Editor's Note: While most companies still view AI as a "productivity tool," Jack Dorsey has taken the question a step further: Is AI rewriting the very logic of how organizations operate? As the co-founder and former CEO of X and the founder of Block, he has long focused on the relationship between technology and organizational forms.

This article starts from history, re-examining why enterprises have evolved into their current forms and why this structure is beginning to loosen. From the Roman legions to modern corporations, organizational evolution over the past two millennia has always revolved around the same constraint: achieving information transmission and coordination within a limited "span of control." Hierarchical structures, middle management, and matrix systems are essentially different solutions to this problem.

The emergence of AI, for the first time, challenges this premise. When information can be modeled, understood, and distributed in real-time, does an organization still need a human-centric coordination mechanism?

Similar changes are already appearing in reality. Recently, the publication Renwu reported that the AI company "Moon Dark Side" operates a team of over 300 people with no departments, no job titles, and no OKRs or KPIs. Collaboration relies on direct communication rather than layered reporting; five co-founders each directly manage 40–50 employees. Meanwhile, Agents are embedded into daily workflows, capable of completing tasks like information organization, product design, and even code generation in a short time. This structure is not simply about "removing management" but rather shifting the complexity upfront into recruitment, fluidity, and tool systems.

Using Block's practices as a starting point, this article further proposes a more radical vision: moving from a "hierarchical organization" to an "intelligent company," replacing traditional information routing systems with a "company world model + customer world model + intelligence layer," and even redefining middle management itself. This is not just an issue of efficiency but potentially a rewrite of organizational forms.

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In the view of Sequoia Capital, "speed" is the best indicator for predicting the success of a startup. Most companies still see AI as a tool to enhance productivity, while only a few have begun to focus on how AI changes the way people collaborate. Block is demonstrating a全新的 path: fundamentally rethinking organizational design and using AI as a compound competitive advantage that continuously amplifies "speed."

The Origin of Hierarchical Organizations: From Roman Legions to Modern Corporations

Two millennia before the corporate organizational chart appeared, the Roman army had already solved a problem that still plagues large organizations today: how to coordinate thousands of people with limited communication and over vast distances.

Their solution was to establish a nested command system with relatively stable "spans of control" at each level. The smallest unit was the "contubernium," consisting of 8 soldiers who shared a tent, equipment, and a mule, led by a decanus. 10 contubernia formed a "century" (actually about 80 men), commanded by a centurion; 6 centuries constituted a cohort; and 10 cohorts formed a legion of about 5000 men.

At each level, there was a clear commander responsible for aggregating information upward and conveying orders downward. This structure from 8 → 80 → 480 → 5000 was essentially an efficient information transmission mechanism, built on a simple yet crucial premise: the number of people one person can effectively manage directly is typically only 3 to 8. The Romans gradually discovered this rule through prolonged warfare. Even today, the U.S. military's hierarchical system largely follows a similar logic. We call this constraint the "span of control," and it remains a fundamental limitation that all large organizations must contend with.

The next major变革 came from Prussia.

After a crushing defeat by Napoleon at the Battle of Jena in 1806, Scharnhorst and Gneisenau led military reforms, proposing an uncomfortable reality: one cannot rely on individual genius; one must rely on systems. They established the "General Staff," training a class of专职 officers whose duty was not to fight but to plan operations, process information, and coordinate across units. Scharnhorst's original intention was to "compensate for the deficiencies of incompetent generals, providing them with the abilities they lack." This was essentially the雏形 of "middle management": a group of professionals responsible for information transmission, pre-calculating decisions, and maintaining the coordination of complex organizations. Simultaneously, the military clearly distinguished between "line" and "staff" functions: the former推进 core tasks, the latter provided professional support. This division is still widely used in businesses today.

In the 1840s and 50s, American railroad companies introduced the military hierarchical system into the business world.

The U.S. Army supplied railroad companies with大量 engineers trained at West Point, who brought military organizational thinking with them. Line and staff structures, divisional划分, and bureaucratic reporting and control systems all originated in the military. In the mid-1850s, Daniel McCallum of the New York and Erie Railroad drew the world's first organizational chart to manage a 500-mile railroad system and thousands of employees. The previous informal management methods suitable for small railroads had failed, leading to frequent train collisions. McCallum institutionalized the Roman-style hierarchical logic: clear levels of authority and responsibility, defined reporting relationships, and structured information flow. This became the prototype for the modern corporation.

Subsequently, Frederick Taylor (known as the "father of scientific management") optimized the internals of this system. He broke down work into specialized tasks, assigned them to trained experts, and managed with quantitative metrics rather than intuition, thus forming the "functional pyramid" structure—an organizational form that maximized efficiency within the existing information routing system.

The first major stress test for this functional structure occurred during WWII with the "Manhattan Project." The project required physicists, chemists, engineers, metallurgists, and military personnel to collaborate across disciplines under extreme secrecy and time pressure to achieve a single goal. Robert Oppenheimer at Los Alamos Laboratory used functional divisions but insisted on open cross-departmental collaboration, resisting the military's "compartmentalization" tendencies. In 1944, when the "implosion problem" became a critical bottleneck, he reorganized teams, creating cross-functional groups—something almost unheard of in the business world at the time. This model worked, but it was a wartime exception, driven by a few exceptional individuals. The question for the post-war business world was: Could this kind of cross-functional collaboration become常态化?

Post-war corporate growth and global expansion made the limitations of the functional structure increasingly apparent.

In 1959, McKinsey's Gilbert Clee and Alfred di Scipio published "Creating a World Enterprise" in the Harvard Business Review, proposing the "matrix organization" framework, combining functional expertise with divisional structure. With Marvin Bower's push, McKinsey helped companies like Shell and General Electric implement this model, achieving a balance between "central standards" and "local flexibility." This system became the paradigm of the "modern enterprise" in the post-war global economy.

