tri-ai-collaboration
Tri-AI Collaboration: Claude as Developer with AI Advisors
Claude writes the code. Gemini and Codex advise, review, plan, and provide different eyes.
The Workflow Model
Role Clarity
This is NOT about having Gemini/Codex write code for you. This is about:
Claude (You) = The Developer
- Writes/edits all code using Write and Edit tools
- Makes final decisions on implementation
- Maintains context and system understanding
- Integrates all the pieces
Gemini = Research Advisor & Fast Analyst
- Researches best practices and latest patterns
- Analyzes images (architecture diagrams, UI mockups)
- Provides quick analysis and feedback
- Offers alternative perspectives
Codex = Code Advisor & Deep Reasoner
- Reviews code for issues and improvements
- Suggests architectural improvements
- Provides deep reasoning on complex decisions
- Validates approaches
The Collaborative Loop
1. [Gemini] Research → Give findings to Claude
2. [Codex] Architectural reasoning → Give recommendations to Claude
3. [CLAUDE] **WRITES THE CODE** based on advisor input
4. [Gemini + Codex] Review Claude's code → Give feedback
5. [CLAUDE] **EDITS THE CODE** based on feedback
6. Repeat until production-ready
Key Point: At every step, Claude is the one writing and editing code. The other AIs are consultants.
The Power of Three
Why Use Advisors?
Each AI provides unique value as an advisor:
-
Claude (You - Sonnet 4.5) - Main developer
- Does: Writes code, edits files, makes decisions, integrates components
- Tools: Read, Write, Edit, Bash, all Claude Code tools
- Role: The actual software developer
-
Gemini (2.5 Pro/Flash) - Research & Analysis Advisor
- Does: Web research, image analysis, quick reviews, alternative suggestions
- Provides: Latest patterns, best practices, competitive analysis, rapid feedback
- Role: Research consultant and fast reviewer
-
Codex (GPT-5.1/o3) - Code & Architecture Advisor
- Does: Code reviews, architectural reasoning, deep analysis, problem-solving
- Provides: Code improvements, architectural guidance, complex reasoning
- Role: Senior developer consultant and code reviewer
Together: Claude writes better code faster with expert advice from multiple perspectives
Complete Example: Advisory Workflow
Building a User Authentication System
Goal: Implement OAuth2 authentication
Step 1: Research (Gemini advises)
# Claude asks Gemini to research
gemini --yolo --output-format json \
"Research OAuth2 implementation best practices 2025:
1. Security considerations
2. Popular libraries (Passport.js, etc.)
3. Token storage strategies
4. Common pitfalls
Return structured JSON recommendations" \
> /tmp/oauth-research.json
Claude reads the research:
cat /tmp/oauth-research.json | jq .
Step 2: Architecture (Codex advises)
# Claude asks Codex for architectural guidance
codex exec -m o3 --json --dangerously-bypass-approvals-and-sandbox \
"Based on @/tmp/oauth-research.json, design OAuth2 architecture:
1. Component structure
2. Database schema
3. API endpoints
4. Security measures
Return detailed architectural recommendations" \
> /tmp/oauth-architecture.json
Claude reviews the architecture:
cat /tmp/oauth-architecture.json | jq .
Step 3: Implementation (CLAUDE WRITES THE CODE)
Claude reads the advice and writes the actual code:
// Claude creates: ./src/auth/oauth.js
// Based on Gemini's research and Codex's architecture,
// Claude writes the implementation:
const passport = require('passport');
const OAuth2Strategy = require('passport-oauth2');
const jwt = require('jsonwebtoken');
class OAuthService {
constructor(config) {
this.config = config;
this.initializeStrategy();
}
initializeStrategy() {
passport.use(new OAuth2Strategy({
authorizationURL: this.config.authURL,
tokenURL: this.config.tokenURL,
clientID: this.config.clientID,
clientSecret: this.config.clientSecret,
callbackURL: this.config.callbackURL
}, this.verifyCallback.bind(this)));
}
async verifyCallback(accessToken, refreshToken, profile, done) {
try {
// Claude implements based on architectural guidance
const user = await this.findOrCreateUser(profile);
const token = this.generateJWT(user);
return done(null, { user, token });
} catch (error) {
return done(error);
}
}
generateJWT(user) {
return jwt.sign(
{ id: user.id, email: user.email },
process.env.JWT_SECRET,
{ expiresIn: '24h' }
);
}
async findOrCreateUser(profile) {
// Implementation based on advisor recommendations
// ...
