Update prompting/maximize-token-efficiency.mdx

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

Author: Gerome-Elassaad

prompting/maximize-token-efficiency.mdx

@@ -128,73 +128,71 @@ When you just want to talk and plan (not write code), use discussion mode:
   **Use Git**: Save your work with Git instead of asking AI to undo things. It's free!
 </Callout>
 
-## Model Selection Strategies
+## Choosing the Right AI Model
 
-### Choose Appropriate Models
+### Pick the Right Model for the Job
 
-Different AI models have different strengths and token costs:
+Different AI models cost different amounts:
 
-- **Use smaller models** for simple tasks, drafting, and initial development
-- **Reserve larger models** for complex reasoning, code review, and final polishing
-- **Consider model context limits** when working with large codebases
-- **Balance cost vs. capability** based on your current development phase
+- **Cheaper models** for simple tasks and quick questions
+- **Expensive models** for hard problems and important code
+- **Check limits** - some models can't handle huge projects
+- **Balance cost and quality** based on what you're doing
 
-### Provider-Specific Optimization
+### Different AI Models
 
-**Anthropic Claude:**
+**Claude (Anthropic):**
 
-- Excellent for reasoning and code generation
-- Higher token costs but superior code quality
-- Best for complex development tasks
+- Great at understanding and writing code
+- Costs more but gives better results
+- Use for complex projects
 
-**OpenAI GPT:**
+**GPT (OpenAI):**
 
-- Fast and cost-effective for many tasks
-- Good for quick iterations and prototyping
-- Consider GPT-4 for complex reasoning tasks
+- Fast and cheaper for many tasks
+- Good for trying things out quickly
+- Use GPT-4 for harder problems
 
-**Other Providers:**
+**Other Models:**
 
-- Evaluate based on specific use cases
-- Consider regional availability and data privacy requirements
-- Compare pricing and performance for your workload
+- Check what they're good at
+- Some work better in certain countries
+- Compare prices for what you need
 
-## Advanced Optimization Techniques
+## Advanced Tips
 
-### Context Management
+### Focus Your Requests
 
-**File-Specific Requests:**
+**Be specific about files:**
 
-- Reference specific files instead of asking about "the entire codebase"
-- Use imports and dependencies to provide necessary context
-- Focus on individual components rather than full applications
+- Name the exact files you're working on
+- Don't ask about "the whole project"
+- Focus on one part at a time
 
-**Progressive Development:**
+**Build gradually:**
 
-- Build core functionality first, then add features incrementally
-- Test each component thoroughly before moving to the next
-- Use modular architecture to keep context windows manageable
+- Start with the main features
+- Test each piece before adding more
+- Keep your code organized in small pieces
 
-### Performance Monitoring
+### Watch Your Usage
 
-**Track Your Usage:**
+**Track what you use:**
 
-- Monitor token consumption across different tasks
-- Identify patterns in high-token activities
-- Adjust your approach based on usage analytics
+- See which tasks use the most tokens
+- Notice patterns in what costs more
+- Change your approach based on what you learn
 
-**Optimize Workflows:**
+**Work smarter:**
 
-- Combine related changes into single requests
-- Use batch operations when possible
-- Plan complex changes to minimize back-and-forth communication
+- Combine related requests into one
+- Do multiple things at once when possible
+- Plan ahead to avoid going back and forth
 
 <Callout type="info">
-  **Token Awareness**: Understanding token consumption helps you work more efficiently and control costs. Focus on
-  quality over quantity in your interactions.
+  **Be Aware**: Understanding tokens helps you save money. Focus on asking good questions, not lots of questions.
 </Callout>
 
 <Callout type="tip">
-  **Continuous Learning**: As you work more with AI models, you'll develop intuition for which approaches are most
-  token-efficient for different types of tasks.
+  **Learn as You Go**: The more you use AI, the better you'll get at knowing which approach saves the most tokens.
 </Callout>