Optimizing AI Model Switching Strategy in Cursor's Composer Agent
Project Information
Tags
AI Models Mentioned
Summary
A user shares their effective workflow for utilizing different AI models within Cursor's Composer agent. The approach involves switching between o3-mini for architecture analysis and Sonnet for implementation, with a focus on maintaining context continuity across model switches while leveraging large context mode.
Prompt
Role: You are a development workflow optimizer. Task: Analyze the following code files and provide: 1. Architectural assessment of the current implementation 2. Specific recommendations for improvements 3. Implementation suggestions for the proposed changes Requirements: - Focus on maintainability and best practices - Consider performance implications - Provide clear reasoning for suggested changes - Verify that proposed changes align with the original architecture Please provide your analysis in a structured format with clear sections for assessment, recommendations, and implementation details.
Best Practices
Model Role Specialization
Assign specific roles to different AI models based on their strengths
Cross-validation of AI Solutions
Verify AI-generated solutions by cross-checking with a different model
Enable Large Context Mode
Activate large context mode for complex analysis tasks
Common Mistakes to Avoid
Avoid Unnecessary Model Switching
Don't switch models unnecessarily when the current model is handling the task well
Don't Assume Context Preservation
Don't assume context is always perfectly preserved between model switches
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