
Sheridan Feucht developed two major features for the davidbau/sidn-handbook repository over a two-month period, focusing on research documentation and front-end structure. Sheridan created a Universality Page detailing how large language models infer agent representations, integrating HTML, CSS, Bootstrap, and MathJax for structured, accessible content. In the following month, Sheridan implemented the Autointerp framework, establishing a reusable documentation backbone for automated interpretability research and introducing the Summarize And Score (SASC) method. The work emphasized maintainable documentation, cross-domain evaluation, and improved onboarding, demonstrating depth in web development, JavaScript, and technical writing without introducing major defects or requiring bug fixes.
Month: 2024-12; Repository: davidbau/sidn-handbook. Summary: Implemented Autointerp framework for automated interpretability documentation and introduced the Summarize And Score (SASC) method. Delivered autointerp directory and initial HTML scaffold, updated assets and the section layout, and added cross-domain evaluation content comparing SASC performance across synthetic modules, BERT, and fMRI data. Commits: e57262bf6c09cff3aee9c777ece138a2ef8d92c2; 15a7df7e34f84142a8f7baf3294cc931ad15283e. Impact: creates a reusable research documentation backbone, improving transparency, collaboration, and onboarding for interpretability studies; enables faster iteration on explainability experiments using LLMs.
Month: 2024-12; Repository: davidbau/sidn-handbook. Summary: Implemented Autointerp framework for automated interpretability documentation and introduced the Summarize And Score (SASC) method. Delivered autointerp directory and initial HTML scaffold, updated assets and the section layout, and added cross-domain evaluation content comparing SASC performance across synthetic modules, BERT, and fMRI data. Commits: e57262bf6c09cff3aee9c777ece138a2ef8d92c2; 15a7df7e34f84142a8f7baf3294cc931ad15283e. Impact: creates a reusable research documentation backbone, improving transparency, collaboration, and onboarding for interpretability studies; enables faster iteration on explainability experiments using LLMs.
Delivered a new Universality Page with comprehensive content on LLMs as agent models for the davidbau/sidn-handbook repo, including structure, assets, Bootstrap styling, MathJax rendering, and references. Completion achieved via four commits enabling incremental release and traceability. No major defects reported; this feature-rich documentation improves onboarding, accelerates future work, and reinforces the product’s value proposition.
Delivered a new Universality Page with comprehensive content on LLMs as agent models for the davidbau/sidn-handbook repo, including structure, assets, Bootstrap styling, MathJax rendering, and references. Completion achieved via four commits enabling incremental release and traceability. No major defects reported; this feature-rich documentation improves onboarding, accelerates future work, and reinforces the product’s value proposition.

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