AI may be giving some people in technology a reason to build something of their own or explore work beyond the industry. That is a hopeful possibility, not a proven general outcome: exposure to AI does not mean a job has disappeared, and leaving tech is not automatically a freer or happier choice.
What the hopeful argument gets right—and what it cannot prove
In a September 16, 2026 essay, James Anderson reflects that pressure in technology could lead some people to redirect their skills toward independent projects, small businesses, crafts, teaching, or a mix of technical and non-technical work. His central idea is an invitation to imagine another path, not a labor-market finding: the essay offers personal observation rather than a survey or verified account of how often workers make these transitions or whether they are better off afterward. Read Anderson’s essay.
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That distinction matters. A possibility can be worth considering without turning into a promise that AI will push people out of tech—or that pressure reliably produces a better life. The same change can open a door for one person and narrow another person’s options.
AI exposure is not the same as job loss
The International Labour Organization’s 2025 update estimates that “One in four workers across the world are in an occupation with some degree of GenAI exposure.” The estimate concerns exposure at the occupational and task level; it does not mean that one in four jobs will disappear. The ILO assesses that most jobs are more likely to be transformed than made redundant, in part because human input remains necessary. That assessment does not rule out displacement for particular workers or occupations. See the ILO’s 2025 update.
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The OECD likewise says the precise effects of generative AI on job creation and displacement remain to be seen. Its 2024 report on OECD regional labor markets cautions that newly created jobs may not benefit people who lose jobs due to automation. A new role somewhere in the economy is not a guarantee of a suitable role for a particular displaced worker. Read the OECD report.
What the software jobs forecast does—and does not—say
The U.S. Bureau of Labor Statistics projected software developer employment to grow 17.9 percent from 2023 to 2033, in projections published March 11, 2025. This is a U.S. occupational forecast, not a current headcount, a guarantee for each software worker, or an estimate of AI’s causal effect on jobs. It is a useful reminder that broad claims that technology work is simply vanishing need qualification, but it cannot settle what will happen to every role or career. See the BLS projection.
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Changing direction is a choice only when there is room to choose
Anderson’s comments include a practical challenge to the hopeful framing. One commenter, Jo Do, wrote, “A new path feels like choice only when there is some runway, health coverage, or community underneath it.” The author agreed that the effects are uneven. These are individual comments, not representative evidence, but they highlight constraints that any real career decision has to account for: income, healthcare, family responsibilities, training access, and support from other people. Read the essay discussion.
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- Income and benefits: What happens to reliable earnings and healthcare coverage during a transition?
- Runway and support: How much time can you spend exploring before you need the next source of income, and who can help?
- Retraining: What time and money would learning a new field require?
- Skill transfer: Which technical, communication, or problem-solving skills carry into the work you want to try?
- Small experiments: Can you test interest or demand with a limited project before making a major commitment?
These are decision questions, not a ranking of career paths. The essay does not provide comparable outcomes for its examples, so no one route—starting a business, teaching, making things, or combining fields—can be called best on its evidence.
The apprenticeship question is still open
A commenter also asks where future senior engineers will gain judgment if junior tasks that once provided early experience are automated. It is a consequential question about how people learn a profession, but the discussion does not establish that a particular apprenticeship route has already disappeared. Treat it as an unresolved challenge, not a settled prediction about engineering careers.
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A useful question, not a forecast
Anderson ends by asking: “if the path you’re on disappeared tomorrow, what’s the thing you’d finally let yourself build — or become?” It can be a worthwhile prompt for reflection, provided it is not mistaken for advice to quit or for evidence that an easier path is waiting. AI may prompt some people to explore beyond tech; whether that becomes a viable choice depends on both their circumstances and the opportunities available to them.
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