Snap CEO Evan Spiegel dropped the news on April 15: 1,000 employees out, 16% of the company’s full-time workforce. Three hundred open positions closed. Expected savings: over $500 million by the second half of 2026.
The reason? AI now generates more than 65% of Snap’s new code. Spiegel said the company is assigning “more critical work to focused teams and AI agents.”
Wall Street loved it. Snap’s stock jumped nearly 8% on the news.
This is the clearest example yet of a public company explicitly tying mass layoffs to AI productivity. Not restructuring. Not “efficiency.” AI is writing the code, so Snap doesn’t need the people who used to.
The Running Total
Snap joins an accelerating wave. The cumulative 2026 tech layoff count has now passed 85,000 workers, with roughly 48% of Q1 cuts attributed directly to AI and automation.
The biggest single hit: Oracle cut up to 30,000 employees on March 31 to redirect an estimated $8 to $10 billion toward AI data center construction. Employees across the U.S., India, Canada, Mexico, and Uruguay received termination emails at 6:00 a.m. with no prior warning.
Goldman Sachs continues to track a net loss of about 16,000 U.S. jobs per month to AI — roughly 25,000 eliminated through substitution, 9,000 created through augmentation. The pain remains concentrated on entry-level positions and workers under 25.
But Here’s the Plot Twist
Two days after Snap’s announcement, a different story broke: companies are quietly rehiring the workers they laid off because of AI.
The numbers are striking. According to a Robert Half study, 29% of companies that laid off workers after implementing AI have already rehired them. A broader survey found 55% of companies now regret their AI-driven cuts, with about half quietly reversing them within six months.
It’s being called the “boomerang” trend, and the reasons are practical. Only about one in five companies said AI fully replaced the eliminated roles without operational issues. The rest discovered that AI couldn’t handle the judgment calls, edge cases, and institutional knowledge that experienced workers carried.
The rehires aren’t cheap. Nearly a third of HR leaders reported losing critical skills and expertise permanently. Companies that cut aggressively are now paying premiums to win people back — often at higher salaries than before, with permanent damage to their employer brands.
Forrester predicts roughly half of 2026’s AI-attributed layoffs will be reversed in some form by year’s end.
The Split That Keeps Widening
The market has fractured into two lanes. In one, companies rush to cut headcount to fund AI infrastructure and impress Wall Street. In the other, they’re paying more than ever for people who actually know what they’re doing.
PwC’s AI Jobs Barometer found a 56% wage premium for roles that require AI skills versus the same roles without. Senior LLM specialists are commanding $240,000 to $350,000. Over 75% of AI job listings now seek domain experts with focused deep knowledge rather than generalists.
Meanwhile, entry-level developer roles have declined 20% to 35% globally in the past year. The class of 2026 is graduating into the worst entry-level market in decades.
Same technology. One group gets raises. The other gets rejection emails.
What This Means
Snap’s layoffs and the boomerang trend aren’t contradictions. They’re two phases of the same cycle.
Phase one: companies get excited about AI productivity numbers, cut headcount, and watch the stock price tick up. Phase two: they discover that AI-generated code still needs experienced developers to review, debug, and architect systems around it. That Snap’s AI writes 65% of new code doesn’t mean it replaced 65% of engineering work — someone still decides what to build, catches the bugs AI introduces, and maintains the systems.
The companies that learn this early save money. The ones that don’t end up in the boomerang column, paying more to undo cuts they celebrated months earlier.
What You Can Do
If you’re established in your career, the market wants you. AI skills plus domain expertise is the most valuable combination in tech right now. Learn the tools, but don’t panic — your experience is exactly what AI can’t replace.
If you’re just starting out, the honest truth is harder. Entry-level roles are contracting and won’t recover to 2022 levels. Focus on areas where AI creates more work than it eliminates: AI governance, security, infrastructure, and roles that require hands-on interaction with physical systems. Build a portfolio that shows you can work with AI to produce results a tool alone can’t.
If you’re a manager deciding headcount, look at the data before swinging the axe. More than half the companies that made AI-driven cuts are regretting them. The savings look good on a quarterly earnings call. The rehiring costs, lost institutional knowledge, and brand damage show up later.