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Technology Munch

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Learning, teaching and working

Generated summaries feel efficient and reliably produce worse recall than notes you wrote badly yourself. What to automate, and what to keep doing by hand.

  1. AI Notes That Help You Learn

    Generated summaries feel efficient and reliably produce worse recall than notes you wrote badly yourself. What to automate instead.

    Analysis

  2. AI for Coursework: The Limits

    What these tools do well for a student, what they do badly, and where the line between help and academic misconduct actually sits.

    Analysis

  3. AI in Teaching: What Helps

    Most classroom AI products solve problems teachers do not have. The genuine wins are administrative, and the genuine risks are about assessment design.

    Analysis

  4. Reliable Analysis and Charts

    Arithmetic done in text is unreliable. Arithmetic done by executing code is not. Which mode your tool is in determines whether you can trust the number.

    Procedure

  5. Running a Useful One-to-One

    The default version is a status update the manager already had. What changes when the meeting belongs to the other person.

    Procedure

  6. Thinking When Answers Come Easily

    A fluent answer to any question in three seconds changes the failure mode. The habits that matter now are about interrogation rather than recall.

    Analysis

  7. What Meeting Summaries Get Wrong

    Automatic notes are convenient and confidently wrong in one specific way that causes real problems: who agreed to do what.

    Reference

  8. Spaced Repetition, With and Without AI

    The technique with the strongest evidence behind it in learning research. What AI changes about it, which is less than the marketing suggests.

    Procedure

8 notes in this section