#deep-dive
Every post tagged "deep-dive".
107 posts · showing 41–50
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Which Jobs Go First: A Framework Rather Than a List
Lists of at-risk occupations age badly because exposure operates on tasks, not titles. Four properties score any task — and two people with the same job can land on opposite sides.
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The Career Risk of Being Excellent at the Thing Being Automated
The most exposed engineers are often the best ones — not despite the skill but because of what the skill is. And the feedback stays good right up until the market for it changes.
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If There's a Bubble, What Survives the Pop?
Whether it's a bubble is unknowable from here. More useful: assuming a correction, which parts survive — and previous cycles have a consistent answer about what separates the two.
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Juniors in an Agent World: The Path That Still Works
"Learn AI tools" is the most common advice and the wrong one — everyone has them. What addresses the actual hiring objection is different, and the path inside is narrower but shorter than it used to be.
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Why Systems Thinking Is Appreciating in Value
"Systems thinking" is vague enough to dismiss until you name the mechanism: agents work locally, and cross-cutting consequences are structurally outside their context. That gap is a person's job.
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Skills to Deepen and Skills to Stop Investing In
The divest list is harder to write than the invest list and more useful — because the default is to keep investing in what you're already good at, and that's often the exposed thing.
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Model, Loop, Harness: Three Layers and Who Owns Each
Three layers, three change rates, three skill requirements. Conflating the loop and the harness is why loop bugs get fixed with prompt edits — and why domain experts can't fix domain problems.
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Prompt Engineering Was the Beginning, Not the Skill
It got named as a discipline when the prompt was the entire interface. It's now one input among several — and if better prompts have stopped helping, five specific things are usually why.
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The Loop Decisions You Only Make Once
Most agent design choices are cheap to revise. Six aren't — and in every case the answer that ages well is the same one, for the same reason.
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Context Engineering Is the Job Now
Not prompt writing — that's the visible part and the small one. The work is deciding what reaches the model, in what form, at what moment, and it's where most agent failures start.