ClickUp has laid off roughly 286 employees – 22 percent of its 1,300-person workforce – and CEO Zeb Evans isn’t framing it as bad news, but rather as a deliberate and strategic blueprint for what he believes the modern technology company should look like.
“This wasn’t about cutting costs,” Evans wrote on X. “Most savings from this change will flow directly back into the people who stay.”
The carrot attached to that claim is striking: remaining employees who deliver “outsized impact using AI” could earn up to $1 million in base salary.
It is a bold reimagining of how tech companies structure compensation, tying pay directly to the ability to extract value from AI rather than to tenure, title, or traditional output metrics.
Agents In, Headcount Out
The restructuring follows an internal AI rollout in which ClickUp has deployed around 3,000 AI agents to handle complex operational tasks across the business, fundamentally changing what it expects from its employees.
Staff are no longer expected to do the work themselves – they’re expected to direct, manage, and quality-check the systems that do it for them.
Evans’ stated goal is to build a “100x org” – a company that punches far above its weight in output relative to headcount.
Rather than measuring AI adoption by token consumption – a controversial practice critics have dubbed “tokenmaxxing” – ClickUp says it focuses on value created and time saved, a distinction Evans is apparently preparing to package into a customer-facing product.
A Vision Already Being Lived?
The broader AI-native model is already drawing significant investor confidence.
Polsia – a one-year-old startup that handles software operations for solopreneurs – is run entirely by its founder and CEO, Ben Cera, with zero additional staff.
The company just raised $30 million at a $250 million valuation, suggesting that the market is increasingly willing to back businesses built around AI from the ground up rather than retrofitted around it.
Industry-Wide, but the Returns Aren’t Guaranteed
ClickUp is far from alone in making the pivot towards AI-first, with the broader tech industry undergoing a dramatic reorientation around AI talent and automation that is simultaneously eliminating roles and creating a new class of extraordinarily well-compensated specialists.
But a recent Gartner survey complicates the narrative considerably.
Around 80 percent of companies deploying autonomous AI have reduced headcount – yet meaningful financial returns remain elusive, raising serious questions about whether the productivity gains being promised are materialising in practice.
Critics suggest some organisations are using unproven AI as a socially palatable reason to downsize, cutting costs under the cover of transformation while the technology quietly fails to deliver.
The Uncomfortable Logic
Even on its own terms, Evans’ vision carries an inherent tension that becomes harder to ignore the further the model is taken.
“The people that automate their jobs with AI will always have a job,” he wrote – but as AI agents absorb more functions and grow more capable, the ceiling for how many people any company actually needs keeps dropping, and today’s AI orchestrator risks becoming tomorrow’s redundancy.
The honest read of Evans’ model is that it creates a perpetual performance race – one where the goalposts move as AI capabilities improve, and employees must not just adopt AI, but continuously prove they are extracting more value from it than the technology could plausibly deliver on its own.
For the 78 percent who kept their jobs, there’s now a million-dollar incentive to prove the model right.
