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Seven People, One Anthropic: The Founding Team Behind ClaudeIn December 2020, Dario Amodei told an all-hands video call at OpenAI that he and six colleagues were leaving to start a company that would put AI safety at its center. The chat filled with surprise and goodbyes. Jack Clark typed: “I love you all.” Then the seven screens went dark. They had been removed from the meeting, their work email and Slack access revoked, their laptops locked remotely.
A few hours earlier they had been senior researchers and managers at one of the leading AI labs. Now they had no jobs, no office systems and no clear next step. Where would the GPUs come from? The money? What would the company be called? Even buying everyone new laptops was an open question. Almost six years later, the company is called Anthropic, its product Claude competes head-on with OpenAI, and the founders are preparing to take it public.
That departure scene comes from an excerpt of Kevin Roose’s new book, published in The Atlantic. It is a better starting point than “seven executives start an AI company”: these were people who had already helped build frontier models, and they were trying to write their disagreements about risk, speed and organizational responsibility into the rules of a new company. Source: The Atlantic
Why they left
The departure is often boiled down to “OpenAI didn’t take safety seriously enough.” That gets the direction right and flattens the rest. Safety was the core disagreement, but it was tied up with who could decide when a product shipped, how the company was run, and whether a safety team could change anything once AI research had become a commercial race.
Dario was OpenAI’s vice president of research. He put conditions to Sam Altman for staying, including giving the safety team the power to block product launches. While those talks were still going, the seven set up a private Slack group called BATNA, a negotiation term for “best alternative to a negotiated agreement.” They were bargaining and preparing an exit at the same time. The talks did not produce a deal.
Daniela negotiated the exit on the group’s behalf. Both sides brought in lawyers and settled on a window during which the departing team could recruit colleagues, plus a one-year mutual no-poach agreement. Dario announced the decision at the all-hands, and Jack left his goodbye in the chat. The details matter: Anthropic was not a group of star scientists who barely knew each other. They had worked inside the same organization and went through a hard collective exit together.
When TIME interviewed him later, Dario was restrained about why they left, putting the weight on mutual trust, shared values and a common mission. He has also argued that AI risk is an empirical question: you have to build and study sufficiently powerful systems to learn what the risks actually are. That is the tension built into Anthropic. It is wary of powerful AI, and it believes it has to push powerful AI forward itself in order to study and manage it. Source: TIME on Anthropic
None of this made the conflict between safety and business go away. It moved the conflict inside Anthropic. Research needs scale and compute. Safety needs time, evaluation and restraint. Commercial growth needs products that keep improving and customers who keep adopting them. What the founders chose together was not to leave the race, but to build a lab that says it will run the race differently.
Six founders’ skills link into one research loop; Daniela’s job of running the company is the outer ring holding it together. Drawn from public roles; not an actual reporting line.
Seven jobs, one company
Dario Amodei: turning scientific judgment into company direction. Dario trained in physics and biophysics and worked at Google Brain and then OpenAI, where he was vice president of research, helped develop large language models, and worked with colleagues on reinforcement learning from human feedback. As Anthropic’s CEO he sets research direction and strategy. His main influence is less any single technique than a question he keeps asking at the level of the organization: if model capabilities grow as expected, what safety machinery does the company need to have in place first? His public writing stresses risk and also describes large possible benefits, for example in biomedicine. He holds both at once, which is part of why Anthropic keeps building while studying how to constrain what it builds. Sources: Dario Amodei’s website, Anthropic leadership
Daniela Amodei: organizing research into a company that ships. Daniela is president and chair of the board, and Dario’s sister. Before Anthropic she worked at Stripe and at OpenAI, in roles spanning safety and policy, people, and engineering management. Her remit covers research, engineering, product, governance and commercial execution, and she manages the executive team. If Dario is usually seen as the company’s technical vision, Daniela’s job is to keep the research organization, product teams, customer demands and company rules all running at once. Her role in negotiating the exit shows she was drawing the company’s organizational boundaries from day one, not holding a symbolic management title. Sources: S-1 management biographies, Anthropic leadership
Tom Brown: making large-model training work as engineering. Tom led engineering on GPT-3 and is now Anthropic’s chief compute officer, responsible for acquiring, scaling and using compute. He is also first author of the GPT-3 paper, “Language Models are Few-Shot Learners.” The 175-billion-parameter GPT-3 showed that scaled-up models could handle many tasks from a few examples. Behind the paper sat hardware scheduling, distributed training, reliability and cost control. Tom’s career connects the scientific ideas behind models with the enormous machinery needed to run them. Compute today is not a back-office budget line; it sets how fast a lab can experiment and where it stands against competitors. Sources: S-1 founder biographies, GPT-3 paper
Jared Kaplan: finding the regularities between scale and capability. Jared is a theoretical physicist and Anthropic’s chief science officer. “Scaling Laws for Neural Language Models,” which he wrote with Dario, Tom, Sam and others, studied how parameters, data and training compute affect a model’s loss. Its empirical regularities help researchers estimate how to split extra compute between model size and data. It did not prove that any capability will appear if you just make models bigger, and it does not replace experiments. What it offers is a testable framework, so frontier experiments are not pure guesswork. Jared now leads Anthropic’s technical research, linking basic science, model development and AI safety. Sources: Johns Hopkins University, Scaling laws paper
Sam McCandlish: making the research loop faster and more reliable. Sam is a physicist who built and led OpenAI’s team studying the science of machine learning and scaling, and he co-authored the scaling laws paper. Anthropic lists him as chief architect, focused on pretraining, research productivity and reinforcement learning infrastructure. Training a large model is not one press of a button. Teams run experiments over and over, track down failures, compare results and reuse systems. Sam’s specialty is the infrastructure for that loop. Tom focuses on compute resources and how they are organized; Sam sits closer to the training pipeline and research tooling. Each depends on the other to turn resources into model progress. Sources: S-1 founder biographies, Anthropic leadership
Chris Olah: trying to open the black box. Chris Olah is an early driver of mechanistic interpretability. He worked at Google Brain, led interpretability research at OpenAI, and co-founded the journal Distill. He describes his goal as reverse-engineering neural networks into algorithms humans can understand. Anthropic’s research on Claude has identified millions of concept features. In one well-known demo, researchers amplified a “Golden Gate Bridge” feature, and the model began describing itself as the Golden Gate Bridge in answer to all kinds of questions. The demo made abstract research concrete, and it also showed that when internal representations are pushed artificially, a model’s behavior can turn strange. Olah’s field has not made models fully transparent, but it has produced new ways to inspect how they work inside. Sources: Chris Olah’s website, Anthropic research
Jack Clark: translating lab language into public questions. Jack was a technology journalist covering supercomputers, neural networks and advanced technology before joining OpenAI to run policy and communications. He is now Anthropic’s head of public benefit and leads the Anthropic Institute, which studies the social effects of frontier AI. His background differs from the technical founders’: while engineers talk about evaluations and training scale, Jack has to connect those ideas to policy, jobs, national security and public understanding. His reporting experience is a bridge between the company and the outside world, not a substitute for technical work. A company studying the public interest also faces a credibility test: who sets the research agenda, and can the conclusions stand apart from the company’s commercial interests? Sources: S-1 founder biographies, Anthropic leadership
Together the seven cover research direction, operations, compute, basic science, training systems, model internals and public policy. That does not mean each guards a separate patch. The research agenda sets compute needs; infrastructure sets experiment speed; explaining model behavior feeds safety evaluation; policy and governance decide how the company answers to the outside world. Anthropic’s early advantage may well come from having all these functions founded by people who had already worked together, rather than bolted on after the company grew.
From papers written at OpenAI in 2020 to the amended S-1 in November 2026. The seven announced their departure in December 2020; Anthropic was founded in 2021.
Writing safety commitments into the rules
The founders left OpenAI with a research plan and also with the intention to change the company’s legal and governance structure. Anthropic is a public benefit corporation, with “the responsible development and maintenance of advanced AI for the long-term benefit of humanity” written into its corporate purpose. It also created a Long-Term Benefit Trust, whose trustees have no financial stake in the company and which shapes the board through a special class of stock.
The amended IPO filing also has Founder LLC hold a single share of Class F stock, giving the seven founders 50.1% of the vote on matters put to shareholders generally. That is a significant founder-control arrangement. The governance picture is not “the founders decide everything,” though. The 50.1% covers general shareholder votes, including the election of directors other than Class T directors. The Long-Term Benefit Trust, through Class T stock, generally has the power to elect and remove the Class T directors, and those directors make up a majority of the board. Economic ownership, shareholder votes and board seats are allocated by different mechanisms. That separation is the system of checks Anthropic is trying to build. Source: amended S-1, November 10
Governance design can change the bar for a decision. It cannot guarantee a good outcome. TIME reported that under its Responsible Scaling Policy, Anthropic committed to holding back releases when a model crosses certain capability thresholds before matching safety measures are ready. The company argues that studying strong models is itself necessary for understanding risk and writing rules. Critics ask how firm these self-imposed limits will stay as revenue, investors and competition grow. Source: TIME on Anthropic’s structure
Left, control: the founders hold the shareholder vote, and the Trust elects most of the board. Right, money: each founder plans to sell about $250 million, roughly 1.4% of Bloomberg’s estimate of their net worth. Figures use the midpoint of the filing’s price range.
