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series · 6 essays

The Human Bargain

The AI productivity story keeps getting told without the people in it. These six essays are about the bargain builders owe the humans whose careers the technology reshapes: honest language, honest math, and operating models that spend the gains deliberately.

The argument opens with the narratives, because both popular frames for AI and jobs serve the companies selling the technology. Builders own that trust deficit, and the essays work from rhetoric toward operations: the layoff math that stops adding up as the subsidy ends, the reorg that should restructure the work before it touches people, and the shift of durable advantage toward judgment. The closing essay lands on the training system: entry-level work was never just cheap execution, and automating it away eats the seed corn.

The thesis behind this thread lives on the Point of View page as "Builders owe a bargain." Read the essays in order; each one raises the stakes of the one before it.

reading order

The essays

  1. 01
    The Companies Spending the Most on AI Have the Most to Gain From Convincing You It Will Take Your Job
    3 min read

    The frames examined: inevitability and competition both serve the vendor, and neither survives contact with demand.

  2. 02
    AI Populism is a Builder's Problem
    6 min read

    The stakes: sociopolitical alignment is part of the engineering problem, and builders set the language.

  3. 03
    The Subsidy and the Severance
    13 min read

    The math: AI's free-lunch phase is ending, which makes AI-driven layoff math harder to defend.

  4. 04
    Your First AI Reorg Should Be the Work, Not the People
    12 min read

    The operating move: redesign workflows, decision rights, and evaluation loops first, and let the org chart follow.

  5. 05
    The More AI We Have, the More Human Judgment Matters
    7 min read

    The shift: as execution becomes abundant, durable advantage moves to judgment, context, and verification.

  6. 06
    Don't Automate the Apprenticeship Out of Engineering
    23 min read

    The long game: entry-level work was the training system that produced the judgment everything else now depends on.

supporting reads

Around the spine

  • Work Is Hard Enough

    The leadership floor: remove the avoidable human drag before asking anyone to absorb an AI transition too.

  • Still in the Code

    The practice: staying hands-on because secondhand models of the work cannot keep up with how fast it changes.