The Zero-Middle-Management Company

An AI Native Company can be defined one step further: a "zero-middle-management company." Zero middle management does not mean no managers, and it does not mean everyone reports directly to the boss. It means the company no longer keeps a permanent layer of people whose main job is aggregating information, passing down instructions, coordinating resources, and supervising process. The coordination work that middle managers used to do gets decomposed into company Context, Skills, Agents, Evals, a permission system, and dynamic DRIs. Managing people still exists — but management no longer automatically comes with a permanent position.

Compressed to one line: traditional companies route information through people; an ANC routes information through systems. Traditional companies bind power to positions; an ANC binds power to outcomes.

Two clarifications up front.

First, zero middle management is not zero management. A company still needs strategy, delegation, arbitration, talent development, conflict resolution, and risk governance. What disappears is the management layer whose main value is moving information around. What stays are the people accountable for outcomes.

Second, zero middle management is not a layoff plan. It is what a mature organization looks like after its capabilities have grown. If a company has no Context, Skills, Agents, Evals, permissions, or audit, firing the middle layer will not produce an AI Native Company — just a company that has lost the ability to coordinate itself.

1. Org charts were always an information technology

Why does every company, past a certain size, inevitably grow a middle layer?

The root cause is not that bosses love bureaucracy. It is that human bandwidth is finite.

A founder can directly understand what five people are doing, but cannot continuously understand what five hundred people do every day. As the organization grows, the company has no choice but to split people into teams, give each team a lead, and hand several leads to a manager one level up.

Employees report to team leads, team leads report to department managers, managers report to directors, and the director finally compresses everything into a slide deck for the boss. Once the boss decides, instructions travel back down the same chain.

So a traditional org chart looks like a division of power, but is really an information system made of people. Every middle layer performs three functions: compress information, relay instructions, coordinate resources.

Middle management is not accidental redundancy. It was the industrial era's infrastructure for scaling organizations. But the system has one unavoidable flaw: information loses fidelity every time it passes through a layer.

A customer says ten things on site. The frontline employee remembers eight, reports five to the manager, three make it into the weekly report, and what reaches the boss's slide might be a single line: "The customer has some concerns about the system experience."

It works the same way downward. The boss asks for "higher customer renewal rates." A few layers of decomposition later, it becomes daily call quotas, forms to fill, and process metrics that have nothing to do with customer value.

So traditional companies live inside a contradiction: the bigger the company, the more it depends on middle layers; the more middle layers, the further the company drifts from real work and real customers.

There used to be no better option, because organizational information could only be understood, summarized, and relayed by humans. That premise has now changed for the first time.

2. The first thing AI replaces may not be employees, but the information routing layer

Today, most so-called AI transformation means buying every employee a large-model subscription.

Employees use AI to write documents, managers use AI to summarize them, directors use AI to turn summaries into briefings, and the boss uses AI to read the briefing. Everyone looks more efficient, but the company's information structure has not changed at all.

A weekly report that took two hours now takes ten minutes; consolidating reports that took half a day now takes half an hour. The result is not that the company got closer to its customers — it is that the old pyramid can now produce more weekly reports.

That is not an AI Native Company.

An AI Native Company does not install a copilot at every node of the traditional org chart. It asks a different question: do these nodes still need to exist?

If customer feedback, project records, meeting notes, contracts, code, orders, quotes, and financial data are already digital, an Agent can read that raw Context directly and continuously work out what is happening in the company: which project is slipping, what the customer actually asked for, where work is being redone, which decisions have already been made, and who should act next.

The boss no longer waits through three layers of reporting to learn what happened on the front line. Employees no longer need three layers of approval to get the background, methods, and resources a task requires.

So AI's biggest impact on organizations may not be one employee doing the work of two. It is the company no longer needing layer after layer of people to move information around.

Once organizational Context can be understood directly by AI, the middle layer's most important function — information routing — starts losing its reason to exist.

