150,000 Tech Workers Laid Off in 2026 While Companies Post Record Profits: The AI Excuse

Something changed in 2026. Companies are no longer blaming layoffs on the economy, post-pandemic corrections, or market downturns. They are blaming AI. And they are doing it while posting record revenue.

The numbers

Through mid-June 2026, 363 layoff events have affected roughly 150,000 tech workers, approximately 974 people per day. Last month alone saw 40,000 cuts. AI has been cited as the primary driver across all industries for three consecutive months (ByteIota).

But here is what makes 2026 different from every previous layoff cycle: these companies are profitable. Many are posting record numbers.

Source: HeroHunt.ai, CNBC

Cloudflare is the clearest example. They cut 1,100 people, 20% of their workforce, in the same earnings call where they reported record quarterly revenue of $639.8 million, up 34% year-over-year. Their internal AI usage had increased 600% in three months. CEO Matthew Prince said it was not a cost-cutting exercise. It was about "defining how a world-class company operates in the agentic AI era" (TechCrunch).

Block went further. Jack Dorsey cut 40% of the workforce. The stock soared 24% the same day. Block posted $2.87 billion in gross profit that quarter, up 24% (CNN).

These are not distressed companies cutting costs to survive. These are profitable companies replacing humans with AI and telling shareholders about it.

What the CEOs are saying

The rhetoric has shifted from hedging to explicit.

Dario Amodei (Anthropic CEO) predicted AI would write "90% of code in 3-6 months" and "essentially all of the code in 12 months" (Yahoo Finance). That timeline has passed. It did not happen at the scale he described.

Mark Zuckerberg said "probably maybe half the development is going to be done by AI" at Meta within a year. Satya Nadella confirmed over 30% of Microsoft's code is AI-generated, targeting 60% by 2026 (TechTimes). Sundar Pichai said 75% of new Google code is AI-generated (Fast Company).

Then there is Jensen Huang. The Nvidia CEO pushed back: "If we convinced all the young college graduates to not be software engineers, and it turns out the United States needs more software engineers than ever, that's hurtful." He accused some CEOs of having a "God complex" about AI apocalypse warnings (Fortune).

Notice the pattern. The companies that sell AI (Anthropic, OpenAI) push the "AI replaces workers" narrative hardest. That narrative drives adoption of their products. The companies that need engineers to build AI features (Google) or sell hardware to make AI possible (Nvidia) are more measured. Follow the incentives.

The "AI wrote half our code" problem

Freshworks CEO Dennis Woodside said "over half our code is written by AI." This is almost certainly true if you measure by lines generated. It is also almost entirely misleading.

If AI writes 100 lines of boilerplate and a human writes 10 lines of critical business logic, AI wrote "91% of the code" but the human wrote most of the value. Lines of code is a terrible productivity metric. Every engineer knows this. The CEOs citing it either do not know or do not care.

The real job of a software engineer is not typing code. It is understanding requirements, designing systems, debugging edge cases, handling production incidents, and making tradeoff decisions. AI can generate a function. It cannot attend a architecture review, negotiate with a product manager about scope, or figure out why the payment service intermittently fails on the third retry.

The real casualties: junior engineers

The layoffs are not hitting evenly. Junior roles are being decimated.

Coinbase's restructuring eliminated "pure managers" in favor of "player-coaches" and introduced "AI-native pods" that could include one-person teams directing AI agents. That is a senior-heavy structure. There is no room for someone who needs mentorship, code review, and time to learn the codebase.

Salesforce cut approximately 5,000 customer service roles across two rounds. CEO Marc Benioff said "I need less heads" while his Agentforce product handled 1.5 million customer conversations alongside human agents (CNBC). Those customer service roles were entry-level positions.

The long-term risk is obvious. If nobody hires juniors today, there are no seniors in five years. You cannot skip the pipeline. But individual companies do not care about the pipeline. They care about this quarter.

The Oracle playbook

Oracle's layoffs are the most disturbing. According to TIME, Oracle ran a deliberate data-collection program asking employees to document their workflows to train AI systems, then used those results to make the same employees redundant. A 30-year veteran technical writer was called while driving to the hospital for back surgery and told she was laid off. $300,000 worth of her stock units vanished overnight. Oracle had posted a 95% jump in net income that quarter and committed to $156 billion in AI infrastructure buildout (TIME).

That is not AI replacing workers. That is using workers to build their own replacement, then firing them with the technology they helped create.

The whiplash

Many affected employees describe a specific kind of betrayal. Their companies spent the previous year encouraging AI adoption, providing internal training, celebrating teams that shipped features faster using AI tools. Then those same productivity gains became the justification for cutting the teams that achieved them.

The message engineers hear is: "Thank you for becoming more productive. Your reward is that we no longer need you."

This creates a chilling effect. Why would any engineer adopt AI tools aggressively if the outcome is their own elimination? Smart engineers are learning to use AI quietly, deliver results slowly enough to avoid drawing attention, and keep their productivity gains invisible.

What is actually happening

Three things are true simultaneously:

1. AI genuinely makes some roles unnecessary. Customer support, content moderation, basic QA testing, and boilerplate code generation are being automated. These are real displacements.

2. Some companies are using AI as cover for pandemic over-hiring corrections. The narrative is convenient. "AI made us do it" plays better with shareholders than "we hired too many people during the boom and are now correcting."

3. The companies cutting the most are also investing the most. Meta raised capex guidance to $125-145 billion for AI infrastructure. Microsoft set $190 billion. The four largest tech companies alone are spending a combined $725 billion on AI capex in 2026 (24/7 Wall St.). The money is not disappearing. It is shifting from payroll to GPU clusters.

What this means for engineers

If you are a software engineer reading this in 2026, here is the honest takeaway:

• AI is not replacing engineering. It is replacing tasks within engineering. The engineers who adapt will be fine. The ones who refuse to use AI tools will not.
• Junior roles are the most vulnerable. If you are early career, focus on skills AI cannot replicate: system design, cross-team communication, domain expertise, and debugging complex production issues.
• "Percentage of code written by AI" is a marketing metric. Do not let it panic you. Code generation is the easiest part of engineering.
• The companies cutting workers while posting record profits are making a bet. They believe smaller, AI-augmented teams can maintain and grow their products. Some of those bets will fail. Companies that tried full AI replacement and had to reverse course already exist (HeroHunt.ai).
• The safest position is being the engineer who can ship complete AI products end-to-end, not just call an API. Full-stack AI engineering, the kind where you control the frontend, the backend, and the model, is where the demand is heading.

The layoffs are real. The AI component is real. But "AI replaces engineers" is a headline, not a fact. The reality is messier, more nuanced, and less apocalyptic than the CEOs selling AI would have you believe.

Sources: ByteIota, HeroHunt.ai, Invezz, CNBC, TechCrunch, CNN, TIME, Fast Company, Fortune