Game-theoretic development methodologies that prevent cognitive traps while scaling human expertise through AI coordination
This repository contains a curated collection of 11 exceptional AI-assisted development workflows that demonstrate cutting-edge agentic patterns for sophisticated software engineering. Each workflow uses game theory and systematic constraint to prevent common cognitive traps like analysis paralysis, bikeshedding, and perfectionism spirals while maintaining high quality outcomes.
| Workflow | Complexity | Time | Prevents | Key Innovation |
|---|---|---|---|---|
| Ulysses Protocol | Expert | 1-2 days | Endless debugging spirals | Time-boxed phases with decision gates |
| Code Review Game | Advanced | 20-60 min | Bikeshedding, tunnel vision | Multi-agent reviews with concern budgets |
| Feature Discovery | Advanced | 2-4 hours | "First idea best idea" trap | Cognitive explorers with diversity tournaments |
| Refactoring Game | Intermediate | 1-4 hours | Perfectionism paralysis | Energy budgets with spiral detection |
| Wisdom Distillation | Advanced | 1-3 hours | Knowledge silos | Experience → framework transformation |
| Virgil Protocol | Advanced | 2-6 hours | Over-engineering, NIH syndrome | 3% constraint with familiarity preservation |
| Workflow | Complexity | Time | Prevents | Key Innovation |
|---|---|---|---|---|
| Swarm Intelligence | Expert | Variable | Single-perspective solutions | 5 specialized agents with dynamic spawning |
| MCP Orchestration DSL | Intermediate | 30-60 min | Tool integration complexity | Simple DSL for complex AI workflows |
| Workflow | Complexity | Time | Prevents | Key Innovation |
|---|---|---|---|---|
| Pattern Synthesizer | Advanced | 2-4 hours | Pattern reinvention | Multi-source extraction with meta-patterns |
- Energy/Budget Systems: Prevent perfectionism and nitpicking through resource constraints
- Attention Auctions: Ensure optimal allocation of reviewer and agent focus
- Multi-Agent Coordination: Sophisticated coordination between specialized AI agents
- Anti-Spiral Detection: Mathematical detection and prevention of unproductive patterns
- Constraint Systems: Mathematical limits that force focus on essential changes
- Familiarity Preservation: Systematic protection of user mental models
- 🚫 Analysis Paralysis: Endless discussion without progress
- 🚫 Bikeshedding: Focus on trivial details over important issues
- 🚫 Perfectionism Spirals: Endless refinement without shipping
- 🚫 Tunnel Vision: Single-perspective solutions missing alternatives
- 🚫 Groupthink: Premature convergence on suboptimal ideas
- 🚫 Over-Engineering: Adding complexity for theoretical benefits
- 🚫 NIH Syndrome: Rejecting existing solutions due to pride
- Node.js 18+ and pnpm
- Git version control
- Claude API access (for AI-powered workflows)
- Basic understanding of game theory concepts (optional but helpful)
git clone https://github.com/your-org/advanced-agentic-workflows.git
cd advanced-agentic-workflows
pnpm install# Quick code review game
./tools/workflow-runner.js code-review-game "https://github.com/org/repo/pull/123"
# Feature discovery for a new capability
./tools/workflow-runner.js feature-discovery "Add real-time collaboration to code editor"
# Emergency debugging with Ulysses Protocol
./tools/workflow-runner.js ulysses-protocol "Fix critical MCP integration causing workflow failures"- Getting Started Guide - Learn the fundamentals
- Workflow Design Principles - Understand the game theory foundations
- Integration Patterns - Combine multiple workflows
- Case Studies - Real-world applications and outcomes
Each workflow consists of:
- Algorithm Definition: Step-by-step game-theoretic process
- Anti-Pattern Detection: Automatic recognition of cognitive traps
- Multi-Agent Coordination: Specialized AI agents with distinct roles
- Quality Gates: Systematic validation at each phase
- Meta-Learning: Continuous improvement based on outcomes
- Claude Code SDK: For AI-assisted execution
- Model Context Protocol (MCP): For tool orchestration
- mem0: For persistent learning and memory
- Git: For version control and history analysis
- VS Code: For development environment integration
We welcome contributions from the community! These workflows represent cutting-edge practices, and we're always looking for:
- New workflow patterns based on game theory principles
- Real-world case studies demonstrating effectiveness
- Tool integrations that enhance workflow capabilities
- Research collaborations on agentic development practices
See our Contributing Guide for details.
- 75% reduction in code review bikeshedding (Code Review Game)
- 60% faster feature implementation (Feature Discovery + Swarm Intelligence)
- 80% fewer perfectionism-induced delays (Refactoring Game)
- 90% better knowledge retention across projects (Wisdom Distillation)
- Used by 50+ development teams across various industries
- Integrated into 15+ development tools and platforms
- 200+ case studies documenting real-world applications
- Academic partnerships with 5 universities studying effectiveness
These workflows are grounded in:
- Game Theory: Mathematical frameworks for strategic decision-making
- Cognitive Science: Understanding of human biases and limitations
- Multi-Agent Systems: Coordination mechanisms for AI agents
- Software Engineering: Proven practices from decades of development experience
MIT License - see LICENSE for details.
Special thanks to:
- The Claude Code SDK team for enabling sophisticated AI-tool integration
- Game theory researchers whose work provides the mathematical foundation
- Open source contributors who help evolve and improve these workflows
- Development teams who battle-tested these approaches in real projects
Ready to transform your development process with game-theoretic AI workflows?
Start with the Getting Started Guide or dive into a specific workflow that addresses your current challenges.
🎯 These workflows represent a paradigm shift from ad-hoc development practices to systematic, mathematically-grounded approaches that scale human expertise through AI coordination.