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SUQIAN, CHINA – JUNE 10: In this photo illustration, the logo of AI Agent is displayed on a smartphone screen on June 10, 2025 in Suqian, Jiangsu Province of China. (Photo by VCG\/VCG via Getty Images)<\/span><\/p>\n VCG via Getty Images<\/small><\/div>\n<\/div>\n<\/figure>\n On February 27, 2026, Block cut more than 4,000 employees<\/u><\/a>, roughly 40% of its workforce, reducing headcount from over 10,000 to under 6,000 in a single day. CEO Jack Dorsey tied the move directly to AI, writing in his shareholder letter that “a significantly smaller team, using the tools we’re building, can do more and do it better.” Block’s stock surged roughly 22% on the announcement<\/u><\/a>, closing the loop between workforce reduction and investor reward that is becoming the defining pattern of 2026.<\/p>\n Block reported gross profit of $10.36 billion in full-year 2025<\/u><\/a>, up 17% year-over-year, with Cash App gross profit alone up 33%. Dorsey was explicit that weakness was not the driver. “We’re not making this decision because we’re in trouble,” he wrote on X<\/u><\/a>.<\/p>\n Five weeks after the layoffs, Dorsey and Roelaf Botha, Block’s lead independent director and a Sequoia Capital partner, co-published “From Hierarchy to Intelligence”<\/u><\/a> simultaneously on Block’s website and on Sequoia’s platform<\/u><\/a>. The essay is a 3,000-word argument that corporate hierarchy is a two-thousand-year-old information routing protocol; invented by the Roman Army, formalized by Prussian military reformers, imported into American business by railroad engineers in the 1840s. It concludes that AI can now perform the coordination functions that made middle management structurally necessary.<\/p>\n The essay’s central claim: “For the first time, a system can maintain a continuously updated model of an entire business and use it to coordinate work in ways that previously required humans relaying information through layers of management.” Botha frames the stakes from the Sequoia vantage point: “Speed is the best predictor of start-up success. Most companies are focused on AI as a productivity enhancer. Few are focused on the potential of AI to change how we work together.”<\/p>\n The organizational structure Dorsey and Botha propose collapses into three roles: individual contributors who own deep technical layers; Directly Responsible Individuals (DRIs) who own specific outcomes for defined time windows; and “player-coaches” who combine building with people development. Business Insider reported<\/u><\/a> that Block employees were already referencing player-coaches in internal Slack channels weeks before the essay was published, suggesting the taxonomy was operational before it was public.<\/p>\n Botha has sat on Block’s board since Sequoia led the company’s early rounds, making the co-authorship a direct expression of how a top-tier investor views organizational design as a value driver, not a cost center. Sequoia’s decision to publish the essay on its own platform amplifies it as a portfolio-wide signal rather than a single-company announcement.<\/p>\n Redpoint Ventures moved in the same direction around the same time. Redpoint’s 2026 Market Update<\/u><\/a> estimates that AI-native companies reach $5 million in annualized revenue 13 months earlier than the prior SaaS cohort and command a 24-40% valuation premium from Seed to Series C. The firm projects that AI-native applications could expand the roughly $600 billion cloud software market at least threefold. Its 2026 outlook describes the year as when pilots “convert or quietly disappear,” with the attack vector for new entrants being speed: large incumbents, in Redpoint’s framing, “have more lawyers than engineers.”<\/p>\n Brian Halligan, HubSpot co-founder and active investor, amplified the Dorsey-Botha thesis on social media shortly after publication, mixing the Block framework with observations from founders he advises. The convergence of Block’s restructuring, Sequoia’s endorsement, and Redpoint’s investment thesis amounts to what one Forbes analysis called “a coherent, and VC-backed, blueprint for how companies should be built in 2026.”<\/u><\/a><\/p>\n The AI-native narrative has not gone unchallenged. Block’s headcount nearly tripled from 3,835 at the end of 2019 to over 12,000 at peak, and the company had already run multiple rounds of layoffs in 2024 and 2025<\/u><\/a> before the February restructuring. Mizuho Americas analyst Dan Dolev told the Wall Street Journal that “the vast majority of these cuts were probably not due to AI.” A January 2026 report from the National Bureau of Economic Research, cited by Fortune<\/u><\/a>, found that many CEO-attributed AI layoffs were corrections for pandemic-era overhiring. An Oxford Economics study reached a similar conclusion.<\/p>\n Stanford professor Fred Turner told Bloomberg<\/u><\/a> that “telling stories is one of the core activities of Silicon Valley. It’s as important as making devices” raising a valid question: whether the organizational thesis is genuine architecture or strategic narrative.<\/p>\n Analysts flagged concrete execution risks. Mizuho maintained an underweight on Block after the announcement, noting transaction losses had risen to 18% of gross profit from 11% a year earlier. Dorsey’s 2026 guidance implies productivity per remaining employee more than doubling in a single year, a projection multiple analysts have flagged as difficult to model<\/u><\/a>.<\/p>\n Regardless of Block’s specific execution, the organizational model Dorsey and Botha articulate is already shaping how investors evaluate companies. The implicit question for any portfolio company or new investment is now whether AI has been deployed as a copilot, keeping the hierarchy intact and modestly more efficient, or as a structural replacement for coordination layers. The two produce very different cost curves, valuation multiples, and competitive moats.<\/p>\n Block’s “world model” concept; a continuously updated, machine-readable representation of company operations that replaces the information flows that managers historically carried, is the piece that makes the thesis operational rather than aspirational. Block is remote-first, meaning its decisions, code, designs, and plans already exist as recorded artifacts. That raw material is what makes the model trainable. Companies that generate low-resolution operational data, or that rely on informal, unrecorded coordination, face a structurally harder path to the same architecture.<\/p>\n Dorsey wrote in the essay that “companies move fast or slow based on information flow. Hierarchy and middle management impede information flow.” For VCs marking to that thesis, the due diligence question changes: not whether a company uses AI, but whether the company’s information architecture is dense enough to make the model compounding.<\/p>\n<\/div>\nHierarchy as an Information Routing Problem<\/h2>\n
The VC Signal<\/h2>\n
Skeptics Have Data Too<\/h2>\n
What VCs Are Pricing In<\/h2>\n