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- Created organized guidelines/ directory with focused documentation: - DESIGN_PHILOSOPHY.md: KISS principle and simplicity focus - MODULE_DEVELOPMENT.md: How to build modules with systems focus - TESTING_STANDARDS.md: Immediate testing patterns - PERFORMANCE_CLAIMS.md: Honest reporting based on CIFAR-10 lessons - AGENT_COORDINATION.md: How agents work together effectively - GIT_WORKFLOW.md: Moved from root, branching standards - Added .claude/README.md as central navigation - Updated CLAUDE.md to reference guideline files - Created CLAUDE_SIMPLE.md as streamlined entry point All learnings from recent work captured in appropriate guidelines
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2.4 KiB
Claude Code Instructions for TinyTorch
📚 START HERE: Read the Guidelines
All development standards, principles, and workflows are documented in the .claude/ directory.
Quick Start
# First, read the overview
cat .claude/README.md
# Then read core guidelines in order:
cat .claude/guidelines/DESIGN_PHILOSOPHY.md # KISS principle
cat .claude/guidelines/GIT_WORKFLOW.md # Git standards
cat .claude/guidelines/MODULE_DEVELOPMENT.md # Building modules
cat .claude/guidelines/TESTING_STANDARDS.md # Testing patterns
🎯 Core Mission
Build an educational ML framework where students learn ML systems engineering by implementing everything from scratch.
Key principles:
- KISS: Keep It Simple, Stupid
- Build to Learn: Implementation teaches more than reading
- Systems Focus: Not just algorithms, but engineering
- Honest Claims: Only report verified performance
⚡ Critical Policies
- ALWAYS use virtual environment (
.venv) - ALWAYS work on feature branches (never main/dev directly)
- ALWAYS test before committing
- NEVER add automated attribution to commits
- NEVER edit .ipynb files directly (edit .py only)
🤖 Working with AI Agents
Always start with the Technical Program Manager (TPM):
- TPM coordinates all other agents
- Don't invoke agents directly
- Follow the workflow in
.claude/guidelines/AGENT_COORDINATION.md
📁 Key Directories
.claude/guidelines/ # All development standards
.claude/agents/ # AI agent definitions
modules/source/ # Module implementations (.py files)
examples/ # Working examples (keep simple)
tests/ # Test suites
🚨 Think Critically
Don't just agree with suggestions. Always:
- Evaluate if it makes pedagogical sense
- Check if there's a simpler way
- Verify it actually works
- Consider student perspective
📋 Before Any Work
- Read guidelines: Start with
.claude/README.md - Create branch: Follow
.claude/guidelines/GIT_WORKFLOW.md - Activate venv:
source .venv/bin/activate - Use TPM agent: For coordinated development
🎓 Remember
"If students can't understand it, we've failed."
Every decision should be:
- Simple
- Verified
- Educational
- Honest
For detailed instructions on any topic, see the appropriate file in .claude/guidelines/