3. Zero middle management does not mean nobody is accountable

The easiest misreading of the "zero-middle-management company" is imagining a company with no management and no boss, where hundreds of people fully self-organize.

That is not realistic.

An AI Native Company still needs clearly accountable owners. What changes is not whether responsibility exists, but how responsibility is produced.

In a traditional company, power comes from position. Because you are the department manager, the department's budget, hiring, projects, and information all flow through you. Whatever the company's most important problem is right now, you permanently occupy that layer of the organization.

In an ANC, power comes from outcomes. Because you are responsible for "deploying the quoting Agent to the front line at 80% adoption within the next 48 days," you temporarily hold the power to mobilize the relevant people, data, and systems. When the task ends, the mandate can end too, or move to another problem.

That is the DRI — the Directly Responsible Individual.

A DRI does not need permanent reports, and does not need to own a department before they can solve a problem. They simply carry final responsibility for a specific outcome over a specific period of time.

So a zero-middle-management company is not everyone reporting to the CEO. It is most work no longer being organized through reporting lines, but through tasks, outcomes, and dynamic mandates.

Traditional companies create positions first and pour tasks into them; an ANC lets problems appear first, then organizes people and Agents around the problem.

4. The middle layer is not replaced by one Agent, but decomposed by a system

"Replace all middle managers with one AI manager" is another oversimplification.

The middle layer's work breaks down into at least five categories:

The first four are mostly information processing, process execution, and outcome verification — they can be handed to systems step by step. The last one involves trust, emotion, value judgment, and long-term human growth. It still needs people.

So an ANC does not swap one Agent in for one manager. It builds a new kind of organizational infrastructure.

Company Context replaces layered reporting. Skills replace methods that lived in veterans' oral tradition. Agents replace repetitive task dispatch, information lookup, and process execution. Evals replace "show it to the boss when you're done." Permissions and audit replace the fuzzy control hidden inside personal positions.

The people who genuinely handle human growth, professional judgment, and conflict become player-coaches: participating in real work while helping others grow.

In an ANC, pure managers detached from the front line become rarer and rarer. People who can both create results and help others create results become more and more important.

5. The four kinds of people in a zero-middle-management company

A mature zero-middle-management company keeps roughly four core roles.

First, the Owner. The Owner decides why the company exists, which outcomes matter most, which boundaries must not be crossed, and who makes the final call in a major conflict. AI can help an Owner see more facts, but cannot replace the attribution of responsibility.

Second, the DRI. A DRI receives a scoped mandate around a concrete problem. They might own a 48-hour sprint or a customer outcome that runs for half a year. As long as the task exists, they hold the power to mobilize the relevant resources; when it ends, the mandate is reassigned.

Third, the Builder. Most people in an ANC should be Builders. Engineers, salespeople, consultants, operators, designers, lawyers, and finance can all be Builders. What matters is not the job title but whether they directly create results. With Agents, one person can lead a fleet of Agents and own a larger, more complete slice of outcome.

Fourth, the player-coach. Still on the field playing, while owning professional standards, talent development, and the hard judgment calls. Their influence comes from expertise and earned trust — not from headcount.

So a zero-middle-management company does not demote all managers into individual contributors. It asks managers to become creators again.

6. Block is publicly trying to remove the permanent middle layer

In the public record, the company closest to this organizational form is not Anthropic, and not OpenAI. It is Block, Square's parent company.

In 2026, Jack Dorsey and Sequoia partner Roelof Botha published "From Hierarchy to Intelligence." Their argument: corporate hierarchy fundamentally exists to solve an information-flow problem. Managers need to know what their teams are doing, then aggregate that upward and relay decisions downward along the org chart.

But Block is a remote-first company. Its discussions, decisions, plans, code, issues, and project progress already live in digital systems. Those records can become the raw material for a company world model.

That world model can continuously understand what is being built, which project is stuck, where resources went, which methods are working, and which results are drifting off target.

If AI can continuously maintain that map of the company, the organization no longer needs managers running recurring meetings, chasing updates, and producing briefings just so the company can know what it is doing.

