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    Mercor reportedly spends 3 times as much on AI inference as on employee salaries

    Foody says the returns from running AI models add to headcount rather than replace it. He uses Mercor’s experience to argue for a path toward roughly 9% average annual GDP growth over five years.

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    TLDR

    Brendan Foody says Mercor spends three times as much on LLM inference—running language models—as on employee salaries, and that the returns support headcount rather than replace it. In his September 13, 2026 projection, he predicts companies will spend as much on inference within five years as they currently spend compensating knowledge workers, which he estimates at roughly $40 trillion annually. If wages remain roughly constant and companies absorb that spending profitably, he argues, the economy would need about $40 trillion in additional annual final economic output. Producing that much more annual GDP in year five than a roughly 3% growth baseline would imply about 9% average annual GDP growth over those five years, he says.

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    7 Sources, first seen 19d ago

    Combined views

    209.1K

    7 Sources, first seen 19d ago

    1.8K likes
    19d ago
    first seen 19d ago
    1.8K likes
    135 comments
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    78 reposts

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    135 comments
    821 saves
    78 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    7 Sources

    @BrendanFoodyOur AI project manager now takes more actions across Slack, Gmail, Drive, and our internal tools than all our employees combined. Because our employees are more productive, we're hiring as fast as we can. Every AI native company feels the same way. This feels like an incredible leading indicator for the labor market.
    @gabriel1every single piece of information that goes into a company will soon pass through ai internal messages, website analytics, customer tickets, meeting transcriptions, any change in internal systems, everything there will soon be an explosion in GDP. habits is the only blocker
    @hnshahInference spend per employee may become one of the most important metrics in business. Mercor already spends 3X more on inference than salaries. The companies that learn how to turn every additional dollar of inference into useful output will have a very different ceiling.
    @menhguin@BrendanFoody sir, we are 4 years into ChatGPT and most people don't know it can code.

    7 Sources

    @BrendanFoodyOur AI project manager now takes more actions across Slack, Gmail, Drive, and our internal tools than all our employees combined. Because our employees are more productive, we're hiring as fast as we can. Every AI native company feels the same way. This feels like an incredible leading indicator for the labor market.
    @gabriel1every single piece of information that goes into a company will soon pass through ai internal messages, website analytics, customer tickets, meeting transcriptions, any change in internal systems, everything there will soon be an explosion in GDP. habits is the only blocker
    @hnshahInference spend per employee may become one of the most important metrics in business. Mercor already spends 3X more on inference than salaries. The companies that learn how to turn every additional dollar of inference into useful output will have a very different ceiling.
    @menhguin@BrendanFoody sir, we are 4 years into ChatGPT and most people don't know it can code.