feat: Add consistent 'Where This Code Lives' template across modules

- Add template section to tensor, layers, activations, and cnn modules
- Create docs/development/module-template.md for future reference
- Clarify learning vs building structure consistently
- Show students where their code will live in the final package
- Decouple learning modules from production organization

docs/development/module-template.md

@@ -0,0 +1,55 @@
+# Module Template: "Where This Code Lives" Section
+
+## 📦 Where This Code Lives in the Final Package
+
+**Learning Side:** You work in `modules/{module_name}/{module_name}_dev.py`  
+**Building Side:** Code exports to `tinytorch.core.{destination}`
+
+```python
+# Final package structure:
+from tinytorch.core.{destination} import {exported_classes}
+from tinytorch.core.tensor import Tensor
+```
+
+**Why this matters:**
+- **Learning:** Focused modules for deep understanding
+- **Production:** Proper organization like industry frameworks
+- **Consistency:** Related functionality grouped together
+
+## Template Variables
+
+Replace these placeholders in each module:
+
+- `{module_name}`: The module directory name (e.g., "tensor", "layers", "cnn")
+- `{destination}`: Where the code exports in the final package (e.g., "tensor", "layers", "activations")
+- `{exported_classes}`: The main classes/functions being exported (e.g., "Tensor", "Dense, Conv2D", "ReLU, Sigmoid")
+
+## Examples
+
+### Tensor Module
+```python
+# Learning Side: modules/tensor/tensor_dev.py
+# Building Side: tinytorch.core.tensor
+from tinytorch.core.tensor import Tensor
+```
+
+### Layers Module  
+```python
+# Learning Side: modules/layers/layers_dev.py
+# Building Side: tinytorch.core.layers
+from tinytorch.core.layers import Dense, Conv2D
+```
+
+### CNN Module
+```python
+# Learning Side: modules/cnn/cnn_dev.py
+# Building Side: tinytorch.core.layers (Conv2D lives with Dense)
+from tinytorch.core.layers import Dense, Conv2D
+```
+
+## Usage Instructions
+
+1. Copy this template section into each module's `*_dev.py` file
+2. Replace the template variables with module-specific values
+3. Update the `#| default_exp` directive to match the destination
+4. Ensure the exported classes match what's actually being exported 

modules/activations/activations_dev.py

@@ -41,6 +41,23 @@ Linear → Activation → Linear = Can learn complex patterns!
 
 Each function serves different purposes and has different mathematical properties.
 
+## 📦 Where This Code Lives in the Final Package
+
+**Learning Side:** You work in `modules/activations/activations_dev.py`  
+**Building Side:** Code exports to `tinytorch.core.activations`
+
+```python
+# Final package structure:
+from tinytorch.core.activations import ReLU, Sigmoid, Tanh
+from tinytorch.core.tensor import Tensor
+from tinytorch.core.layers import Dense, Conv2D
+```
+
+**Why this matters:**
+- **Learning:** Focused modules for deep understanding
+- **Production:** Proper organization like PyTorch's `torch.nn.functional`
+- **Consistency:** All activation functions live together in `core.activations`
+
 ---
 
 Let's start building! 🚀

modules/cnn/cnn_dev.py

@@ -22,6 +22,26 @@ Welcome to the CNN module! Here you'll implement the core building block of mode
 - (Stretch) Explore stride, padding, pooling, and multi-channel input
 """
 
+# %% [markdown]
+"""
+## 📦 Where This Code Lives in the Final Package
+
+**Learning Side:** You work in `modules/cnn/cnn_dev.py`  
+**Building Side:** Code exports to `tinytorch.core.layers`
+
+```python
+# Final package structure:
+from tinytorch.core.layers import Dense, Conv2D  # Both layers together!
+from tinytorch.core.activations import ReLU
+from tinytorch.core.tensor import Tensor
+```
+
+**Why this matters:**
+- **Learning:** Focused modules for deep understanding
+- **Production:** Proper organization like PyTorch's `torch.nn`
+- **Consistency:** All layers (Dense, Conv2D) live together in `core.layers`
+"""
+
 # %%
 #| default_exp core.cnn
 

modules/layers/layers_dev.py

@@ -30,13 +30,26 @@ Welcome to the Layers module! This is where neural networks begin. You'll implem
 This module builds on the **activations** module:
 - **activations** → **layers** → **networks**
 - Clean separation of concerns: math functions → layer building blocks → full networks
+"""
 
-## Module → Package Structure
-**🎓 Teaching vs. 🔧 Building**: 
-- **Learning side**: Work in `modules/layers/layers_dev.py`  
-- **Building side**: Exports to `tinytorch/core/layers.py`
+# %% [markdown]
+"""
+## 📦 Where This Code Lives in the Final Package
 
-This module builds the fundamental transformations that compose into neural networks.
+**Learning Side:** You work in `modules/layers/layers_dev.py`  
+**Building Side:** Code exports to `tinytorch.core.layers`
+
+```python
+# Final package structure:
+from tinytorch.core.layers import Dense, Conv2D  # All layers together!
+from tinytorch.core.activations import ReLU, Sigmoid, Tanh
+from tinytorch.core.tensor import Tensor
+```
+
+**Why this matters:**
+- **Learning:** Focused modules for deep understanding
+- **Production:** Proper organization like PyTorch's `torch.nn`
+- **Consistency:** All layers (Dense, Conv2D) live together in `core.layers`
 """
 
 # %%

modules/tensor/tensor_dev.py

@@ -20,12 +20,27 @@ Welcome to the Tensor module! This is where TinyTorch really begins. You'll impl
 - Handle shape management, data types, and memory layout
 - Build the foundation for neural networks and automatic differentiation
 
-## Module → Package Structure
-**🎓 Teaching vs. 🔧 Building**: 
-- **Learning side**: Work in `modules/tensor/tensor_dev.py`  
-- **Building side**: Exports to `tinytorch/core/tensor.py`
+"""
 
-This module builds the core data structure that all other TinyTorch components will use.
+# %% [markdown]
+"""
+## 📦 Where This Code Lives in the Final Package
+
+**Learning Side:** You work in `modules/tensor/tensor_dev.py`  
+**Building Side:** Code exports to `tinytorch.core.tensor`
+
+```python
+# Final package structure:
+from tinytorch.core.tensor import Tensor
+from tinytorch.core.layers import Dense, Conv2D
+from tinytorch.core.activations import ReLU, Sigmoid, Tanh
+```
+
+**Why this matters:**
+- **Learning:** Focused modules for deep understanding
+- **Production:** Proper organization like PyTorch's `torch.tensor`
+- **Consistency:** Core data structure lives in `core.tensor`
+"""
 """
 
 # %%