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In a personal essay, developer Manuel Darcemont recalls that his great-great-grandfather left farriery in rural France and became a mechanic as cars replaced horses. Darcemont says the family kept its broader purpose of helping people get around, but stresses that one family story does not prove how AI will affect developers.
Developer Manuel Darcemont has described how his great-great-grandfather changed careers from farriery to mechanics as motor vehicles displaced horse transport, using the family history to reflect on developers’ concerns about AI. Darcemont says the story offers personal perspective, not proof that workers facing automation will find an equivalent path.
Darcemont writes that his great-great-grandfather worked as a farrier in Mandres-en-Barrois, a rural village in France, shoeing horses and repairing farmers’ carts. The account does not establish exactly when or what prompted his change of trade. Darcemont says the man may have seen a car in a nearby town or read about one in a newspaper, and that he later became a mechanic.
The family’s work then remained connected to transport, though the technology changed. Darcemont describes the shift as a move from horses to engines while continuing to help people get around. He recalls his father loving his work as a mechanic, and says the garage came to feel like a longstanding family tradition.
He relates that history to developers who worry about how AI may change their jobs. His argument is that some people are drawn to making things, solving problems and seeing others use what they build—not solely to writing code. But he explicitly cautions that his family’s experience cannot establish what will happen to other workers or industries.
Purpose Beyond the Coding Work
The essay speaks to a practical question raised by automation: which parts of a job are a task, and which parts are its purpose? Darcemont’s family story suggests that a person’s work can change substantially while a broader service remains. For developers, that may mean separating an interest in building useful products from attachment to one particular tool or method.
That is a reflection, not a forecast. The source gives no employment data, research findings or evidence about AI’s effects on developer jobs. Its relevance lies in offering a personal way to think about uncertainty, while reminding readers that a story about one family cannot tell us how widespread or manageable future job changes will be.
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From Horse Work to Motor Repair
Darcemont places the family’s career change against the arrival of motor vehicles in the area around Mandres-en-Barrois. He compares that shift with the introduction of tractors for farmers, arguing that technological change could be felt locally even before people had social media to follow distant debate. The essay does not provide dates, records or further detail about the transition.
He also recognizes a limit in the family history: readers hear about the ancestor who became a mechanic, not those farriers who did not make the same change. The account is therefore a personal recollection and interpretation, not a representative history of farriers or a direct comparison between early motorisation and today’s AI systems.
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What One Family Story Cannot Show
The source does not give a publication date, a detailed chronology of the ancestor’s career, or evidence documenting how the family’s work changed. Darcemont says he cannot know whether his great-great-grandfather saw a car or read about one before becoming a mechanic. That account is presented as family history, not independently verified documentation.
More broadly, the essay does not establish how AI will affect developer employment, which roles may change, or whether people can move into comparable work. It offers no evidence that the transition from farriery to mechanics is a reliable model for current technology changes. Darcemont explicitly says the success story may leave out people who did not make a similar switch.
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The Question for Developers Now
The essay offers no announced follow-up, policy proposal or prediction about the pace of AI adoption. Its next step is a question for individual readers: identify what they value about their work beyond the current tools, and consider whether those motivations could take another form.
Whether that approach will help developers respond to changes in hiring or working practices remains unknown. The source provides no timeline or employment outlook. Any broader assessment would require evidence about how organizations use AI and what happens to affected workers, beyond the family history Darcemont recounts.
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Key Questions
What happened to Darcemont’s great-great-grandfather?
According to Darcemont, he worked as a farrier in Mandres-en-Barrois before becoming a mechanic as motor vehicles replaced horse-based transport. The source does not give a precise date or a documented account of what prompted the change.
What does the family story have to do with AI?
Darcemont uses the career change to reflect on developers’ concerns about AI and whether their deeper interest is in creating and solving problems rather than coding alone. He presents this as a personal analogy, not evidence of AI’s employment effects.
Does the essay predict that developers will find new jobs?
No. Darcemont says his ancestor’s experience does not prove what will happen to other workers. The essay does not offer an employment forecast or claim that people affected by AI will find equivalent roles.
What does Darcemont say developers may value beyond coding?
He points to making things, solving problems and seeing people use what they build. His suggestion is to think about those motivations separately from the tools used to do the work.
Source: hn
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