Managing a Company Valued at Nearly a Trillion Dollars, Anthropic's CEO Has Only One Direct Report

marsbitОпубликовано 2026-06-12Обновлено 2026-06-12

Введение

Anthropic CEO Dario Amodei has only one direct report, his chief of staff, in a stark departure from the tech industry trend of CEOs managing many direct reports. Company executives instead report to President Daniela Amodei, Dario's sister, who handles daily operations. This structure allows Dario, a researcher by background, to focus his time on long-term strategy, research direction, and cultivating company culture, which he sees as critical as Anthropic grows rapidly and hires from larger tech firms. He spends significant time on company-wide meetings and writing about AI's societal impact. Harvard professor Raffaella Sadun suggests such a narrow span of control is suitable for companies like Anthropic that face novel, high-stakes problems requiring top-level judgment, as it protects the CEO's time as the scarcest resource.

Bloomberg interviewed Anthropic CEO Dario Amodei and uncovered a very interesting detail: as the CEO of a company valued at nearly a trillion dollars, he has only one direct report.

That is his Chief of Staff, Avital Balwit. All other company executives (CFO, CCO, etc.) do not report to him, but instead report to his sister, President Daniela Amodei. Daniela handles the daily operations and is accountable to the board.

Why It's Unusual

The prevailing trend in the tech industry now is "flattening," where CEOs directly manage an increasing number of people. Jensen Huang manages 60 people and holds no one-on-one meetings, with the logic being "if the CEO directly manages 60 people, you can eliminate 7 layers of management." Sam Altman manages about 6.

Dario manages only 1, going completely against this trend.

Why He Does It This Way

Dario's background is as an academic researcher (Ph.D. in biophysics from Princeton, previously a researcher at Google and OpenAI), not a professional manager.

He believes the CEO's greatest value lies in "zooming out" activities: strategic direction, research judgment, organizational culture, and contemplating the impact of AI on human civilization. These tasks require large blocks of uninterrupted time. Daily management ("zooming in") fragments time, preventing deep thinking on big-picture issues. Therefore, he completely separates these two functions, focusing solely on the former and handing the latter entirely to Daniela.

His exact words are: "If you have a bunch of things to deal with tomorrow, it's very hard to focus on the strategic big picture."

Where He Spends His Time

He spends roughly half his time on cultural development. Specifically, he holds a bi-weekly all-hands meeting called the "Dario Vision Quest," where he writes a long memo and speaks for an hour.

His biggest worry is: as the company rapidly expands from a few hundred to 2,500 people, with many new hires coming from large tech companies, if Anthropic's culture isn't proactively instilled, these employees will default to replicating the practices of their former companies, diluting the company culture.

He spends the remaining time on research direction, strategy, and writing long-form public articles. He dedicates significant time to thinking about what AI means for human civilization and outputs his thoughts through these long public articles.

The Logic Behind the Sibling Division of Labor

This arrangement is not arbitrary but based on their complementary backgrounds. Dario comes purely from a research background, having served as VP of Research at OpenAI; Daniela comes from an operational background, having been an early employee at Stripe and leading safety and policy teams at OpenAI, being more adept at managing "people." They each do what they excel at.

Another notable detail: All seven of Anthropic's co-founders are still with the company.

In tech startups, it's common for co-founders to leave over time; having all seven remain is indeed rare. The Amodei siblings point to this as proof of the company's cultural cohesion.

A Harvard Professor's Explanation: What Kind of Company Needs What Kind of Management Span

Harvard Business School professor Raffaella Sadun provides a framework. She compares a company to a problem-solving machine: lower-level employees handle routine problems, while harder, newer problems move up the hierarchy.

If a company mostly faces known types of problems, the CEO can manage many people because those underneath can handle things themselves. The leaders of various divisions at Nvidia know what they need to do, so Jensen Huang can manage 60 people and the operation still runs smoothly.

But if a company constantly faces entirely new, high-risk problems without ready-made answers, the CEO needs a narrower span of control to reserve time for the matters that truly require his judgment. Anthropic is such a case: where are the safety boundaries, should they cooperate with the military, how to choose the technological path for the next-generation model—these are all novel questions.

