In a recent Guardian piece, Varsha Bansal reports on how AI disruption has triggered major layoffs across the tech industry and left many software engineers underemployed. Software engineering, once among the best-paying professions in the US with reliable upward mobility, is changing faster than the rank-and-file anticipated. Bansal spoke with more than a dozen engineers who described frustration, anxiety, and a scramble to adapt as the value of their skills becomes unclear.
Below are key highlights from the Bansal’s article:
- The scale of the disruption. Bansal reports that more than 600,000 US tech workers have lost their jobs since ChatGPT’s release in 2022, per Layoff.fyi. Unemployment among computer science graduates rose to 7% in 2024, with underemployment above 19%, and US tech job postings fell 36% between 2020 and 2025. Google now says 75% of its code is written by AI. Matt, an engineer who asked not to be named, told Bansal his job has shifted from coding and architecture toward reviewing AI-generated code. He spends his four-hour train commute building a browser game by hand to stay sharp. “I am actively trying to keep my axe sharp,” he said.
- Adapting to the AI era. Bansal profiles George Dover, a six-year software engineer laid off from Intuit Mailchimp in late 2024, who took work as a substitute kindergarten teacher while job hunting. Rather than give up, he taught himself to evaluate AI-generated code, checking for errors, redundancies, bugs, and security gaps. Nearly two years and 400 applications later, he landed a software engineering role oriented toward AI. Experts told Bansal this is where the profession is heading. “It’s clear that the skill of writing code is over,” said Bouke Klein Teeselink of King’s College London. Wharton’s Ethan Mollick agrees the work has shifted rather than vanished: the value now lies in defining problems, designing systems, and directing AI tools well. Harvard’s David Malan adds a practical reason humans will remain: AI is expensive, and companies are likely to settle on a balance of engineers supported by AI rather than replaced by it.
- The highs and lows of coding. Bansal traces the arc from the 2013 “learn to code” boom, when President Obama launched a $4bn Computer Science for All initiative and bootcamp enrollment exploded, to the disillusionment now setting in. Sam, a Los Angeles engineer who pivoted into the field a decade ago, told Bansal that AI has taken over “the creative, fun part of the job” and left him with the worst part: reviewing code he didn’t write. He fears a layoff would end his career entirely. “I’m thinking as I sit in my office, ‘What if I opened a food truck? What if I got into forestry?’” he said. The mood is showing up in the numbers: undergraduate computer science enrollment fell 8.1% and graduate enrollment dropped 14% in the 2025-2026 school year.
- Tech workers unite in their plight. Bansal reports that engineers are increasingly organizing. Kaitlin Cort quit her job and founded What We Will, a resource center helping tech workers navigate layoffs, negotiate severance, access unemployment support, upskill, and organize unions. “I can see that the pace at which AI was getting better was faster than the pace at which I was getting better,” she told Bansal. The center has run campaigns supporting workers at Amazon, Oracle, and Meta, and Cort now receives at least 10 applications a day, with rising interest in unionization specifically. She is building largely without precedent. “We just, as an industry, don’t have a guild,” she said. “We don’t have regulations or standards that are really shared.”
Bansal paints a vivid picture of a profession being transformed from within. Its practitioners are neither obsolete nor secure, but they are refusing to wait for the inevitable. They sharpen their skills on train rides, teach themselves to audit the machines that have replaced them, and, for the first time, openly ask whether the industry that once encouraged a generation to learn to code owes them anything in return.
Acknowledgement: This summary was generated using AI writing tools as part of my experimental learning process. For more information, check out the original article listed below.