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MAJOR MILESTONE: Successfully balanced robustness with educational accessibility
Core Changes:
- **TinyTorch Assumptions Framework**: docs/tinytorch-assumptions.md
- "Production Concepts, Educational Implementation" philosophy
- 20% complexity for 80% learning objectives
- Clear guidelines for type systems, error handling, memory analysis
- **Module 02 Tensor Simplifications**:
- Simplified dtype system: Union[str, np.dtype, type] → string-only
- Added module-level assumption documentation
- Enhanced visual diagrams with narrative descriptions ("The Story")
- Preserved core concepts while reducing implementation barriers
- **Narrative Learning Enhancement**:
- Step-by-step explanations for complex visual diagrams
- "What's happening" sections for memory layout, broadcasting
- Concrete analogies (memory as library, cache as city blocks)
Team Consensus Achieved:
- Educational Review Expert: Progressive disclosure, cognitive load management
- ML Framework Advisor: Essential vs optional complexity identification
- Education Architect: Learning objective alignment
- Module Developer: Implementation feasibility validation
- Technical Program Manager: Coordinated framework implementation
Validation Results:
- Module 02 passes all tests with simplified complexity
- Students can implement tensor concepts without Union type confusion
- Production context preserved in advanced sections
- Clear path from educational to production understanding
Next: Apply framework to remaining modules for consistent complexity management