Her conclusion is: "The manager's time is the scarcest resource."

The essence of organizational structure is to protect this scarce resource.

Full Translation:

Anthropic CEO Dario Amodei Has Only One Direct Report

Bloomberg · June 10, 2026

Key Takeaways

· Anthropic PBC CEO Dario Amodei has only one direct report, Chief of Staff Avital Balwit, which is extremely rare in the tech industry.

· The company's executive team reports to Anthropic President Daniela Amodei, who handles daily operations and is accountable to the board, allowing Dario to focus on strategic thinking and research direction.

· Dario spends a significant amount of time discussing Anthropic's culture with employees. Maintaining the company culture is his and Daniela's top priority amid rapid growth.

Despite Dario Amodei's immense influence at Anthropic PBC, the co-founder and chief executive officer has just one direct subordinate at the artificial intelligence company.

This is uncommon in the tech industry. Many tech leaders today are flattening hierarchies and broadening their spans of control. OpenAI CEO Sam Altman has about six direct reports, while Nvidia CEO Jensen Huang says 60 people report directly to him.

Anthropic is experimenting with a different leadership model: a CEO who leaves almost all his time for strategic thinking, organizational culture, and input on research direction and strategy, rather than managing senior executives. The company's executive team instead reports to Dario's sister, Anthropic President Daniela Amodei, who oversees most daily operations and is accountable to the Anthropic board. The only person Dario directly manages is his chief of staff, Avital Balwit.

"It is incredibly freeing," Dario said in an interview with Emily Chang for Bloomberg's "The Circuit" program. "It allows me to do all the things I should be doing much more easily than I ever did before."

For Dario, a first-time founder and a Princeton Ph.D. in biophysics whose early career was spent in a research lab, that often means spending a lot of time thinking about artificial intelligence and its implications for humanity. He does this via companywide "Vision Quest" meetings—where he reflects on a broad range of topics—and long public essays.

"It's a matter of focus and context in many ways. If you have a bunch of things you have to deal with tomorrow, it's very hard to focus on the strategic big picture," he said. "And so separating these two things can often be very useful so you can do both well."

Before co-founding Anthropic, Dario was a vice president of research at OpenAI, leaving over disagreements with the ChatGPT maker's leadership to start Anthropic in 2021. Prior to that, he was a senior research scientist at Google.

Daniela has more experience managing people at tech startups, having been an early employee at Stripe and also leading safety and policy teams at OpenAI.

Anthropic, valued at close to $1 trillion in its latest funding round, is working toward a public listing ahead of rival OpenAI.

The company brought on veteran tech executives in 2024, including Chief Financial Officer Krishna Rao, and in 2025 hired Chief Commercial Officer Paul Smith to support rapid expansion. They work alongside all seven of Anthropic's co-founders, whom the Amodei siblings have long cited as evidence of a cohesive culture.

Dario estimates he spends "maybe half" his time talking to employees about "Anthropic culture and how culture works," and said maintaining the company's culture is perhaps his and Daniela's "No. 1 priority."

"When you're growing this fast, you hire a lot of people from big tech companies. And if you don't tell them how Anthropic works, they will naturally replicate the only thing they know, which is how their previous companies work," he said.

Harvard Business School economist and management professor Raffaella Sadun says that how many people a CEO directly manages, beyond personal preference or leadership style, also reflects the nature of the organization's work. A company can be thought of as a problem-solving machine, she says, with lower-level staff handling routine matters and tougher issues and exceptions moving up the chain.

That suggests a CEO can have a wider span of control when other leaders in the organization are seasoned experts who can independently handle their areas of responsibility; but when a company faces a steady stream of novel problems and high-stakes decisions that require more senior judgment—like Anthropic—a narrower span might be necessary.

In either case, the organization must be thoughtfully constructed. "The manager's time is the scarcest resource," Sadun said. Ideally, a company's architecture is designed to protect that resource.

Связанные с этим вопросы

QWhat is the unconventional aspect of Dario Amodei's leadership at Anthropic?

AAs the CEO of a company valued at nearly a trillion dollars, Dario Amodei has only one direct report: his chief of staff, Avital Balwit. This contrasts sharply with the broader industry trend of CEOs expanding their span of control.