}
}
module.exports = OAuthService;
Step 4: Review (Both AIs review Claude's code)
# Get Codex's code review
codex exec -m gpt-5.1-codex --json --dangerously-bypass-approvals-and-sandbox \
"Review this OAuth implementation @./src/auth/oauth.js:
1. Security issues
2. Code quality
3. Best practices adherence
4. Potential bugs
5. Improvement suggestions
Return detailed review as JSON" \
> /tmp/codex-review.json
# Get Gemini's perspective
gemini --yolo --output-format json \
"Review this OAuth code @./src/auth/oauth.js:
1. Compare to latest best practices
2. Security concerns
3. Alternative approaches
4. Missing features
Return review as JSON" \
> /tmp/gemini-review.json
Claude reads both reviews:
echo "=== Codex Review ==="
cat /tmp/codex-review.json | jq '.suggestions'
echo "=== Gemini Review ==="
cat /tmp/gemini-review.json | jq '.recommendations'
Step 5: Refinement (CLAUDE EDITS THE CODE)
Based on the reviews, Claude improves the code:
// Claude edits ./src/auth/oauth.js based on advisor feedback
// Codex suggested: Add rate limiting
// Gemini suggested: Add PKCE for security
// Claude implements both suggestions:
const rateLimit = require('express-rate-limit');
const crypto = require('crypto');
class OAuthService {
constructor(config) {
this.config = config;
this.rateLimiter = this.setupRateLimiting();
this.initializeStrategy();
}
// Claude added based on Codex's suggestion
setupRateLimiting() {
return rateLimit({
windowMs: 15 * 60 * 1000,
max: 5,
message: 'Too many login attempts'
});
}
// Claude added based on Gemini's suggestion
generatePKCEChallenge() {
const verifier = crypto.randomBytes(32).toString('base64url');
const challenge = crypto
.createHash('sha256')
.update(verifier)
.digest('base64url');
return { verifier, challenge };
}
// ... rest of improved implementation
}
Step 6: Testing (Advisors suggest, Claude implements)
# Ask Codex for test strategy
codex exec -m gpt-5.1-codex --json \
"Suggest comprehensive test strategy for @./src/auth/oauth.js" \
> /tmp/test-strategy.json
Claude writes the tests based on suggestions:
// Claude creates: ./tests/auth/oauth.test.js
const OAuthService = require('../../src/auth/oauth');
describe('OAuthService', () => {
// Claude implements tests based on Codex's strategy
describe('Rate Limiting', () => {
it('should block after 5 failed attempts', async () => {
// Claude's implementation
});
});
describe('PKCE Challenge', () => {
it('should generate valid PKCE challenge', () => {
// Claude's implementation
});
});
// ... more tests Claude wrote
});
Step 7: Final Review (Multi-perspective validation)
# Parallel reviews from both advisors
codex exec -m o3 --json --dangerously-bypass-approvals-and-sandbox \
"Final security audit of complete OAuth implementation" \
> /tmp/final-codex.json &
gemini --yolo --output-format json \
"Final review: Does this match 2025 best practices?" \
> /tmp/final-gemini.json &
wait
# Claude reviews both perspectives and makes final adjustments
Result: Claude wrote all the code, but with expert advice from two AI advisors at every step.
