Jack Dorsey’s Block Cuts Hundreds of Jobs as AI Mandates and Morale Plummet

In early February, hundreds of workers were laid off at jack dorsey’s Block, setting off a drawn-out process that employees say has left morale collapsing and performance anxiety spreading across teams. The layoffs and a top-down push to adopt generative AI tools matter now because management tied the staffing changes to performance assessments while telling staff the reductions will continue through the end of this month.

Block workforce reductions and scale

Company-wide actions that began this month have already removed hundreds of roles and could ultimately affect up to 10 percent of the workforce. Before the headcount reductions began, Block had around 11, 000 people on staff. Management has carried out the firings over the course of weeks rather than as a single event, and employees were told that the process will continue through the end of this month.

All-hands meeting and employee complaints

A recent all-hands meeting produced sharply critical feedback from staff. One complaint submitted to leadership read, "Morale is probably the worst I’ve felt in four years, " and added that "the overarching culture at Block is crumbling. " Another note from the same meeting warned: "We don't yet know if our livelihoods will be affected, and this makes it incredibly hard to make major life choices without knowing if we still have a job next week. " A transcript of that meeting captures these concerns and the sense of uncertainty among employees.

Arnaud Weber and the 'performance' message

After the initial wave of cuts, Arnaud Weber, Block’s engineering lead, sent an internal email framing the departures as performance-related rather than cost-saving. Weber wrote, "As part of our 2025 performance cycle, we have parted ways with teammates who weren't meeting the expectations of their role. " He added that "These departures were based on clear performance gaps, role expectations, and alignment coming out of calibrations on the bar for each level. " Many employees expressed shock and disagreement with that internal messaging.

Jack Dorsey and weekly updates

Employees are currently expected to send a weekly update email to Jack Dorsey. He then uses generative AI to summarize the thousands of messages. In the same all-hands meeting, Dorsey highlighted frequent topics cited by workers in their messages: "widespread concerns about layoffs, " "performance anxiety, " and "the tension between accelerating delivery through AI adoption versus maintaining code quality and engineering rigor. " He reiterated that the firings were for performance reasons, saying there was "a sizable portion of our population that have been phoning it in. "

Generative AI expectations and engineering tension

Management has pushed remaining staff to adopt generative AI tools as a way to maximize productivity, warning that Block could be outpaced by competitors if employees do not use such tools. That mandate has been met with resistance: one current Block employee called the approach "crazy, " saying, "Top-down mandates to use large language models are crazy. If the tool were good, we’d all just use it. " Employees describe a growing tension between accelerating delivery through AI adoption and preserving code quality and engineering rigor.

Organizational context: Square, Cash App and leadership

Block is the parent company behind the merchant payment processor Square and the payment app Cash App. Jack Dorsey cofounded the company in 2009 after previously cofounding Twitter. Seven current and former Block employees, speaking on the condition of anonymity, described internal operations and raised concerns about how the reductions and AI directives are being implemented. A Block spokesperson did not respond to requests for comment.

What makes this notable is the combination of a protracted, large-scale reduction in force and an explicit push to bake generative AI into everyday engineering workflow: the layoffs have produced immediate anxiety and concrete changes to routine communication, and those shifts are driving questions about performance standards, tool efficacy, and the company's longer-term engineering culture.