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Cal Newport

The computer scientist and productivity theorist who argued, years before large language models arrived, that the modern knowledge economy systematically destroys the cognitive conditions that produce its most valuable outputs—and who has spent the AI era showing why that danger is now categorically more acute.
Cal Newport is a professor of computer science at Georgetown University who has spent two decades building a theory of human cognitive work that runs against every default of the digital age. His 2016 book Deep Work introduced the central distinction of his framework: deep work, professional activity performed in distraction-free concentration that pushes cognitive capabilities to their limit, versus shallow work, logistical tasks performed while distracted. The distinction was always more urgent than it sounded, because Newport's structural observation was not that deep work is pleasant but that the modern knowledge economy systematically destroys the conditions for it while depending on its outputs for all the value it produces. The arrival of large language models has made the stakes of this argument much higher, because AI can now produce the outputs of deep work without producing the cognitive development that the practice requires; a knowledge worker can spend three
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