QWhy does Dario Amodei choose to have only one direct report?

ADario comes from a research background and believes the CEO's primary value lies in 'zoom out' activities like strategic direction, research judgment, organizational culture, and pondering AI's impact on humanity. He delegates all day-to-day 'zoom in' operational management to his sister, President Daniela Amodei, to protect large blocks of uninterrupted thinking time.

QHow does Dario Amodei spend most of his time at Anthropic?

AHe spends roughly half his time on cultural-building activities, primarily through bi-weekly all-hands meetings called 'Dario Vision Quest,' where he presents a long memo. The rest of his time is dedicated to research direction, strategy, and writing long-form public articles on AI's implications for civilization.

QWhat is the rationale behind the division of responsibilities between Dario and Daniela Amodei?

AThe division is based on complementary expertise. Dario's background is purely in research, while Daniela has extensive operational experience from roles at Stripe and OpenAI. This setup allows each to focus on their strengths: Dario on long-term strategy and culture, Daniela on daily operations and people management.

QAccording to Professor Raffaella Sadun, what determines the optimal span of control for a CEO?

AProfessor Sadun explains that a CEO's span of control depends on the nature of the problems the company faces. If a company deals mostly with known problems where leaders can operate independently, a wider span (more direct reports) is feasible. If it constantly faces novel, high-stakes problems requiring senior judgment (like Anthropic), a narrower span is necessary to protect the CEO's time, which is the most scarce resource.

Похожее

The Revelation from the Raydium Theft Incident: New DeFi Vulnerabilities Lurking in Forgotten Old Contracts

**Raydium Exploit Reveals DeFi's Hidden Risk: Forgotten "Zombie" Contracts** A recent attack on Raydium's deprecated V3 AMM pools resulted in a loss of approximately $1.34 million. The hacker exploited pools that were no longer supported by Raydium's current UI or SDK but remained fully functional and accessible on-chain. This incident highlights a critical, often overlooked category of risk in DeFi: inactive or legacy smart contracts that projects fail to properly decommission. Since March 2025, there have been at least 8 publicly reported attacks targeting such abandoned contracts, with total losses around $10.8 million. Including older pools and deprecated features, the count rises to 10 incidents with roughly $22.5 million in losses. These "zombie contracts" represent a lifecycle management failure rather than a code vulnerability, yet they are typically misclassified under general "code bug" categories in security reports, masking the true scale of the problem. The root cause is that projects often merely document a contract as "deprecated" without taking essential technical steps to secure it: withdrawing remaining assets, disabling external call functions, and implementing ongoing monitoring. These forgotten, under-monitored components become prime targets for attackers. To address this, the industry needs to recognize "zombie contracts" as a distinct risk category and establish standardized decommissioning protocols. Essential steps should include: 1) a formal retirement announcement, 2) removal of all front-end integrations, 3) withdrawal of locked assets, 4) disabling key contract functions, 5) ongoing security monitoring, 6) clear user communication, and 7) a post-mortem analysis. The value of a DeFi project lies not only in its current TVL but also in the security of its historical codebase, which has now become a new attack surface.

Foresight News16 мин. назад

The Revelation from the Raydium Theft Incident: New DeFi Vulnerabilities Lurking in Forgotten Old Contracts

Foresight News16 мин. назад

Robots Begin to 'Consume Data': The Hidden Production Chain from Indian Data Factories to Billion-Dollar Humanoid Robots

