When Block Cuts Half Its Workforce, There Are No Villains in the AI-Driven Wave of Job Losses
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When Block Cuts Half Its Workforce, There Are No Villains in the AI-Driven Wave of Job Losses
2028 Global Intelligence Crisis: The First Chapter in Reality
Navigating Web3 tides with focused insightsBy: Yellow Lobster, TechFlow
On February 22, an article titled “The 2028 Global Intelligence Crisis” went viral across financial circles. Authored by macroeconomic research firm Citrini Research, the piece takes the form of a “memo from the future,” set in June 2028, retrospectively tracing how an AI-triggered economic crisis gradually escalated into systemic collapse.
One sentence in the article reads: “In early 2026, the first wave of layoffs—triggered by human intelligence being replaced—began. Profits expanded, earnings exceeded expectations, and stock prices hit record highs.”
Four days later, that sentence was no longer a thought experiment.
On February 26, Jack Dorsey posted on X: “we're making @blocks smaller today.”
Block—a fintech company housing Square and Cash App—released its Q4 earnings that same day. Gross profit rose 24% year-on-year; earnings per share surpassed analyst expectations. Simultaneously, Dorsey announced layoffs of over 4,000 employees—46% of Block’s total workforce.
Upon the announcement, Block’s stock surged 24% after hours.
The company’s earnings rose 24%. Its stock price rose 24%. And 4,000 people received termination notices.
Citrini’s “2028 nightmare” didn’t wait until 2028—it began its first act this past Thursday.
We’re Not in Trouble
Historically, every major round of layoffs has followed a predictable CEO letter formula: “Market conditions are challenging. Our strategic direction is shifting. We’ve made a difficult decision. We thank every colleague for their contributions.”
Dorsey’s letter broke the mold.
“We’re not in trouble. Our business is strong… but something has changed. Internally, we’ve observed that smaller teams—working alongside the intelligent tools we’re building and deploying—can do more, and do it better. And the capabilities of these tools are compounding week after week.”
No mention of a market winter. The company is thriving—yet you’re no longer needed. This candor is unsettling.
Previous layoff narratives carried an implicit promise: “When the market recovers, we’ll rehire.” This time, Dorsey offered no such assurance. Instead, he presented a new logic: Small teams augmented by AI can accomplish what large teams once did—and even more. So why retain so many people?
Investors fully endorsed this logic—voting with a 24% stock price surge.
There’s another detail, perhaps overlooked.
To instill an “AI-first” work culture, Dorsey previously required every employee to email him weekly listing five recent accomplishments. Thousands of emails flooded in—and Dorsey processed them using AI to generate summaries, which he then read.
Using AI to assess who can prove they won’t be replaced by AI—and letting AI determine who gets laid off—this detail is the most precise metaphor for the entire story.
A Timeline, An Acceleration
Block is no outlier. It’s the latest manifestation of a trend already two years in motion.
Step back, and the acceleration along this trajectory is dizzying.
In 2024, Klarna CEO Sebastian Siemiatkowski publicly declared that the company’s AI customer service assistant handled work equivalent to that of 700 full-time employees. At the time, most dismissed it as a tech showcase—a headline-grabbing number, a story to convince investors.
In April 2025, an internal memo from Shopify CEO Tobi Lütke leaked. One line, later widely quoted, stated: “Before requesting additional headcount, teams must first demonstrate that the task cannot be performed by AI.”
That same year, Duolingo announced its “AI-first” strategy and terminated numerous content creation outsourcing contracts. IBM acknowledged replacing 8,000 HR roles with AI; CEO Arvind Krishna, in interviews, named the specific department and headcount without hesitation.
Salesforce cut 4,000 customer support positions. CEO Marc Benioff stated: “AI now handles roughly half of the company’s work.”
By end-2025, U.S. employment tracker Challenger, Gray & Christmas reported over 55,000 layoffs directly attributable to AI.
In early 2026, Amazon announced two rounds of corporate job cuts totaling ~30,000 positions. Law firm Baker McKenzie followed closely, eliminating 600–1,000 research, marketing, and administrative support roles—an industry long considered one of AI’s hardest-to-penetrate fortresses.
On February 26, 2026: Block. A profitable company. A single-round layoff of 46% of its workforce.
But layoffs are merely the most visible blade.
A Harvard study revealed a subtler statistic: After AI adoption, tech firms reduced hiring of entry-level staff by an average of five people per quarter. No announcements. No press releases. Job postings quietly vanished from recruitment sites. New graduates’ applications disappeared into silence—never explained in rejection letters.
