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David Friedberg david friedberg: Anthropic is trying to commoditize everyone's business. Friedberg, a life-sciences CEO and All-In host, sat in on Anthropic's enterprise pitch to biotech: share your proprietary data, get model access. Nearly every company he spoke with reached the same conclusion - sharing the data makes Anthropic's...

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51,986 просмотров • 1 месяц назад •via X (Twitter)

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Dario Amodei keeps warning that open-source AI models are dangerous and need to be restricted. David Sacks David Sacks answered with a rhetorical question: "Dangerous to whom?" It was the sharpest thing said on the latest All-In The All-In Podcast. Not dangerous to the enterprise that wants to keep control of its own data. Open weights are what finally give that enterprise a choice. It is dangerous to Anthropic's business model. That model only works if customers have no real alternative at the model layer. So the safety argument starts to look like a moat argument wearing a lab coat. Line it up with the rest of the strategy. Dominate the layer everyone builds on. Launch Claude into science, security, legal, finance, and design, the verticals your own customers used to own. And campaign to restrict the open models that would hand those customers the exit. Here is the giveaway. When the person selling you safety also needs you to have no other option, you are not who is being kept safe.
0:22

Dario Amodei keeps warning that open-source AI models are dangerous and need to be restricted. David Sacks David Sacks answered with a rhetorical question: "Dangerous to whom?" It was the sharpest thing said on the latest All-In The All-In Podcast. Not dangerous to the enterprise that wants to keep control of its own data. Open weights are what finally give that enterprise a choice. It is dangerous to Anthropic's business model. That model only works if customers have no real alternative at the model layer. So the safety argument starts to look like a moat argument wearing a lab coat. Line it up with the rest of the strategy. Dominate the layer everyone builds on. Launch Claude into science, security, legal, finance, and design, the verticals your own customers used to own. And campaign to restrict the open models that would hand those customers the exit. Here is the giveaway. When the person selling you safety also needs you to have no other option, you are not who is being kept safe.

Fireside Alpha

10,037 просмотров • 1 месяц назад

Big pharma just handed the AI industry one of the most important reality checks of 2026 (Save this). david friedberg revealed that Anthropic approached major life sciences companies with a pitch, share your proprietary data, sign an NDA and we will give you early access to a specialized life sciences model and nearly every company they spoke with said no. Here is what these pharma companies understood that many enterprises still have not. A large pharmaceutical company may have spent decades and tens of billions of dollars generating proprietary datasets, clinical trial results, genomic sequences, drug interaction data, compound libraries. That data is the business and the competitive moat that separates them from every other player in the industry lives in those datasets. Handing it to an AI lab in exchange for early access to a model is essentially handing your most valuable asset to a company whose entire business model depends on combining your data with everyone else's and then selling the output back to you and to your competitors. Palantir CEO Alex Karp made this exact point that enterprise leaders are paying for AI tokens that generate no tangible business value while simultaneously surrendering their most sensitive operational data to external providers. He called this transferring a company's alpha, the unique advantage that secures the business directly to a third-party lab. Microsoft CEO Satya Nadella echoed the same concern independently, warning that entire sectors might find their accumulated knowledge commoditized if they do not build their own data and model ownership layers. The structural problem is not unique to pharma but it applies to every enterprise sector. Every time an employee runs a query through a third-party frontier model, proprietary workflows, customer data, and strategic processes pass through infrastructure the enterprise does not control. The data already shows the market moving, Open-source captured 67% of all AI tokens processed in the first half of 2026, up from a fraction of that just twelve months earlier. The performance gap between proprietary frontier models and open-source alternatives has nearly closed, DeepSeek costs approximately 1/36th of GPT-5 for comparable workloads. What pharma figured out and what enterprises across every sector are starting to realize is that the model is not the moat but the data is. And once you hand your data to a model company, you have permanently surrendered the asset that took you decades and billions of dollars to build.
3:21

