Somebody always says it out loud first
This week: Jack Dorsey’s 40% cut, Nvidia’s numbers that didn’t satisfy, and the Microsoft AI chief who put a countdown clock on your job.
Hey there,
News moved quickly this week, and so did opinions. Three big stories came one after another, all raising the same question: what happens to knowledge workers as AI keeps advancing?
Every client conversation lately circles back to this. Not in a “sky is falling” way—just practical. What does your team actually need humans for, and what’s just inertia? The companies that take time to sort this out now will be in far better shape than the ones scrambling to react later.
At Lupa, we work with companies to hire with purpose. Before a job goes live, we dig into what the role actually needs to accomplish. That’s become more useful in 2026 than it ever was a few years ago.
Let’s get into it.
🌐 News Shortlist
1. Jack Dorsey Cut 40% of Block’s Workforce and Said Most Companies Will Do the Same
Recap: On February 26, Block — the parent company of Square and Cash App — announced it was laying off more than 4,000 employees, reducing its workforce from roughly 10,000 to under 6,000. CEO Jack Dorsey tied the decision directly to AI, writing in a shareholder letter that “intelligence tools have changed what it means to build and run a company.” The business is not in distress; Block reported $2.87 billion in gross profit in Q4, up 24% year over year. Dorsey said he expected most companies to reach the same conclusion within a year. Block’s stock surged as much as 24% on the news. Critics noted that Block more than doubled its headcount between 2019 and 2022, and some analysts attributed the cut as much to COVID-era overhiring correction as to genuine AI displacement.
Forget the headcount. The way markets responded says more: Block slashed nearly half its staff, profits stayed strong, and shares jumped 24%. Investors are favoring lean, AI-powered teams these days—even if AI isn’t doing all the work yet.
Dorsey avoided the usual corporate language. There was no mention of restructuring or realignment. He pointed to AI as the reason and acted on it. Some of this is just correcting overhiring from the COVID boom, but the way he explained it is what’s getting other boards’ attention.
If you’re running a team, pay attention to what markets actually care about right now. The companies getting rewarded are lean and know how to use AI. Hanging on to a bloated headcount from the old growth-at-all-costs playbook? That’s a harder story to sell.
Slashing staff doesn’t make AI effective overnight. Block spent years developing its own AI tools before cutting headcount. They got efficient, then made staffing changes. Companies that try it the other way around are just putting new labels on layoffs.
Advice:
Before you consider how many people AI could replace, ask yourself how much of your current work is clearly defined enough for AI to handle. Most teams need more clarity before they worry about headcount. Focus on that first.
2. Nvidia Beat Estimates by a Wide Margin — and the Stock Fell Anyway
Recap: Nvidia reported fiscal Q4 2026 results on February 25, posting $68.1 billion in revenue — up 73% year over year and well ahead of analyst estimates. Data center revenue hit $62.3 billion, up 75%. The company guided Q1 2027 revenue to $78 billion, also above expectations. Despite what one Morgan Stanley analyst called “the largest, cleanest beat and raise in the history of the semis industry,” Nvidia shares dropped more than 5% the following day. Investor concerns centered on whether hyperscaler AI infrastructure spending — forecast to approach $700 billion combined this year across Alphabet, Amazon, Meta, and Microsoft — would ultimately generate returns. China remains excluded from revenue projections due to export restrictions.
The numbers are huge, but the reaction tells you more about where we are right now.
Nvidia’s numbers would have seemed impossible a few years ago. The infrastructure and demand are real, and even Jensen Huang says agentic AI is here. But Wall Street’s focus has changed. Now, it’s all about whether these huge investments will actually pay off.
It’s a fair question. Big tech companies are investing hundreds of billions in AI. Some bets will pay off, while others might end up like the fiber glut of 1999: useful later, but too much too soon. No one really knows what’s ahead.
AI infrastructure spending keeps unlocking new capabilities, and tools that were out of reach two years ago are suddenly affordable. Plenty of teams are paying for the tech, but the real difference comes from actually using it to change how work gets done—not just letting subscriptions pile up.
The teams seeing real value from AI have changed their habits along with their tools. That takes time. You don’t get it just by springing for the new license.
Advice:
Review the AI tools your team pays for. For each tool, ask yourself what would stop working or slow down if you stopped using it tomorrow. If the answer is “not much,” you’re likely stuck in a subscription trap. Choose one workflow and rebuild it around the tool before adding more.
3. Microsoft’s AI Chief Says White-Collar Work Will Be Fully Automated in 18 Months
Recap: In an interview with the Financial Times published in late February, Mustafa Suleyman, CEO of Microsoft AI, said he expects AI to reach “human-level performance on most, if not all professional tasks” within 12 to 18 months. He listed lawyers, accountants, project managers, and marketing professionals as those most at risk. Suleyman pointed to faster computing power and the rapid changes already happening in software engineering, where he said engineers have shifted from writing code to “debugging, scrutinizing, and strategic work.” His statement came the same week as Block’s layoffs and a viral essay comparing today’s AI moment to the early days of COVID, which was widely shared and debated.
Every so often, another big AI name says something like this, the internet debates it, and then moves on. AI is going to reshape white-collar work—no question. The real issue is the fixation on an 18-month timeline and the word “automated.”
“AI can do this task” isn’t the same as “AI has replaced this job.” The gap isn’t technical; it’s organizational. Companies already have AI tools for drafting, summarizing, writing copy—you name it. But changing how work actually gets done takes much longer. The real holdup is whether leadership is willing to rethink workflows, structures, and accountability.
Suleyman knows it, too. And, of course, he works at Microsoft, which has every reason to hype this timeline. That doesn’t mean he’s wrong—but it’s something to keep in mind.
From what I’ve seen, the first roles to disappear aren’t always the easiest to automate on paper. It’s the fuzzy jobs—where no one’s sure what the person really does, value isn’t clear, and a manager can quietly hand it to AI without pushback. The well-defined, judgment-heavy roles? Those tend to stick around. The vague ones don’t.
Advice:
Take a hard look at your team. Instead of thinking about what AI could do in theory, figure out which roles actually deliver clear, uniquely human value. Can you sum up what unique judgment each person brings—something AI can’t reliably match? If not, you don’t have to cut the role, but you should talk about it now, before you’re forced to.
That’s it for this week.
All three stories point in the same direction: markets are rewarding companies that figure out how to use AI for real efficiency, and the conversation about what that means for teams is speeding up faster than most leaders realize.
I’m not here for the doomsday predictions, and you shouldn’t be either. The real question is: if AI can handle more work, what should your team focus on? The companies that figure this out and hire for it will be the ones people want to join in the future.
That’s the conversation I have with clients every week. If it’s one you want to have, reach out or reply here.
Until next time,
Joseph Burns
CEO & Founder, Lupa