This is not an abstract governance debate. The more Claude succeeds, the more compute, talent and customers Anthropic needs. The more of those it has, the more safety research it can afford, and the more it runs into conflicts between growth speed, product launches and risk management. The problem the company was founded to solve turns into a harder one once it is operating at scale.
Wealth from the IPO, and a test
The amended filing of November 10, 2026 shows each of the seven founders planning to sell about 3.38 million shares in the IPO. At $74, the midpoint of the $70–$78 range, that comes to about $250 million each and about $1.75 billion for all seven. Bloomberg, citing the Bloomberg Billionaires Index, estimates each founder’s net worth at about $18 billion. The planned sale is a share count multiplied by an assumed price; net worth is an estimate of everything a person owns. Neither is cash already received, and the seven do not hold identical assets. Sources: amended S-1, Bloomberg
Alongside the wealth is a pledge. When they founded the company, the co-founders pledged to give 80% of their Anthropic equity to charity. The amended filing shows the company has already contributed 5% of its shares to the Anthropic Public Benefit Fund, with Jack Clark and Buddy Shah as its initial managers. In an October announcement, the company estimated that these arrangements, together with an employee equity donation program, would eventually put about 20% of its shares toward the public benefit. The filing also states that the founders’ 80% pledge is voluntary and revocable and does not create legally binding obligations. How fast the money is given and where it goes will depend on future disclosures. Sources: Anthropic Public Benefit Fund announcement, The Chronicle of Philanthropy
The scope of “seven co-founders” is also easy to misread. Anthropic’s public list and Founder LLC include Dario, Daniela, Tom, Jack, Jared, Sam and Chris. Ben Mann played an important role early on and is often called a co-founder, but the filing states that he is not a member of Founder LLC. The “seven” in the news refers to the people in this founder voting structure, not a complete ranking of early contributors. Source: S-1 founder disclosure
Told only through IPO wealth, this story quickly becomes seven new billionaires splitting the take. The better question is whether the organizational problem they left a leading lab to solve has actually been solved. When AI capability and company revenue speed up together, who has the authority to say “wait”? Can internal safety evaluations hold against a market timetable? How will the charitable equity turn into results the public can see?
The seven gave Anthropic an unusual mix: people who had trained large models by hand, people who understood the cost of compute, people who studied the regularities and internals of models, and people who ran the organization and talked to the public. The company they built has shown that a safety story can run alongside commercial competition. The next problem is showing that this is more than an early-stage ideal, and that it still holds once scale, profit and power have all grown fast.
#Anthropic #artificialintelligence #Claude
Seven People, One Anthropic: The Founding Team Behind Claude
In December 2020, Dario Amodei told an all-hands video call at OpenAI that he and six colleagues were leaving to start a company that would put AI safety at its center. The chat filled with surprise and goodbyes. Jack Clark typed: “I love you all.” Then the seven screens went dark. They had been removed from the meeting, their work email and Slack access revoked, their laptops locked remotely.
A few hours earlier they had been senior researchers and managers at one of the leading AI labs. Now they had no jobs, no office systems and no clear next step. Where would the GPUs come from? The money? What would the company be called? Even buying everyone new laptops was an open question. Almost six years later, the company is called Anthropic, its product Claude competes head-on with OpenAI, and the founders are preparing to take it public.
That departure scene comes from an excerpt of Kevin Roose’s new book, published in The Atlantic. It is a better starting point than “seven executives start an AI company”: these were people who had already helped build frontier models, and they were trying to write their disagreements about risk, speed and organizational responsibility into the rules of a new company. Source: The Atlantic
Why they left
The departure is often boiled down to “OpenAI didn’t take safety seriously enough.” That gets the direction right and flattens the rest. Safety was the core disagreement, but it was tied up with who could decide when a product shipped, how the company was run, and whether a safety team could change anything once AI research had become a commercial race.
Dario was OpenAI’s vice president of research. He put conditions to Sam Altman for staying, including giving the safety team the power to block product launches. While those talks were still going, the seven set up a private Slack group called BATNA, a negotiation term for “best alternative to a negotiated agreement.” They were bargaining and preparing an exit at the same time. The talks did not produce a deal.
Daniela negotiated the exit on the group’s behalf. Both sides brought in lawyers and settled on a window during which the departing team could recruit colleagues, plus a one-year mutual no-poach agreement. Dario announced the decision at the all-hands, and Jack left his goodbye in the chat. The details matter: Anthropic was not a group of star scientists who barely knew each other. They had worked inside the same organization and went through a hard collective exit together.
When TIME interviewed him later, Dario was restrained about why they left, putting the weight on mutual trust, shared values and a common mission. He has also argued that AI risk is an empirical question: you have to build and study sufficiently powerful systems to learn what the risks actually are. That is the tension built into Anthropic. It is wary of powerful AI, and it believes it has to push powerful AI forward itself in order to study and manage it. Source: TIME on Anthropic
None of this made the conflict between safety and business go away. It moved the conflict inside Anthropic. Research needs scale and compute. Safety needs time, evaluation and restraint. Commercial growth needs products that keep improving and customers who keep adopting them. What the founders chose together was not to leave the race, but to build a lab that says it will run the race differently.
Six founders’ skills link into one research loop; Daniela’s job of running the company is the outer ring holding it together. Drawn from public roles; not an actual reporting line.
Seven jobs, one company
Dario Amodei: turning scientific judgment into company direction. Dario trained in physics and biophysics and worked at Google Brain and then OpenAI, where he was vice president of research, helped develop large language models, and worked with colleagues on reinforcement learning from human feedback. As Anthropic’s CEO he sets research direction and strategy. His main influence is less any single technique than a question he keeps asking at the level of the organization: if model capabilities grow as expected, what safety machinery does the company need to have in place first? His public writing stresses risk and also describes large possible benefits, for example in biomedicine. He holds both at once, which is part of why Anthropic keeps building while studying how to constrain what it builds. Sources: Dario Amodei’s website, Anthropic leadership
Daniela Amodei: organizing research into a company that ships. Daniela is president and chair of the board, and Dario’s sister. Before Anthropic she worked at Stripe and at OpenAI, in roles spanning safety and policy, people, and engineering management. Her remit covers research, engineering, product, governance and commercial execution, and she manages the executive team. If Dario is usually seen as the company’s technical vision, Daniela’s job is to keep the research organization, product teams, customer demands and company rules all running at once. Her role in negotiating the exit shows she was drawing the company’s organizational boundaries from day one, not holding a symbolic management title. Sources: S-1 management biographies, Anthropic leadership
Tom Brown: making large-model training work as engineering. Tom led engineering on GPT-3 and is now Anthropic’s chief compute officer, responsible for acquiring, scaling and using compute. He is also first author of the GPT-3 paper, “Language Models are Few-Shot Learners.” The 175-billion-parameter GPT-3 showed that scaled-up models could handle many tasks from a few examples. Behind the paper sat hardware scheduling, distributed training, reliability and cost control. Tom’s career connects the scientific ideas behind models with the enormous machinery needed to run them. Compute today is not a back-office budget line; it sets how fast a lab can experiment and where it stands against competitors. Sources: S-1 founder biographies, GPT-3 paper
Jared Kaplan: finding the regularities between scale and capability. Jared is a theoretical physicist and Anthropic’s chief science officer. “Scaling Laws for Neural Language Models,” which he wrote with Dario, Tom, Sam and others, studied how parameters, data and training compute affect a model’s loss. Its empirical regularities help researchers estimate how to split extra compute between model size and data. It did not prove that any capability will appear if you just make models bigger, and it does not replace experiments. What it offers is a testable framework, so frontier experiments are not pure guesswork. Jared now leads Anthropic’s technical research, linking basic science, model development and AI safety. Sources: Johns Hopkins University, Scaling laws paper
Sam McCandlish: making the research loop faster and more reliable. Sam is a physicist who built and led OpenAI’s team studying the science of machine learning and scaling, and he co-authored the scaling laws paper. Anthropic lists him as chief architect, focused on pretraining, research productivity and reinforcement learning infrastructure. Training a large model is not one press of a button. Teams run experiments over and over, track down failures, compare results and reuse systems. Sam’s specialty is the infrastructure for that loop. Tom focuses on compute resources and how they are organized; Sam sits closer to the training pipeline and research tooling. Each depends on the other to turn resources into model progress. Sources: S-1 founder biographies, Anthropic leadership
Chris Olah: trying to open the black box. Chris Olah is an early driver of mechanistic interpretability. He worked at Google Brain, led interpretability research at OpenAI, and co-founded the journal Distill. He describes his goal as reverse-engineering neural networks into algorithms humans can understand. Anthropic’s research on Claude has identified millions of concept features. In one well-known demo, researchers amplified a “Golden Gate Bridge” feature, and the model began describing itself as the Golden Gate Bridge in answer to all kinds of questions. The demo made abstract research concrete, and it also showed that when internal representations are pushed artificially, a model’s behavior can turn strange. Olah’s field has not made models fully transparent, but it has produced new ways to inspect how they work inside. Sources: Chris Olah’s website, Anthropic research
Jack Clark: translating lab language into public questions. Jack was a technology journalist covering supercomputers, neural networks and advanced technology before joining OpenAI to run policy and communications. He is now Anthropic’s head of public benefit and leads the Anthropic Institute, which studies the social effects of frontier AI. His background differs from the technical founders’: while engineers talk about evaluations and training scale, Jack has to connect those ideas to policy, jobs, national security and public understanding. His reporting experience is a bridge between the company and the outside world, not a substitute for technical work. A company studying the public interest also faces a credibility test: who sets the research agenda, and can the conclusions stand apart from the company’s commercial interests? Sources: S-1 founder biographies, Anthropic leadership
Together the seven cover research direction, operations, compute, basic science, training systems, model internals and public policy. That does not mean each guards a separate patch. The research agenda sets compute needs; infrastructure sets experiment speed; explaining model behavior feeds safety evaluation; policy and governance decide how the company answers to the outside world. Anthropic’s early advantage may well come from having all these functions founded by people who had already worked together, rather than bolted on after the company grew.
From papers written at OpenAI in 2020 to the amended S-1 in November 2026. The seven announced their departure in December 2020; Anthropic was founded in 2021.
Writing safety commitments into the rules
The founders left OpenAI with a research plan and also with the intention to change the company’s legal and governance structure. Anthropic is a public benefit corporation, with “the responsible development and maintenance of advanced AI for the long-term benefit of humanity” written into its corporate purpose. It also created a Long-Term Benefit Trust, whose trustees have no financial stake in the company and which shapes the board through a special class of stock.
The amended IPO filing also has Founder LLC hold a single share of Class F stock, giving the seven founders 50.1% of the vote on matters put to shareholders generally. That is a significant founder-control arrangement. The governance picture is not “the founders decide everything,” though. The 50.1% covers general shareholder votes, including the election of directors other than Class T directors. The Long-Term Benefit Trust, through Class T stock, generally has the power to elect and remove the Class T directors, and those directors make up a majority of the board. Economic ownership, shareholder votes and board seats are allocated by different mechanisms. That separation is the system of checks Anthropic is trying to build. Source: amended S-1, November 10
Governance design can change the bar for a decision. It cannot guarantee a good outcome. TIME reported that under its Responsible Scaling Policy, Anthropic committed to holding back releases when a model crosses certain capability thresholds before matching safety measures are ready. The company argues that studying strong models is itself necessary for understanding risk and writing rules. Critics ask how firm these self-imposed limits will stay as revenue, investors and competition grow. Source: TIME on Anthropic’s structure
Left, control: the founders hold the shareholder vote, and the Trust elects most of the board. Right, money: each founder plans to sell about $250 million, roughly 1.4% of Bloomberg’s estimate of their net worth. Figures use the midpoint of the filing’s price range.
This is not an abstract governance debate. The more Claude succeeds, the more compute, talent and customers Anthropic needs. The more of those it has, the more safety research it can afford, and the more it runs into conflicts between growth speed, product launches and risk management. The problem the company was founded to solve turns into a harder one once it is operating at scale.
Wealth from the IPO, and a test
The amended filing of November 10, 2026 shows each of the seven founders planning to sell about 3.38 million shares in the IPO. At $74, the midpoint of the $70–$78 range, that comes to about $250 million each and about $1.75 billion for all seven. Bloomberg, citing the Bloomberg Billionaires Index, estimates each founder’s net worth at about $18 billion. The planned sale is a share count multiplied by an assumed price; net worth is an estimate of everything a person owns. Neither is cash already received, and the seven do not hold identical assets. Sources: amended S-1, Bloomberg
Alongside the wealth is a pledge. When they founded the company, the co-founders pledged to give 80% of their Anthropic equity to charity. The amended filing shows the company has already contributed 5% of its shares to the Anthropic Public Benefit Fund, with Jack Clark and Buddy Shah as its initial managers. In an October announcement, the company estimated that these arrangements, together with an employee equity donation program, would eventually put about 20% of its shares toward the public benefit. The filing also states that the founders’ 80% pledge is voluntary and revocable and does not create legally binding obligations. How fast the money is given and where it goes will depend on future disclosures. Sources: Anthropic Public Benefit Fund announcement, The Chronicle of Philanthropy
The scope of “seven co-founders” is also easy to misread. Anthropic’s public list and Founder LLC include Dario, Daniela, Tom, Jack, Jared, Sam and Chris. Ben Mann played an important role early on and is often called a co-founder, but the filing states that he is not a member of Founder LLC. The “seven” in the news refers to the people in this founder voting structure, not a complete ranking of early contributors. Source: S-1 founder disclosure
Told only through IPO wealth, this story quickly becomes seven new billionaires splitting the take. The better question is whether the organizational problem they left a leading lab to solve has actually been solved. When AI capability and company revenue speed up together, who has the authority to say “wait”? Can internal safety evaluations hold against a market timetable? How will the charitable equity turn into results the public can see?
The seven gave Anthropic an unusual mix: people who had trained large models by hand, people who understood the cost of compute, people who studied the regularities and internals of models, and people who ran the organization and talked to the public. The company they built has shown that a safety story can run alongside commercial competition. The next problem is showing that this is more than an early-stage ideal, and that it still holds once scale, profit and power have all grown fast.
#Anthropic #artificialintelligence #Claude
A few hours earlier they had been senior researchers and managers at one of the leading AI labs. Now they had no jobs, no office systems and no clear next step. Where would the GPUs come from? The money? What would the company be called? Even buying everyone new laptops was an open question. Almost six years later, the company is called Anthropic, its product Claude competes head-on with OpenAI, and the founders are preparing to take it public.
That departure scene comes from an excerpt of Kevin Roose’s new book, published in The Atlantic. It is a better starting point than “seven executives start an AI company”: these were people who had already helped build frontier models, and they were trying to write their disagreements about risk, speed and organizational responsibility into the rules of a new company. Source: The Atlantic
Why they left
The departure is often boiled down to “OpenAI didn’t take safety seriously enough.” That gets the direction right and flattens the rest. Safety was the core disagreement, but it was tied up with who could decide when a product shipped, how the company was run, and whether a safety team could change anything once AI research had become a commercial race.
Dario was OpenAI’s vice president of research. He put conditions to Sam Altman for staying, including giving the safety team the power to block product launches. While those talks were still going, the seven set up a private Slack group called BATNA, a negotiation term for “best alternative to a negotiated agreement.” They were bargaining and preparing an exit at the same time. The talks did not produce a deal.
Daniela negotiated the exit on the group’s behalf. Both sides brought in lawyers and settled on a window during which the departing team could recruit colleagues, plus a one-year mutual no-poach agreement. Dario announced the decision at the all-hands, and Jack left his goodbye in the chat. The details matter: Anthropic was not a group of star scientists who barely knew each other. They had worked inside the same organization and went through a hard collective exit together.
When TIME interviewed him later, Dario was restrained about why they left, putting the weight on mutual trust, shared values and a common mission. He has also argued that AI risk is an empirical question: you have to build and study sufficiently powerful systems to learn what the risks actually are. That is the tension built into Anthropic. It is wary of powerful AI, and it believes it has to push powerful AI forward itself in order to study and manage it. Source: TIME on Anthropic
None of this made the conflict between safety and business go away. It moved the conflict inside Anthropic. Research needs scale and compute. Safety needs time, evaluation and restraint. Commercial growth needs products that keep improving and customers who keep adopting them. What the founders chose together was not to leave the race, but to build a lab that says it will run the race differently.
Six founders’ skills link into one research loop; Daniela’s job of running the company is the outer ring holding it together. Drawn from public roles; not an actual reporting line.
Seven jobs, one company
Dario Amodei: turning scientific judgment into company direction. Dario trained in physics and biophysics and worked at Google Brain and then OpenAI, where he was vice president of research, helped develop large language models, and worked with colleagues on reinforcement learning from human feedback. As Anthropic’s CEO he sets research direction and strategy. His main influence is less any single technique than a question he keeps asking at the level of the organization: if model capabilities grow as expected, what safety machinery does the company need to have in place first? His public writing stresses risk and also describes large possible benefits, for example in biomedicine. He holds both at once, which is part of why Anthropic keeps building while studying how to constrain what it builds. Sources: Dario Amodei’s website, Anthropic leadership
Daniela Amodei: organizing research into a company that ships. Daniela is president and chair of the board, and Dario’s sister. Before Anthropic she worked at Stripe and at OpenAI, in roles spanning safety and policy, people, and engineering management. Her remit covers research, engineering, product, governance and commercial execution, and she manages the executive team. If Dario is usually seen as the company’s technical vision, Daniela’s job is to keep the research organization, product teams, customer demands and company rules all running at once. Her role in negotiating the exit shows she was drawing the company’s organizational boundaries from day one, not holding a symbolic management title. Sources: S-1 management biographies, Anthropic leadership
Tom Brown: making large-model training work as engineering. Tom led engineering on GPT-3 and is now Anthropic’s chief compute officer, responsible for acquiring, scaling and using compute. He is also first author of the GPT-3 paper, “Language Models are Few-Shot Learners.” The 175-billion-parameter GPT-3 showed that scaled-up models could handle many tasks from a few examples. Behind the paper sat hardware scheduling, distributed training, reliability and cost control. Tom’s career connects the scientific ideas behind models with the enormous machinery needed to run them. Compute today is not a back-office budget line; it sets how fast a lab can experiment and where it stands against competitors. Sources: S-1 founder biographies, GPT-3 paper
Jared Kaplan: finding the regularities between scale and capability. Jared is a theoretical physicist and Anthropic’s chief science officer. “Scaling Laws for Neural Language Models,” which he wrote with Dario, Tom, Sam and others, studied how parameters, data and training compute affect a model’s loss. Its empirical regularities help researchers estimate how to split extra compute between model size and data. It did not prove that any capability will appear if you just make models bigger, and it does not replace experiments. What it offers is a testable framework, so frontier experiments are not pure guesswork. Jared now leads Anthropic’s technical research, linking basic science, model development and AI safety. Sources: Johns Hopkins University, Scaling laws paper
Sam McCandlish: making the research loop faster and more reliable. Sam is a physicist who built and led OpenAI’s team studying the science of machine learning and scaling, and he co-authored the scaling laws paper. Anthropic lists him as chief architect, focused on pretraining, research productivity and reinforcement learning infrastructure. Training a large model is not one press of a button. Teams run experiments over and over, track down failures, compare results and reuse systems. Sam’s specialty is the infrastructure for that loop. Tom focuses on compute resources and how they are organized; Sam sits closer to the training pipeline and research tooling. Each depends on the other to turn resources into model progress. Sources: S-1 founder biographies, Anthropic leadership
Chris Olah: trying to open the black box. Chris Olah is an early driver of mechanistic interpretability. He worked at Google Brain, led interpretability research at OpenAI, and co-founded the journal Distill. He describes his goal as reverse-engineering neural networks into algorithms humans can understand. Anthropic’s research on Claude has identified millions of concept features. In one well-known demo, researchers amplified a “Golden Gate Bridge” feature, and the model began describing itself as the Golden Gate Bridge in answer to all kinds of questions. The demo made abstract research concrete, and it also showed that when internal representations are pushed artificially, a model’s behavior can turn strange. Olah’s field has not made models fully transparent, but it has produced new ways to inspect how they work inside. Sources: Chris Olah’s website, Anthropic research
Jack Clark: translating lab language into public questions. Jack was a technology journalist covering supercomputers, neural networks and advanced technology before joining OpenAI to run policy and communications. He is now Anthropic’s head of public benefit and leads the Anthropic Institute, which studies the social effects of frontier AI. His background differs from the technical founders’: while engineers talk about evaluations and training scale, Jack has to connect those ideas to policy, jobs, national security and public understanding. His reporting experience is a bridge between the company and the outside world, not a substitute for technical work. A company studying the public interest also faces a credibility test: who sets the research agenda, and can the conclusions stand apart from the company’s commercial interests? Sources: S-1 founder biographies, Anthropic leadership
Together the seven cover research direction, operations, compute, basic science, training systems, model internals and public policy. That does not mean each guards a separate patch. The research agenda sets compute needs; infrastructure sets experiment speed; explaining model behavior feeds safety evaluation; policy and governance decide how the company answers to the outside world. Anthropic’s early advantage may well come from having all these functions founded by people who had already worked together, rather than bolted on after the company grew.
From papers written at OpenAI in 2020 to the amended S-1 in November 2026. The seven announced their departure in December 2020; Anthropic was founded in 2021.
Writing safety commitments into the rules
The founders left OpenAI with a research plan and also with the intention to change the company’s legal and governance structure. Anthropic is a public benefit corporation, with “the responsible development and maintenance of advanced AI for the long-term benefit of humanity” written into its corporate purpose. It also created a Long-Term Benefit Trust, whose trustees have no financial stake in the company and which shapes the board through a special class of stock.
The amended IPO filing also has Founder LLC hold a single share of Class F stock, giving the seven founders 50.1% of the vote on matters put to shareholders generally. That is a significant founder-control arrangement. The governance picture is not “the founders decide everything,” though. The 50.1% covers general shareholder votes, including the election of directors other than Class T directors. The Long-Term Benefit Trust, through Class T stock, generally has the power to elect and remove the Class T directors, and those directors make up a majority of the board. Economic ownership, shareholder votes and board seats are allocated by different mechanisms. That separation is the system of checks Anthropic is trying to build. Source: amended S-1, November 10
Governance design can change the bar for a decision. It cannot guarantee a good outcome. TIME reported that under its Responsible Scaling Policy, Anthropic committed to holding back releases when a model crosses certain capability thresholds before matching safety measures are ready. The company argues that studying strong models is itself necessary for understanding risk and writing rules. Critics ask how firm these self-imposed limits will stay as revenue, investors and competition grow. Source: TIME on Anthropic’s structure
Left, control: the founders hold the shareholder vote, and the Trust elects most of the board. Right, money: each founder plans to sell about $250 million, roughly 1.4% of Bloomberg’s estimate of their net worth. Figures use the midpoint of the filing’s price range.
This is not an abstract governance debate. The more Claude succeeds, the more compute, talent and customers Anthropic needs. The more of those it has, the more safety research it can afford, and the more it runs into conflicts between growth speed, product launches and risk management. The problem the company was founded to solve turns into a harder one once it is operating at scale.
Wealth from the IPO, and a test
The amended filing of November 10, 2026 shows each of the seven founders planning to sell about 3.38 million shares in the IPO. At $74, the midpoint of the $70–$78 range, that comes to about $250 million each and about $1.75 billion for all seven. Bloomberg, citing the Bloomberg Billionaires Index, estimates each founder’s net worth at about $18 billion. The planned sale is a share count multiplied by an assumed price; net worth is an estimate of everything a person owns. Neither is cash already received, and the seven do not hold identical assets. Sources: amended S-1, Bloomberg
Alongside the wealth is a pledge. When they founded the company, the co-founders pledged to give 80% of their Anthropic equity to charity. The amended filing shows the company has already contributed 5% of its shares to the Anthropic Public Benefit Fund, with Jack Clark and Buddy Shah as its initial managers. In an October announcement, the company estimated that these arrangements, together with an employee equity donation program, would eventually put about 20% of its shares toward the public benefit. The filing also states that the founders’ 80% pledge is voluntary and revocable and does not create legally binding obligations. How fast the money is given and where it goes will depend on future disclosures. Sources: Anthropic Public Benefit Fund announcement, The Chronicle of Philanthropy
The scope of “seven co-founders” is also easy to misread. Anthropic’s public list and Founder LLC include Dario, Daniela, Tom, Jack, Jared, Sam and Chris. Ben Mann played an important role early on and is often called a co-founder, but the filing states that he is not a member of Founder LLC. The “seven” in the news refers to the people in this founder voting structure, not a complete ranking of early contributors. Source: S-1 founder disclosure
Told only through IPO wealth, this story quickly becomes seven new billionaires splitting the take. The better question is whether the organizational problem they left a leading lab to solve has actually been solved. When AI capability and company revenue speed up together, who has the authority to say “wait”? Can internal safety evaluations hold against a market timetable? How will the charitable equity turn into results the public can see?
The seven gave Anthropic an unusual mix: people who had trained large models by hand, people who understood the cost of compute, people who studied the regularities and internals of models, and people who ran the organization and talked to the public. The company they built has shown that a safety story can run alongside commercial competition. The next problem is showing that this is more than an early-stage ideal, and that it still holds once scale, profit and power have all grown fast.
#Anthropic #artificialintelligence #Claude
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Article
⚡️ Anthropic is going public — you can apply through Walt(English translation — in the comments)
In a week, one of the fastest-growing companies in the history of technology will go public. Anthropic has announced a price range of $70–78 per share. Trading under the ticker ANT is expected to begin on November 19.
You can apply through Walt to participate in Anthropic’s IPO (ANTx) before trading begins.
🔎 Why is Anthropic interesting to investors?
According to Morningstar analysts, no technology company has ever grown this quickly:
⚡️ Anthropic is going public — you can apply through Walt
(English translation — in the comments)
In a week, one of the fastest-growing companies in the history of technology will go public. Anthropic has announced a price range of $70–78 per share. Trading under the ticker ANT is expected to begin on November 19.
You can apply through Walt to participate in Anthropic’s IPO (ANTx) before trading begins.
🔎 Why is Anthropic interesting to investors?
According to Morningstar analysts, no technology company has ever grown this quickly:
In a week, one of the fastest-growing companies in the history of technology will go public. Anthropic has announced a price range of $70–78 per share. Trading under the ticker ANT is expected to begin on November 19.
You can apply through Walt to participate in Anthropic’s IPO (ANTx) before trading begins.
🔎 Why is Anthropic interesting to investors?
According to Morningstar analysts, no technology company has ever grown this quickly:
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AI fever in #WallStreet
#Anthropic 's IPO sparks massive oversubscription and is shaping up to be the largest IPO in history
Institutional appetite for artificial intelligence appears to have reached a new boiling point. Anthropic's highly anticipated Initial Public Offering (IPO), creators of the #Claude model, is sparking a veritable race among major investors seeking to secure their share in what promises to be a historic milestone for financial markets.
Record oversubscription: Buy orders have exceeded the total number of shares available in the initial offering several times over.
On track to become the largest IPO in history: Investor appetite is accelerating rapidly, positioning Anthropic's stock market debut as a candidate to become the largest IPO ever recorded.
Voracious institutional appetite: The impressive demand has been driven by “large-scale expressions of interest” from major market players, according to sources familiar with the confidential process.
A sign of strength for the sector: The flood of orders confirms that, despite fears of a correction in the technology sector, frontier AI infrastructure and development remain the top priority for capital allocation.
$ANTHROPIC
{future}(ANTHROPICUSDT)
AI fever in #WallStreet
#Anthropic 's IPO sparks massive oversubscription and is shaping up to be the largest IPO in history
Institutional appetite for artificial intelligence appears to have reached a new boiling point. Anthropic's highly anticipated Initial Public Offering (IPO), creators of the #Claude model, is sparking a veritable race among major investors seeking to secure their share in what promises to be a historic milestone for financial markets.
Record oversubscription: Buy orders have exceeded the total number of shares available in the initial offering several times over.
On track to become the largest IPO in history: Investor appetite is accelerating rapidly, positioning Anthropic's stock market debut as a candidate to become the largest IPO ever recorded.
Voracious institutional appetite: The impressive demand has been driven by “large-scale expressions of interest” from major market players, according to sources familiar with the confidential process.
A sign of strength for the sector: The flood of orders confirms that, despite fears of a correction in the technology sector, frontier AI infrastructure and development remain the top priority for capital allocation.
$ANTHROPIC
#Anthropic 's IPO sparks massive oversubscription and is shaping up to be the largest IPO in history
Institutional appetite for artificial intelligence appears to have reached a new boiling point. Anthropic's highly anticipated Initial Public Offering (IPO), creators of the #Claude model, is sparking a veritable race among major investors seeking to secure their share in what promises to be a historic milestone for financial markets.
Record oversubscription: Buy orders have exceeded the total number of shares available in the initial offering several times over.
On track to become the largest IPO in history: Investor appetite is accelerating rapidly, positioning Anthropic's stock market debut as a candidate to become the largest IPO ever recorded.
Voracious institutional appetite: The impressive demand has been driven by “large-scale expressions of interest” from major market players, according to sources familiar with the confidential process.
A sign of strength for the sector: The flood of orders confirms that, despite fears of a correction in the technology sector, frontier AI infrastructure and development remain the top priority for capital allocation.
$ANTHROPIC
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🔥 BIG NEWS: Anthropic IPO!
Anthropic’s 7 co-founders are reportedly set to sell $1.75 BILLION worth of shares in the upcoming IPO, around $250M each, according to Bloomberg.
Each founder could see their net worth reach nearly $18 BILLION.
That’s a massive payday!
🚀 But here's the big question:
Would you buy $ANTHROPIC on Day One, or wait for a price correction?
Bullish or Bearish?
#AnthropicIPO #AI #Claude
🔥 BIG NEWS: Anthropic IPO!
Anthropic’s 7 co-founders are reportedly set to sell $1.75 BILLION worth of shares in the upcoming IPO, around $250M each, according to Bloomberg.
Each founder could see their net worth reach nearly $18 BILLION.
That’s a massive payday!
🚀 But here's the big question:
Would you buy $ANTHROPIC on Day One, or wait for a price correction?
Bullish or Bearish?
#AnthropicIPO #AI #Claude
Anthropic’s 7 co-founders are reportedly set to sell $1.75 BILLION worth of shares in the upcoming IPO, around $250M each, according to Bloomberg.
Each founder could see their net worth reach nearly $18 BILLION.
That’s a massive payday!
🚀 But here's the big question:
Would you buy $ANTHROPIC on Day One, or wait for a price correction?
Bullish or Bearish?
#AnthropicIPO #AI #Claude
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🚀 Anthropic IPO: Could It Become One of the Biggest AI Investment Opportunities?
Artificial Intelligence is growing faster than ever, and Anthropic is becoming one of the major names in the AI industry with its Claude AI technology.
If Anthropic eventually goes public through an IPO, it could attract significant attention from investors around the world.
🔥 Why should investors watch Anthropic?
$IPO.ETF $AI
- Growing demand for AI technology.
- Claude AI competing in the global AI market.
- Increasing interest in AI infrastructure and automation.
- Potential opportunities in the future AI economy.
💡 The big question is: Will Anthropic become one of the most influential publicly traded AI companies?
Remember, an IPO is not guaranteed, and potential opportunities always come with risks. Do your own research before investing.
#AnthropicIPO #BinanceSquare #AI #Claude AI #ArtificialIntelligence #CryptoCommunity #TechInvesting
#anthropicipo
🚀 Anthropic IPO: Could It Become One of the Biggest AI Investment Opportunities?
Artificial Intelligence is growing faster than ever, and Anthropic is becoming one of the major names in the AI industry with its Claude AI technology.
If Anthropic eventually goes public through an IPO, it could attract significant attention from investors around the world.
🔥 Why should investors watch Anthropic?
$IPO.ETF $AI
- Growing demand for AI technology.
- Claude AI competing in the global AI market.
- Increasing interest in AI infrastructure and automation.
- Potential opportunities in the future AI economy.
💡 The big question is: Will Anthropic become one of the most influential publicly traded AI companies?
Remember, an IPO is not guaranteed, and potential opportunities always come with risks. Do your own research before investing.
#AnthropicIPO #BinanceSquare #AI #Claude AI #ArtificialIntelligence #CryptoCommunity #TechInvesting
#anthropicipo
Artificial Intelligence is growing faster than ever, and Anthropic is becoming one of the major names in the AI industry with its Claude AI technology.
If Anthropic eventually goes public through an IPO, it could attract significant attention from investors around the world.
🔥 Why should investors watch Anthropic?
$IPO.ETF $AI
- Growing demand for AI technology.
- Claude AI competing in the global AI market.
- Increasing interest in AI infrastructure and automation.
- Potential opportunities in the future AI economy.
💡 The big question is: Will Anthropic become one of the most influential publicly traded AI companies?
Remember, an IPO is not guaranteed, and potential opportunities always come with risks. Do your own research before investing.
#AnthropicIPO #BinanceSquare #AI #Claude AI #ArtificialIntelligence #CryptoCommunity #TechInvesting
#anthropicipo
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Anthropic released Claude Fable 5.2 on November 9, and Mythos 5.2 became available at the same time, but only to verified organizations. Fable scored 49.1% on the FrontierCode 2.0 coding benchmark, higher than Opus 5.5's 45.5%; its input price dropped from $10 to $8 per million tokens, and output is about 30% faster. Interestingly, Anthropic said that it deliberately kept the capabilities most likely to accelerate AI research at the level of Opus 5.5 instead of making them available. The stronger the models get, the more obvious these holdbacks become. Do you think this is responsible, or are they afraid things will move too fast?
#热点背后的利益 #Claude
Anthropic released Claude Fable 5.2 on November 9, and Mythos 5.2 became available at the same time, but only to verified organizations. Fable scored 49.1% on the FrontierCode 2.0 coding benchmark, higher than Opus 5.5's 45.5%; its input price dropped from $10 to $8 per million tokens, and output is about 30% faster. Interestingly, Anthropic said that it deliberately kept the capabilities most likely to accelerate AI research at the level of Opus 5.5 instead of making them available. The stronger the models get, the more obvious these holdbacks become. Do you think this is responsible, or are they afraid things will move too fast?
#热点背后的利益 #Claude
#热点背后的利益 #Claude
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🚀 Can $ANTHROPIC Really Hold a $1 Trillion+ Valuation?
The AI revolution is growing fast, but can every AI company justify its massive valuation?
Anthropic has huge potential with Claude and its expanding AI ecosystem. However, a drop in valuation expectations from $2 trillion to around $1.5 trillion raises an important question.
Is this a buying opportunity or a warning sign?
I believe AI has a massive future, but long-term success will depend on real revenue, strong adoption, and sustainable growth — not just hype.
My question is simple:
Would you invest in $ANTHROPIC at a $1 trillion+ valuation?
🔥 Bullish or Bearish?
Share your thoughts below!
#AnthropicIPO #AI #Claude #IPO
🚀 Can $ANTHROPIC Really Hold a $1 Trillion+ Valuation?
The AI revolution is growing fast, but can every AI company justify its massive valuation?
Anthropic has huge potential with Claude and its expanding AI ecosystem. However, a drop in valuation expectations from $2 trillion to around $1.5 trillion raises an important question.
Is this a buying opportunity or a warning sign?
I believe AI has a massive future, but long-term success will depend on real revenue, strong adoption, and sustainable growth — not just hype.
My question is simple:
Would you invest in $ANTHROPIC at a $1 trillion+ valuation?
🔥 Bullish or Bearish?
Share your thoughts below!
#AnthropicIPO #AI #Claude #IPO
The AI revolution is growing fast, but can every AI company justify its massive valuation?
Anthropic has huge potential with Claude and its expanding AI ecosystem. However, a drop in valuation expectations from $2 trillion to around $1.5 trillion raises an important question.
Is this a buying opportunity or a warning sign?
I believe AI has a massive future, but long-term success will depend on real revenue, strong adoption, and sustainable growth — not just hype.
My question is simple:
Would you invest in $ANTHROPIC at a $1 trillion+ valuation?
🔥 Bullish or Bearish?
Share your thoughts below!
#AnthropicIPO #AI #Claude #IPO
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Anthropic announced last night: Claude Fable 5.2 and Mythos 5.2 are now available. They share the same underlying model family and specialize in the toughest technical tasks.
Fable 5.2 is available across all platforms; Mythos is offered through their expanded Life Sciences / Cyber Verification programs for organizations working in biology and cybersecurity. Prices have also come down: $8 per million input tokens and $40 for output. There’s also an optional Fast mode that can generate up to about 2.5× faster.
A few of the official benchmark results are impressive: around 1,000 Fable 5.2 agents formalized Fermat’s Last Theorem in 30 hours; the model also solved two open theoretical physics problems related to black holes. On the hardware side, a one-line prompt produced three working electronic devices. For everyday coding, they still recommend starting with Opus 5.5 and moving up for harder tasks.
Their IPO roadshow also kicks off this week. They’re making a big move with the model first—the pace is intense.
#Anthropic #Claude #AI
Anthropic announced last night: Claude Fable 5.2 and Mythos 5.2 are now available. They share the same underlying model family and specialize in the toughest technical tasks.
Fable 5.2 is available across all platforms; Mythos is offered through their expanded Life Sciences / Cyber Verification programs for organizations working in biology and cybersecurity. Prices have also come down: $8 per million input tokens and $40 for output. There’s also an optional Fast mode that can generate up to about 2.5× faster.
A few of the official benchmark results are impressive: around 1,000 Fable 5.2 agents formalized Fermat’s Last Theorem in 30 hours; the model also solved two open theoretical physics problems related to black holes. On the hardware side, a one-line prompt produced three working electronic devices. For everyday coding, they still recommend starting with Opus 5.5 and moving up for harder tasks.
Their IPO roadshow also kicks off this week. They’re making a big move with the model first—the pace is intense.
#Anthropic #Claude #AI
Fable 5.2 is available across all platforms; Mythos is offered through their expanded Life Sciences / Cyber Verification programs for organizations working in biology and cybersecurity. Prices have also come down: $8 per million input tokens and $40 for output. There’s also an optional Fast mode that can generate up to about 2.5× faster.
A few of the official benchmark results are impressive: around 1,000 Fable 5.2 agents formalized Fermat’s Last Theorem in 30 hours; the model also solved two open theoretical physics problems related to black holes. On the hardware side, a one-line prompt produced three working electronic devices. For everyday coding, they still recommend starting with Opus 5.5 and moving up for harder tasks.
Their IPO roadshow also kicks off this week. They’re making a big move with the model first—the pace is intense.
#Anthropic #Claude #AI
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Claude’s new models have officially arrived!
Anthropic has launched Fable 5.2 and Mythos 5.2, showcasing AI’s ability to tackle major engineering and scientific tasks.
Five impressive highlights:
① More than 1,000 AI agents collaborated to build a bootable operating system in 8 days.
② Formally verified Fermat’s Last Theorem in 30 hours.
③ Helped solve two open problems in black hole physics.
④ Designed three fully functional electronic devices from scratch.
⑤ Output speeds increased by up to 30%, while API prices dropped by 20%.
The two models use the same underlying model, but differ in their safety restrictions and who can access them.
Fable 5.2 is available to the general public, while Mythos 5.2 requires approval.
These are still official tests and collaborations, but they already point to an important direction:
AI isn’t just answering questions anymore. It’s starting to coordinate teams, design products, and even take part in real scientific research.
Future AI may increasingly resemble an entire engineering team.
#區塊101 #Claude #Anthropic #AI #ArtificialIntelligence #TechNews
Claude’s new models have officially arrived!
Anthropic has launched Fable 5.2 and Mythos 5.2, showcasing AI’s ability to tackle major engineering and scientific tasks.
Five impressive highlights:
① More than 1,000 AI agents collaborated to build a bootable operating system in 8 days.
② Formally verified Fermat’s Last Theorem in 30 hours.
③ Helped solve two open problems in black hole physics.
④ Designed three fully functional electronic devices from scratch.
⑤ Output speeds increased by up to 30%, while API prices dropped by 20%.
The two models use the same underlying model, but differ in their safety restrictions and who can access them.
Fable 5.2 is available to the general public, while Mythos 5.2 requires approval.
These are still official tests and collaborations, but they already point to an important direction:
AI isn’t just answering questions anymore. It’s starting to coordinate teams, design products, and even take part in real scientific research.
Future AI may increasingly resemble an entire engineering team.
#區塊101 #Claude #Anthropic #AI #ArtificialIntelligence #TechNews
Anthropic has launched Fable 5.2 and Mythos 5.2, showcasing AI’s ability to tackle major engineering and scientific tasks.
Five impressive highlights:
① More than 1,000 AI agents collaborated to build a bootable operating system in 8 days.
② Formally verified Fermat’s Last Theorem in 30 hours.
③ Helped solve two open problems in black hole physics.
④ Designed three fully functional electronic devices from scratch.
⑤ Output speeds increased by up to 30%, while API prices dropped by 20%.
The two models use the same underlying model, but differ in their safety restrictions and who can access them.
Fable 5.2 is available to the general public, while Mythos 5.2 requires approval.
These are still official tests and collaborations, but they already point to an important direction:
AI isn’t just answering questions anymore. It’s starting to coordinate teams, design products, and even take part in real scientific research.
Future AI may increasingly resemble an entire engineering team.
#區塊101 #Claude #Anthropic #AI #ArtificialIntelligence #TechNews
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Verified
Defies the AI storm!
#Anthropic keeps its IPO on track and targets a Wall Street debut next week
Steady toward #WallStreet
Anthropic, the creator of #Claude , is moving ahead with its plans to complete its IPO at the end of this month, brushing aside recent market volatility related to investments in artificial intelligence.
Investor meetings: The company has key strategic meetings scheduled with major investors throughout this week to shore up support ahead of its stock market debut.
Target date: The company’s timeline indicates that its shares will officially begin trading on the stock market next Thursday or Friday.
$ANTHROPIC
{future}(ANTHROPICUSDT)
Defies the AI storm!
#Anthropic keeps its IPO on track and targets a Wall Street debut next week
Steady toward #WallStreet
Anthropic, the creator of #Claude , is moving ahead with its plans to complete its IPO at the end of this month, brushing aside recent market volatility related to investments in artificial intelligence.
Investor meetings: The company has key strategic meetings scheduled with major investors throughout this week to shore up support ahead of its stock market debut.
Target date: The company’s timeline indicates that its shares will officially begin trading on the stock market next Thursday or Friday.
$ANTHROPIC
#Anthropic keeps its IPO on track and targets a Wall Street debut next week
Steady toward #WallStreet
Anthropic, the creator of #Claude , is moving ahead with its plans to complete its IPO at the end of this month, brushing aside recent market volatility related to investments in artificial intelligence.
Investor meetings: The company has key strategic meetings scheduled with major investors throughout this week to shore up support ahead of its stock market debut.
Target date: The company’s timeline indicates that its shares will officially begin trading on the stock market next Thursday or Friday.
$ANTHROPIC
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Claude’s parent company loses nearly $1 trillion in valuation in a month💥
▫️Last month, the market was still touting an IPO valuation of around $2 trillion for Anthropic
▫️After AI stocks plunged, investors’ bids fell back to around $1–1.3 trillion
▫️It plans to list on Nasdaq under the ticker ANT, but expectations for a pre-Thanksgiving listing are under pressure
▫️Prediction markets: the odds of a listing before December 1 fell from around 80% to around 50%
As the AI bubble deflates, will even Claude have to go public at a discount? What do you think?👇 (Not investment advice)
#Anthropic #Claude #IPO
Claude’s parent company loses nearly $1 trillion in valuation in a month💥
▫️Last month, the market was still touting an IPO valuation of around $2 trillion for Anthropic
▫️After AI stocks plunged, investors’ bids fell back to around $1–1.3 trillion
▫️It plans to list on Nasdaq under the ticker ANT, but expectations for a pre-Thanksgiving listing are under pressure
▫️Prediction markets: the odds of a listing before December 1 fell from around 80% to around 50%
As the AI bubble deflates, will even Claude have to go public at a discount? What do you think?👇 (Not investment advice)
#Anthropic #Claude #IPO
▫️Last month, the market was still touting an IPO valuation of around $2 trillion for Anthropic
▫️After AI stocks plunged, investors’ bids fell back to around $1–1.3 trillion
▫️It plans to list on Nasdaq under the ticker ANT, but expectations for a pre-Thanksgiving listing are under pressure
▫️Prediction markets: the odds of a listing before December 1 fell from around 80% to around 50%
As the AI bubble deflates, will even Claude have to go public at a discount? What do you think?👇 (Not investment advice)
#Anthropic #Claude #IPO
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I came across Anthropic connecting Claude Code to your phone: the Claude app now has a Code tab where you can monitor sessions, review changes, and send instructions.
You can pick up sessions from your local machine using Remote Control; repositories on GitHub can also be added to cloud sessions—and they keep running even when your phone is locked. Anthropic also says you can have it monitor PRs and fix CI issues or review comments along the way. Dispatch (letting the desktop app assign tasks for you) requires Pro / Max / Ultra.
Put simply, coding agents are no longer tied to the screen at your desk. Terminal commands and permission modes are still limited on mobile, so you’ll still need a computer for heavy lifting. But the way is now open to “reviewing a batch of changes while you’re out and about.”
#AI #Claude #Anthropic
I came across Anthropic connecting Claude Code to your phone: the Claude app now has a Code tab where you can monitor sessions, review changes, and send instructions.
You can pick up sessions from your local machine using Remote Control; repositories on GitHub can also be added to cloud sessions—and they keep running even when your phone is locked. Anthropic also says you can have it monitor PRs and fix CI issues or review comments along the way. Dispatch (letting the desktop app assign tasks for you) requires Pro / Max / Ultra.
Put simply, coding agents are no longer tied to the screen at your desk. Terminal commands and permission modes are still limited on mobile, so you’ll still need a computer for heavy lifting. But the way is now open to “reviewing a batch of changes while you’re out and about.”
#AI #Claude #Anthropic
You can pick up sessions from your local machine using Remote Control; repositories on GitHub can also be added to cloud sessions—and they keep running even when your phone is locked. Anthropic also says you can have it monitor PRs and fix CI issues or review comments along the way. Dispatch (letting the desktop app assign tasks for you) requires Pro / Max / Ultra.
Put simply, coding agents are no longer tied to the screen at your desk. Terminal commands and permission modes are still limited on mobile, so you’ll still need a computer for heavy lifting. But the way is now open to “reviewing a batch of changes while you’re out and about.”
#AI #Claude #Anthropic
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On the eve of Anthropic’s IPO, key employees are leaving one after another? Even Claude Code’s product lead has joined OpenAI!! 🤯🤯
Cat Wu, known in the AI world as “Sister Cat,” announced just two days ago that she was leaving Anthropic—and today she officially announced she’s joining OpenAI to lead product management for a core product team, focusing on AI agents for individuals and teams.
She joined Anthropic in 2024. She was one of the key people who helped turn Claude Code from an internal tool into the AI coding product developers now use everywhere. Later, she also led Claude Cowork, which focuses on non-coding use cases.
Based on Silicon Valley’s typical four-year vesting schedule with a one-year cliff, she should already have a good chunk of her Anthropic equity vested. Leaving before the IPO probably won’t affect that equity. She gets to benefit from Anthropic’s IPO, then go to OpenAI and get a fresh grant of options—jealous 😭
And she’s not the only one. On the same day, Austin Lau, Anthropic’s fifth marketing hire and the company’s first growth hire, also announced he was joining OpenAI.
With key employees defecting to its biggest competitor one after another on the eve of its IPO, I think there must be some pretty serious management issues inside Anthropic. Otherwise, why would anyone jump ship to a competitor at a time like this??#Anthropic #AI #OpenAI #Claude
On the eve of Anthropic’s IPO, key employees are leaving one after another? Even Claude Code’s product lead has joined OpenAI!! 🤯🤯
Cat Wu, known in the AI world as “Sister Cat,” announced just two days ago that she was leaving Anthropic—and today she officially announced she’s joining OpenAI to lead product management for a core product team, focusing on AI agents for individuals and teams.
She joined Anthropic in 2024. She was one of the key people who helped turn Claude Code from an internal tool into the AI coding product developers now use everywhere. Later, she also led Claude Cowork, which focuses on non-coding use cases.
Based on Silicon Valley’s typical four-year vesting schedule with a one-year cliff, she should already have a good chunk of her Anthropic equity vested. Leaving before the IPO probably won’t affect that equity. She gets to benefit from Anthropic’s IPO, then go to OpenAI and get a fresh grant of options—jealous 😭
And she’s not the only one. On the same day, Austin Lau, Anthropic’s fifth marketing hire and the company’s first growth hire, also announced he was joining OpenAI.
With key employees defecting to its biggest competitor one after another on the eve of its IPO, I think there must be some pretty serious management issues inside Anthropic. Otherwise, why would anyone jump ship to a competitor at a time like this??#Anthropic #AI #OpenAI #Claude
Cat Wu, known in the AI world as “Sister Cat,” announced just two days ago that she was leaving Anthropic—and today she officially announced she’s joining OpenAI to lead product management for a core product team, focusing on AI agents for individuals and teams.
She joined Anthropic in 2024. She was one of the key people who helped turn Claude Code from an internal tool into the AI coding product developers now use everywhere. Later, she also led Claude Cowork, which focuses on non-coding use cases.
Based on Silicon Valley’s typical four-year vesting schedule with a one-year cliff, she should already have a good chunk of her Anthropic equity vested. Leaving before the IPO probably won’t affect that equity. She gets to benefit from Anthropic’s IPO, then go to OpenAI and get a fresh grant of options—jealous 😭
And she’s not the only one. On the same day, Austin Lau, Anthropic’s fifth marketing hire and the company’s first growth hire, also announced he was joining OpenAI.
With key employees defecting to its biggest competitor one after another on the eve of its IPO, I think there must be some pretty serious management issues inside Anthropic. Otherwise, why would anyone jump ship to a competitor at a time like this??#Anthropic #AI #OpenAI #Claude
风中浪客:
这就跳了？Anthropic最近人走得有点勤啊
1
1
949
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Bullish
Anthropic recently disclosed quarterly revenue of about $17 billion, but a net loss of $23.3 billion over the same period; the company has pledged up to $895.4 billion in AI computing and infrastructure spending. Investor discussions of its IPO valuation have fallen from around $2 trillion to between $1.5 trillion and $1.75 trillion.
Revenue is exploding, losses are growing even faster, and capital spending is approaching astronomical levels—is this company building the infrastructure of the next generation, or is it saddling public-market investors with the computing bill for the next decade ahead of time?
#AnthropicIPO遭投资者压价，估值盼降至1.5万亿美元 #AI泡沫 #Claude
{future}(ETHUSDT)
{future}(BTCUSDT)
Anthropic recently disclosed quarterly revenue of about $17 billion, but a net loss of $23.3 billion over the same period; the company has pledged up to $895.4 billion in AI computing and infrastructure spending. Investor discussions of its IPO valuation have fallen from around $2 trillion to between $1.5 trillion and $1.75 trillion.
Revenue is exploding, losses are growing even faster, and capital spending is approaching astronomical levels—is this company building the infrastructure of the next generation, or is it saddling public-market investors with the computing bill for the next decade ahead of time?
#AnthropicIPO遭投资者压价，估值盼降至1.5万亿美元 #AI泡沫 #Claude
Revenue is exploding, losses are growing even faster, and capital spending is approaching astronomical levels—is this company building the infrastructure of the next generation, or is it saddling public-market investors with the computing bill for the next decade ahead of time?
#AnthropicIPO遭投资者压价，估值盼降至1.5万亿美元 #AI泡沫 #Claude
440
I’m currently using 6 AI plans at once, and only spending about $283 in cash per month. A lot of people have asked where I get all those quotas, so here’s the full story:
1. Claude Max 20x, $250/month
App Store subscription (it’s $200 on the official website, so the App Store costs a bit more). There are two quota limits: a 5-hour window and a weekly cap; there’s no fixed token count. I tested it for a month in April, and at API prices, I used over $3,000 worth. Now I save it for the most valuable work: making decisions, writing code, and reviewing the results.
2. X Premium+, €377/year, equivalent to $33/month
Includes Grok, with a weekly quota pool. It can also be used to activate Grok Bot, see #4.
3. Cursor, $0
I’m a Cursor Friend, so I get Ultra free every month. Grok 4.7 and Composer share a weekly quota. Note: Using Claude or GPT in Cursor doesn’t count against this quota; they’re charged separately at API rates.
In October, X launched a bundled subscription. After getting advice from AI, I decided not to combine Cursor Ultra with my existing X Premium+. Good thing, too—I saw someone lose their Friends status after combining them, taking a huge loss. Glad I listened to the AI’s advice and assessed things first. One more time AI saved me money.
4. Two Grok Bot accounts, $0
I activated the first through Cursor Ultra. For the second, on another device, I used a new Cursor account and selected “Get access with Grok,” going through the X Premium+ option to activate a separate account (I wrote about the process in August). Each has its own weekly quota, and they don’t affect each other.
5. ChatGPT / Codex, $0
My Pro plan expired in mid-October, and I didn’t renew. But at the end of September, the official account gave away 62,500 points that can be used with Codex, expiring on December 31. I tested it and found that roughly 43,000 tokens use up 1 point.
A few tips for not letting anything go to waste:
· First, check whether each plan’s quota is weekly, monthly, or point-based. Weekly quotas disappear if unused, so prioritize those.
· Use the free and bundled plans first, and save the ones you pay for yourself for the toughest tasks.
· Always check the expiration date on bonus points. I have over 50,000 points, and at my current rate, more than half will expire unused by the end of the year. So next, I’ll need to send Codex some work specifically.
#AI #Claude #Grok
I’m currently using 6 AI plans at once, and only spending about $283 in cash per month. A lot of people have asked where I get all those quotas, so here’s the full story:
1. Claude Max 20x, $250/month
App Store subscription (it’s $200 on the official website, so the App Store costs a bit more). There are two quota limits: a 5-hour window and a weekly cap; there’s no fixed token count. I tested it for a month in April, and at API prices, I used over $3,000 worth. Now I save it for the most valuable work: making decisions, writing code, and reviewing the results.
2. X Premium+, €377/year, equivalent to $33/month
Includes Grok, with a weekly quota pool. It can also be used to activate Grok Bot, see #4.
3. Cursor, $0
I’m a Cursor Friend, so I get Ultra free every month. Grok 4.7 and Composer share a weekly quota. Note: Using Claude or GPT in Cursor doesn’t count against this quota; they’re charged separately at API rates.
In October, X launched a bundled subscription. After getting advice from AI, I decided not to combine Cursor Ultra with my existing X Premium+. Good thing, too—I saw someone lose their Friends status after combining them, taking a huge loss. Glad I listened to the AI’s advice and assessed things first. One more time AI saved me money.
4. Two Grok Bot accounts, $0
I activated the first through Cursor Ultra. For the second, on another device, I used a new Cursor account and selected “Get access with Grok,” going through the X Premium+ option to activate a separate account (I wrote about the process in August). Each has its own weekly quota, and they don’t affect each other.
5. ChatGPT / Codex, $0
My Pro plan expired in mid-October, and I didn’t renew. But at the end of September, the official account gave away 62,500 points that can be used with Codex, expiring on December 31. I tested it and found that roughly 43,000 tokens use up 1 point.
A few tips for not letting anything go to waste:
· First, check whether each plan’s quota is weekly, monthly, or point-based. Weekly quotas disappear if unused, so prioritize those.
· Use the free and bundled plans first, and save the ones you pay for yourself for the toughest tasks.
· Always check the expiration date on bonus points. I have over 50,000 points, and at my current rate, more than half will expire unused by the end of the year. So next, I’ll need to send Codex some work specifically.
#AI #Claude #Grok
1. Claude Max 20x, $250/month
App Store subscription (it’s $200 on the official website, so the App Store costs a bit more). There are two quota limits: a 5-hour window and a weekly cap; there’s no fixed token count. I tested it for a month in April, and at API prices, I used over $3,000 worth. Now I save it for the most valuable work: making decisions, writing code, and reviewing the results.
2. X Premium+, €377/year, equivalent to $33/month
Includes Grok, with a weekly quota pool. It can also be used to activate Grok Bot, see #4.
3. Cursor, $0
I’m a Cursor Friend, so I get Ultra free every month. Grok 4.7 and Composer share a weekly quota. Note: Using Claude or GPT in Cursor doesn’t count against this quota; they’re charged separately at API rates.
In October, X launched a bundled subscription. After getting advice from AI, I decided not to combine Cursor Ultra with my existing X Premium+. Good thing, too—I saw someone lose their Friends status after combining them, taking a huge loss. Glad I listened to the AI’s advice and assessed things first. One more time AI saved me money.
4. Two Grok Bot accounts, $0
I activated the first through Cursor Ultra. For the second, on another device, I used a new Cursor account and selected “Get access with Grok,” going through the X Premium+ option to activate a separate account (I wrote about the process in August). Each has its own weekly quota, and they don’t affect each other.
5. ChatGPT / Codex, $0
My Pro plan expired in mid-October, and I didn’t renew. But at the end of September, the official account gave away 62,500 points that can be used with Codex, expiring on December 31. I tested it and found that roughly 43,000 tokens use up 1 point.
A few tips for not letting anything go to waste:
· First, check whether each plan’s quota is weekly, monthly, or point-based. Weekly quotas disappear if unused, so prioritize those.
· Use the free and bundled plans first, and save the ones you pay for yourself for the toughest tasks.
· Always check the expiration date on bonus points. I have over 50,000 points, and at my current rate, more than half will expire unused by the end of the year. So next, I’ll need to send Codex some work specifically.
#AI #Claude #Grok
85
·
--
AI costs fall, but business growth is hindered
Anthropic lowers the cost of using Claude, promoting AI adoption, but rising costs challenge business growth, and the AI industry faces challenges.#AI #Anthropic #Claude
AI costs fall, but business growth is hindered
Anthropic lowers the cost of using Claude, promoting AI adoption, but rising costs challenge business growth, and the AI industry faces challenges.#AI #Anthropic #Claude
Anthropic lowers the cost of using Claude, promoting AI adoption, but rising costs challenge business growth, and the AI industry faces challenges.#AI #Anthropic #Claude
37
·
--
AI costs fall, but business growth is hindered
Anthropic lowers the cost of using Claude, promoting AI adoption. However, rising costs challenge business growth, and the AI industry faces challenges in its development.#AI #Anthropic #Claude
AI costs fall, but business growth is hindered
Anthropic lowers the cost of using Claude, promoting AI adoption. However, rising costs challenge business growth, and the AI industry faces challenges in its development.#AI #Anthropic #Claude
Anthropic lowers the cost of using Claude, promoting AI adoption. However, rising costs challenge business growth, and the AI industry faces challenges in its development.#AI #Anthropic #Claude
36
·
--
AI costs decline, but business growth is hindered
Anthropic lowers the cost of using Claude, promoting wider AI adoption. However, rising costs challenge business growth, and the AI industry faces challenges in its development.#AI #Anthropic #Claude
AI costs decline, but business growth is hindered
Anthropic lowers the cost of using Claude, promoting wider AI adoption. However, rising costs challenge business growth, and the AI industry faces challenges in its development.#AI #Anthropic #Claude
Anthropic lowers the cost of using Claude, promoting wider AI adoption. However, rising costs challenge business growth, and the AI industry faces challenges in its development.#AI #Anthropic #Claude
37
·
--
AI costs are falling, but business growth is stalling
Anthropic is lowering the cost of using Claude to promote AI adoption, but rising costs are challenging business growth, and the AI industry’s development faces challenges.#AI #Anthropic #Claude
AI costs are falling, but business growth is stalling
Anthropic is lowering the cost of using Claude to promote AI adoption, but rising costs are challenging business growth, and the AI industry’s development faces challenges.#AI #Anthropic #Claude
Anthropic is lowering the cost of using Claude to promote AI adoption, but rising costs are challenging business growth, and the AI industry’s development faces challenges.#AI #Anthropic #Claude
35
·
--
AI costs are falling, but business growth is being hindered
Anthropic is lowering the cost of using Claude to promote AI adoption, but rising costs are challenging business growth, and the AI industry faces hurdles.#AI #Anthropic #Claude
AI costs are falling, but business growth is being hindered
Anthropic is lowering the cost of using Claude to promote AI adoption, but rising costs are challenging business growth, and the AI industry faces hurdles.#AI #Anthropic #Claude
Anthropic is lowering the cost of using Claude to promote AI adoption, but rising costs are challenging business growth, and the AI industry faces hurdles.#AI #Anthropic #Claude
24
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