focusing on:

  • Risk parity (equal risk contribution from different assets)
  • Economic cycle awareness (growth/inflation scenarios)
  • Diversification across uncorrelated assets
  • Conservative leverage when appropriate

Complete LLM Prompt

Prompt
"Help me create a Ray Dalio investment agent for the AI Hedge Fund project.
 
CONTEXT: I'm working on the AI Hedge Fund project. The system has 18 existing agents like Warren Buffett, Michael Burry, etc. I want to add Ray Dalio's "All Weather" philosophy.
 
TASK: Create src/agents/ray_dalio.py following the existing agent pattern.
 
RAY DALIO'S APPROACH:
- Risk parity: Equal risk contribution from different positions
- Economic scenarios: Consider growth/inflation environments  
- Diversification: Prefer uncorrelated assets
- Volatility analysis: Focus on risk-adjusted returns
- Conservative: Avoid concentration risk
 
REQUIREMENTS:
1. Copy the structure from src/agents/warren_buffett.py
2. Create RayDalioSignal class with signal/confidence/reasoning
3. Implement ray_dalio_agent() function
4. Add quantitative analysis focusing on:
   - Portfolio correlation analysis
   - Volatility metrics
   - Risk-adjusted returns (Sharpe ratio focus)
   - Economic sensitivity indicators
5. Create LLM prompt that thinks like Dalio
6. Update any necessary imports and data models
 
ANALYSIS LOGIC SHOULD INCLUDE:
- analyze_risk_parity(): Calculate risk contribution of positions
- analyze_correlation(): Check correlation with existing holdings  
- analyze_volatility(): Assess price stability
- analyze_economic_sensitivity(): Check inflation/growth sensitivity
 
PROMPT PERSONALITY: Conservative, risk-focused, emphasizes diversification and "not putting all eggs in one basket."
 
Please provide the complete ray_dalio.py file following the project's patterns."

Task Checklist

✅ Phase 1: Code Structure

  • Copy src/agents/warren_buffett.py as template
  • Rename class to RayDalioSignal
  • Rename main function to ray_dalio_agent()
  • Update imports and agent_id references

✅ Phase 2: Quantitative Analysis

  • Implement analyze_risk_parity() - calculate position risk contributions
  • Implement analyze_correlation() - check asset correlation matrix
  • Implement analyze_volatility() - assess price stability metrics
  • Implement analyze_economic_sensitivity() - inflation/growth indicators
  • Update data fetching to include volatility and correlation data

✅ Phase 3: LLM Integration

  • Create Ray Dalio personality prompt (conservative, diversification-focused)
  • Update reasoning template to emphasize risk management
  • Test prompt generates appropriate Dalio-style language
  • Ensure signal logic aligns with “All Weather” philosophy

✅ Phase 4: System Integration

  • Add new agent to frontend node mappings
  • Update backend agent registry
  • Test agent runs without errors in CLI
  • Test agent appears in web interface
  • Verify agent integrates with existing risk management

✅ Phase 5: Testing & Validation

  • Run agent on test stocks (AAPL, SPY, TLT for diversification)
  • Compare results with existing agents
  • Verify reasoning reflects Dalio’s philosophy
  • Test in complete strategy workflow
  • Document any special configuration needed

Success Criteria

  • ✅ Agent analyzes stocks with focus on risk and diversification
  • ✅ Reasoning sounds like Ray Dalio’s investment philosophy
  • ✅ Integrates seamlessly with existing system
  • ✅ Provides unique value compared to existing agents
  • ✅ Works in both CLI and web interface

Common Issues & Solutions

Issue: “ModuleNotFoundError for new agent” Solution: Ensure proper imports and add to __init__.py files

Issue: “Agent not appearing in web interface”
Solution: Update frontend node mappings in app/frontend/src/data/

Issue: “LLM prompt too generic” Solution: Add more specific Dalio quotes and philosophy in prompt template

Issue: “Analysis too similar to existing agents” Solution: Focus on unique metrics like risk parity and correlation analysis

System ArchitectureOverview