ClickUp, the productivity platform valued at $4 billion, has laid off 22 per cent of its workforce. CEO Zeb Evans broke the news on X, describing the move not as a cost-cutting measure but as a fundamental shift in how the company operates. The savings from the layoffs, he said, will be redirected into the salaries of remaining employees, with the introduction of salary bands reaching up to $1 million per year in cash.
The restructuring is built around what Evans calls a “100x org.” The idea is that artificial intelligence agents have fundamentally changed what it takes to build software, and the roles needed to operate at the highest level are now different. Incremental improvements to existing systems, he argued, won't get ClickUp to its goals. The company needs to rebuild from the ground up.
The move follows months of aggressive AI adoption inside ClickUp. A Fortune profile published just days before the layoffs revealed that the company now runs roughly 3,000 internal AI agents across its departments. That gives the company a 3:1 ratio of agents to employees. Evans had already mandated that all staff go through an AI agent trained to stand in his place before contacting him directly.
The layoffs are part of a broader trend in the tech industry. In 2026 so far, more than 100,000 jobs have been cut across roughly 250 events. Meta cut 8,000 roles the same week despite record revenue. Oracle eliminated up to 30,000 positions to fund AI infrastructure. GitLab restructured for what it called the “agentic era.” The pattern is consistent: companies report record performance and cut headcount simultaneously, redirecting savings into AI investments.
The 100x Org Model
Evans outlined three categories of employees he sees as essential to the new model. The first is “builders,” which he splits into 10x engineers and 10x product managers. His claim is blunt: the best engineers are not writing code any more. They are directing agents that write code. The skill that matters is judgment, the ability to orchestrate and review. AI makes the best engineers wildly more productive, he wrote, while everyone else using AI slows them down.
He called this the “great reckoning of AI coding” and said every company will face it soon. Companies celebrating 500 per cent more pull requests are generating volume, not outcomes. More code, in his view, is just another bottleneck. The real bottleneck now is human judgment in evaluating the output of AI agents. Engineers who understand the system architecture and can review agent-generated code become exponentially more valuable than those who simply churn out code themselves.
The second category is “system managers,” or agent managers. These are people who automate their own jobs with AI and then become owners of the systems they built. Evans argued that anyone who automates their role will always have a job. The underlying systems, not the individual tasks, are what matter. In practice, this means employees are expected to train AI agents to take over their routine work, then shift their focus to improving and maintaining those agents. This creates a cycle of continuous automation that reduces the need for headcount while increasing the leverage of existing staff.
The third category is “front-liners,” the people who spend their time with customers. In a world saturated with AI communication, Evans said, human contact becomes the one bottleneck companies should not try to replace. Front-liners should spend nearly 100 per cent of their time in meetings with customers, while the systems around those meetings are fully automated. This includes scheduling, note-taking, follow-ups, and data analysis. The human touch remains the differentiator in customer relationships, especially as competitors rely more on chatbots and automated support.
Merging Roles and New Compensation
Evans also noted that product management and design are merging. Designers with customer focus become more like product managers. Product managers with UX intuition become more like designers. The bottleneck of user research is gone, he claimed, because a single mention to an agent can kick off and analyse a research cycle. This blurring of roles reflects a broader trend in tech where AI tools collapse traditional job boundaries. Employees are expected to wear multiple hats, with AI handling the grunt work of research and analysis that once required dedicated teams.
The most provocative element of the announcement is the compensation model. ClickUp is introducing salary bands that reach $1 million per year in cash. The path is available to nearly anyone in the company who produces “100x impact” by creating or managing AI systems. In a world where the best people create 100 times more output, Evans argued, companies cannot afford to lose them and should aim to retain them for decades. This is a direct challenge to the traditional top-heavy compensation structures that reward seniority and title over measurable impact.
The compensation bands are structured to reward those who build or manage AI systems that generate tenfold or hundredfold productivity gains. For example, a system manager who automates a critical business process and makes it run 100 times more efficiently could qualify for the top band. Similarly, a builder who creates an AI agent that replaces the work of ten human employees would see a significant raise. Evans emphasized that these bands are not limited to executives or engineers; any employee who can demonstrate this level of impact is eligible.
Industry Context and Reactions
ClickUp's move comes amid a broader reckoning in the tech industry. The pattern of record profits and simultaneous layoffs has become increasingly common. Companies are under pressure from investors to show they are adapting to the AI era, and cutting headcount is a visible way to demonstrate commitment to efficiency. However, critics argue that many of these layoffs are not strategic but rather a way to boost short-term financial metrics in advance of IPO or earnings calls.
In the case of ClickUp, the company reported roughly $300 million in annual recurring revenue as of 2025 and has been eyeing an IPO. The company acquired AI coding platform Codegen late last year, signalling a clear direction toward AI-driven development. With AI reshaping the economics of developer tools and productivity software, Evans is betting that a smaller, better-paid workforce directing thousands of agents will outperform the company it replaces.
Not everyone is convinced. In China, courts have ruled that replacing workers with AI is not legal grounds for dismissal. In the US, no such protection exists. For the 22 per cent of ClickUp employees who lost their jobs this week, the distinction matters. Labour advocates argue that the rapid shift toward AI-driven organizations risks creating a two-tier system: a small elite of highly paid AI orchestrators and a large pool of displaced workers without clear paths to re-employment.
Some industry analysts have questioned whether the 100x org model is sustainable. They point out that AI agents still require human oversight and that the technology is not yet reliable enough to handle complex, nuanced tasks without frequent intervention. Evans's claim that the best engineers are now director of agents rather than coders may hold true for some, but not for all. The risk is that companies overestimate the capabilities of AI and underestimate the value of human intuition and context.
Meanwhile, competitors are watching closely. Other project management and productivity tools are also investing in AI, but few have been as explicit about restructuring around it. Asana has introduced AI-powered features but has not announced a similar structural overhaul. Monday.com has focused on automation but maintained a more traditional workforce model. ClickUp's aggressive move sets a precedent that could force others to follow or risk falling behind in efficiency.
For the employees who remain at ClickUp, the promise of million-dollar salaries comes with high expectations. They will be expected to continuously prove their impact in a system where metrics are closely tracked. The company has not disclosed how many employees will qualify for the top bands, but Evans's language suggests that only a small percentage will reach that level. Still, the signal is clear: ClickUp is betting that very high compensation for a very few will drive extraordinary output from the rest.
In the longer term, the success of the 100x org model will depend on whether AI agents can truly deliver the productivity gains Evans envisions. If they do, ClickUp could become a blueprint for future tech companies. If they don't, the company may find itself with a skeleton crew and a massive compensation liability. The tech industry is watching closely, and the outcome could influence hiring and compensation practices for years to come.
Source: TNW | Apps News