klotz: programming*

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  1. A paraphrasing of Gerald Jay Sussman's explanation for MIT's switch from Scheme to Python in its undergraduate computer science program, focusing on the changing nature of programming and the need to adapt to modern systems and libraries.
  2. This report details the progress of the Medley Interlisp Project in 2025, including work on the core system, community outreach, and future plans for preserving and reviving the historical Interlisp environment.
  3. An article detailing FastRender, a web browser built by Cursor using thousands of parallel coding agents. It explores the project's goals, architecture, and surprising findings about using AI for software development.
  4. The article emphasizes the importance of optimizing AI coding agent context to improve efficiency and performance. The author shares four key techniques: maintaining an updated AGENTS.md file, providing documentation links, sharing IaC stack context, and starting new threads for new tasks.

    **Bullet Points:**
    - **Always update AGENTS.md**: Store coding rules and preferences across threads to improve consistency and reduce errors.
    - **Provide documentation links**: Ensure agents use up-to-date API and syntax information by linking to current docs.
    - **Provide IaC stack as context**: Share infrastructure details (e.g., database tables) to reduce token usage and improve speed.
    - **Start new threads for new contexts**: Avoid context noise by initiating fresh threads when switching tasks or projects.
  5. Python 3.14.1 is the latest release of the Python programming language, offering bug fixes and improvements.
  6. A STEAM education robot that makes teaching and learning robot programming simple and fun, featuring advanced programmable capabilities, 160+ mechanical parts, and the ability to build 10 different configurations.
  7. A historical document detailing the origins and development of the EMACS editor, tracing its roots from early TECO-based systems like TMACS and TECMAC through its evolution on Multics and ITS. Includes email exchanges and notes from key figures like RMS, GLS, and EAK.
  8. An article detailing the author's experience replacing bash scripts with Python, outlining the improvements in readability, error handling, and testability, as well as the challenges encountered during the migration.
  9. This blog post details the implementation of a 'Particle Life' simulation using WebGPU. It covers the model's mechanics, the rationale for using WebGPU, the simulation loop, force computation techniques (including parallel prefix sum), rendering details, and provides a link to an interactive demo.
  10. A machine learning library for unsupervised time series anomaly detection. Orion provides verified ML pipelines to identify rare patterns in time series data.

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