On 26 February, Jack Dorsey fired over 4,000 people — nearly half of Block's entire workforce. His reason wasn't revenue trouble. It wasn't restructuring. He pointed at their in-house AI platform, called "Goose," and said it could do the work instead. Block's stock jumped 24% the same day.
Then he said the quiet part out loud: "The majority of companies will reach the same conclusion within the next year."
That's not a prediction from some analyst. That's a CEO who just did it, telling you everyone else is about to follow.
If you're interviewing for anything right now — engineering, product, operations, marketing, anything — this changes what you need to walk in ready to talk about. Not eventually. Now.
This Isn't the First Wave of AI Layoffs. It's the Loudest.
Let's be clear about why Block matters more than the other headlines.
Tech layoffs have been brutal all year. Challenger data showed 108,000 job cuts in January alone — the worst January since 2009. Amazon's slashed 16,000 roles. Autodesk and Salesforce each cut about a thousand. But most of those companies wrapped it in corporate language. "Strategic realignment." "Operational efficiency."
Dorsey didn't bother. He said the AI is better. He said the humans are redundant. And the market rewarded him for saying it.
That's the shift. It's no longer something companies whisper about internally. It's a public strategy that investors love. Which means every hiring manager at every company watching Block's stock price just got a very clear message about what leadership expects.
And that changes what they're going to ask you.
The Question You're About to Get (and Most People Botch)
Here's what's already happening in interview rooms, whether it's phrased this directly or not: "How do you work with AI?"
I've heard this question destroy genuinely talented candidates. Not because they don't use AI — most do. Because their answer sounds like everyone else's. "I use AI to boost my productivity." "I leverage ChatGPT for brainstorming." That's the 2024 answer. It was fine then. It's nothing now.
After Block, interviewers aren't checking whether you've heard of AI tools. They're checking whether you'd survive if your company deployed its own Goose tomorrow. Different question entirely.
The answer they want to hear has three parts, and most candidates only deliver one.
Part 1: What You Actually Use AI For (Specifics Only)
Not "various tasks." Not "day-to-day efficiency." Name the tool. Name the task. Name the result.
"I use Claude to generate first-draft test suites from our API specs. It saves roughly four hours per sprint. But I review every assertion manually because it consistently misjudges our edge cases around currency rounding."
That's twenty seconds. It's specific. It shows judgment. And it sounds like someone who actually does this, not someone who read a LinkedIn post about it.
Part 2: What You Do That AI Can't
This is where most people go blank. And honestly, it's the most important part.
After watching Dorsey cut 4,000 engineers because an AI could replace their output, every interviewer is now silently asking: "Could I justify keeping this person if our AI got twice as good next quarter?"
You need to answer that question without them having to ask it. The skills that survive are the ones AI consistently fails at: navigating ambiguous requirements across multiple stakeholders, making judgment calls with incomplete data, building trust with a difficult client, knowing when the technically correct answer is organisationally wrong.
I once worked with a candidate who'd been laid off from a FAANG company. Brilliant engineer. His first few mock interviews were disasters because every answer was about execution speed and technical output — exactly the stuff AI is eating first. We rebuilt his stories around the decisions he'd made that required reading people, not code. He landed a senior role within three weeks.
Part 3: How You'd Adapt if AI Took Over 40% of Your Current Role
This is the Block question. And it's coming.
Morgan Stanley published a report the same week as the Block layoffs showing that 27% of employees have already been retrained in the past twelve months. They identified entire new job categories — AI governance specialists, "vibe coders" who prototype with AI before handing off, hybrid product-engineer roles that didn't exist eighteen months ago.
A strong answer here sounds something like: "If AI handled all the routine implementation, I'd shift toward the architectural decisions and cross-team coordination that require context AI doesn't have. I've already started doing this — I spend less time writing boilerplate and more time on system design reviews and stakeholder alignment."
That's not hypothetical. That's someone who's already moving.
What Changed After Block (and What Hasn't)
Here's what I'd tell anyone interviewing this month.
What changed: The pretence is gone. Before Block, AI displacement was something companies talked about cautiously, in future tense. Now it's something a CEO bragged about and got a 24% stock bump for. Interviewers are going to probe your AI readiness harder and more directly because their own leadership is asking them the same questions internally.
What hasn't changed: The fundamentals of a great interview answer are exactly the same. Structured storytelling. Specific examples. Quantified impact. The ability to go three levels deep when pressed. None of that's different. What's different is the content of your stories needs to demonstrate that you're not competing with AI — you're the person who makes AI useful.
What also hasn't changed: Most candidates won't prepare for this. They'll walk in with the same generic "I use AI tools" line and wonder why they didn't advance. The bar hasn't moved to some impossible height. It's just moved away from where most people are aiming.
How to Prepare Before Your Next Interview
This isn't something you can wing. Generic answers about AI collapse the second a good interviewer pushes back. Here's what actually works.
Build three AI stories using the STAR method.
One where AI dramatically improved your work — with the specific tool, task, and measurable outcome. One where AI produced something wrong and you caught it — what was the error, what tipped you off, what did you do. One where you deliberately chose not to use AI and can explain exactly why.
Three stories. Minimum. You can flex them across a dozen different questions.
Audit your current role for the "Goose test."
Look at everything you do in a typical week. Which tasks could an AI platform handle tomorrow? Which ones couldn't? If you can't identify at least three things you do that require human judgment, relationship navigation, or ambiguity tolerance — that's the prep work. Not for the interview. For your career.
Practise saying it out loud.
Written prep and spoken delivery are completely different skills. The moment an interviewer asks "What would you do if AI could handle 40% of your current role?" you need a fluent, composed answer — not a deer-in-headlights pause while you try to assemble something. That fluency only comes from repetition.
This is exactly what Instant Interview is designed for — live voice sessions where you can rehearse these answers against an AI interviewer that pushes back, asks follow-ups, and scores your delivery on structure, pace, and filler word rate. It's the closest thing to the real pressure of the room.
The Bottom Line
Dorsey didn't just lay off 4,000 people. He gave every company in the world permission to say what they've been thinking: AI can replace roles, not just assist them. Investors cheered. Other CEOs are watching.
You can't control any of that. What you can control is walking into your next interview with specific, practised, three-levels-deep answers that prove you're the person who makes AI work — not the person AI replaces.
That's always been the game. It's just louder now.
Jacob, Instant Interview
