Jack Dorsey Cut 40% of Block's Staff. Now What?

When Jack Dorsey announced Thursday that Block would be cutting 4,000 employees—40% of the company's workforce—he framed it as an unavoidable consequence of AI transformation. "The intelligence tools we're creating and using paired with smaller and flatter teams are enabling a new way of working which fundamentally changes what it means to build and run a company," he wrote in his memo to staff.

The market loved it. Block's stock surged 25% in overnight trading. But almost immediately, a different narrative emerged: This wasn't about AI at all. This was about covering up years of mismanagement with the most convenient excuse in tech.

What's interesting isn't which story is true—it's that we can't actually tell. And that ambiguity tells us something important about where we are right now.

The AI Efficiency Story Has Problems

Dorsey's memo carefully avoided using the term "AI," opting instead for "intelligence tools." Block did develop an internal AI agent called Goose last year, initially for coding but later expanded across non-technical teams. Brad Axen, Block's tech lead for AI, claimed in March that sales teams were analyzing thousands of leads "in hours instead of days" and project managers were cutting administrative time by 75%.

But if AI really enabled this level of efficiency, why did Block's headcount grow from 3,900 in December 2019 to 12,500 in December 2022? As bond investor Will Slaughter put it: "Unwinding less than half an insane COVID overhiring binge has much more to do with Jack Dorsey's managerial incompetence than whether AI is going to take your job."

The comparison to Dorsey's tenure at Twitter was unavoidable. Elon Musk cut roughly 80% of Twitter's workforce, and the platform... kept functioning. Morning Brew co-founder Austin Reef pointed out that Robinhood operates with 2,500 employees and a $70 billion market cap, while Coinbase has 4,500 employees and a $50 billion market cap. Block, even after cuts, still has 6,000 employees for a $30 billion market cap.

Dorsey eventually responded to critics, acknowledging the COVID overhiring but arguing Block was now targeting "$2 million gross profit per person, 4x our pre-COVID efficiency." Whether that's an AI story or a returning-to-sanity story remains unclear.

The "AI Laundering" Question

Economics researcher Alex Emas coined a term for what might be happening: "AI laundering, or blaming AI for layoffs you were going to do anyway."

Here's what makes this moment unusual: We don't actually have clear precedent for massive layoffs directly attributed to AI efficiency gains. Amazon CEO Andy Jassy talked about AI's long-term workforce effects last summer, but when Amazon's layoffs came, AI wasn't cited as the cause. Duolingo cut contractors after switching to AI-generated content, then backtracked. Klarna reduced headcount by 40% after adopting AI customer service bots, but later attributed it to "natural attrition" rather than layoffs.

Block represents something different—a CEO explicitly connecting a 40% workforce reduction to AI capabilities. Whether that connection is genuine or opportunistic, it creates a template.

And templates get copied.

What Happens When This Becomes Normal

The fear isn't hard to articulate. If Wall Street rewards 40% workforce reductions with 25% stock surges, and AI provides plausible cover, why wouldn't other CEOs follow? As one observer put it: "When Wall Street companies see that they can cut their employee stack by 30 to 40%... and see that their stock pumps like this and just blame AI, easy mode."

Dorsey himself seems to believe this is inevitable. On Thursday's earnings call, he told investors: "Within the next year, I believe the majority of companies will reach the same conclusion and make similar structural changes. I'd rather get here honestly and on our own terms than be forced into it reactively."

But here's where the story gets complicated. Amanda, who works in developer relations at Block, offered a sobering perspective: "Every single person I met at Block was using and making an impact with AI at levels on the forefront, not just devs. And in my team, AI was an ingrained part of our work, all of us. Not trying to scare anyone, but that's not it. Teams are getting leaner, period. You do need to master this tooling, but that alone will not make you stand out or protect you."

If true, that's actually more unsettling than the "learn AI or get fired" narrative. It suggests we're not in a skills gap problem. We're in a structural shift where the same work simply requires fewer people, regardless of how proficient those people are with the tools.

The Repricing

What we're watching is a massive collective recalibration. Dorsey mentioned something that keeps coming up in AI discussions: "Something happened in December of last year where the models got an order of magnitude more capable and more intelligent." Whether that's objectively true or represents a psychological threshold, it's affecting decision-making across the industry.

Companies are making dramatic moves—40% cuts, $40 billion market cap swings—not because they have clarity about where AI is heading, but because they don't. The uncertainty itself is driving action. Executives would rather be early (or appear early) than be caught flat-footed.

The question isn't whether AI enables these efficiency gains. In many cases, it probably does. The question is: Are we making decisions based on what AI can actually do today, or based on what we're afraid it might do tomorrow? And if everyone's acting on fear of being late, what happens when all those bets come due?

Block's stock jump might look prescient in a year. Or it might look like the market pricing in a story it wanted to believe. Right now, genuinely, nobody knows.

Marcus Chen-Ramirez is a senior technology correspondent for Buzzrag, covering AI, software development, and the intersection of technology and society.