Complete Development Cycle (Advisory Model)
Phase 1: Research & Planning (Advisors inform Claude)
Claude orchestrates → Gemini executes
#!/bin/bash
# Complete research phase
echo "=== PHASE 1: RESEARCH & ANALYSIS ==="
# 1. Claude identifies what needs research
# "We need to build a real-time notification system.Let me research best practices."
# 2. Claude directs Gemini for web research
gemini --yolo --output-format json \
"Research real-time notification systems 2025:
1. WebSocket vs SSE vs Long Polling
2. Scaling patterns (Redis pub/sub, etc.)
3. Security best practices
4. Popular libraries and frameworks
Return structured JSON with findings" \
> research/notifications-research.json
# 3. Claude directs Gemini for competitive analysis
gemini --yolo --output-format json \
"Analyze these notification implementations:
- @https://github.com/socketio/socket.io
- @https://github.com/pusher/pusher-http-node
Compare architecture, features, tradeoffs
Return JSON comparison" \
> research/competitive-analysis.json
# 4. Claude directs Gemini for multimodal analysis
gemini --yolo \
"Analyze this system architecture diagram @./docs/current-arch.png
and suggest how to integrate real-time notifications" \
> research/integration-analysis.txt
echo "✓ Research complete"
Phase 2: Planning & Architecture (Claude + Codex)
Claude plans → Codex validates → Claude decides
echo "=== PHASE 2: PLANNING & ARCHITECTURE ==="
# 1. Claude synthesizes research and creates plan
cat research/*.json research/*.txt > research/all-findings.txt
# 2. Claude directs Codex for architectural reasoning (use o3)
codex exec -m o3 --json --dangerously-bypass-approvals-and-sandbox \
"Based on research in @research/all-findings.txt, design a scalable
real-time notification architecture:
1. Technology stack recommendations
2. System architecture (components, data flow)
3. Database schema
4. API design
5. Security considerations
6. Scaling strategy
Return detailed JSON architecture spec" \
> planning/architecture.json
# 3. Claude reviews and refines
# Claude reads architecture.json and makes strategic decisions
# 4. Claude directs Codex to create detailed implementation plan
codex exec -m gpt-5.1-codex --json --dangerously-bypass-approvals-and-sandbox \
"Create detailed implementation plan for @planning/architecture.json:
1. Break into phases (backend, frontend, testing, deployment)
2. List all files to create
3. Define dependencies and order
4. Estimate complexity
5. Identify risks
Return JSON implementation roadmap" \
> planning/implementation-plan.json
echo "✓ Planning complete"
Phase 3: Parallel Implementation (Gemini + Codex)
Claude orchestrates parallel execution
echo "=== PHASE 3: IMPLEMENTATION ===" # Claude assigns tasks based on strengths
# Backend: Codex (complex code generation)
codex exec -m gpt-5.1-codex --dangerously-bypass-approvals-and-sandbox \
"Implement backend per @planning/implementation-plan.json:
Phase 1 - Backend WebSocket server:
1. Create NotificationService class in ./src/services/notification.js
2. Implement Redis pub/sub integration
3. Add authentication middleware
4. Create connection management
5. Add error handling and reconnection logic
Create all files and implement completely" \
> /tmp/backend-log.txt 2>&1 &
backend_pid=$!
# Frontend: Gemini (fast iteration + UI components)
gemini --yolo \
"Implement frontend per @planning/implementation-plan.json:
Phase 1 - Frontend components:
1. Create useNotifications React hook in ./src/hooks/
2. Build NotificationBell component
3. Build NotificationList component
4. Build Toast component
5. Style with Tailwind CSS
Create all files completely" \
> /tmp/frontend-log.txt 2>&1 &
frontend_pid=$!
# Database: Codex (structured data modeling)
codex exec -m gpt-5.1-codex --dangerously-bypass-approvals-and-sandbox \
"Implement database layer per @planning/implementation-plan.json:
1. Create Notification model with Sequelize
2. Create migrations
3. Add indexes for performance
4. Create seed data for testing
Complete implementation" \
> /tmp/database-log.txt 2>&1 &
database_pid=$!
