Tech layoffs hit their highest single-month total in years this May, with AI cited as the leading cause by Challenger, Gray & Christmas—yet SignalFire's hiring data tells a different story. The venture firm tracked millions of employees across 80 million companies and found that engineers are actually gaining ground inside tech's reset rather than being swept out by it. Total large-tech company hiring sits 25% below 2019 levels, but engineering roles are down only 11%, and at the twelve "Tech Majors"—Alphabet, Meta, Apple, Amazon, Microsoft, Netflix, NVIDIA, Tesla, Uber, Airbnb, Block, and Stripe—engineers now represent 55% of new hires versus 46% in 2019. Early-stage startups have even pushed engineering hiring 7% above 2019 baselines.

The Gap Between Layoff Rhetoric and Hiring Reality

SignalFire's head of research Asher Bantock put it plainly: "The rationale given for lots of layoffs is consistently AI, and specifically they'll say AI with respect to code; they'll say one engineer could do the job of however many engineers in the past. What we're seeing on the ground is a little inconsistent with that." The firm argues hiring data captures priorities more cleanly than layoff statistics, since laid-off workers often delay updating employment status. Companies keep invoking AI when they cut jobs—yet those same companies are still funneling headcount toward software builders even as total tech hiring contracts.

Jevons Paradox in Action

The most compelling frame is that AI coding tools are improving the unit economics of software work, not erasing it. When a resource becomes more efficient, demand for it can rise because people find new uses for the cheaper capacity—classic Jevons paradox. Bantock described what SignalFire sees on the ground: "They're suddenly a lot more productive, and there's endless work for them to do." Nvidia CEO Jensen Huang made a similar point at Stanford's Graduate School of Business in April, rejecting claims that AI will destroy software engineering jobs and noting his own engineers are using agentic AI and remain "busier than ever." The shift appears real: routine coding and boilerplate work faces pressure, but architecture, system design, agent oversight, and product judgment still require human ownership.

Broader Labor Market Data Supports the Nuance

Yale Budget Lab's analysis across the entire economy found no clear links yet between AI exposure and unemployment following ChatGPT's release. The occupational mix is changing somewhat faster than historical norms, but not dramatically—and researchers say better data is still needed. Anthropic's own economics team offers a split message that reflects this uncertainty. CEO Dario Amodei warned last year that AI could wipe out half of entry-level white-collar jobs and push unemployment to 20% within five years, yet head of economics Peter McCrory told TechCrunch in March: "There's at least no larger material difference in unemployment rates" between workers using Claude for automated tasks versus those in less AI-exposed roles requiring physical interaction. The headline risk is real; the measured labor impact remains uneven.

What This Means for Builders and Founders

For founders, the SignalFire data supports a narrow but useful point: small teams can do more with AI, but early-stage startups still hired significantly more engineers in 2025 than in 2019, suggesting technical talent remains central when companies are building product rather than only managing growth. For experienced developers who can direct AI tools effectively, reach is expanding—individual contributors can own more ground and deliver more output than the pre-AI baseline. The pressure concentrates where work is repetitive and easy to specify; resilience appears strongest for engineers owning architecture, production reliability, and cross-functional judgment.

Key Takeaways

  • Engineering roles are down 11% from 2019 versus 25% for total tech hiring—engineers are gaining share of a shrinking pie
  • At the twelve largest tech companies, engineers went from 46% to 55% of new hires over six years
  • Early-stage startup engineering hiring is actually 7% above 2019 levels
  • AI coding tools appear to be raising output and creating more work rather than eliminating the function

The Bottom Line

The narrative that AI is eating software jobs doesn't match where companies are actually spending scarce headcount. Engineers who can direct, review, integrate, and own systems remain in demand—the ones getting squeezed are routine implementation roles that AI can specify away. If you're building with these tools rather than just using them, the market still wants you.