Robots have started to 'consume data,' driving the formation of a new industrial supply chain focused on producing training data for embodied AI. Unlike large language models, which are trained on vast internet text corpora, embodied AI models face a 'data desert' in the physical world. This has created a massive demand for first-person perspective video data (Ego Data), captured by workers wearing cameras in places like Indian garment factories. Companies like Neocambrian AI are establishing 'data factories' where workers perform standardized tasks (e.g., sorting clothes, kitchen organization) to generate thousands of hours of video. Research, such as NVIDIA's EgoScale, demonstrates that scaling this human demonstration data predictably improves robot performance, particularly for dexterous manipulation. This has validated a training path combining large-scale human data for pre-training with smaller amounts of robot-specific data for fine-tuning. The value of different data types varies significantly, forming a 'data pyramid.' The base consists of low-cost, large-scale internet and Ego Data. Higher layers include more expensive motion-capture data (e.g., from data gloves), simulation/synthetic data, and the most costly and scarce layer: real robot teleoperation data. This demand has spawned a layered ecosystem of data suppliers: low-cost data factories, motion capture and alignment specialists, robot-native teleoperation service providers, simulation data companies, and platforms aiming for data standardization. Robot companies themselves are adopting a 'layered procurement' strategy: outsourcing generic Ego Data while building in-house capabilities for robot-specific adaptation data and the critical deployment/failure data generated in real-world applications. The industry is shifting focus from hardware and basic mobility to the data pipelines required for general-purpose capability. While parallels exist to data labeling companies like Scale AI in the LLM boom, the physical complexity of robot data—involving action success ambiguity and sim-to-real gaps—requires more integrated solutions for data collection, annotation, and a continuous feedback loop. The race is on to build the data engines that will teach robots to operate reliably in the unstructured real world.

marsbit2 ч. назад

Robots Begin to 'Consume Data': The Hidden Production Chain from Indian Data Factories to Billion-Dollar Humanoid Robots

marsbit2 ч. назад

Spicy Commentary | Michael Saylor's 'Player Talk'; 60-Year-Old Aunt Liquidated After 'Scamming a Young Man'

**"Spicy Commentary": Three Tales of Crypto's Wild Week** This week's "Spicy Commentary" column highlights three dramatic stories from the cryptocurrency world. First, **MicroStrategy's Michael Saylor** addressed the controversy over his company potentially selling Bitcoin. At the BTC Prague event, he clarified, "I never said the company can't sell Bitcoin. I told *you* never to sell *your* Bitcoin." This "do as I say, not as I do" stance was criticized by netizens as peak linguistic gymnastics, noting a history of him previously stating the company would "never" sell. Second, a **bizarre fraud case** emerged from Beijing. A 60-year-old woman, obsessed with getting rich from crypto but unwilling to risk her own savings, posed online as the 20-something "god-daughter" of a high-ranking official. She catfished a young man, convincing him to give her over 200,000 yuan for fabricated emergencies. She then invested all the stolen money into cryptocurrency with 10x leverage, only to lose everything in a market crash. The woman was sentenced to four years in prison for fraud. Finally, a **sobering trader's tale** surfaced on Reddit. A user posted "Tale of a crypto trader," confessing their net worth had plummeted from a peak of $45 million to roughly $17,200, primarily due to holding meme coins too long. The post, described as a crypto "book of confessions," sparked reactions ranging from sympathy to critique about greed, poor risk management, and the perils of treating meme coins as long-term investments instead of taking profits. The column concludes that this week featured masterful rhetoric, elaborate scams, and extreme financial volatility, stitching together another chapter in crypto's unpredictable theater.

Foresight News3 ч. назад

Spicy Commentary | Michael Saylor's 'Player Talk'; 60-Year-Old Aunt Liquidated After 'Scamming a Young Man'

Foresight News3 ч. назад

Tremble Humans, AI Continues Its Accelerated Sprint

Trembling, Humans: AI Continues Its Accelerated Sprint Yes, AI is still rapidly accelerating. While deep learning seemed to stall quickly in its early years, large models after years of development show no sign of hitting their ceiling. At the Zhiyuan Conference 2026, the focus is on enabling AI to move from the digital world into the physical world. Scaling Law remains effective, continuing to drive advancements in both large language models and multimodal models. The industry is now entering a phase of pursuing World Models, though unresolved technical paths and data issues mean this exploration may take 3-5 more years. Concurrently, breakthroughs in Agents are accelerating AI's real-world application in fields like healthcare and meetings. Making Agents truly useful requires key hardware-software co-design, evident from the strong presence of chip vendors at the conference. We stand at a new historical threshold where AI is becoming a foundational force reshaping the world. The first day of the conference highlighted AI's evolution from "knowing how to chat" to "knowing how to work." Scaling Law persists, World Models are the next key battleground, and Agents are transitioning from usable to好用 (user-friendly). Scaling Law is not ending but diversifying. New models like Anthropic's Fable 5 demonstrate scaling through parameter size, synthetic data, and reinforcement learning. Advancements in AI Coding and Agent deployment are enabling a trend of AI self-evolution, potentially allowing AI to take over digital world iterations. World Models represent the next frontier for large models extending into the physical realm, but no current model is truly impressive at solving real-world problems. Technical consensus is lacking, with debates on data sources (video, simulation, real-world). Different approaches are emerging: language-centric, pixel-centric, 3D-structure-centric, and visual-representation-centric models. Zhiyuan Institute is exploring a fifth path: unified latent space modeling fusing language and visual representations, and introduced its own under-development World Model, Physis-v0.1. On the product side, Agents are key to bringing AI into daily life. Since 2025, the "Year of the Agent," products have become more proactive and capable of complex tasks. Zhiyuan showcased four vertical Agents for cardiac diagnosis, autonomous research, meeting summarization, and protein risk discovery. However, technical challenges remain, particularly in context engineering like memory and orchestration. "Harness" – the engineering framework around an Agent – is crucial for maximizing its capabilities by clarifying intent, designing workflows, and incorporating validation and feedback. In summary, AI's breakneck pace continues on multiple fronts: foundational model scaling, the ambitious pursuit of World Models for physical understanding, and the ongoing refinement of practical Agents. The journey from capable to truly reliable and useful AI systems is well underway.

marsbit3 ч. назад

Tremble Humans, AI Continues Its Accelerated Sprint

marsbit3 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Как купить S

Добро пожаловать на HTX.com! Мы сделали приобретение Sonic (S) простым и удобным. Следуйте нашему пошаговому руководству и отправляйтесь в свое крипто-путешествие.Шаг 1: Создайте аккаунт на HTXИспользуйте свой адрес электронной почты или номер телефона, чтобы зарегистрироваться и бесплатно создать аккаунт на HTX. Пройдите удобную регистрацию и откройте для себя весь функционал.Создать аккаунтШаг 2: Перейдите в Купить криптовалюту и выберите свой способ оплатыКредитная/Дебетовая Карта: Используйте свою карту Visa или Mastercard для мгновенной покупки Sonic (S).Баланс: Используйте средства с баланса вашего аккаунта HTX для простой торговли.Третьи Лица: Мы добавили популярные способы оплаты, такие как Google Pay и Apple Pay, для повышения удобства.P2P: Торгуйте напрямую с другими пользователями на HTX.Внебиржевая Торговля (OTC): Мы предлагаем индивидуальные услуги и конкурентоспособные обменные курсы для трейдеров.Шаг 3: Хранение Sonic (S)После приобретения вами Sonic (S) храните их в своем аккаунте на HTX. В качестве альтернативы вы можете отправить их куда-либо с помощью перевода в блокчейне или использовать для торговли с другими криптовалютами.Шаг 4: Торговля Sonic (S)С легкостью торгуйте Sonic (S) на спотовом рынке HTX. Просто зайдите в свой аккаунт, выберите торговую пару, совершайте сделки и следите за ними в режиме реального времени. Мы предлагаем удобный интерфейс как для начинающих, так и для опытных трейдеров.

1.4k просмотров всегоОпубликовано 2025.01.15Обновлено 2026.06.02

Как купить S

Sonic: Обновления под руководством Андре Кронье – новая звезда Layer-1 на фоне спада рынка

Он решает проблемы масштабируемости, совместимости между блокчейнами и стимулов для разработчиков с помощью технологических инноваций.

2.3k просмотров всегоОпубликовано 2025.04.09Обновлено 2025.04.09

Sonic: Обновления под руководством Андре Кронье – новая звезда Layer-1 на фоне спада рынка

HTX Learn: Пройдите обучение по "Sonic" и разделите 1000 USDT

HTX Learn — ваш проводник в мир перспективных проектов, и мы запускаем специальное мероприятие "Учитесь и Зарабатывайте", посвящённое этим проектам. Наше новое направление .

1.8k просмотров всегоОпубликовано 2025.04.10Обновлено 2025.04.10

HTX Learn: Пройдите обучение по "Sonic" и разделите 1000 USDT

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на S (S) представлены ниже.

活动图片