Big pharma just handed the AI industry one of the most important reality checks of 2026 (Save this). david friedberg revealed that Anthropic approached major life sciences companies with a pitch, share your proprietary data, sign an NDA and we will give you early access to a specialized life sciences model and nearly every company they spoke with said no. Here is what these pharma companies understood that many enterprises still have not. A large pharmaceutical company may have spent decades and tens of billions of dollars generating proprietary datasets, clinical trial results, genomic sequences, drug interaction data, compound libraries. That data is the business and the competitive moat that separates them from every other player in the industry lives in those datasets. Handing it to an AI lab in exchange for early access to a model is essentially handing your most valuable asset to a company whose entire business model depends on combining your data with everyone else's and then selling the output back to you and to your competitors. Palantir CEO Alex Karp made this exact point that enterprise leaders are paying for AI tokens that generate no tangible business value while simultaneously surrendering their most sensitive operational data to external providers. He called this transferring a company's alpha, the unique advantage that secures the business directly to a third-party lab. Microsoft CEO Satya Nadella echoed the same concern independently, warning that entire sectors might find their accumulated knowledge commoditized if they do not build their own data and model ownership layers. The structural problem is not unique to pharma but it applies to every enterprise sector. Every time an employee runs a query through a third-party frontier model, proprietary workflows, customer data, and strategic processes pass through infrastructure the enterprise does not control. The data already shows the market moving, Open-source captured 67% of all AI tokens processed in the first half of 2026, up from a fraction of that just twelve months earlier. The performance gap between proprietary frontier models and open-source alternatives has nearly closed, DeepSeek costs approximately 1/36th of GPT-5 for comparable workloads. What pharma figured out and what enterprises across every sector are starting to realize is that the model is not the moat but the data is. And once you hand your data to a model company, you have permanently surrendered the asset that took you decades and billions of dollars to build.

Milk Road AI

16,317 просмотров • 1 месяц назад

David Friedberg says Anthropic asked big pharma for their data and nearly everyone said no "There's been an effort by Anthropic to sign up life sciences companies to contribute to a new life sciences focused model. They're approaching these large companies with large proprietary data sets and saying, if you share your data, we will give you early access, some sort of proprietary value. Sign this NDA and you can participate with us." "I think nearly everyone I've spoken with has woken up to the fact that they are trying to commoditize everyone's business. If all of the tens of billions of dollars you have invested in experiments and product development, and you've generated all of this proprietary data along the way, that data is a true asset of your organization. It's an asset that you've spent billions of dollars developing." "And by handing it over to a model company to then combine with other people's data, you are commoditizing the one core differentiation that you have. And so everyone is largely saying no." "I think what everyone's realizing is they're better off developing their own weights and their own models using either an open source basis or there might be some intermediary business model that evolves."
3:21

David Friedberg says Anthropic asked big pharma for their data and nearly everyone said no "There's been an effort by Anthropic to sign up life sciences companies to contribute to a new life sciences focused model. They're approaching these large companies with large proprietary data sets and saying, if you share your data, we will give you early access, some sort of proprietary value. Sign this NDA and you can participate with us." "I think nearly everyone I've spoken with has woken up to the fact that they are trying to commoditize everyone's business. If all of the tens of billions of dollars you have invested in experiments and product development, and you've generated all of this proprietary data along the way, that data is a true asset of your organization. It's an asset that you've spent billions of dollars developing." "And by handing it over to a model company to then combine with other people's data, you are commoditizing the one core differentiation that you have. And so everyone is largely saying no." "I think what everyone's realizing is they're better off developing their own weights and their own models using either an open source basis or there might be some intermediary business model that evolves."

dnap

287,391 просмотров • 1 месяц назад

David Sacks broke down on the All-In podcast why Alex Karp's CNBC outburst was not a meltdown but a warning, and then laid out exactly how Anthropic is running the same playbook Microsoft used to kill an entire generation of software companies. The media called Karp unhinged. Sacks said the opposite. Karp was describing what enterprise customers actually want. Control over their compute, their models, their data, their alpha. Ownership of the means of production. Then he named the proof. Anthropic's chief product officer sat on Figma's board. He did not resign until 3 days before Anthropic launched Claude Design, a direct competitor. Figma's stock is down 50 percent this year. Sacks called it a pattern. Claude Code, Claude Science, Claude Security, Claude Legal, Claude Financial. Every vertical where a customer built value on top of Anthropic's model got absorbed by Anthropic itself. Word Perfect and Lotus 123 got replaced by Excel and Word. Nobody who went to bed with Microsoft in the 80s woke up with their business intact. What do you think?
2:59

