There is a specific kind of vertigo that comes from watching a machine effortlessly perform your life’s work. For Aditya Agarwal, an early Facebook engineer and former CTO of Dropbox, that vertigo hit after a weekend of coding with an AI assistant. His realization was absolute: we will never write code by hand again.
When the specialized skills we have spent decades mastering become free and abundant, the foundation of our professional identity inevitably trembles. Agarwal captures the duality of this moment perfectly, describing it as a mixture of “wonder with a profound sadness.”
“There’s something deeply disorienting about watching the pillars of your professional identity, what you built and how you built it, get reproduced in a weekend by a tool that doesn’t need to eat or sleep.”
The conversation around AI tends to flatten this emotional reality into two distinct camps: the doomers who foresee total replacement, and the boosters who promise a frictionless utopia.
But lived experience is messier. We are capable of holding grief and wonder in the same hand.
We can mourn the craftsmen we were, even as we sprint toward the architects we are about to become.
Because here is the secret about the disorientation of progress: it passes.
Once the initial shock fades, what replaces it is a wild, unconstrained energy.
When the mechanical friction of creation vanishes—when a week’s worth of coding can be accomplished in an afternoon—the scope of our ambition expands. We are no longer limited by the keystrokes we can manage in a day, but by the edges of our imagination. We aren’t watching ourselves become obsolete; we are watching our lifelong constraints dissolve.
This shift is rewriting the social contract of knowledge work, starting with how we evaluate human potential. For decades, the corporate world has relied on a calcified heuristic for hiring: brand-name universities, FAANG experience, and years of tenure. We worshipped the resume.
Now, that playbook is breaking down. In evaluating engineers and founders navigating this transition, Agarwal notes that traditional pedigrees predict almost nothing about a person’s ability to thrive. The new dividing line isn’t generational, and it certainly isn’t educational. It is entirely dispositional.
“The trait that matters most isn’t intelligence, or credentials or years of experience. It’s someone’s relationship with change—not whether they’ve seen change before, but whether they run toward it.”
The new currency of the working world is restlessness.
Restlessness is the refusal to settle into the comfort of the way things used to be. It is the constitution of a builder who cannot stop tinkering, who treats every new AI tool as a puzzle to be solved before the day is out. In an economy where the “how” of knowledge work is increasingly automated, the premium shifts entirely to adaptability, curiosity, and vision.
This democratization of capability forces a deeply uncomfortable, deeply human reckoning. We have to let go of the identities we forged under old paradigms to become whatever comes next.
The technology didn’t create this human challenge—it merely made it impossible to ignore.
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