Competitive Multi-Agent Code Generation
High-assurance workflow for critical features using multi-agent competitive generation, independent evaluation, and evidence-based synthesis to produce superior solutions.
Overview
Competitive Multi-Agent Code Generation
High-assurance workflow for critical features using multi-agent competitive generation, independent evaluation, and evidence-based synthesis to produce superior solutions.
For simple features that don't require competitive exploration, use Feature Development workflow.
When to Use
- Quality-critical implementations - Authentication, payment processing, data validation
- Novel or ambiguous requirements - No clear "right answer", multiple valid approaches
- High-stakes architectural decisions - API design, schema design, core algorithms
- Avoiding local optima - When single-agent reflection might miss better approaches
When NOT to Use
- Simple, well-defined tasks with obvious solutions
- Time-sensitive changes where speed matters more than exploration
- Trivial bug fixes or typos
- Tasks with only one viable approach
Plugins Needed
Workflow
How It Works
PHASE 1: COMPETITIVE GENERATION
┌─────────────────────────────────────────────────────────────────────────────────┐
│ Task ───┬─ Agent 1 → Draft → Self-Critique → Revise → Solution A ─┐ │
│ ├─ Agent 2 → Draft → Self-Critique → Revise → Solution B ─┼─┐ │
│ └─ Agent 3 → Draft → Self-Critique → Revise → Solution C ─┘ │ │
└─────────────────────────────────────────────────────────────────────────────────┘
│
▼
PHASE 2: MULTI-JUDGE EVALUATION
┌─────────────────────────────────────────────────────────────────────────────────┐
│ ┌─ Judge 1 → Evaluate → Verify → Report A ─┐ │
│ ├─ Judge 2 → Evaluate → Verify → Report B ─┼─ Consensus Analysis │
│ └─ Judge 3 → Evaluate → Verify → Report C ─┘ │
└─────────────────────────────────────────────────────────────────────────────────┘
│
▼
PHASE 3: ADAPTIVE STRATEGY
┌─────────────────────────────────────────────────────────────────────────────────┐
│ Clear Winner? → SELECT_AND_POLISH │
│ All Flawed? → REDESIGN (restart Phase 1) │
│ Split Vote? → FULL_SYNTHESIS │
└─────────────────────────────────────────────────────────────────────────────────┘
│
▼
QUALITY GATES
┌─────────────────────────────────────────────────────────────────────────────────┐
│ Write Tests → Review Changes → Create Commit │
└─────────────────────────────────────────────────────────────────────────────────┘
1. Competitive Implementation
Use /do-competitively to generate multiple solutions, evaluate them independently, and synthesize the best elements.
/do-competitively "Implement JWT authentication middleware with token refresh, rate limiting, and secure session management"
What happens:
- 3 agents independently design and implement solutions with self-critique
- 3 judges evaluate each solution using structured rubrics with verification
- Adaptive strategy selects: polish the winner, redesign if all flawed, or synthesize best elements
For specific output location:
/do-competitively "Design user authentication schema" --output "src/models/auth.ts"
With custom evaluation criteria:
/do-competitively "Create API rate limiting middleware" --criteria "security,performance,maintainability"
After completion, review the synthesized solution to ensure it meets your requirements.
2. Write Tests
Use /write-tests to generate comprehensive test coverage for the synthesized solution.
/write-tests
Or with specific focus:
/write-tests Focus on security edge cases and error handling
Verify all tests pass before continuing.
3. Review Local Changes
Use /review-local-changes for final multi-agent validation.
/review-local-changes
Address Critical and High priority findings before committing.
4. Create Commit
Use /commit to create a well-formatted conventional commit.
/commit
Quality Comparison
| Aspect | Feature Development | Reliable Engineering |
|---|---|---|
| Agents | 1 (with self-reflection) | 3 generators + 3 judges |
| Exploration | Single path | Multiple competing approaches |
| Issue Detection | 40-60% (self-critique) | 70-85% (competitive + judges) |
| Cost | Lower | 4-6x higher |
| Time | Faster | Slower |
| Best For | Simple, clear tasks | Critical, ambiguous tasks |
Advanced: Combining with Tree of Thoughts
For tasks requiring exploration before commitment, use /tree-of-thoughts first:
# Explore approaches first
/tree-of-thoughts "Design caching strategy for high-traffic API"
# Then implement the winning approach competitively
/do-competitively "Implement Redis-based caching with the write-through pattern identified above"
Advanced: Debate-Based Evaluation
For highest-stakes decisions where consensus is critical:
# Implement competitively
/do-competitively "Design payment processing flow" --output "src/services/payment.ts"
# Evaluate with iterative debate
/judge-with-debate --solution "src/services/payment.ts" --task "Payment processing implementation" --criteria "security:30,correctness:30,reliability:20,performance:20"
Tips
- Reserve for critical work - The 4-6x cost overhead is only justified for high-stakes implementations
- Specify criteria - Custom evaluation criteria improve judge alignment with your priorities
- Review synthesis - Always validate the final synthesized solution makes coherent sense
- Iterate if needed - If REDESIGN strategy triggers, provide more context on second attempt
- Use for learning - Competitive execution reveals trade-offs between approaches
Theoretical Foundation
This workflow combines research-backed techniques:
| Technique | Source | Benefit |
|---|---|---|
| Constitutional AI Self-Critique | Bai et al., 2022 | 40-60% issue reduction before review |
| Chain of Verification | Dhuliawala et al., 2023 | Reduces judge bias |
| Multi-Agent Debate | Du et al., 2023 | Diverse perspectives improve reasoning |
| Self-Consistency | Wang et al., 2022 | Multiple paths improve reliability |