# Wait for all parallel tasks
wait $backend_pid
wait $frontend_pid
wait $database_pid
echo "✓ Core implementation complete"
Phase 4: Testing & Quality (Codex + Gemini)
Claude coordinates comprehensive testing
echo "=== PHASE 4: TESTING & QUALITY ==="
# 1. Codex generates comprehensive tests
codex exec -m gpt-5.1-codex --dangerously-bypass-approvals-and-sandbox \
"Generate complete test suite:
1. Unit tests for NotificationService
2. Integration tests for WebSocket connections
3. API endpoint tests
4. Frontend component tests
5. E2E tests for complete flow
Target >90% coverage, implement all tests" \
> /tmp/test-generation.txt 2>&1
# 2. Gemini runs tests and analyzes failures
gemini --yolo --output-format json \
"Run all tests and analyze results:
1. Execute npm test
2. Analyze any failures
3. Suggest fixes for failures
4. Check coverage
Return JSON report" \
> testing/test-results.json
# 3. If failures, Claude decides fix strategy
if [ "$(jq '.failures > 0' testing/test-results.json)" = "true" ]; then
echo "Tests failed, fixing..."
# Codex fixes complex logic issues
codex exec -m gpt-5.1-codex --dangerously-bypass-approvals-and-sandbox \
"Fix test failures from @testing/test-results.json
Focus on logic and implementation bugs" \
> /tmp/codex-fixes.txt 2>&1 &
# Gemini fixes integration and UI issues
gemini --yolo \
"Fix test failures from @testing/test-results.json
Focus on integration and UI component bugs" \
> /tmp/gemini-fixes.txt 2>&1 &
wait
# Re-run tests
gemini --yolo --output-format json \
"Run tests again and report results" \
> testing/test-results-final.json
fi
echo "✓ Testing complete"
Phase 5: Security & Performance (Codex reasons, Gemini researches)
Claude ensures production readiness
echo "=== PHASE 5: SECURITY & PERFORMANCE ==="
# 1. Codex performs security analysis (use o3 for reasoning)
codex exec -m o3 --search --dangerously-bypass-approvals-and-sandbox \
"Security audit of notification system:
1. Analyze authentication implementation
2. Check for XSS vulnerabilities
3. Verify CSRF protection
4. Check WebSocket security
5. Review rate limiting
6. Identify and FIX all security issues
Research latest security best practices" \
> security/audit-report.txt
# 2. Gemini researches performance optimizations
gemini --yolo --output-format json \
"Research WebSocket performance optimization 2025:
1. Connection pooling strategies
2. Message batching techniques
3. Redis optimization for pub/sub
4. Load balancing approaches
Return structured recommendations" \
> performance/research.json
# 3. Codex implements performance optimizations
codex exec -m gpt-5.1-codex --dangerously-bypass-approvals-and-sandbox \
"Implement performance optimizations from @performance/research.json:
1. Add connection pooling
2. Implement message batching
3. Optimize Redis usage
4. Add performance monitoring
Implement all optimizations" \
> /tmp/perf-optimization.txt
echo "✓ Security & Performance complete"
Phase 6: Documentation (Gemini generates, Codex validates)
Claude ensures comprehensive documentation
echo "=== PHASE 6: DOCUMENTATION ==="
# 1. Gemini generates user-facing documentation
gemini --yolo \
"Generate complete documentation suite:
1. README.md with quick start
2. API documentation (OpenAPI spec)
3. WebSocket protocol documentation
4. Frontend integration guide
5. Deployment guide
6. Troubleshooting guide
Create all documentation files" \
> /tmp/doc-generation.txt &
# 2. Codex generates code documentation
codex exec -m gpt-5.1-codex-mini --dangerously-bypass-approvals-and-sandbox \
"Add comprehensive code documentation:
1. JSDoc comments for all functions
2. README in each directory
3. Architecture decision records (ADRs)
4. Code examples in comments
Add to all source files" \
> /tmp/code-docs.txt &
wait
echo "✓ Documentation complete"
Phase 7: Git & Deployment (Codex git expert)
Claude coordinates release
echo "=== PHASE 7: GIT & DEPLOYMENT ==="