David Sacks broke down on the All-In podcast why Alex Karp's CNBC outburst was not a meltdown but a warning, and then laid out exactly how Anthropic is running the same playbook Microsoft used to kill an entire generation of software companies. The media called Karp unhinged. Sacks said the opposite. Karp was describing what enterprise customers actually want. Control over their compute, their models, their data, their alpha. Ownership of the means of production. Then he named the proof. Anthropic's chief product officer sat on Figma's board. He did not resign until 3 days before Anthropic launched Claude Design, a direct competitor. Figma's stock is down 50 percent this year. Sacks called it a pattern. Claude Code, Claude Science, Claude Security, Claude Legal, Claude Financial. Every vertical where a customer built value on top of Anthropic's model got absorbed by Anthropic itself. Word Perfect and Lotus 123 got replaced by Excel and Word. Nobody who went to bed with Microsoft in the 80s woke up with their business intact. What do you think?

Ihtesham Ali

153,361 просмотров • 1 месяц назад

Palantir CEO Alex Karp on why the model is not the moat. The application layer is: "To make them valuable in an enterprise, like a battlefield, regulated, or manufacturing context, you have to have what's called an application layer." "We have this thing called ontology that now everyone's copying. It takes a large language model and makes it safe and useful and precise." "Safe because it doesn't touch your underlying data." "Safe because it prevents the large language model from caching your data and replicating your business." The tell for any enterprise AI pitch: ask what sits between the model and your data. If the answer is nothing, you are not buying leverage. You are renting a fast way to hand your business to whoever owns the weights. Alex Karp, CEO of Palantir, on CNBC.
0:24

Palantir CEO Alex Karp on why the model is not the moat. The application layer is: "To make them valuable in an enterprise, like a battlefield, regulated, or manufacturing context, you have to have what's called an application layer." "We have this thing called ontology that now everyone's copying. It takes a large language model and makes it safe and useful and precise." "Safe because it doesn't touch your underlying data." "Safe because it prevents the large language model from caching your data and replicating your business." The tell for any enterprise AI pitch: ask what sits between the model and your data. If the answer is nothing, you are not buying leverage. You are renting a fast way to hand your business to whoever owns the weights. Alex Karp, CEO of Palantir, on CNBC.

Karl Mehta

31,891 просмотров • 1 месяц назад

.Chamath Palihapitiya says Palantir CEO Alex Karp is " an incredible, smart, brilliant guy" who "completely nailed it and called out on its face the huge risk" of giving your company's alpha to OpenAI and Anthropic: "If you are a reasonable company, why are you not finding an independent way to access this intelligence in a way that doesn't leak your edge away?" "To do so at this point now is kind of becoming derelict and irresponsible." "Back then, you could be experimenting because you didn't know any better." "Now, when you know all of these data points, to continue to make the same decision is really insanely dumb." Via The All-In Podcast David Sacks david friedberg @jason
1:05

.Chamath Palihapitiya says Palantir CEO Alex Karp is " an incredible, smart, brilliant guy" who "completely nailed it and called out on its face the huge risk" of giving your company's alpha to OpenAI and Anthropic: "If you are a reasonable company, why are you not finding an independent way to access this intelligence in a way that doesn't leak your edge away?" "To do so at this point now is kind of becoming derelict and irresponsible." "Back then, you could be experimenting because you didn't know any better." "Now, when you know all of these data points, to continue to make the same decision is really insanely dumb." Via The All-In Podcast David Sacks david friedberg @jason

Jawwwn

503,913 просмотров • 1 месяц назад

📈 Brad Gerstner showed a fascinating chart on the latest episode of The All-In Podcast: "In 2022, NVIDIA and AMD had basically the same revenue, $25 billion. This year, Nvidia will do 10x that, at roughly $210B - $230B, and AMD will do $33 billion. Not much more than they were doing when the companies were tied in 2022. So Nvidia has captured nearly 100% of the incremental AI data center revenues over the course of the last two and a half years." -Brad Gerstner on the All In Football Show with @jason, Chamath Palihapitiya, David Sacks and david friedberg
1:56