Block proposes three core roles for this: Individual Contributors who directly create results, DRIs who own specific problems and customer outcomes, and player-coaches who work while developing others.

Its public essay contains one very direct line: There is no need for a permanent middle management layer.

That line should not be misread as "Block is already a fully mature zero-middle-management company." Block itself openly admits the transition is early, and that some mechanisms may break before they mature.

The accurate statement is: Block has not finished zero middle management — it is among the first large tech companies to publicly and systematically move toward zero permanent middle management.

Source: Block, "From Hierarchy to Intelligence" (block.xyz/inside/from-hierarchy-to-intelligence)

7. Claude is turning this from theory into infrastructure

Block did not just publish an organizational theory essay.

Internally it has deployed Goose, an open-source Agent built on Claude, connecting the model to the company's data, tools, and workflows.

According to Anthropic's published case study, 75% of Block engineers save 8–10+ hours per week; thousands of employees across roles now use Goose; non-technical staff can generate SQL, query data, and automate workflows directly, instead of filing a request with the data team and waiting in the queue.

The most important meaning of those numbers is not "engineers got more efficient."

The real organizational change is this: employees started calling the company's data and tools directly, without needing a manager to coordinate with another department first.

A product manager who wanted usage data on a feature used to contact the data team, explain the request, wait for scheduling, align on definitions, and then receive a report. Now they can have an Agent query the data, generate the SQL, explain the results, and turn the analysis into the next action.

What got removed is not just one data analyst's work — it is the communication, scheduling, approvals, and management that used to surround that work.

Source: Claude × Block case study (claude.com/customers/block)

An even more direct case is LaunchNotes. It hands project data from GitHub, Jira, and Linear to Claude for analysis — auto-generating personalized progress updates, catching anomalies, and understanding engineering context. Incident identification became 5x faster, and meeting time dropped by 50%.

Collecting progress, spotting blockers, running syncs, nudging owners — that is the most common work of engineering middle management. Claude is not "playing the role of a manager," but it has taken over much of the information-gathering and synchronization work managers used to do.

Source: LaunchNotes × Claude case study (claude.com/customers/graph)

Anthropic's internal survey of 132 engineers and researchers shows respondents already use Claude in about 59% of their work, self-reporting roughly 50% productivity gains. The average number of consecutive actions Claude Code executes has grown from about 10 half a year ago to about 20.

Which means Agents are moving from "helping a person with one step" toward "independently owning a stretch of work."

Source: Anthropic, "How AI Is Transforming Work at Anthropic" (anthropic.com/research/how-ai-is-transforming-work-at-anthropic)

8. Neither Anthropic nor OpenAI is a zero-middle-management company

A factual clarification is needed here.

Anthropic uses Claude deeply and emphasizes high trust, small teams, and individual agency — but it is not a zero-middle-management company. Anthropic still publicly hires Research Managers and Engineering Managers, with responsibilities covering team execution, performance, career development, hiring, and cross-team communication.

OpenAI is not one either. Its public job postings still show multiple layers of managers, regional leads, and global leads. An APAC sales development leader manages frontline SDR managers and sales teams across markets; HRBP roles explicitly coach managers and participate in org design and talent planning.

Square cannot be called a zero-middle-management company on its own either. Square is now a business brand under Block; the org transformation was proposed by the parent company.

So the accurate judgment today is: Anthropic is a deeply AI-powered company, but not a zero-middle-management company. OpenAI is a company that produces AI, but is not one either. Block is one of the most aggressive large companies publicly moving toward zero permanent middle management — and the experiment is not finished.

Which also shows: building the most advanced AI and using AI to rebuild your own organization are two different things.

9. Zero middle management starts from company Context, not from the org chart

Many bosses reading this far will have a first reaction: should I start cutting management layers?

No.

If your company's real information still lives in personal WeChat threads, paper documents, Excel files, employees' heads, and disconnected software, the middle layer is still your most important information connector.

