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

@@ -118,31 +118,31 @@ Build a modern e-commerce dashboard using AI code generation with:
   as needed.
 </Callout>
 
-## Best Practices Summary
+## AI prompt engineering best practices summary
 
-### Essential Prompting Principles
+### Essential AI prompting principles for code generation
 
-1. **Clarity First**: Be specific about what you want to build and how it should work
-2. **Technology Specification**: Clearly state your preferred frameworks and libraries
-3. **Context Provision**: Include relevant background information and constraints
-4. **Iterative Approach**: Start simple, then add complexity through follow-up prompts
+1. **Clarity first**: Be specific about what you want to build with AI code generation and how it should work
+2. **Technology specification**: Clearly state your preferred frameworks and libraries for LLM understanding
+3. **Context provision**: Include relevant background information and constraints for better AI results
+4. **Iterative AI approach**: Start simple, then add complexity through follow-up prompts for optimal code generation
 
-### Quality Checklist
+### AI code generation quality checklist
 
-**Before Submitting:**
+**Before submitting AI prompts:**
 
-- ✅ Goal is clearly defined
-- ✅ Technology stack is specified
-- ✅ Key features are listed
-- ✅ User requirements are outlined
-- ✅ Success criteria are defined
+- ✅ Goal is clearly defined for LLM understanding
+- ✅ Technology stack is specified for AI code generation
+- ✅ Key features are listed for comprehensive AI development
+- ✅ User requirements are outlined for accurate LLM results
+- ✅ Success criteria are defined for measurable AI outcomes
 
-**During Development:**
+**During AI-powered development:**
 
-- 🔄 Provide feedback on generated code
-- 🔄 Request specific modifications
-- 🔄 Ask for explanations when needed
-- 🔄 Use discussion mode for planning
+- 🔄 Provide feedback on AI-generated code for improvement
+- 🔄 Request specific modifications from LLM for refinement
+- 🔄 Ask for AI explanations when needed for understanding
+- 🔄 Use AI discussion mode for architecture planning
 
 ### Common Success Patterns