Update CLI references and virtual environment activation

- Replace all 'python bin/tito.py' references with correct 'tito' commands
- Update command structure to use proper subcommands (tito system info, tito module test, etc.)
- Add virtual environment activation to all workflows
- Update Makefile to use correct tito commands with .venv activation
- Update activation script to use correct tito path and command examples
- Add Tiny🔥Torch branding to activation script header
- Update documentation to reflect correct CLI usage patterns

.cursor/rules/module-development-best-practices.mdc

@@ -314,11 +314,14 @@ class TestCompleteMLSystem:
 ### Running Tests (ALWAYS THROUGH PYTEST)
 
 ```bash
+# Activate environment first
+source bin/activate-tinytorch.sh
+
 # Test specific module (recommended)
-python bin/tito.py test --module networks
+tito test --module networks
 
 # Test all modules
-python bin/tito.py test --all
+tito test --all
 
 # Run specific test file directly with pytest
 python -m pytest modules/source/04_networks/tests/test_networks.py -v

.cursor/rules/tinytorch-project-structure.mdc

@@ -1,6 +1,3 @@
----
-description: A guide to the project structure of the TinyTorch ML framework.
----
 
 # TinyTorch Project Structure Guide
 
@@ -28,9 +25,12 @@ This is an educational ML Systems course repository organized into progressive m
 - [tinytorch/datasets/](mdc:tinytorch/datasets/) - Data loading utilities
 - [tinytorch/configs/](mdc:tinytorch/configs/) - Configuration management
 
-### Development Tools
-- [bin/tito.py](mdc:bin/tito.py) - Main CLI tool for sync, test, and build operations
-- [bin/activate-tinytorch.sh](mdc:bin/activate-tinytorch.sh) - Environment activation script
+## Core Infrastructure
+
+- [bin/tito](mdc:bin/tito) - Main CLI tool for sync, test, and build operations
+- [bin/activate-tinytorch.sh](mdc:bin/activate-tinytorch.sh) - Virtual environment activation script
+- [tito/](mdc:tito/) - CLI implementation with modular command structure
+- [Makefile](mdc:Makefile) - Build automation and development shortcuts
 
 ## Module Structure Pattern
 
@@ -46,10 +46,9 @@ modules/{module_name}/
 
 ## Development Workflow
 
-1. **Write**: Edit `modules/{module}/module_dev.py` with `#| export` directives
-2. **Sync**: Run `python bin/tito.py sync --module {module}` 
-3. **Test**: Run `python bin/tito.py test --module {module}`
-4. **Build**: Code exports to `tinytorch/core/{component}.py`
+1. **Activate environment**: `source bin/activate-tinytorch.sh`
+2. **Sync**: Run `tito module export --module {module}`
+3. **Test**: Run `tito module test --module {module}`
 
 The `#| default_exp` directive controls where code exports to in the package.
  
@@ -59,5 +58,7 @@ The `#| default_exp` directive controls where code exports to in the package.
  
 
 
+The `#| default_exp` directive controls where code exports to in the package.
+ 
 The `#| default_exp` directive controls where code exports to in the package.
  

.cursor/rules/user-preferences.mdc

@@ -1,7 +1,3 @@
----
-description: User preferences and development conventions for TinyTorch, including module naming patterns, commit frequency, testing standards, and NBDev integration workflow.
-alwaysApply: false
----
 
 
 # User Preferences and Conventions
@@ -13,6 +9,7 @@ alwaysApply: false
 - **README focus**: Keep main project README focused on overarching goals, not module details
 - **Component terminology**: Call code components 'modules' instead of 'parts'
 - **Testing framework**: Always use pytest for all tests - no manual testing or other frameworks
+- **Brand formatting**: In headers and titles, use "Tiny🔥Torch" (with flame emoji after "Tiny"), not "🔥TinyTorch". In regular text, "TinyTorch" is acceptable
 
 ## Educational Workflow
 
@@ -38,11 +35,8 @@ alwaysApply: false
 - **pytest only**: All tests must use pytest framework with proper test classes
