Knowledge Workers: The Existential Crisis Noema Exposes

⏱️ Lectura: 11 min

A financial analyst spends half an hour explaining EBITDA and expansion margins over the phone, sitting in a train car. When he reaches the last station, instead of putting away his laptop, he pulls out two knitting needles and starts a wool hat for his niece. Aaron Horwath, who witnessed the scene, uses it to open an essay on the existential crisis of knowledge workers published in Noema Magazine.

📑 En este artículo

1. TL;DR
2. What happened: the disillusionment of knowledge workers
3. Context and history: from vocation to workism
4. Technical details and data
5. How to measure burnout on your team
6. Impact and analysis
7. What’s next
8. Frequently Asked Questions
   1. What is workism?
   2. Why do senior executives feel this crisis too if they’re better protected from AI?
   3. Is this phenomenon exclusive to Silicon Valley, or does it also show up in Latin America?
   4. How is this crisis different from previous waves of automation?
   5. How can a development team spot early signs of disillusionment?
9. References

Horwath runs AI operations at a creative technology company and writes from inside the industry: among his colleagues, more and more people dream of giving it all up for pottery, painting, or a farm, right as artificial intelligence redefines which tasks remain human.

TL;DR

• Noema Magazine published Aaron Horwath’s essay on the disillusionment of knowledge workers in tech.
• The piece revisits workism, the concept Derek Thompson defined in The Atlantic in 2019 for work as a secular religion.
• Layoffs.fyi recorded more than 260,000 tech layoffs in 2023, a wave that kept hitting the sector in the following years.
• Gallup estimates that only a minority of employees worldwide feel truly engaged with their work.
• The essay describes well-paid professionals who dream of knitting, making pottery, or moving to a farm to escape work.
• The phenomenon doesn’t discriminate by rank: senior executives with decades of experience, the best protected in the market, also doubt their careers.
• Horwath connects the current anguish to existential questions, not just economic ones, something different from previous crises like outsourcing.

What happened: the disillusionment of knowledge workers

Horwath isn’t describing an isolated case. In coffee shops and dimly lit bars, he hears colleagues talk about leaving the office for pottery, painting, or crochet: old, manual trades with a tangible result at the end of the day. Others talk about disappearing, moving to a farm, or going off-grid. These aren’t passing fantasies: they’re signs of a deeper doubt about whether knowledge work ever had a real purpose.

What’s striking, according to the essay, is that this anguish doesn’t discriminate by rank. Knowledge workers weathered recessions, outsourcing, and earlier waves of automation without losing faith in a career as a life project. This time, even senior executives with decades of experience (in theory the best protected from AI’s advance) doubt the meaning of what they built.

For a developer in Latin America, the diagnosis lands differently. For more than a decade, learning to code worked as a promise of social mobility and economic stability in the region. Seeing that same promise questioned from inside the industry that sold it is no small thing: it shifts the conversation from which language to learn to why learn it at all.

Context and history: from vocation to workism

The concept that best names this unease isn’t new. In 2019, Derek Thompson wrote in The Atlantic about workism: the pronounced tendency, among the most educated and highest paid professionals in the United States, to look to work for the sense of community and purpose that earlier generations found in religion. For Thompson, choosing the office over a day of rest was, for that professional class, where they felt most like themselves.

Workism turned every job into an identity project. Before, a vocation implied a skill, a value, and a desire to contribute something useful: more than a job, a calling. Workism went a step further: it made self-worth entirely dependent on productivity and title. That design turns out to be fragile right when a new technology starts to question the value of the skill that held up that identity.

That fragility also has a measurable counterpart. Layoffs.fyi documented more than 260,000 layoffs in the tech sector during 2023, and the wave kept hitting in the following years, with restructurings that combined cost cutting and AI adoption. You don’t need to lose your job to feel the tremor: watching colleagues leave is enough for the question of who’s next to settle into any team.

💭 Key: unlike previous recessions or outsourcing waves, this one doesn’t just threaten income: it questions whether the craft itself ever had meaning.

Technical details and data

The unease isn’t just anecdotal. Gallup measures worker engagement worldwide in its annual State of the Global Workplace report and, year after year, finds that only a minority of the global workforce reports being truly engaged with their work. That data point, holding steady over time, is the statistical backdrop to the coffee-break conversations Horwath describes: the disconnection didn’t start with AI, but AI gave it a concrete, current reason to become visible.

Add to that backdrop a structural shift tracked by the Anthropic Economic Index: the adoption of AI assistants for code writing and analysis tasks is moving fast inside software companies. The point isn’t how much specific code a model writes, but that the traditional status ladder (from junior to senior, measured by how much complex code you can write on your own) no longer works the same way when a tool levels much of that task.