Citrini’s Spiral
Return to the viral article.
What makes Citrini’s scenario so unsettling isn’t just its dystopian portrait of AI sweeping through labor markets—it’s its depiction of a logically coherent, entirely rational death spiral.
Here’s how the spiral operates:
AI expands corporate profits. Those profits are reinvested in AI—more investment yields stronger AI capabilities. Stronger AI renders more jobs replaceable. More unemployment means less consumer spending. Shrinking demand pressures more companies to adopt AI to cut costs further—advancing AI capabilities yet again.
Citrini dubbed this loop the Intelligence Displacement Spiral.
They wrote: “Each company’s individual decisions are rational. The collective outcome is catastrophic.”
Now compare this to what unfolded at Block that day: gross profit up 24%, stock price up 24%, 4,000 people laid off—the savings redirected into AI tools. From Dorsey’s perspective, it was a perfectly rational decision. He even explained in his open letter why he opted for one massive layoff instead of multiple phased reductions: because the latter would continuously erode morale and trust.
From a corporate governance standpoint, it’s textbook execution. From the perspective of those 4,000 individuals, it’s life shattered.
Citrini’s narrative includes a real person (anonymized): a friend who served as a senior product manager at Salesforce, earning $180,000 annually, and lost his job in the company’s third round of layoffs in 2025. After six months of searching, he found no comparable role—and eventually began driving for Uber, reducing his annual income to $45,000.
This isn’t just one person’s story.
Citrini performed a simple multiplication in the article: multiply this individual’s trajectory by the hundreds of thousands of white-collar workers facing similar fates across major cities—and consumer demand contraction ceases to be abstract macro data. It becomes a foreseeable, quantifiable reality.
This story is unfolding globally—in real time—perhaps even around you and me.
No Villains to Identify
Citrini’s article states:
“Historical disruption models hold that incumbent firms resist new technologies, only to be incrementally displaced by agile new entrants—eventually collapsing. Kodak, Blockbuster, and BlackBerry followed precisely this path. But 2026 is different: incumbents aren’t resisting—not because they welcome change, but because they cannot afford the cost of resistance.”
This is the key to understanding the entire situation.
Klarna was disrupted by AI—so it deployed AI to cut costs and shed staff. Salesforce’s software products faced AI-driven competition—so it replaced 4,000 customer support agents with AI. Block was swept up by AI’s wave across fintech—so it announced AI-powered organizational restructuring, cutting nearly half its workforce.
These firms weren’t victims defeated by AI. They’re AI’s most aggressive adopters—and the ones defeated are their own employees.
This is the part most resistant to moral framing.
After the 2008 financial crisis, people knew whom to blame: Wall Street bankers, traders packaging toxic mortgage bonds, regulators failing in oversight. Anger had concrete targets—even physical addresses—sparking Occupy Wall Street.
This time is different.
It’s hard to claim Dorsey acted wrongly—Block’s stock price tells you what the market thinks. The 4,000 laid-off employees also did nothing wrong; they simply occupied roles undergoing structural redefinition. AI itself is certainly no villain—it’s merely a tool, improving at a pace unprecedented in human history.
Responsibility diffuses across the entire system—like salt dissolving in water. You taste the saltiness, but you can’t locate the grain.
Two lines from Citrini’s article received little attention—but may be its deepest:
“This is the first time in history that the economy’s most productive asset has generated fewer, not more, jobs. No existing framework applies—because none were designed for a world where scarce production inputs become abundant.”
After every prior technological revolution, humanity found new roles. Steam engines displaced hand-weavers—but created railway workers, factory supervisors, and urban planners. The internet eliminated travel agencies, physical record stores, and classified ads—but birthed product managers, data analysts, and content creators. Each time, “jobs of the future” were initially unimaginable—yet they emerged, and in sufficient numbers.
This comforting pattern faces its first true challenger.
Because this time, “jobs of the future”—such as AI trainers, prompt engineers, or AI product managers—are themselves being learned and executed by AI. Workers displaced cannot simply “upskill” into AI-related roles—because those roles, too, are contracting.
Harvard researchers documented a phenomenon: After AI adoption, tech firms’ entry-level hiring dropped by over 50%. Not because those roles vanished—but because they were never created in the first place.
An entire generation trained for an industry—only to find, upon graduation, that the industry quietly decided it no longer needs entry-level humans.
We cannot pretend there’s still time to figure things out slowly.
Citrini concludes: The canary is still alive—but miners’ problems have never been whether the canary died, but whether, when it begins to falter, you know where the exit is.
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