 - **Comprehensive coverage**: Tests should cover functionality, edge cases, and integration
 - **Professional structure**: Use test classes, fixtures, and descriptive test names
-- **CLI integration**: Tests must be compatible with `python bin/tito.py test --module {name}`
-
-These preferences ensure consistency across the TinyTorch educational framework and smooth development workflow.
- 
-- **Package structure**: Code exports from `modules/` to `tinytorch/` package
+- **CLI integration**: Tests must be compatible with `tito module test --module {name}` (requires virtual environment activation)
+- **Environment setup**: Always activate virtual environment with `source bin/activate-tinytorch.sh` before running commands
 
 These preferences ensure consistency across the TinyTorch educational framework and smooth development workflow.
  

Makefile

@@ -36,22 +36,22 @@ install:
 # Export notebooks to Python package
 sync:
 	@echo "🔄 Exporting notebooks to Python package..."
-	python bin/tito.py sync
+	@source .venv/bin/activate && python3 bin/tito export --all
 
 # Run all tests
 test:
 	@echo "🧪 Running all tests..."
-	python bin/tito.py test --all
+	@source .venv/bin/activate && python3 bin/tito module test --all
 
 # Run setup module tests specifically
 test-setup:
 	@echo "🧪 Running setup module tests..."
-	python bin/tito.py test --module setup
+	@source .venv/bin/activate && python3 bin/tito module test --module setup
 
 # Clean notebook outputs and Python cache
 clean:
 	@echo "🧹 Cleaning notebook outputs and cache..."
-	python bin/tito.py nbdev --clean
+	@source .venv/bin/activate && python3 bin/tito module clean
 	find . -type d -name "__pycache__" -exec rm -rf {} + 2>/dev/null || true
 	find . -type f -name "*.pyc" -delete 2>/dev/null || true
 	@echo "✅ Cleanup complete!"
@@ -59,12 +59,12 @@ clean:
 # Build documentation
 docs:
 	@echo "📚 Building documentation..."
-	python bin/tito.py nbdev --build-docs
+	@source .venv/bin/activate && python3 bin/tito package build-docs
 
 # Start Jupyter Lab
 jupyter:
 	@echo "🚀 Starting Jupyter Lab..."
-	python bin/tito.py jupyter --lab
+	@source .venv/bin/activate && python3 bin/tito system jupyter --lab
 
 # Alias for jupyter
 lab: jupyter
@@ -72,12 +72,12 @@ lab: jupyter
 # Show system information
 info:
 	@echo "ℹ️ System information..."
-	python bin/tito.py info
+	@source .venv/bin/activate && python3 bin/tito system info
 
 # Run environment diagnosis
 doctor:
 	@echo "🔬 Running environment diagnosis..."
-	python bin/tito.py doctor
+	@source .venv/bin/activate && python3 bin/tito system doctor
 
 # Setup new environment (for first-time users)
 setup:

bin/activate-tinytorch.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# TinyTorch Environment Activation & Setup
+# Tiny🔥Torch Environment Activation & Setup
 
 # Check if virtual environment exists, create if not
 if [ ! -d ".venv" ]; then
@@ -16,15 +16,15 @@ if [ ! -d ".venv" ]; then
     echo "✅ Environment created!"
 fi
 
-echo "🔥 Activating TinyTorch environment..."
+echo "🔥 Activating Tiny🔥Torch environment..."
 source .venv/bin/activate
 
 # Create tito alias for convenience
-alias tito="python3 bin/tito.py"
+alias tito="python3 bin/tito"
 
 echo "✅ Ready to build ML systems!"
 echo "💡 Quick commands:"
-echo "   tito info      - Check system status"
-echo "   tito test      - Run tests" 
-echo "   tito doctor    - Diagnose issues"
-echo "   jupyter notebook  - Start Jupyter for interactive development"
+echo "   tito system info      - Check system status"
+echo "   tito module test      - Run tests" 
+echo "   tito system doctor    - Diagnose issues"
+echo "   tito system jupyter   - Start Jupyter for interactive development"

modules/source/00_setup/README.md

@@ -74,7 +74,7 @@ Run the comprehensive test suite using pytest:
 
