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Recent computer science graduates are facing a difficult transition into tech work, but the reported evidence does not show that AI alone caused the slowdown. A New York Times report published Aug. 10, 2025, described prolonged job searches, repeated rejections and automated screening concerns; GeekWire summarized the story the next day. Together, the accounts point to several pressures—fewer entry-level openings, layoffs and possible automation—rather than one proven explanation.
What the reports say about new graduates’ job searches
The New York Times said more than 150 students and recent graduates responded to its questions. Their accounts included applications to companies, nonprofits and government agencies, coding assessments, live-coding interviews, long stretches without replies and fallback work. These are reported experiences, not a representative survey: the article does not establish that respondents reflect all new graduates.
One especially stark example was Zach Taylor, an Oregon State University graduate. He told the Times he had applied for 5,762 tech jobs after graduating in 2023, received 13 interviews and had no full-time offer at the time his experience was reported. That is one person’s account, not a typical-outcome estimate. Taylor said, “It is difficult to find the motivation to keep applying.” (The New York Times, Aug. 10, 2025)
Unemployment figures reported in 2025
The Times attributed figures to a Federal Reserve Bank of New York report showing unemployment rates of 6.1% for computer science graduates and 7.5% for computer engineering graduates ages 22–27. It compared those rates with 3% for biology and art history graduates. These are figures cited in the 2025 article, not current 2026 labor-market data; the article does not provide enough information to treat them as a forecast or as a measure of every graduate’s job prospects.
How much of the difficulty is caused by AI?
AI may be part of the story, but the reporting does not establish that it caused the overall hiring slowdown or any named applicant’s rejection. It describes two distinct possible effects: AI coding tools may reduce demand for some junior software-engineering work, while employers may use AI systems to scan résumés or screen applicants. A third use runs in the other direction: job seekers are also using AI to tailor résumés and complete applications.
Automation and entry-level work
Matthew Martin, a U.S. senior economist at Oxford Economics, told the Times: “The unfortunate thing right now, specifically for recent college grads, is those positions that are most likely to be automated are the entry-level positions that they would be seeking.” That is an attributed assessment about exposure to automation, not proof that AI eliminated a specific number of jobs or explains the labor-market conditions as a whole.
Automated screening and the applicant experience
Some graduates told the Times they worried that automated screening removed human judgment from the first stage of hiring. Audrey Roller, a Clark University data science graduate, said: “Some companies are using A.I. to screen candidates and removing the human aspect,” adding, “It’s hard to stay motivated when you feel like an algorithm determines whether you get to pay your bills.” The report does not show that a screening algorithm rejected Roller or another named graduate.
The distinction matters for job seekers: an automated system may affect how an application is processed, but a silent rejection does not reveal why it happened. The accounts describe frustration and uncertainty, not a documented causal audit of employers’ screening systems.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsWhy one school’s hiring figures do not settle the wider picture
GeekWire reported a counterexample from the University of Washington’s Paul G. Allen School: university data showed Amazon hired more than 100 engineers from the latest graduating class discussed in the article, while Microsoft, Meta and Google each hired more than 20. These figures describe one school and one graduating class. They are not directly comparable with the Times’ unemployment rates or individual job-search stories, which cover different people, measures and populations.
The contrast shows why both claims can be true: some graduates may find jobs at major employers while others endure long searches, and a university’s hiring results cannot establish a national trend. (GeekWire, Aug. 11, 2025)
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What skills educators say still matter
University of Washington leaders quoted by GeekWire argued that computer science education is broader than writing code. Paul G. Allen School director Magdalena Balazinska said, “Coding, or the translation of a precise design into software instructions, is dead,” then clarified: “AI can do that. We have never graduated coders. We have always graduated software engineers.”
Professor Ed Lazowska emphasized the work around code: “Design is not dead, working in teams is not dead, figuring out what problems need to be solved — and what the right approach is to tackling those problems — is not dead, and understanding how humans are going to use and be influenced by digital technology is not dead.” These are educators’ perspectives on durable capabilities, not a guarantee that every employer will hire for the same mix of skills.
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What graduates should take from the reporting
- Do not treat a difficult search as proof that your degree has no value. The reporting contains both prolonged job-search accounts and hiring at a particular university; neither alone describes every graduate’s prospects.
- Do not assume AI explains every rejection. The sources discuss possible automation and screening effects but do not identify AI as the cause of any named applicant’s outcome.
- Read the August 2025 figures as a dated snapshot. They do not establish the state of the 2026 job market.
- Look beyond coding alone when preparing to demonstrate your abilities. The UW educators pointed to design, teamwork, problem definition, choice of approach and understanding how people use technology as important parts of software engineering.
Jamie Spoeri, a Georgetown University graduate, captured both sides of the uncertainty: “It’s demoralizing to lose out on opportunities because of A.I.,” she said. “But I think, if we can adapt and rise to the challenge, it can also open up new opportunities.” The reporting offers no guarantee about how quickly those opportunities will emerge; it does show why the answer is more complicated than either “AI took the jobs” or “graduates simply need to code more.”
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