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Scan for outdated or missing drivers - takes under a minuteDriver Scan →Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →No. The current evidence does not support the idea that coding jobs as a whole will disappear by October 2029. The latest U.S. Bureau of Labor Statistics (BLS) projection for software developers expects employment to keep growing through 2035, and Federal Reserve researchers found that employment among coding-intensive occupations slowed after ChatGPT arrived but kept growing. Neither finding guarantees any particular job, and neither is a three-year forecast. What the evidence does support is a narrower conclusion: coding work is changing, and the pace of hiring is uncertain.
What the three-year question actually asks
The headline combines three terms that need to be pinned down before the answer means anything.
- “Coding jobs.” Coding is a task, not an occupation. Most of the labor-market data covers software developers, a broad BLS category. Programming-intensive roles such as some data, web and QA positions overlap with it but are measured differently. A decline in one narrow role does not equal the end of the category.
- “Cease to exist.” This is a much higher bar than shrinking. Employment can fall, hiring can slow, and wages can change while millions of people still write code for a living. The evidence below speaks to growth and slowdown, not to elimination.
- “In three years.” Three years from today is October 2029. The BLS projection most relevant here runs from 2025 to 2035, so it describes a ten-year path and does not produce a year-by-year number for 2029.
Reader wording varies, but most versions of this question collapse into the same concern: “Will AI replace programmers?”, “Will software developers lose their jobs to AI?” and “Is coding still a good career?” Each of these depends on the same evidence, though they ask for different things.
What the latest employment projection says
The BLS projections, displayed through O*NET OnLine (which cites BLS data from 2026), cover software developers in the United States from 2025 to 2035. The key figures are:
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- Projected employment growth of 10 percent over the decade.
- About 1,717,800 software developer jobs in 2025, rising to a projected 1,892,600 in 2035.
- 95,300 projected job openings per year. Openings include replacement of workers who leave, not only new positions, so they are not a count of net new jobs.
These are projections of employment levels. They are not estimates of how much AI causes any change, and they do not predict whether a specific person will be hired. The source is at O*NET OnLine’s software developer trends page, and the BLS program overview is at bls.gov/emp.
What the Federal Reserve study found
In a March 2026 paper, AI and Coder Employment: Compiling the Evidence, Federal Reserve economists Leland D. Crane and Paul E. Soto examined coding-intensive occupations around the time ChatGPT was introduced. Their conclusion is specific: “Coder employment has continued to grow in recent years, though much more slowly than it did pre-2022.”
That sentence contains the core of the answer. Growth slowed, and it did not stop. The authors describe their conclusions as their own views and their work as preliminary. The paper also does not prove that AI alone caused the slowdown, since hiring also responds to interest rates, the post-2021 tech hiring correction and other pressures. The full paper is at federalreserve.gov.
What BLS says about AI and the work itself
BLS separates the tasks in a job from the job itself. Its occupational case study on computer occupations, published in February 2025, notes that developers can use generative AI to write, test and document code, to improve data quality and to draft user stories. That describes task exposure: parts of the work can be assisted or sped up.
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The same study identifies forces pulling in opposite directions:
- Higher productivity could lower software prices and increase demand for software, which supports employment.
- Businesses may need developers to build AI-based products and to maintain AI systems, which also supports employment.
- Fewer hours may be needed per unit of output, which weighs on employment.
BLS concludes that the net effect is highly uncertain, in its words: “The effects of AI proliferation on this occupation are highly uncertain.” Note that this case study used information available in June 2024 and the earlier 2023–33 projection. It is useful for its task analysis and its account of uncertainty, but it is not the current forecast. It is available at bls.gov’s Monthly Labor Review article on AI impacts in employment projections.
Comparing the evidence
The three main sources answer different questions, and they should not be read as a single forecast.
| Source | Evidence type | Scope | Date | What it can and cannot tell you |
|---|---|---|---|---|
| BLS employment projections (via O*NET) | Projected employment levels and openings | United States, software developers | Displayed 2026; covers 2025–35 | Shows the expected ten-year direction. Cannot isolate AI’s effect or give a 2029 figure. |
| Federal Reserve paper (Crane and Soto) | Observed employment trends around ChatGPT’s introduction | United States, coding-intensive occupations | March 2026 | Shows growth slowed after 2022 but continued. Cannot prove AI is the sole cause. |
| BLS AI case study | Task-level analysis and scenario reasoning | United States, computer occupations | Published February 2025; uses June 2024 information | Explains which tasks AI touches and why the outcome is uncertain. Not a current forecast. |
Where the evidence stops
Several gaps matter for a reader making decisions:
- Geography. These sources cover the United States. They do not establish what happens in other labor markets, where hiring, wages and outsourcing differ.
- Career stage. The data does not separate entry-level programmers from experienced developers, so it cannot confirm or rule out a squeeze on new graduates.
- Time horizon. The projection runs to 2035 and the observed trend is measured over recent years. Neither is a precise 2029 prediction.
- Causation. Observed slowdowns and projected growth both reflect many forces at once. Attributing them to AI requires more than these sources provide.
What this means for your money plans
The evidence points to planning for change rather than planning for disappearance. A few practical steps follow from that:
- Stress-test income for a slower hiring market. Assume that finding a new role may take longer than it did before 2022, and keep enough cash to cover that period.
- Keep skills adjacent to the work. The BLS case study points to demand for people who build and maintain AI systems, and for people who define requirements and check output. Skills in those areas are less exposed to task automation than routine implementation alone.
- Watch the indicators that actually move. The most useful signals are the BLS projection updates, the Federal Reserve’s follow-up work on coder employment, and openings data for entry-level roles in your own region.
- Avoid decisions based on the headline. A single three-year prediction cannot support large irreversible choices, such as leaving a career entirely or taking on debt to retrain, without a specific reason beyond the headline.
Coding remains a large occupation with a projected rise in employment, but the path into it is less predictable than it was. Plan for a more competitive market and a changing mix of tasks, not for an abrupt end.
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