Jack Dorsey said he’s still hiring for his fintech company Block — even after he just laid off 40% of its workforce.
The cofounder said during an earnings call on Thursday that he expects to bring in more senior AI engineering talent to the team. The company’s stock was up nearly 23% after trading hours as of 7 p.m. Eastern Time.
On Thursday, Dorsey said in a memo to employees that Block was cutting its head count from 10,000 people to “just under 6,000.” The reason, he said, was because AI is unlocking “a new way of working” with “smaller and flatter teams.”
“We’re not making this decision because we’re in trouble. Our business is strong. Gross profit continues to grow, we continue to serve more and more customers, and profitability is improving,” Dorsey wrote in the memo. “But something has changed.”
Dorsey said in an earnings call on Thursday that AI tools have increased productivity at the company with a 40% increase in production code shipment per engineer since September.
“We’ve seen engineering work that would have taken weeks to complete be done by a small team in a fraction of the time with agentic coding tools,” he said.
Despite the layoffs, Dorsey said during the call that Block expects to invest in hiring.
“We see meaningful opportunity to invest in our people and invest in hiring, invest in retaining a world-class team to deliver for our customers; ultimately, we expect to hire some more senior AI engineering talent who will continue to level up our engineering and product capabilities,” he said.
Dorsey and a spokesperson for Block did not immediately respond to a request for comment.
AI’s impact is being felt across industries and roles, as companies find ways to automate work. One study by Stanford University researchers found that early-career positions in fields such as software engineering and customer service are on the decline.
Some workers have also said that their responsibilities have increased with AI. A software engineer told Business Insider that the simultaneous increase in productivity and workload is leading to “AI fatigue.”
Read the full article here
