Tech workers fear doing more for the same pay more than losing their jobs to AI
The productivity gains from AI have turned into higher expectations, and Segal writes that people "are running out of room to breathe."
Lenny's Podcast: Product | Growth | Career · Why the AI’s honeymoon is ending (and tech workers are feeling it) | Noam SegalThe biggest fear in tech right now is not losing your job to AI. It ranks second to last on the list of worries, according to Noam Segal, who ran a survey of tech workers about AI.
What ranks first is being expected to produce more without extra pay. Segal describes it as a squeeze, with workers pressed to get more done in fewer hours without more money.
The second biggest fear is closely related: that the pace has become unsustainable. By pace, Segal means both the daily velocity of work, how much has to be shipped every day, and the pace of technological change itself.
Learning each new model, framework, and way of working eats into focused work time, creating what he calls an "evil downward spiral." In Segal's words, "The speed AI unlocked got plowed straight back into expectations." He adds that "the people expected to hit it are running out of room to breathe."
Questions people ask
Are tech workers actually burned out, or just complaining about change?
Yes, by his survey's numbers: significant burnout rose sharply while career optimism fell. The squeeze helps explain why: people are shipping faster than ever, yet feel more tired and less able to do meaningful work.
Does that mean tech workers are not worried about layoffs at all?
Layoff anxiety is widespread, with more than 70% worried to some degree. But in the ranking of specific fears about AI, being asked to produce ever more for the same pay outranked being replaced, which suggests the daily grind feels more immediate than a future layoff.
Why would AI tools that save time make work feel faster and more exhausting?
Because new models, frameworks, and ways of working keep arriving, and workers must spend work time learning them. That learning time takes away from core, focused work time, while daily output expectations keep rising.