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Experimental Studies

This section documents our experimental studies of Claude CLI. Each experiment is designed to investigate specific aspects of Claude CLI's architecture and behavior.

Experiment Categories​

Semantic Chunking Studies​

These experiments investigate how Claude CLI processes large codebases:

Differential Update Studies​

These experiments analyze how Claude CLI handles codebase changes:

Session Management Studies​

These experiments explore how Claude CLI maintains session state:

Hybrid Architecture Studies​

These experiments investigate how Claude CLI balances local and remote processing:

Running Experiments​

Our experimental code is available in the experiments directory of our repository. Each experiment includes:

  1. A detailed README explaining the experiment's purpose and methodology
  2. Python scripts for running the experiment
  3. Analysis notebooks for examining the results

To run experiments yourself, follow these steps:

# Clone the repository
git clone https://github.com/your-github-username/sonnet-3.7-docs.git
cd sonnet-3.7-docs

# Install dependencies
pip install -r experiments/requirements.txt

# Run a specific experiment
python experiments/chunking/analyze_chunking.py --repo=/path/to/test/repo --query="Explain the auth system"

# Generate analysis report
python experiments/chunking/generate_report.py --results=results/chunking_analysis_*.json

Experimental Implementations​

Based on our experimental findings, we've developed several experimental implementations:

These implementations are educational in nature and designed to test our understanding of Claude CLI's architectural patterns.

Join Our Community: Contributing Your Experiments​

We're building a vibrant community of researchers, developers, and AI enthusiasts exploring Claude 3.7 Sonnet's capabilities. Your contributions can help everyone gain deeper insights into how these advanced models work.

Why Contribute?​

  • Advance Collective Knowledge: Your experiments help us all better understand these powerful AI systems
  • Gain Recognition: Get credit for your innovative approaches and findings
  • Connect with Peers: Join a community of like-minded researchers and practitioners
  • Shape the Future: Influence the direction of AI tooling and best practices

How to Contribute​

  1. Share Your Ideas: Start with an idea for an experiment – perhaps a usage pattern you've observed, a hypothesis about how Claude works, or a novel approach to prompt engineering

  2. Fork & Implement: Fork our repository, implement your experiment, and document your methodology

  3. Submit a PR: Open a pull request with your experiment, including:

    • Clear documentation of your methodology
    • Your implementation code
    • Analysis of results
    • Any visualizations or insights

  4. Join the Discussion: Engage with feedback and collaborate to refine your contribution

Types of Contributions We're Looking For​

  • Novel Prompting Techniques: Experiments with different prompt structures and their effects
  • Multi-Modal Integration Studies: How Claude processes and relates different types of content
  • Performance Benchmarks: Comparative studies in specific domains
  • Tool Usage Patterns: Analysis of how Claude uses different tools
  • Context Window Optimization: Techniques for maximizing the value of context
  • Information Retrieval Patterns: How Claude searches for and retrieves information

Getting Started​

Check our experimental template for a structure to follow when creating your own experiment.

For more detailed guidelines, see our contribution guidelines.

Ready to contribute? Join our Discord community or open a discussion to share your ideas!