 ```bash
 # Using the TinyTorch CLI (recommended)
-python bin/tito.py test --module setup
+tito test --module setup
 
 # Or directly with pytest
 python -m pytest modules/setup/tests/test_setup.py -v
@@ -92,14 +92,28 @@ The test suite includes **20 comprehensive tests** covering:
 - ✅ **Error recovery** - Graceful handling of missing files
 - ✅ **Integration testing** - All components work together
 
+## Getting Started
+
+### Prerequisites
+
+1. **Activate the virtual environment**:
+   ```bash
+   source bin/activate-tinytorch.sh
+   ```
+
+2. **Test the setup module**:
+   ```bash
+   tito test --module setup
+   ```
+
 ## Development Workflow
 
 This module teaches the core TinyTorch development cycle:
 
 1. **Write code** in the notebook using `#| export` directives
-2. **Export code** with `python bin/tito.py sync --module setup`
-3. **Run tests** with `python bin/tito.py test --module setup`
-4. **Check progress** with `python bin/tito.py info`
+2. **Export code** with `tito sync --module setup`
+3. **Run tests** with `tito test --module setup`
+4. **Check progress** with `tito info`
 
 ## Key Concepts
 

modules/source/02_activations/README.md

@@ -46,11 +46,22 @@ This module teaches you the mathematical foundations that make deep learning pos
 
 ## 🚀 Getting Started
 
+### Prerequisites
+
+1. **Activate the virtual environment**:
+   ```bash
+   source bin/activate-tinytorch.sh
+   ```
+
+2. **Start development environment**:
+   ```bash
+   tito jupyter
+   ```
+
 ### Development Workflow
 
 1. **Open the development file**:
    ```bash
-   python bin/tito.py jupyter
    # Then open assignments/source/02_activations/activations_dev.py
    ```
 
@@ -66,12 +77,12 @@ This module teaches you the mathematical foundations that make deep learning pos
 
 4. **Test as you go**:
    ```bash
-   python bin/tito.py test --module activations
+   tito test --module activations
    ```
 
 5. **Export to package**:
    ```bash
-   python bin/tito.py sync
+   tito sync
    ```
 
 ### 📊 Visual Learning Features
@@ -127,19 +138,17 @@ def forward(self, x: Tensor) -> Tensor:
     return Tensor(np.tanh(x.data))
 ```
 
-## 🧪 Testing Your Implementation
+### Testing Your Implementation
 
-### Unit Tests
-```bash
-python bin/tito.py test --module activations
-```
+1. **Run the tests**:
+   ```bash
+   tito test --module activations
+   ```
 
-**Test Coverage**:
-- ✅ Mathematical correctness
-- ✅ Numerical stability
-- ✅ Shape preservation
-- ✅ Edge cases
-- ✅ Function properties
+2. **Export to package**:
+   ```bash
+   tito sync
+   ```
 
 ### Manual Testing
 ```python
@@ -201,7 +210,7 @@ output = relu(input_tensor)
 
 ### Issue 4: Import Errors
 **Problem**: Cannot import after implementation
-**Solution**: Run `python bin/tito.py sync` to export to package
+**Solution**: Run `tito sync` to export to package
 
 ## 📈 Performance Considerations
 
@@ -234,7 +243,7 @@ These functions are the mathematical foundation for everything that follows!
 ## 🎉 Success Criteria
 