Cut it in that state, and the organization's information will not flow into AI. It will walk out the door with the people.

So an ANC transformation cannot start by redrawing the org chart. It starts by punching through real business.

Pick one business point specific enough to prove value. Send an FDE into the field to understand the real process, connect the necessary data and tools, and ship the first usable system.

Only after employees start using it can the system collect real feedback. Which rules need adding, which permissions must stay closed, which exceptions need a human, which judgments depend on veterans' experience — you only learn these inside the business.

That feedback gets distilled into Context, Skills, and Evals, and only then can Agents gradually take on more complete tasks.

When more and more information no longer depends on reporting, more and more methods no longer depend on oral tradition, and more and more tasks no longer depend on a coordinator, the org structure earns the conditions to flatten naturally.

Do not cut the middle layer first and then build the ANC. Build organizational intelligence first, and let part of the middle layer's functions naturally lose their reason to exist.

10. 48 hours, 48 days, 48 weeks — the road from middle layers to zero

The zero-middle-management company fits inside Lawted's 48 theory.

In 48 hours, an FDE proposes a surface and punches through one point — bypassing traditional project approval, reporting, and cross-department coordination — so the boss directly sees business value. This stage does not change the organization. It proves that some things can be done fast without the original seven or eight roles and layers of collaboration.

In 48 days, the system is deployed to employees. Real usage collects company Context, and the experience scattered across brains, chat logs, and files gets distilled into a knowledge base, Skills, workflows, and Evals. This stage starts distilling the middle layer: the rules, experience, and judgment managers used to hold become capabilities the organization can call repeatedly.

In 48 weeks, validated Agents start owning end-to-end tasks. The company redraws the division of work, responsibility, permissions, and risk between humans and AI, and some permanent departments are replaced by dynamic DRIs and task-based teams. Only this stage truly rebuilds the middle layer.

So the three stages compress into: bypass the middle layer in 48 hours, distill it in 48 days, rebuild it in 48 weeks.

Zero middle management is not a 48-hour slogan. It is an organizational outcome that may appear after 48 weeks.

11. Five questions that tell you whether a company is an ANC

In the future, judging whether a company is an AI Native Company should not depend on how many model subscriptions it bought or how many prompts its employees write per day. Ask five questions.

One: can the boss understand what is really happening on the front line without waiting for three layers of reporting?

Two: can employees get the Context, Skills, data, and tools a task requires without a leader coordinating for them?

Three: do the company's key capabilities live in a few veterans' heads, or have they become organizational assets every employee and Agent can call?

Four: is work judged acceptable because "the boss took a look," or because clear, executable, traceable Evals exist?

Five: does a person get resources and decision rights because they permanently occupy a position, or because they are currently responsible for a concrete outcome?

If these questions still resolve through hierarchy, the company is at best using AI.

Only when information no longer depends on middle-layer relay, methods no longer depend on personal monopoly, tasks can be executed by Agents, quality can be verified by Evals, and responsibility can dynamically reorganize around outcomes — only then does it truly start becoming an AI Native Company.

Coda: management stays, the management layer goes

A traditional company is a pyramid.

Information climbs level by level from the bottom; power descends level by level from the top. Middle managers stand at every node, compressing information, relaying orders, coordinating resources, keeping process alive.

An AI Native Company looks more like a continuously learning organizational intelligence.

Company Context remembers. Skills accumulate methods. Agents execute. Evals judge. The permission system controls risk. DRIs own concrete outcomes. Player-coaches own human growth.

So what zero middle management removes is not management, and not responsibility.

It removes one default assumption of the industrial age: that a person can permanently occupy a layer of the company by collecting information, holding meetings, relaying instructions, and managing others.

Future companies will still have founders, still have owners, still have people with deeper experience and better judgment. But their value will no longer come from standing on the path information must pass through. It will come from setting direction, carrying responsibility, making judgment calls, and growing people.

In an AI Native Company, everyone must ultimately stay close to one of two things: real work, or real customers.

Leave the information hauling to the Agents.