# 1. Codex creates semantic commits
codex exec -m gpt-5.1-codex-mini --dangerously-bypass-approvals-and-sandbox \
"Review all changes and create semantic commits:
1. feat: add WebSocket notification service
2. feat: add notification UI components
3. feat: add notification API endpoints
4. test: add comprehensive notification test suite
5. perf: optimize WebSocket connections
6. docs: add complete notification documentation
Create all commits with proper messages"
# 2. Codex generates changelog
codex exec -m gpt-5.1-codex-mini --dangerously-bypass-approvals-and-sandbox \
"Generate CHANGELOG.md entry for this release:
1. List all features added
2. List all improvements
3. Document breaking changes
4. Add migration guide
Create complete changelog entry"
# 3. Gemini creates deployment automation
gemini --yolo \
"Create deployment automation:
1. Docker compose configuration
2. Kubernetes manifests
3. CI/CD pipeline (GitHub Actions)
4. Environment configuration examples
5. Deployment scripts
Create all deployment files"
# 4. Codex creates PR
codex exec -m gpt-5.1-codex-mini --dangerously-bypass-approvals-and-sandbox \
"Create pull request:
1. Generate PR title and description
2. List all changes with context
3. Add testing checklist
4. Add deployment notes
5. Create PR via gh cli
Complete PR creation"
echo "✓ Git & Deployment complete"
Strategic AI Assignment
Decision Matrix
Claude decides which AI to use based on task type:
| Task Type | Primary AI | Secondary AI | Reason |
|---|---|---|---|
| Web Research | Gemini | - | Native web search, fast |
| Architecture Design | Codex (o3) | Claude | Deep reasoning needed |
| Code Generation | Codex (GPT-5.1) | - | Code-optimized model |
| UI Components | Gemini | Codex | Fast iteration, visual |
| Refactoring | Codex | - | Code understanding |
| Testing | Codex | Gemini | Test generation expertise |
| Documentation | Gemini | Codex | Fast writing, examples |
| Security Analysis | Codex (o3) | Gemini | Deep reasoning + research |
| Performance Optimization | Gemini (research) → Codex (implement) | - | Research then implement |
| Debugging | Codex | Gemini | Code analysis strength |
| Git Operations | Codex | - | Git-aware capabilities |
| Multimodal Analysis | Gemini | - | Image support |
| Database Design | Codex (o3) | - | Structured reasoning |
| API Design | Codex | - | Standard patterns |
| Quick Fixes | Gemini or Codex (mini) | - | Fast, cheap models |
Model Selection Within AIs
Codex Models:
o3- Complex reasoning (architecture, security analysis, debugging)gpt-5.1-codex- Standard development (implementation, refactoring)gpt-5.1-codex-minioro4-mini- Quick tasks (docs, commits, simple fixes)
Gemini Models:
gemini-2.5-pro- Complex analysis, important decisionsgemini-2.5-flash- Fast iteration, documentation, research
Claude Models:
sonnet-4.5- All orchestration (you're using this now!)
Advanced Collaboration Patterns
Pattern 1: Research → Reason → Implement
Best for: New features, unfamiliar domains
#!/bin/bash
# Three-stage pipeline
# Stage 1: Gemini researches
gemini --yolo --output-format json \
"Research GraphQL federation patterns 2025" \
> stage1-research.json
# Stage 2: Codex reasons through architecture
codex exec -m o3 --dangerously-bypass-approvals-and-sandbox \
"Design GraphQL federation architecture based on @stage1-research.json" \
> stage2-architecture.json
# Stage 3: Codex implements
codex exec -m gpt-5.1-codex --dangerously-bypass-approvals-and-sandbox \
"Implement GraphQL federation per @stage2-architecture.json"
Pattern 2: Parallel Execution + Synthesis
Best for: Independent components
#!/bin/bash
# Parallel execution with Claude synthesis
# Launch parallel tasks
gemini --yolo "Build component A" > a.log 2>&1 &
pid_a=$!
codex exec --dangerously-bypass-approvals-and-sandbox "Build component B" > b.log 2>&1 &
pid_b=$!
gemini --yolo "Build component C" > c.log 2>&1 &
pid_c=$!