Subsequently, to address the complexity and bureaucratization of the matrix structure, new management frameworks continuously emerged.

McKinsey proposed the "7-S Model" in the 1970s, distinguishing between "hard elements" (strategy, structure, systems) and "soft elements" (shared values, skills, staff, style), emphasizing that structure alone cannot guarantee organizational effectiveness and requires coordination at the cultural and human levels.

In recent decades, tech companies have conducted more radical experiments with organizational structure.

Spotify introduced cross-functional squads and short-cycle iterations; Zappos experimented with Holacracy, eliminating management titles; Valve adopted a flat structure with no formal hierarchy. These attempts all revealed the limitations of traditional hierarchies but failed to completely solve the problem: Spotify returned to traditional management as it scaled, Zappos experienced significant employee turnover, and Valve's model was difficult to scale beyond a few hundred people. When organizations reach thousands of people, they still have to revert to hierarchical coordination because there is no more effective information routing mechanism.

This constraint is exactly the same problem faced by the Romans and the Marines in WWII: a smaller span of control means增加层级, and增加层级 slows down information flow. For two thousand years, organizational innovation has always tried to circumvent this trade-off but has never truly broken it.

So, What's Different Now?

At Block, we have begun to question a fundamental assumption: that organizations must use humans as the coordination mechanism, adopting hierarchical structures. Our goal is to replace the functions of hierarchy with systems. Currently, most companies are just equipping employees with AI co-pilots, making existing structures run a bit better, but the essence remains unchanged. What we want to build is another form: a company that is itself an "intelligent agent" (or even a small AGI).

We are not the first organization to try to move beyond hierarchy. Haier's "Rendanheyi," platform organizations, "data-driven management,"等都是 similar explorations. But they lack a key element: technology that can truly承担 coordination functions. AI is that technology. For the first time, a system has emerged that can continuously maintain a model of the entire enterprise's operation and coordinate based on it, without humans transmitting information through hierarchies.

To achieve this, a company needs two things: a "world model" of its own operations, and sufficiently rich customer signals.

Block operates remotely, and all work leaves a recordable "trace": decisions, discussions, code, designs, plans, problems, and progress. These constitute the raw materials for the company's world model.

In traditional companies, managers are responsible for understanding team status and transmitting information up and down;而在一个"machine-readable" organization, AI can continuously build this global view: what is being done, where things are stuck, how resources are allocated, what works, what doesn't. This information, previously carried by hierarchy, is now carried by the model.

But system capability depends on the quality of input signals, and "money" is the most真实 signal. People might lie on surveys, ignore ads, abandon shopping carts, but when they spend, save, transfer, borrow, or repay, these actions are real. Block sees both sides of a transaction simultaneously daily: the buyer through Cash App and the seller through Square, along with merchant operational data. This allows it to build a rare customer world model—an understanding of financial behavior per customer and merchant based on real transaction signals, and these signals continuously accumulate and strengthen.

The company world model and the customer world model together form the foundation of a new type of company. In this model, the company no longer operates with product teams围绕既定 roadmaps, but is built around four cores:

First, capabilities: foundational financial capabilities like payments, lending, card issuing, banking, buy-now-pay-later, payroll, etc. These are not products but underlying modules, with no interface, but possessing reliability, compliance, and performance requirements.

Second, world model:包括 the company model (understanding its own operations) and the customer model (built on transaction data, representing customers and markets), gradually evolving into a system with causal and predictive capabilities.

Third, intelligence layer: at specific moments, for specific customers,组合 capabilities to actively provide solutions. For example, when the system predicts a restaurant's cash flow is about to tighten, it automatically组合 loan and repayment options and pushes them in advance; or when user behavior changes suggest they are moving, it automatically configures new financial service combinations. None of this requires prior design by product managers.

Fourth, interfaces: like Square, Cash App, Afterpay, TIDAL, etc. These are just delivery interfaces; real value is generated by the model and intelligence layer.

When the system attempts to组合 a solution but finds it lacks a certain capability, this "failure signal" becomes the future product roadmap. The traditional method of product managers envisioning needs is directly replaced by real customer behavior.

In this structure, the organization也随之 changes. In traditional companies, intelligence is distributed among people and routed by hierarchy; here, intelligence resides in the system, and people are at the "edge." The edge is where intelligence meets reality. People can perceive intuition, culture, trust, and complex situations that the model cannot capture, and they play a role in ethical and high-risk decisions. But they don't need to coordinate through hierarchy because the world model provides the necessary context.

In practice, the organization will simplify into three types of roles:

· IC (Individual Contributor): experts who build capabilities, models, and interfaces;

· DRI (Directly Responsible Individual): mobilizes resources around specific problems or customer outcomes;

· Player-coach: participates in frontline work while also cultivating talent, replacing traditional managers.

Fixed middle management layers are no longer needed; the remaining coordination work is done by the system.

Block is currently still in the early stages of this transition, which will be a difficult process, and some attempts may fail. But we are公开 this direction because we believe every company will eventually face the same question: Are you continuously deepening your understanding of a complex problem?

If the answer is no, AI is just a cost-cutting tool; if the answer is yes, AI will reveal the true essence of the company.

Block's answer is the "Economic Graph": connecting millions of merchants and consumers, understanding the behavior on both sides of transactions in real-time, and continuously accumulating. We believe this model of "organizing a company with intelligence rather than hierarchy" will reshape how various enterprises operate in the coming years.

The speed of a company fundamentally depends on the speed of information flow. Hierarchy and middle management slow down this flow. For two thousand years, from the Roman army to modern enterprises, we had no better alternative. But now, this premise is changing. Block is building the next form.