Twitter co-founder Jack Dorsey’s financial services company Block has announced it will fire 40 percent of staff – around 4,000 people – because new “intelligence tools” the company is implementing “can do more and do it better.”
The company announced the sackings in the shareholder letter [PDF] accompanying its Q4 earnings announcement on Thursday. The payments and crypto company reported quarterly revenue of about $6.25 billion – up 3.6 percent year-over-year – and gross profit of around $2.9 billion. The company made $1 billion of gross profit in December 2025 alone. Full-year revenue came in at about $24.2 billion, and gross profit was around $10.36 billion.
“2025 was a strong year for us,” Dorsey wrote in the shareholder letter, before posing the question, “Why are we changing how we operate going forward?”
His answer, spread across the letter and a Xeet, is that AI has already changed the way Block works, so it needs to change its structure.
“We’re already seeing that 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. and that’s accelerating rapidly,” he wrote on X.
Financial services, so probably transcribing people’s shitty scribbled expense reports into actually usable structured data, and doing it flawlessly enough they don’t get sued.
Edit: Apparently this is the parent company of Square. That’s not something that should really need a huge staff to maintain.
Can we start placing bets on when we find out that the “AI tools” they’re using are just sweat shop workers in Bangladesh processing invoices?
Eh, I know this is the anti-AI instance, but reading and interpreting things like that is something you can verifiably get AI to do 90% of the time.
Because 90% accuracy is acceptable for financial institutions …
I’ve got an idea. If 90% of AI’s output is accurate, just have humans review the 10% that will be inaccurate.
(Yes I am an AI expert, how did you know)
Which outputs are accurate, and which ones are inaccurate? How could you tell? What steps did you take to verify accuracy? Was verifying it a manual process?
That’s easy. You just get a second AI to ask the first AI if their responses were accurate or not
(/s)
This is unironically what I’ve seen people try to do, except they assume the second AI is correct.
Unrelated, but this is how GANs work to some extent. GANs train during the back-and-forth though, while LLMs do not.
No, it’s really not. Thus the 6000 remaining employees.
(Assuming this is a significant part of their business)
Hell USPS has been using machine learning (yes a kind of AI but not the kind they are implying) for years to do that kind of thing.
Kind of
They’ve had several address resolution centers around the country, where reviewers look at mail and figure out it’s address. They don’t physically handle the mail, it’s an image on a screen.
Iirc they’ve been doing it this way since the 70s
No? For everything they can they just use OCR and then send it on its way without a human having ever seen it sometimes. If the hand writing is bad enough that the machine can’t figure it out that’s where the human reviewers come in.
They own Square which is a card processing service typically used by small vendors. If you’ve ever gone to a festival or concert merch table or farmers market and they accepted credit card, it was probably Square.
Ah, never mind. Weird they don’t just call themselves Square.
They were called that for most of their history until Jack Dorsey wanted to change the name to hype some crypto.
Lol!
Okay, that’s way too right now. Of course he did.
All this talk is too meta for me.
…Like the company Meta, after they named themselves after the Metaverse.
That worked out swimmingly for them.
Right. So, generating training data :-)