Professional profile	Traditional relationship with work	Tension in 2026	Warning sign
Junior / bootcamp	Code is the fast track to financial stability	AI generates boilerplate faster than a junior	Fewer entry-level job postings
Senior / staff engineer	Technical experience defines status on the team	AI assistants narrow the gap on routine tasks	Doubt about what’s left that’s unique to the craft
Executive / C-level	Title and results give the career meaning	Better protected, but responsible for deciding what gets automated	Emptiness despite financial security
Freelance / contractor	Every delivered project sustains income	Competes with per-task AI agent rates	Constant pressure to lower prices

How to measure burnout on your team

You don’t need to wait for a corporate survey to detect this tension within a team. Simple, cheap-to-collect data of your own is enough to see whether AI assistance is rising while perceived meaning is falling.

import csv
from datetime import date

def log_entry(sentido, horas, notas=""):
    with open("burnout_log.csv", "a", newline="") as f:
        writer = csv.writer(f)
        writer.writerow([date.today().isoformat(), sentido, horas, notas])

if __name__ == "__main__":
    log_entry(sentido=3, horas=8.5, notas="end of month sprint")

This script saves, day by day, a subjective meaning score (1 to 5) along with hours worked. Run it at the end of each workday and add a short context note.

import csv
import subprocess

def porcentaje_commits_ia(desde="7.days.ago"):
    asistidos = subprocess.run(
        ["git", "log", f"--since={desde}", "--grep=Co-authored-by: Claude", "--oneline"],
        capture_output=True, text=True
    )
    total = subprocess.run(
        ["git", "log", f"--since={desde}", "--oneline"],
        capture_output=True, text=True
    )
    n_asistidos = len(asistidos.stdout.splitlines())
    n_total = max(len(total.stdout.splitlines()), 1)
    return n_asistidos / n_total * 100

with open("burnout_log.csv") as f:
    ultimo_sentido = int(list(csv.reader(f))[-1][1])

print(f"AI in commits: {porcentaje_commits_ia():.1f}% | reported meaning: {ultimo_sentido}/5")

Run this on Fridays: it cross-references the percentage of commits with agent co-authorship against your latest meaning score. If AI assistance rises week over week while the score drops, it’s an early signal, not proof.

To confirm the log is filling in correctly, run tail -n 5 burnout_log.csv before each team retro.

Impact and analysis

The question the essay leaves open is uncomfortable: what happens to an entire industry if a significant portion of its workforce stops believing in a career as a life project? In the short term, the most visible answer is quiet quitting: people doing the bare minimum, saving their real energy for the weekend’s manual hobby, and no longer fighting for the next promotion.

In the medium term, the risk is structural. Software teams depend on someone experienced who wants to mentor juniors, defend an architecture in a difficult meeting, or carry a project through a rough patch. If that senior layer disconnects emotionally, it doesn’t disappear from payroll, but the energy that sustains long-term quality does.

There’s also a side that Horwath himself acknowledges with discomfort: much of this anguish arises in a professional class that, during the pandemic, worked from the couch while other essential workers were exposed to risk, and that today builds the very AI tools threatening jobs outside the tech industry. The unease is real, but it doesn’t erase that contradiction.

flowchart TD
    A["Vocation: work gives meaning"] --> B["Workism: work replaces identity"]
    B --> C["AI automates status tasks"]
    C --> D["Existential doubt"]
    D --> E["Manual craft or hobby"]
    D --> F["Career reinvention"]
    D --> G["Prolonged burnout"]

⚠️ Careful: Horwath’s essay is a piece of journalism, not a study with a representative sample: his observations come from informal conversations among peers, not a controlled survey.

What’s next

There’s no single solution in sight. Some companies are already experimenting with shorter workweeks or hybrid schedules as a partial response to the overload, while others are doubling down on productivity pressure backed by AI itself. Neither path resolves the underlying question the essay raises: what replaces work as a source of meaning when work itself changes shape.

What does seem likely is that the conversation will stop being a niche topic among office colleagues. As more well-paid professionals speak publicly about giving it all up for a manual trade, the question will reach boardrooms that today treat it as an HR anecdote, not a business risk.

📖 Summary on Telegram: View summary

Try it yourself: build your own burnout_log.csv this week, run the correlation script against your commits, and compare your perceived meaning against your actual hours before drawing conclusions about your own career.

Frequently Asked Questions

What is workism?

It’s the term journalist Derek Thompson used in 2019, in The Atlantic, to describe how the most educated and highest paid professionals in the United States began looking to work for the sense of community and purpose they once sought in religion.

Why do senior executives feel this crisis too if they’re better protected from AI?

Because economic protection doesn’t resolve the underlying question: if much of their professional value depended on a technical skill that AI already matches on specific tasks, title and salary stop being enough of an answer to why am I doing this.

Is this phenomenon exclusive to Silicon Valley, or does it also show up in Latin America?

The original essay describes offices and trains in the United States, but the mechanism (a promise of stability through code that’s starting to wobble) applies to any market where coding was sold as a guarantee of social mobility, including the region’s tech hubs.

How is this crisis different from previous waves of automation?

The questions stopped being purely economic. Previous recessions, outsourcing, and automation threatened income; this wave calls into question the very purpose of a career, even among those who keep their job and salary.

How can a development team spot early signs of disillusionment?

By cross-referencing simple, self-collected data: hours worked, the percentage of AI-assisted commits, and a subjective meaning score reported week by week, as in this article’s script. No single metric is enough on its own, but the trend does give a warning.

References

• Noema Magazine: Aaron Horwath’s original essay on the disillusionment of knowledge workers in tech.
• The Atlantic: Derek Thompson’s 2019 article that coined the concept of workism.
• Gallup: the annual State of the Global Workplace report on worker engagement worldwide.
• Layoffs.fyi: a historical tracker of layoffs in the tech industry, including the 2023 wave.
• Anthropic Economic Index: research on the economic impact of AI use in the workplace.

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Imagen destacada: Foto de Giorgio Sannino en Unsplash