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TENSOR MODULE IMPROVEMENTS: Enhanced pedagogical quality and systems thinking Key Enhancements: ✅ Fixed module reference numbers (Module 05 Autograd, Module 02 Activations) ✅ Updated export instructions (tito module complete 01) ✅ Added comprehensive systems analysis sections: - Memory efficiency at production scale (7B parameter models) - Broadcasting in transformer architectures - Gradient compatibility and computational graphs Deep Systems Insights Added: 🧠 Memory optimization strategies for large language models 🧠 Transformer broadcasting patterns and attention mechanisms 🧠 Gradient flow architecture and autograd preparation 🧠 Production connections to PyTorch/TensorFlow patterns Educational Improvements: 📚 Enhanced Build → Use → Reflect pedagogical framework 📚 Concrete production examples (GPT-3 memory requirements) 📚 Clear connections between tensor design and ML system constraints 📚 Actionable analysis replacing generic placeholder questions Result: Tensor module now provides deep systems understanding while maintaining strong implementation foundation. All tests pass, ready for student use.