As a developer who recently canceled my Cursor subscription, I've discovered that combining free APIs with custom prompts and rules can actually provide a better experience than the paid version. Here's how you can optimize your Cursor AI setup without spending a dime.
Leveraging Free LLM APIs
OpenRouter now offers three powerful free APIs that are competing with top-tier models:
meta-llama/llama-3.1-405b-instruct
meta-llama/llama-3.2-90b-vision-instruct
meta-llama/llama-3.1-70b-instruct
What's particularly impressive is that the llama-3.1-405b-instruct model ranks just below Claude 3.5 Sonnet and GPT-4 in Human Eval testing, making it a highly competitive option for development work.
Optimizing Cursor Settings
Custom AI Rules
To enhance Cursor's performance, you can implement the following settings under Settings > Rules for AI
:
DO NOT GIVE ME HIGH LEVEL SHIT, IF I ASK FOR FIX OR EXPLANATION, I WANT ACTUAL CODE OR EXPLANATION!!! I DON'T WANT "Here's how you can blablabla"
- Be casual unless otherwise specified
- Be terse
- Suggest solutions that I didn't think about—anticipate my needs
- Treat me as an expert
- Be accurate and thorough
- Give the answer immediately. Provide detailed explanations after
- Value good arguments over authorities
- Consider new technologies and contrarian ideas
- You may use high levels of speculation or prediction, just flag it
- No moral lectures
- Discuss safety only when crucial and non-obvious
- Provide closest acceptable response for content policy issues
- Cite sources at the end, not inline
- No need to mention knowledge cutoff or AI disclosure
- Respect prettier preferences for code
- Split responses when needed
Project-Specific Configuration
Create a .cursorrules
file in your project root to define specialized behavior. This is particularly useful for deep learning and AI development projects. The configuration should include:
Expertise Definition: Specify the AI's role as an expert in relevant technologies
Development Principles: Define coding standards and best practices
Framework-Specific Guidelines: Include rules for PyTorch, Transformers, Diffusers, etc.
Performance Optimization: Specify GPU utilization and training practices
Error Handling: Define debugging and logging preferences
Enhanced Code Documentation
For better code documentation, create an add-comments.md
file in your project root with guidelines for AI-assisted commenting. Key aspects to include:
Analysis requirements for code structure
Comment formatting preferences
Focus on explaining the "why" and "how"
Guidelines for documentation depth
Preservation of code formatting
Benefits of This Setup
Cost Efficiency: Access to powerful AI models without subscription fees
Customization: Tailored responses that match your development style
Improved Output: More direct, practical assistance without unnecessary explanation
Professional Focus: Treatment as an expert with advanced solutions
Framework-Specific Expertise: Specialized knowledge for AI/ML development
Conclusion
By implementing these configurations, you can create a more efficient and powerful development environment with Cursor AI, potentially surpassing the functionality of the paid version. The combination of free APIs and custom configurations provides a robust solution for developers working with modern AI tools and frameworks.
Remember that all these optimizations are completely free, making it an attractive option for developers looking to maximize their AI-assisted development workflow without additional costs.