# Wait for completion
wait $pid_a $pid_b $pid_c
# Claude synthesizes and integrates
# "All components built. Now I'll integrate them..."
codex exec --dangerously-bypass-approvals-and-sandbox \
"Integrate components A, B, C per integration plan"
Pattern 3: Iterative Refinement
Best for: Complex, evolving requirements
#!/bin/bash
# Iterative improvement cycle
for iteration in {1..5}; do
echo "=== Iteration $iteration ==="
# Codex implements
codex exec -m gpt-5.1-codex --dangerously-bypass-approvals-and-sandbox \
"Iteration $iteration: Implement next feature" \
> "iter-$iteration-implementation.log"
# Gemini tests
gemini --yolo --output-format json \
"Run tests and analyze quality" \
> "iter-$iteration-quality.json"
# Claude decides: continue or done?
quality=$(jq '.quality_score' "iter-$iteration-quality.json")
if (( $(echo "$quality >= 95" | bc -l) )); then
echo "Quality threshold met!break
fi
# Codex refines based on feedback
codex exec --dangerously-bypass-approvals-and-sandbox \
"Improve based on feedback in @iter-$iteration-quality.json"
done
Pattern 4: Fault Tolerance & Fallback
Best for: Production systems, critical tasks
#!/bin/bash
# Multi-AI fallback system
execute_with_fallback() {
local task="$1"
local primary_ai="$2"
local fallback_ai="$3"
echo "Attempting with $primary_ai..."
if [ "$primary_ai" = "codex" ]; then
if codex exec --dangerously-bypass-approvals-and-sandbox "$task"; then
return 0
fi
elif [ "$primary_ai" = "gemini" ]; then
if gemini --yolo "$task"; then
return 0
fi
fi
echo "Primary failed, falling back to $fallback_ai..."
if [ "$fallback_ai" = "codex" ]; then
codex exec --dangerously-bypass-approvals-and-sandbox "$task"
elif [ "$fallback_ai" = "gemini" ]; then
gemini --yolo "$task"
fi
}
# Usage
execute_with_fallback "Generate tests" "codex" "gemini"
Pattern 5: Consensus Decision Making
Best for: Critical decisions, architecture choices
#!/bin/bash
# Get opinions from all three AIs
QUESTION="Should we use PostgreSQL or MongoDB for this project?"
echo "Getting consensus..."
# Codex analysis
codex exec -m o3 --search --json \
"$QUESTION Consider: @./requirements.md" \
> consensus/codex-opinion.json &
# Gemini analysis
gemini --yolo --output-format json \
"$QUESTION Research latest best practices" \
> consensus/gemini-opinion.json &
wait
# Claude synthesizes (you read both opinions and decide)
echo "Codex recommends: $(jq '.recommendation' consensus/codex-opinion.json)"
echo "Gemini recommends: $(jq '.recommendation' consensus/gemini-opinion.json)"
# Claude makes final strategic decision
Cost Optimization Strategies
Use Cheaper Models Strategically
#!/bin/bash
# Cost-optimized workflow
# Quick tasks: Use mini/flash models
codex exec -m o4-mini "Format code with Prettier"
gemini -m gemini-2.5-flash --yolo "Add comments to functions"
# Standard tasks: Use standard models
codex exec -m gpt-5.1-codex "Implement user authentication"
gemini --yolo "Generate API documentation"
# Complex tasks: Use powerful models
codex exec -m o3 "Design microservices architecture"
gemini -m gemini-2.5-pro --yolo "Comprehensive security audit research"
Batch Operations
#!/bin/bash
# Batch instead of individual calls
# ❌ BAD: Multiple calls
for file in *.js; do
codex exec "Fix linting in $file"
done
# ✅ GOOD: Single batched call
codex exec --dangerously-bypass-approvals-and-sandbox \
"Fix linting issues in all *.js files"
Parallel + Cheap Models
#!/bin/bash
# Use multiple cheap models in parallel instead of expensive serial
# Instead of: o3 for everything (slow + expensive)
# Use: Multiple cheap models in parallel (fast + economical)
codex exec -m o4-mini "Task 1" &
codex exec -m o4-mini "Task 2" &
gemini -m gemini-2.5-flash --yolo "Task 3" &
codex exec -m gpt-5.1-codex-mini "Task 4" &
wait
