Task: Create a Global Unique Identifier Generator (GSID)
Purpose: Explore different strategies for AI-assisted development
Original Project: metarhia/metautil/tree/gsid-ai
This project demonstrates three different approaches to AI-assisted development by implementing a Global Unique Identifier (GSID) generator. Each approach represents a different strategy for working with AI tools, from basic prompting to structured technical specifications.
- 1-Prompt/ - Short prompt in vibe coding style
- 2-Chat-steps/ - Step-by-step chat with AI in vibe coding style
- 3-Tech-specs/ - Technical specification implementation
- benchmark.js - Performance comparison tool
- README.md - This file
Basic vibe coding without deep understanding of the task or development process.
Characteristics:
- Minimal task description
- Limited understanding of AI-generated code quality
- Basic implementation without optimization
- Focus on quick results rather than best practices
Human Developer Time: ~5-10 minutes
- Task Definition: 2 minutes (basic prompt)
- Code Review: none
- Testing: 3 minutes (basic validation)
Iterative vibe coding with desire for improvement but limited technical depth.
Characteristics:
- Interactive development process
- Attempts to improve implementation
- Limited understanding of code quality and optimization
- Focus on incremental improvements
Human Developer Time: ~20-30 minutes
- Initial Task: 5 minutes
- Code Review & Refactoring: 5 minutes (SRP violations, unnecessary methods)
- Architecture Decisions: 5 minutes (class structure, method removal)
- Testing & Validation: 5 minutes (comprehensive testing)
Professional development workflow with AI as a regular team member.
Characteristics:
- Detailed technical specifications
- Clear requirements and constraints
- Focus on performance, security, and best practices
Human Developer Time: ~2-3 hours
- Requirements Analysis: 30 minutes (detailed specifications)
- Technical Design: 45 minutes (performance targets)
- Implementation Planning: 30 minutes (optimization strategies)
- Testing Strategy: 20 minutes
- Performance Analysis: 30 minutes
| Approach | Time | Quality | Performance | Method | Cost |
|---|---|---|---|---|---|
| Short Prompt | ~5 min | Basic | 1.02M IDs/sec | Basic AI prompt | $5-10 |
| Step-by-Step Chat | ~20 min | Good | 1.00M IDs/sec | Iterative AI development | $10-20 |
| Technical Specification | ~2 hours | Excellent | 4.65M IDs/sec | Detailed AI specifications | $150-250 |
| Expert Traditional | ~18 min | Excellent | 5M+ IDs/sec | Optimized implementation | $25-50 |
Key Insights:
- Technical specification requires 24x more time but produces 4.6x better performance
- Step-by-step chat provides 4x time investment for moderate quality improvement
- Short prompt is fastest but produces lowest quality results
- Time investment directly correlates with code quality and performance
Based on comprehensive benchmarking, the implementations show significant differences:
| Implementation | Performance | Memory Usage | Size | Entropy |
|---|---|---|---|---|
| Tech-specs | 4.65M IDs/sec | 57MB | 24 chars | 0.177 bits/char |
| UUID v4 | 1.93M IDs/sec | 341MB | 36 chars | 0.103 bits/char |
| Chat-steps | 1.00M IDs/sec | 69MB | 27 chars | 0.152 bits/char |
| Prompt | 1.02M IDs/sec | 71MB | 27 chars | 0.141 bits/char |
Key Findings: Tech-specs approach produces the most efficient implementation - 2.4x faster and 6x more memory efficient than UUID v4.
- Cursor: claude-4-sonnet, claude-3.5-sonnet, gpt-4.1, o3, gemini-2.5-pro
- VS Code with Copilot: gpt-4.1, claude-4-sonnet, gemini-2.5
- ChatGPT: gpt-4o, o4-mini-high, gpt-4.1, gpt-4.5
- Clone the repository:
git clone <repository-url> - Open folder:
cd CodeWithAI - Install dependencies:
npm i - Run tests:
npm t - Run benchmark:
node benchmark.js
- Technical specifications produce the most efficient and maintainable code with AI
- Iterative development can improve results a little but requires technical expertise
- Basic prompting often leads to functional but suboptimal implementations
This project is part of the original metarhia/metautil repository and follows its licensing terms.