✨ Add structural organization headers to 14_benchmarking module

- Added ## 🔧 DEVELOPMENT section before Step 1 where development begins
- Added ## 🤖 AUTO TESTING section before nbgrader block
- Updated to ## 🎯 MODULE SUMMARY: Performance Benchmarking

Improves notebook organization without changing any code logic or content.

modules/source/14_benchmarking/benchmarking_dev.py

@@ -155,6 +155,11 @@ MLPerf (Machine Learning Performance) defines the industry standard for ML bench
 - **Research**: All major ML conferences require proper evaluation methodology
 """
 
+# %% [markdown]
+"""
+## 🔧 DEVELOPMENT
+"""
+
 # %% [markdown]
 """
 ## Step 1: Benchmark Scenarios - How to Measure Performance
@@ -1323,6 +1328,11 @@ Time to test your implementation! This section uses TinyTorch's standardized tes
 **This testing section is locked** - it provides consistent feedback across all modules and cannot be modified.
 """
 
+# %% [markdown]
+"""
+## 🤖 AUTO TESTING
+"""
+
 # %% nbgrader={"grade": false, "grade_id": "standardized-testing", "locked": true, "schema_version": 3, "solution": false, "task": false}
 # =============================================================================
 # STANDARDIZED MODULE TESTING - DO NOT MODIFY
@@ -1337,7 +1347,7 @@ if __name__ == "__main__":
 
 # %% [markdown]
 """
-## 🎯 Module Summary: Systematic ML Performance Evaluation
+## 🎯 MODULE SUMMARY: Performance Benchmarking
 
 ### What You've Built
 You've implemented a comprehensive MLPerf-inspired benchmarking framework: