From Housemate Arguments to a $300 Billion Showdown: WSJ Long-Form Article First Reveals the Decade-Long Personal Feud Between Anthropic and OpenAI Founders

marsbitPublicado a 2026-03-28Actualizado a 2026-03-28

Resumen

The Wall Street Journal reveals the decade-long personal rift between Anthropic and OpenAI founders, Dario and Daniela Amodei, and OpenAI's Sam Altman and Greg Brockman. The conflict, rooted in philosophical differences over AI development and governance, began in 2016. Tensions escalated over leadership disputes, credit attribution, and management styles, culminating in the Amodeis and nearly a dozen employees leaving OpenAI in late 2020 to form Anthropic. Today, both companies are valued over $300 billion, competing fiercely while their founders' unresolved personal animosity continues to shape the global AI landscape.

Wall Street Journal reporter Keach Hagey published a long-form investigative report, systematically disclosing for the first time, through extensive interviews with current and former employees and people close to executives at both companies, the decade-long personal feud between the founders of Anthropic and OpenAI. What shaped the global AI landscape was not just a battle over technological roadmaps, but also a never-healed personal wound.

Dario Amodei's rhetoric internally in recent months has been far more intense than in public. He compared Sam Altman's legal dispute with Elon Musk to "Hitler vs. Stalin," called OpenAI President Greg Brockman's $2.5 million donation to a pro-Trump super PAC "evil," and likened OpenAI and other competitors to "tobacco companies selling products they know are harmful."

After the Pentagon dispute escalated, he wrote on Slack calling OpenAI "mendacious," stating, "These facts indicate a pattern of behavior I have seen repeatedly in Sam Altman."

Internally, Anthropic refers to this branding strategy as creating a "healthy alternative" to its competitor. An ad during this year's Super Bowl, which implicitly mocked OpenAI for embedding ads in its chatbot, is a public manifestation of this strategy.

The story begins in the living room of a shared house on Delano Street in San Francisco in 2016. Dario and his sister Daniela Amodei lived there, and OpenAI co-founder Brockman often visited due to his personal friendship with Daniela. One day, Brockman, Dario, and Daniela's then-fiancé, effective altruism philanthropist Holden Karnofsky, sat together arguing about the right path for AI development: Brockman believed all Americans should be informed about what was happening at the AI frontier, while Dario and Karnofsky believed sensitive information should be reported to the government first, not broadcast to the public. This disagreement later became the philosophical dividing line between the two companies.

Impressed by OpenAI's talent roster, Dario joined in mid-2016, staying up late with Brockman training AI agents to play video games. But over four years of working together, conflicts deepened around power and a sense of belonging. In 2017, Musk, OpenAI's main funder at the time, demanded a list of each employee's contributions and conducted layoffs based on it. About 10% to 20% of the roughly 60-person team were fired one by one. Dario saw this as cruel; one of those laid off later became an Anthropic co-founder.

That same year, an ethics advisor hired by Dario proposed that OpenAI act as a coordinating entity between AI companies and the government. Brockman extrapolated from this the idea of "selling AGI to the nuclear powers on the UN Security Council." Dario considered this近乎叛国 (close to treasonous) and once considered resigning.

After Musk exited in 2018, Altman took over leadership. He and Dario agreed that employees lacked confidence in the leadership of Brockman and Chief Scientist Ilya Sutskever. Dario stayed on the condition that the two would no longer be his supervisors, but soon discovered that Altman had simultaneously promised the latter two the authority to fire him—two contradictory promises.

After the development of the GPT series began, the most intense conflict among executives erupted over who could work on the language model project. Dario, then research director, barred Brockman from involvement. Daniela, who co-led the project with Alec Radford, threatened to resign as lead. Radford's personal wishes were caught in a proxy war among the executives.

Dario's seniority grew with the success of GPT-2 and GPT-3, but he felt Altman downplayed his contributions. He was angry when Brockman went on a podcast to discuss the OpenAI charter, feeling his greater contribution to the charter warranted an invitation; he was similarly displeased to learn that Brockman and Altman were meeting former President Obama but excluded him.

The conflict came to a head in a confrontational meeting. Altman called the Amodei siblings into a conference room, accusing them of encouraging colleagues to submit negative feedback about him to the board. They denied it. Altman said the information came from another executive. Daniela immediately called that executive in to confront them, and the person said they knew nothing about it.

Altman then denied having said that. A fierce argument ensued. In early 2020, Altman asked executives to write peer reviews for each other. Brockman wrote a strongly worded review accusing Daniela of abusing power and using bureaucratic processes to exclude dissenters; Altman previewed it and called it "tough but fair." Daniela rebutted it point by point. The argument escalated to the point where Brockman once proposed withdrawing the review.

At the end of 2020, the team centered around Dario decided to leave, with Daniela leading negotiations with lawyers regarding their departure. Altman personally went to Dario's home to persuade him to stay. Dario proposed reporting directly only to the board and explicitly stated he could not work with Brockman. Before leaving, he wrote a long memo dividing AI companies into "market-oriented" and "public benefit-oriented" types, suggesting the ideal mix was 75% public benefit, 25% market. Weeks later, Dario, Daniela, and nearly a dozen employees left OpenAI to found Anthropic.

Five years later, both companies are valued at over $300 billion and are racing to be the first to IPO. During the group photo at the closing of the AI summit in New Delhi this February, Indian Prime Minister Modi and the tech leaders present raised their hands high. Amodei and Altman chose not to participate, only awkwardly bumping elbows.

Preguntas relacionadas

QWhat was the core philosophical disagreement about AI development between Dario Amodei and Greg Brockman in 2016?

AThe core disagreement was about how to disseminate information about AI advancements. Greg Brockman believed the information should be broadcast to the entire American public, while Dario Amodei and Holden Karnofsky argued that sensitive information should be reported to the government first, not broadcast publicly.

QWhat internal brand strategy does Anthropic use to position itself against OpenAI?

AAnthropic's internal brand strategy is to position itself as a 'healthy alternative' to its competitors, specifically OpenAI. This was exemplified by a Super Bowl ad that implicitly criticized OpenAI for placing ads in its chatbot.

QWhat major event involving Elon Musk at OpenAI did Dario Amodei view as 'cruel'?

ADario Amodei viewed Elon Musk's directive in 2017 to rank every OpenAI employee by contribution and subsequently lay off 10% to 20% of the roughly 60-person team as a 'cruel' event.

QWhat was the final ultimatum Dario Amodei gave to Sam Altman in an attempt to stay at OpenAI before leaving?

ADario Amodei's final ultimatum was that he would only stay at OpenAI if he reported directly to the board and made it clear that he could not work with Greg Brockman.

QHow did Dario Amodei categorize AI companies in a memo written just before leaving OpenAI, and what was his proposed ideal ratio?

AIn his memo, Dario Amodei categorized AI companies into 'market-driven' and 'public benefit' types. He proposed that the ideal mix for a company should be 75% public benefit and 25% market-driven.

Lecturas Relacionadas

Agent Race Ends, Super Workbench Takes Over

The era of fragmented AI agents is ending. Over the past month, China's tech giants—Tencent, Alibaba, and ByteDance—have simultaneously shifted strategy: instead of launching new, standalone AI agents, they are consolidating their various agent projects into unified "super workbenches." Tencent integrated its QClaw teams into WorkBuddy, a strategic product hailed as a potential third flagship after QQ and WeChat. Alibaba is merging its QoderWork, Wukong, and MuleRun agents into a new "Qianwen Office" platform under DingTalk's leadership. ByteDance rebranded its TRAE SOLO coding agent to TRAE Work, signaling a broader focus on workflow collaboration. This convergence marks a pivotal industry consensus. The initial exploration phase, where companies rapidly built numerous overlapping agents for different scenarios, proved costly and inefficient. With open-source tools eroding technical barriers, competition has shifted from agent creation to resource consolidation and cost control. Historically, platform wars are won not by creating more products, but by simplifying them—as seen with browsers unifying web access and super-apps consolidating services. Now, the "super workbench" aims to become the unified AI entry point for work. This reflects a deeper market realization: the primary audience for AI is no longer just programmers (a market in the tens of millions) but all knowledge workers (a market of billions). The real opportunity lies in augmenting everyday tasks—managing emails, documents, data, and meetings—across the entire workday. The core battleground is becoming control over the primary AI entry point that employees use daily. Tencent's WorkBuddy leverages WeChat and Tencent Docs; Alibaba's Qianwen Office taps into DingTalk's organizational data; ByteDance's TRAE Work integrates with Feishu's workflows. Whoever owns this "super workbench" gains strategic control over orchestrating enterprise data and APIs. This shift is redefining enterprise software. Traditional SaaS applications, valued for their user interfaces, will recede into the background. Their core functionalities will be exposed as standardized "Skills" or APIs for the super workbench's agents to invoke. Software value will shift from selling user seats to charging based on API calls and outcomes delivered. The evolution of agents is moving through clear stages: first as novel standalone products, then as consolidated primary work entry points, and finally as pervasive, invisible capabilities embedded into the digital fabric. The recent moves by major tech firms signal the transition from the first stage into the second, accelerating toward the third. In the end, the most successful agent technology may become invisible—like electricity or the HTTP protocol—a fundamental, unnamed infrastructure powering work itself.

marsbitHace 7 min(s)

Agent Race Ends, Super Workbench Takes Over

marsbitHace 7 min(s)

Michael Saylor: 110 Reasons to Oppose BIP-110

Michael Saylor presents 110 arguments against Bitcoin Improvement Proposal (BIP) 110, a soft fork aimed at restricting certain non-monetary data storage uses (like inscriptions) on the Bitcoin blockchain. He acknowledges the proponents' valid concerns—such as node costs, fee pressure, and preserving Bitcoin's monetary focus—but fundamentally disagrees with the proposed solution. Saylor argues that BIP 110 represents a dangerous precedent of using consensus rules to enforce value judgments on transaction validity, moving away from Bitcoin's core principles of neutrality and permissionless innovation. His key objections are organized into eleven categories: 1) It violates neutrality and hard consensus by banning currently valid transactions. 2) It fails to meet the high burden of proof required for a consensus change, lacking concrete data on the alleged crisis. 3) Its seven bundled technical restrictions are overly broad, targeting generic script functionalities and blocking future upgrade paths. 4) It sacrifices compatibility and future optionality by closing off designed upgrade hooks. 5) Its temporary rules add significant complexity (grandfathering, expiry states) without sufficient justification. 6) The economic and security impacts, particularly on miner revenue and fee markets, are uncertain and unmodeled. 7) Superior, market-based tools (fee markets, relay/mining policies) already exist to manage blockchain load. 8) It stifles innovation by creating a chilling effect for developers. 9) Its modified activation mechanism (55% threshold, forced signaling) is aggressive and risks network splits. 10) The precedent it sets—using consensus to suppress disliked but legal uses—is more dangerous than the problem it aims to solve. 11) A better path exists: improving measurements, refining resource-based policies, and allowing market forces to work. Saylor concludes that Bitcoin's strength lies in its neutral rules, open markets, and hard consensus. Changing these foundational elements to target specific use cases is an unnecessary and risky "iatrogenic" intervention. He advocates for guarding Bitcoin's neutrality rather than acting as its redeemer.

marsbitHace 22 min(s)

Michael Saylor: 110 Reasons to Oppose BIP-110

marsbitHace 22 min(s)

Trading

Spot
活动图片