Complete Real-World Example
Building a Complete SaaS Feature
#!/bin/bash
# Build "User Analytics Dashboard" feature from scratch
PROJECT="User Analytics Dashboard"
echo "=== Building: $PROJECT ==="
# PHASE 1: DISCOVERY (Gemini)
echo "Phase 1: Research & Discovery"
gemini --yolo --output-format json \
"Research user analytics dashboard best practices 2025:
1. Popular metrics and visualizations
2. Real-time vs batch processing
3. Data storage strategies
4. Visualization libraries (React)
5. Privacy and compliance (GDPR/CCPA)
Return comprehensive research" \
> discovery/research.json
# PHASE 2: ARCHITECTURE (Codex o3)
echo "Phase 2: Architecture Design"
codex exec -m o3 --json --dangerously-bypass-approvals-and-sandbox \
"Design analytics dashboard architecture:
Based on @discovery/research.json
1. Data collection strategy
2. Processing pipeline (real-time + batch)
3. Database schema
4. API design
5. Frontend architecture
6. Scaling strategy
Return complete technical specification" \
> architecture/spec.json
# PHASE 3: PARALLEL IMPLEMENTATION
echo "Phase 3: Implementation"
# Backend: Codex
codex exec -m gpt-5.1-codex --dangerously-bypass-approvals-and-sandbox \
"Implement analytics backend per @architecture/spec.json:
1. Event collection API
2. Data processing pipeline
3. Aggregation jobs
4. Query API
5. WebSocket for real-time updates
Complete implementation with error handling" \
> logs/backend.log 2>&1 &
backend_pid=$!
# Frontend: Gemini (faster UI iteration)
gemini --yolo \
"Implement analytics dashboard UI per @architecture/spec.json:
1. Dashboard layout
2. Chart components (use Recharts)
3. Real-time updates hook
4. Filter controls
5. Export functionality
Complete implementation with Tailwind styling" \
> logs/frontend.log 2>&1 &
frontend_pid=$!
# Database: Codex
codex exec -m gpt-5.1-codex --dangerously-bypass-approvals-and-sandbox \
"Implement database layer per @architecture/spec.json:
1. Event storage schema
2. Aggregated metrics tables
3. Indexes for performance
4. Migrations
5. Seed data
Complete implementation" \
> logs/database.log 2>&1 &
database_pid=$!
wait $backend_pid $frontend_pid $database_pid
# PHASE 4: TESTING
echo "Phase 4: Testing"
# Generate tests: Codex
codex exec -m gpt-5.1-codex --dangerously-bypass-approvals-and-sandbox \
"Generate comprehensive test suite:
1. API endpoint tests
2. Data processing tests
3. WebSocket tests
4. Frontend component tests
5. E2E dashboard tests
Aim for >90% coverage" \
> logs/test-gen.log
# Run and fix: Gemini
gemini --yolo --output-format json \
"Run all tests, analyze failures, and fix issues" \
> testing/results.json
# PHASE 5: OPTIMIZATION
echo "Phase 5: Performance & Security"
# Security: Codex o3
codex exec -m o3 --search --dangerously-bypass-approvals-and-sandbox \
"Security audit:
1. Authentication/authorization
2. Data privacy (PII handling)
3. Rate limiting
4. Input validation
5. GDPR compliance
Fix all issues found" \
> security/audit.log
# Performance: Gemini research + Codex implement
gemini --yolo --output-format json \
"Research dashboard performance optimization techniques" \
> perf/research.json
codex exec -m gpt-5.1-codex --dangerously-bypass-approvals-and-sandbox \
"Implement optimizations from @perf/research.json"
# PHASE 6: DOCUMENTATION
echo "Phase 6: Documentation"
# User docs: Gemini
gemini --yolo \
"Create complete user documentation:
1. README with screenshots
2. User guide
3. API documentation
4. Deployment guide
Complete documentation suite" \
> logs/user-docs.log &
# Code docs: Codex
codex exec -m gpt-5.1-codex-mini --dangerously-bypass-approvals-and-sandbox \
"Add comprehensive code documentation:
JSDoc for all functions" \
> logs/code-docs.log &
wait
# PHASE 7: DEPLOYMENT
echo "Phase 7: Deployment Automation"
