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AI at Work

Tweets, posts, and field notes on how people and companies are actually adopting AI at work.

  1. Tweet

    Mar 17, 2026

    Agentic software work needs ruthless deletion, not just better tools

    Useful AI-at-work lesson: when software gets cheaper to generate, teams need stronger editing instincts, not weaker ones. The bottleneck shifts from producing code to curating, discarding, and reshaping it fast enough that low-quality output does not accumulate into system drag.

    Author
    Malte Ubl
    Published
    Mar 17, 2026
    Tags
    agents code-quality engineering software-development workflow

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  2. Article

    Mar 17, 2026

    AI fatigue comes from review overload and constant tool churn

    This is a sharp AI-at-work diagnosis because it explains why teams can feel faster and more burned out at the same time. As AI shifts engineers from making to reviewing, and from deep focus to rapid context switching, the real bottleneck becomes human judgment, not code generation speed.

    Source
    Siddhant Khare
    Published
    Mar 17, 2026
    Tags
    agents burnout code-review engineering workflow

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  3. Tweet

    Mar 16, 2026

    Authentic human charisma becomes more valuable as AI mediates more work

    Useful AI-at-work lens: when synthetic fluency becomes cheap, distinctively human taste, energy, and point of view become scarcer and therefore more valuable. The advantage shifts from merely producing polished output to showing unmistakable personality, judgment, and live presence.

    Author
    Walter Kirn
    Published
    Mar 16, 2026
    Tags
    ai-adoption authenticity culture differentiation work

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