 You've mastered this module when:
-- [ ] All tests pass (`python bin/tito.py test --module activations`)
+- [ ] All tests pass (`tito test --module activations`)
 - [ ] You understand why each function is useful
 - [ ] You can explain the mathematical properties
 - [ ] You can use activations in neural networks

modules/source/06_dataloader/README.md

@@ -35,9 +35,9 @@ modules/dataloader/
 ### Step 1: Complete Prerequisites
 Make sure you've completed the foundational modules:
 ```bash
-python bin/tito.py test --module setup    # Should pass
-python bin/tito.py test --module tensor   # Should pass
-python bin/tito.py test --module layers   # Should pass
+tito test --module setup    # Should pass
+tito test --module tensor   # Should pass
+tito test --module layers   # Should pass
 ```
 
 ### Step 2: Open the Data Development File
@@ -46,7 +46,7 @@ python bin/tito.py test --module layers   # Should pass
 cd modules/dataloader/
 
 # Convert to notebook if needed
-python bin/tito.py notebooks --module dataloader
+tito notebooks --module dataloader
 
 # Open the development notebook
 jupyter lab dataloader_dev.ipynb
@@ -63,10 +63,10 @@ The development file guides you through building:
 ### Step 4: Export and Test
 ```bash
 # Export your dataloader implementation
-python bin/tito.py sync --module dataloader
+tito sync --module dataloader
 
 # Test your implementation
-python bin/tito.py test --module dataloader
+tito test --module dataloader
 ```
 
 ## 📚 What You'll Implement
@@ -150,7 +150,7 @@ The tests follow the **"Build → Use → Understand"** pattern with real CIFAR-
 
 ```bash
 # Run all tests (downloads real CIFAR-10 data)
-python bin/tito.py test --module dataloader
+tito test --module dataloader
 
 # Run specific test categories
 python -m pytest tests/test_dataloader.py::TestDatasetInterface -v      # Test abstract interface
@@ -226,7 +226,7 @@ The development notebook includes **visual feedback** for learning and debugging
 
 Your data module is complete when:
 
-1. **All tests pass**: `python bin/tito.py test --module dataloader`
+1. **All tests pass**: `tito test --module dataloader`
 2. **Data classes import correctly**: `from tinytorch.core.dataloader import Dataset, DataLoader`
 3. **Dataset loading works**: Can create datasets and access samples
 4. **Batching works**: DataLoader produces correct batch shapes

modules/source/07_autograd/README.md

@@ -75,11 +75,22 @@ print(layer.bias.grad)     # Bias gradients
 
 ## 🚀 Getting Started
 
+### Prerequisites
+
+1. **Activate the virtual environment**:
+   ```bash
+   source bin/activate-tinytorch.sh
+   ```
+
+2. **Start development environment**:
+   ```bash
+   tito jupyter
+   ```
+
 ### Development Workflow
 
 1. **Open the development file**:
    ```bash
-   python bin/tito.py jupyter
    # Then open modules/source/07_autograd/autograd_dev.py
    ```
 
@@ -91,7 +102,7 @@ print(layer.bias.grad)     # Bias gradients
 
 3. **Test your implementation**:
    ```bash
-   python bin/tito.py test --module 07_autograd
+   tito test --module 07_autograd
    ```
 
 ## 📊 Understanding Automatic Differentiation
@@ -137,7 +148,7 @@ df/dy = df/da * da/dy + df/db * db/dy = (-1)(1) + (5)(-1) = -6
 
 ### Unit Tests
 ```bash
-python bin/tito.py test --module 07_autograd
+tito test --module 07_autograd
 ```
 
 **Test Coverage**:
@@ -217,7 +228,7 @@ print(layer2.weights.grad)
 
 Your autograd module is complete when:
 
-1. **All tests pass**: `python bin/tito.py test --module 07_autograd`
+1. **All tests pass**: `tito test --module 07_autograd`
 2. **Variable imports correctly**: `from tinytorch.core.autograd import Variable`
 3. **Basic operations work**: Can create Variables and do arithmetic
 4. **Gradients compute correctly**: Backward pass produces correct gradients