We're Already Nostalgic for Work Before AI

The First Nostalgia Will Be for Effort

In a few years, the most impressive thing you'll be able to say about your work is that it took a long time.

At some point in the not‑too‑distant future, someone will describe their product the way a chef describes a dish: hand‑made. Not AI‑assisted. Not auto‑generated. Built line by line, deliberately, the old way.

It will sound eccentric at first. And then, almost immediately, it will sound impressive.

We've seen this pattern before. Tools that disappear because they're inefficient rarely stay culturally dead. They tend to come back as artifacts of meaning.

Consider vinyl. According to the Recording Industry Association of America, U.S. vinyl sales surpassed $1 billion in 2025, representing nearly half of global vinyl revenue -- a remarkable milestone in an era dominated by streaming (RIAA, March 2026). Streaming is objectively more convenient, portable, and scalable. But vinyl persists because inconvenience, over time, becomes character.

Or take typewriters. In January 2026, CNN profiled collectors and repair shops seeing renewed demand for manual machines, driven in part by younger generations seeking a break from screens (CNN, "How typewriters are making a comeback"). The typewriter didn't return because it's faster than Google Docs. It returned because it feels intentional.

Film photography tells a similar story. Eastman Kodak has expanded its film offerings amid sustained demand for analog formats, prompting headlines about whether film is "going mainstream again" (Digital Camera World, March 2026). Digital cameras are superior by almost every measurable standard. But film encodes constraint. Constraint encodes craft.

Knowledge work before AI is headed in the same direction.

How AI Removes Friction -- and Meaning Along With It

The core promise of AI is friction removal. It compresses tasks that once took hours into seconds. Code becomes prompting. Research becomes synthesis. Spreadsheets become conversations. Slide decks assemble themselves.

For decades, professional competence was expressed through operational fluency. You proved seriousness by knowing Excel shortcuts, by navigating a codebase unaided, by debugging manually at inconvenient hours. These skills weren't just technical -- they were social signals. They demonstrated endurance and control.

AI flattens that gradient. According to the 2025 Stack Overflow Developer Survey, 84% of developers use or plan to use AI tools -- yet trust in those tools has fallen sharply, with a significant portion expressing skepticism about reliability and accuracy (Byteiota summary of survey findings). Adoption is rising. Confidence is not.

That tension matters.

When execution becomes cheap and universal, effort becomes invisible. And when effort disappears from view, people begin to feel that something essential has been lost -- not because the old work was enjoyable, but because it was formative.

Why Humans Romanticize Difficulty

The romanticization of pre‑AI work will not be an anomaly. It fits a long historical pattern.

In the late 19th century, the Arts and Crafts movement emerged as an explicit reaction to industrial mass production. Thinkers like William Morris argued that mechanization had degraded craftsmanship and aesthetic integrity. The movement valorized hand production precisely because factories had made it unnecessary (Britannica, Arts and Crafts movement).

The pattern repeats: industrialization creates abundance; abundance creates sameness; sameness creates longing for the handmade.

AI is industrialization for cognition.

In a world where competent output can be generated instantly, manual work will take on narrative weight. Not because it produces better results in every case, but because it signals choice. Saying something was built without AI will increasingly function the way "small batch" or "single origin" does now: as shorthand for deliberate constraint.

We won't romanticize spreadsheets themselves. We'll romanticize what they required -- patience, linear reasoning, careful attention to detail.

Craft Signaling in a Post‑Execution World

We are already seeing the beginnings of resistance.

Some engineers publicly describe disabling AI coding assistants after experiencing declining code quality or over‑reliance. On developer forums and in engineering blogs, teams have written about banning GitHub Copilot temporarily to regain focus and judgment. While AI adoption is widespread, a parallel conversation about cognitive atrophy and trust has emerged.

This doesn't mean AI is going away. It means identity is shifting.

There will likely be startups that market themselves as "hand‑coded" to signal auditability. Consulting firms that emphasize human‑only analysis as insulation from algorithmic monoculture. Educational programs that stress foundational manual methods as cognitive training, much like learning long division before calculators.

Manual work will become a form of craft signaling.

In saturated environments, differentiation migrates from execution to taste. When everyone can generate competent code, the premium shifts to architecture. When everyone can draft a passable essay, the premium shifts to original framing.

But humans don't just value outcomes. They value stories. And "I built this without AI" will carry narrative force.

When Execution Stops Being Identity

For a long time, doing the work was who you were. You were the person who knew how to build the spreadsheet model from scratch, who could reason through the codebase without autocomplete, who could wrestle complexity unaided.

AI turns execution into infrastructure. Just as nobody defines themselves today by knowing how to operate a printing press, future professionals won't define themselves by writing boilerplate.

They'll define themselves by vision and judgment.

And yet, the pendulum rarely settles on pure efficiency. In a world saturated with machine‑generated competence, there will be something quietly compelling about the person who can say they did it themselves -- even if it took longer, even if it wasn't strictly necessary.

What we will miss is not the spreadsheet itself, or the repetitive lines of code. We will miss the visible struggle that once signaled mastery.

Not because work was better before AI.

But because it was harder -- and history suggests that once difficulty becomes optional, it often becomes desirable.