Update prompting/prompt-engineering-guide.mdx

Co-Authored-By: mintlify[bot] <109931778+mintlify[bot]@users.noreply.github.com>

Author: Gerome-Elassaad

prompting/prompt-engineering-guide.mdx

@@ -58,39 +58,39 @@ Build a modern e-commerce dashboard using AI code generation with:
 - Include authentication requirements
 - Define data validation approach (Zod, Joi)
 
-## Advanced Prompting Techniques
+## Advanced AI prompting techniques for code generation
 
-### Contextual Information
+### Contextual information for better LLM results
 
-**Provide Relevant Context:**
+**Provide relevant context for AI code generation:**
 
-- Include existing code snippets when relevant
-- Reference specific files or components
-- Mention current technology constraints
-- Specify performance requirements
+- Include existing code snippets when relevant for AI understanding
+- Reference specific files or components for LLM context
+- Mention current technology constraints for AI-powered development
+- Specify performance requirements for optimized code generation
 
-**Progressive Refinement:**
+**Progressive refinement with AI prompting:**
 
-- Start with high-level requirements
-- Add implementation details iteratively
-- Use follow-up prompts for clarification
-- Build upon previous responses
+- Start with high-level requirements for AI planning
+- Add implementation details iteratively for better LLM results
+- Use follow-up prompts for AI clarification
+- Build upon previous AI responses for iterative development
 
-### Model-Specific Optimization
+### LLM-specific optimization for AI coding
 
-**Claude/Gemini Models:**
+**Claude/Gemini AI models:**
 
-- Provide comprehensive context upfront
-- Use structured formats (numbered lists, sections)
-- Include examples and edge cases
-- Specify output format preferences
+- Provide comprehensive context upfront for better AI code generation
+- Use structured formats (numbered lists, sections) for LLM understanding
+- Include examples and edge cases for robust AI development
+- Specify output format preferences for consistent code generation
 
-**GPT Models:**
+**GPT AI models:**
 
-- Break complex requests into smaller parts
-- Use clear, direct language
-- Provide concrete examples
-- Specify desired output structure
+- Break complex requests into smaller parts for better LLM processing
+- Use clear, direct language for optimal AI code generation
+- Provide concrete examples for accurate LLM understanding
+- Specify desired output structure for consistent AI results
 
 ### Error Prevention