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In a personal essay, developer Manuel Darcemont recounts how his great-great-grandfather left farriery in rural France and became a mechanic as cars replaced horses. Darcemont says the family story offers perspective on developers’ AI anxieties, but does not prove workers will adapt in the same way; he argues people may carry their underlying purpose into new kinds of work.
Developer Manuel Darcemont says his great-great-grandfather left work as a farrier in rural France and became a mechanic as cars displaced horse-drawn transport, a family history Darcemont uses to reflect on developers’ fears about AI. His essay offers a personal analogy for technological change, not evidence that today’s workers will follow the same path.
Darcemont writes that his ancestor worked in Mandres-en-Barrois, shoeing horses and repairing farmers’ carts. He does not know exactly what prompted the change, saying the man may have seen a car in a nearby town or read about one in a newspaper. What Darcemont says happened afterward is clearer: his great-great-grandfather became a mechanic, as did later men in the family.
In Darcemont’s account, the work changed but its purpose remained: helping people get around. He recalls his father’s enthusiasm for his job as a mechanic and says the family’s connection to that work came to feel longstanding, even though it began with a shift away from horses.
The essay turns from family history to software development and AI. Darcemont says developers are asking what will become of their jobs as AI advances. He suggests that people who value making things, solving problems and seeing others use what they build may be able to preserve those motivations even if the tools or tasks change. He does not claim that coding jobs are safe or that every worker can make a similar move.
Purpose Beyond Writing Code
The essay speaks to a practical concern for developers: which parts of their work matter most if AI changes how software is produced. Darcemont’s distinction is between a job’s method—writing code—and its broader purpose, such as building useful products or solving problems for other people.
That framing can help readers think about adaptation without treating technological change as either a guaranteed disaster or an easy opportunity. But the account is one family’s experience. It cannot establish how widespread job changes will be, whether displaced developers will find comparable roles, or how quickly employers will adopt AI tools. The essay’s value is as reflection, not as a forecast or labor-market study.
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From Horse Work to Motors
Darcemont compares the present discussion of AI with earlier changes in transport and agriculture. He points to the arrival of cars and tractors as examples of technologies that affected people’s work locally, before modern social media could spread anxiety and speculation. His comparison is intended to remind readers that people facing new machinery also had reasons to worry about their livelihoods.
He also makes a limit of the family story explicit: not every farrier became a mechanic. Darcemont acknowledges that he may know his ancestor’s story precisely because it ended in a path that continued through the family. The source gives no dates for the career change and no independent records of the ancestor’s circumstances, so the account should be read as a family recollection rather than a documented history of the wider trade.
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Limits of the Family Analogy
The source does not provide a publication date, a precise timeline for the ancestor’s career change, or documentation beyond Darcemont’s family account. It also does not include employment data, interviews with other developers, or evidence about AI’s effects on software jobs.
It remains unclear how AI will alter developers’ roles, which tasks may change, and whether workers whose jobs are affected will be able to move into work that uses their existing skills. Darcemont presents these questions as open; he does not say his ancestor’s experience predicts their answers.
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Questions for Developers Ahead
Darcemont’s essay does not announce a policy, product or research milestone, and it does not set out a concrete next step for the industry. Its immediate invitation is reflective: developers can ask what they value about their work beyond the act of coding, and which parts of that purpose might carry into different tools or roles.
For a clearer picture of AI’s effects, readers will need evidence beyond personal histories, including reporting on workplace adoption, hiring, job changes and workers’ experiences. Until such evidence is available, the family story remains a personal lens on uncertainty, rather than a measure of what comes next.
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Key Questions
What is the essay about?
Developer Manuel Darcemont recalls that his great-great-grandfather moved from farriery to mechanics as cars replaced horse-powered transport. He connects that family story with current concerns about AI and software work.
Does Darcemont say AI will replace developers?
No. He describes developers’ anxiety about what AI may mean for their work, but does not predict the scale of job losses or claim that developers will all find new roles.
What does the author say stayed the same?
Darcemont says the family retained a purpose of helping people get around, even as its work shifted from caring for horses to repairing vehicles.
Does the family story prove workers can adapt to technology?
No. Darcemont explicitly notes that not every farrier became a mechanic and says his family’s experience does not prove what will happen to workers facing AI-related change.
What is Darcemont’s advice to developers?
He encourages people to stay open to changing how they work while holding on to the purpose behind it, such as making things, solving problems and helping others use what they build.
Source: hn
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