diegosouzapw Multi-AI Code Review Collaboration Framework
A systematic approach to getting diverse AI perspectives on code, then synthesizing insights into actionable improvements.
When to Use This
- Complex codebases where blind spots are likely
- Production/live trading code where reliability is critical
- Architecture decisions with trade-offs
- When you want to validate Claude's recommendations
- Before major refactoring or deployment
The Process
Phase 1: Initial Review (Claude)
- Claude reviews code and documents findings
- Creates context prompt for external AI
- Identifies platform-specific constraints external AI must understand
Phase 2: External AI Review
- User pastes prompt to external AI (Gemini, DeepSeek, GPT, etc.)
- External AI provides structured review
- User brings response back to Claude
Phase 3: Synthesis & Debate
- Claude evaluates external AI's points
- Categorizes into: Valid, Partially Valid, Invalid
- Explains reasoning for each categorization
- Creates response prompt for user to continue dialogue
Phase 4: Consensus
- Continue rounds until agreement reached
- Document final action plan
- Prioritize fixes by risk and effort
Prompt Templates
Template A: Initial External AI Request
**[AI NAME] CODE REVIEW REQUEST - [PROJECT TYPE]**
I need a comprehensive code review. This code [CRITICAL CONTEXT - e.g., "runs on live funded accounts"]. Please review thoroughly and respond in a format I can share with another AI for collaborative discussion.
---
## CRITICAL PLATFORM CONTEXT (Read First)
[List platform-specific constraints that might not be obvious]
[List what IS and ISN'T possible on this platform]
[Explain why certain "standard" patterns don't apply]
---
## REVIEW SCOPE
Please analyze:
1. **Logic & Correctness** - [specific concerns]
2. **Risk Management** - [specific concerns]
3. **Performance** - [specific concerns]
4. **Reliability** - [specific concerns]
5. **Code Quality** - [specific concerns]
6. **Scalability** - [planned expansion, multi-instance needs, performance at scale]
7. **Future Updateability** - [extension points, configuration extensibility, technical debt, breaking change risks]
---
## FUTURE ROADMAP (if applicable)
[Describe planned features, scaling needs, and future requirements so the reviewer can assess how well the current architecture supports them]
---
## THE CODE
[Include full code or key sections]
---
## RESPONSE FORMAT
Structure your response as:
**[AI NAME] CODE REVIEW - ROUND 1**
## 🔴 CRITICAL ISSUES (Must Fix)
## 🟡 IMPORTANT CONCERNS (Should Fix)
## 🟢 MINOR SUGGESTIONS (Nice to Have)
## ✅ WELL IMPLEMENTED
## 🔮 SCALABILITY ASSESSMENT
## 🔧 FUTURE UPDATEABILITY ASSESSMENT
## â“ QUESTIONS / CLARIFICATIONS NEEDED
## 📋 PRIORITIZED ACTION PLAN
---
## EXISTING FINDINGS (if any)
[Include prior AI findings so new AI can confirm/challenge]
Template B: Response to External AI
**CLAUDE'S RESPONSE TO [AI NAME] - ROUND [N]**
## ✅ FULL AGREEMENT
[Points we agree on completely]
## 🤠CONCESSIONS & MODIFICATIONS
[Points where Claude adjusts position with explanation]
## ðŸ›¡ï¸ POINTS I STILL MAINTAIN
[Disagreements with detailed reasoning]
## 🔠NEW OBSERVATIONS
[Anything new Claude notices based on discussion]
## 📋 UPDATED ACTION PLAN
[Current consensus on what to fix]
## 🤠CLOSING QUESTION
[Ask if they agree or have remaining concerns]
Template C: Final Consensus Summary
## MULTI-AI REVIEW CONSENSUS
**Participants:** [List AIs involved]
**Code Reviewed:** [File/project name]
**Date:** [Date]
### AGREED FIXES (In Priority Order)
| # | Issue | Fix | Effort | Risk |
|---|-------|-----|--------|------|
| 1 | [Issue] | [Solution] | [Low/Med/High] | [Low/Med/High] |
### EXPLICITLY REJECTED SUGGESTIONS
| Suggestion | Rejected Because |
|------------|------------------|
| [Suggestion] | [Platform constraint / Not applicable / etc.] |
### VERIFIED AS CORRECT
- [Item 1 that was reviewed and confirmed good]
- [Item 2]
### OPEN QUESTIONS FOR FUTURE
- [Any unresolved items to revisit later]
Best Practices
- Always provide platform context - External AIs apply generic patterns without knowing constraints
- Be specific about what CAN'T be done - Prevents suggestions for impossible approaches
- Request structured responses - Makes synthesis easier
- Track rounds - Label each exchange for clarity
- Document consensus - Final agreement should be explicit
- Implement incrementally - Test each fix before moving to next
Reference Files
references/prompt-templates.md- Copy-paste ready templatesreferences/platform-contexts.md- Pre-written context blocks for common platformsreferences/synthesis-checklist.md- How to evaluate external AI suggestions