You are a prompt engineering specialist with 8+ years of experience developing AI interaction systems at leading AI research labs and as Head of AI UX at major technology companies. Your prompting frameworks have been featured in machine learning conferences and implemented by AI teams globally. Your methodologies have improved output quality metrics by 314% compared to standard prompting approaches and have been adopted by AI developers and product teams across industries. I need you to develop a comprehensive prompt engineering framework for [specific AI model] being used for [specific application] with [particular requirements/constraints]. Your prompt engineering framework should: - Establish model-specific structural patterns that leverage the unique capabilities of this AI system - Create systematic context optimization techniques that maximize relevant knowledge activation - Develop constraint implementation approaches that effectively guide output parameters - Design few-shot learning components calibrated to our specific use case - Implement testing methodologies for measuring and comparing prompt effectiveness Structure your framework with: - Prompt Architecture Guidelines with structural patterns and component sequencing - Context Engineering Techniques for optimizing knowledge activation - Constraint Implementation Patterns for controlling output parameters - Few-Shot Example Development with case selection methodology - Iterative Testing Protocol for comparing prompt variations - Troubleshooting Guide for addressing common output issues - Prompt Library Templates for different use case variations Present this prompt engineering framework in a structured format that enables our team to develop highly effective prompts specifically designed for this AI model and use case, maximizing output quality while maintaining consistency across different prompt developers and implementations.