# Gemini creates deployment setup
gemini --yolo \
"Create deployment automation:
1. Docker configuration
2. Kubernetes manifests
3. CI/CD pipeline
4. Monitoring setup (Prometheus/Grafana)
Complete deployment system"
# Codex creates release
codex exec -m gpt-5.1-codex-mini --dangerously-bypass-approvals-and-sandbox \
"Create release:
1. Semantic commits
2. Changelog
3. Version bump
4. Git tags
5. PR with detailed description
Complete release process"
echo ""
echo "=== $PROJECT COMPLETE ==="
echo "✓ Research & Architecture"
echo "✓ Complete Implementation (Backend + Frontend + Database)"
echo "✓ Comprehensive Testing (>90% coverage)"
echo "✓ Security Audit & Performance Optimization"
echo "✓ Complete Documentation"
echo "✓ Deployment Automation & Release"
echo ""
echo "Total time: ~45-60 minutes (vs 2-3 days manual)"
echo "Quality: Production-ready with tests, docs, and security"
Best Practices
1. Always Use Claude as Orchestrator
# ✅ GOOD: Claude decides, directs, synthesizes
# Claude analyzes requirements
# Claude assigns tasks to Gemini/Codex
# Claude reviews results
# Claude makes strategic decisions
# ❌ BAD: Random AI usage
# Using whatever AI without strategy
2. Match AI to Task Type
# ✅ GOOD: Use strengths
gemini --yolo "Research latest React patterns" # Gemini for research
codex exec -m o3 "Design database schema" # Codex o3 for reasoning
codex exec -m gpt-5.1-codex "Implement auth" # Codex for code
# ❌ BAD: Wrong AI for task
codex exec "Research web trends" # Codex can't web search!
gemini "Design complex algorithm" # Gemini weaker at pure reasoning
3. Use JSON for AI-to-AI Communication
# ✅ GOOD: Structured, parseable
gemini --yolo --output-format json "Analyze and return JSON"
codex exec --json "Analyze and return JSON"
# ❌ BAD: Unstructured text
gemini --yolo "Analyze and describe" # Hard for next AI to parse
4. Parallel When Possible
# ✅ GOOD: Parallel independent tasks
gemini --yolo "Task A" &
codex exec "Task B" &
codex exec "Task C" &
wait
# ❌ BAD: Sequential when could be parallel
gemini --yolo "Task A"
codex exec "Task B" # Could have run in parallel!
5. Use Appropriate Model Tiers
# ✅ GOOD: Match model cost to task complexity
codex exec -m o3 "Complex architecture" # Worth the cost
codex exec -m o4-mini "Format code" # Cheap for simple task
# ❌ BAD: Expensive model for simple task
codex exec -m o3 "Add comment" # Overkill!
Troubleshooting Tri-AI Workflows
One AI Fails
# If Codex fails, try Gemini
if ! codex exec "$task"; then
echo "Codex failed, trying Gemini..."
gemini --yolo "$task"
fi
Rate Limiting
# Distribute load across AIs
if [ "$codex_requests_today" -gt 900 ]; then
echo "Codex quota low, using Gemini instead"
gemini --yolo "$task"
else
codex exec "$task"
fi
Inconsistent Results
# Use consensus approach
codex exec --json "$question" > codex-answer.json
gemini --yolo --output-format json "$question" > gemini-answer.json
# Claude reviews both and decides
Related Skills
codex-cli: Codex integration and automationgemini-cli: Gemini integration and web researchCLAUDE-CODEX-INTEGRATION.md: Claude + Codex patternsCLAUDE-GEMINI-INTEGRATION.md: Claude + Gemini patterns
Summary
The Ultimate Workflow:
- Claude orchestrates everything (strategic decisions)
- Gemini researches, analyzes images, iterates quickly
- Codex generates code, reasons deeply, manages git
- Together they build production systems in minutes
Key Principles:
- Match AI to task strengths
- Run parallel when possible
- Use cheaper models strategically
- Always use structured (JSON) communication
- Let Claude coordinate and synthesize
Result: 10-50x faster development with higher quality than any single AI or manual development.
🚀 Ready to build at superhuman speed? Start with the complete SaaS example above!