📈 Brad Gerstner showed a fascinating chart on the latest episode of The All-In Podcast: "In 2022, NVIDIA and AMD had basically the same revenue, $25 billion. This year, Nvidia will do 10x that, at roughly $210B - $230B, and AMD will do $33 billion. Not much more than they were doing when the companies were tied in 2022. So Nvidia has captured nearly 100% of the incremental AI data center revenues over the course of the last two and a half years." -Brad Gerstner on the All In Football Show with @jason, Chamath Palihapitiya, David Sacks and david friedberg

bg2clips

11,303 просмотров • 10 месяцев назад

David Sacks: Anthropic Is Trying to Crush Open Source AI and the American Developers Who Use It David Sacks: “I know people don't have a lot of sympathy for Chinese companies, that's fine. I'm not defending Chinese companies. I'm defending American developers who need to be able to use everything in the public domain. And let me give you an example. Cursor rolled out its new product, Composer 2. They were able to post-train that model using Kimi K2.5 on their own proprietary coding data. They started with a Chinese open source model, and then they used their own data, and they came up with a new derivative product. This is the way that open source works. You take things that are in the public domain, you fork them, you make them your own. And by the way, once it's in the public domain, it's not a Chinese model anymore. No data is going back to China, nothing's going back to China. An American company has taken open source contributions in the public domain, made it their own, and then developed their own model. And if you say that American companies can't do that, or that somehow it's tainted with IP theft, you are basically going to put a dagger through the heart of the entire American open source ecosystem. And that is exactly what Anthropic wants, because they do not want to have the competition.”
0:59

David Sacks: Anthropic Is Trying to Crush Open Source AI and the American Developers Who Use It David Sacks: “I know people don't have a lot of sympathy for Chinese companies, that's fine. I'm not defending Chinese companies. I'm defending American developers who need to be able to use everything in the public domain. And let me give you an example. Cursor rolled out its new product, Composer 2. They were able to post-train that model using Kimi K2.5 on their own proprietary coding data. They started with a Chinese open source model, and then they used their own data, and they came up with a new derivative product. This is the way that open source works. You take things that are in the public domain, you fork them, you make them your own. And by the way, once it's in the public domain, it's not a Chinese model anymore. No data is going back to China, nothing's going back to China. An American company has taken open source contributions in the public domain, made it their own, and then developed their own model. And if you say that American companies can't do that, or that somehow it's tainted with IP theft, you are basically going to put a dagger through the heart of the entire American open source ecosystem. And that is exactly what Anthropic wants, because they do not want to have the competition.”

The All-In Podcast

277,664 просмотров • 23 дней назад

David Sacks: Anthropic Is Great at Two Things, Releasing Products and Scaring People “Anthropic has proven that it's very good at two things. One is product releases. The second is scaring people. And we've seen a pattern in their previous releases where, at the same time they roll out a new model or a new model card, something like that, they also roll out some study showing really the worst possible implications of where the technology could lead.” Source: The All-In Podcast
1:38

David Sacks: Anthropic Is Great at Two Things, Releasing Products and Scaring People “Anthropic has proven that it's very good at two things. One is product releases. The second is scaring people. And we've seen a pattern in their previous releases where, at the same time they roll out a new model or a new model card, something like that, they also roll out some study showing really the worst possible implications of where the technology could lead.” Source: The All-In Podcast

Mario Nawfal

50,266 просмотров • 4 месяцев назад

The most dangerous thing a company can do right now is rent intelligence from the same place as its competitors (Save this). You cannot rent intelligence from the same place that rents it to your competitor as Chamath Palihapitiya points out. If every company in an industry is feeding their workflows into the same frontier model, they are all converging on the same outputs, the same decisions, the same product improvements. The model becomes the equalizer and everyone pays a premium to become more mediocre. This is happening exactly as Chamath predicted, and the evidence is now concrete. Anthropic and OpenAI have established what analysts are now openly calling an emerging model layer duopoly. Anthropic crossed $45 billion ARR in may 2026, more than tripling from $9 billion at the end of 2025, OpenAI was at roughly $24 to $33 billion ARR at the same time. Together, the two companies combined could hit $160 to $240 billion ARR by end of 2026 and Anthropic and OpenAI now control 88% of enterprise LLM spend. That concentration is the structural problem Chamath is pointing at. And Anthropic isn't just winning on merit because it's actively lobbying for regulatory outcomes that would make that duopoly permanent. Dario Amodei has explicitly framed open source models as unsafe, pushing a safety agenda that, if enshrined in regulation, would effectively make it illegal for enterprises to use the cheaper, private, sovereign alternatives locking them into a closed model dependency by government decree rather than by choice. So you have market forces producing a duopoly, and potential regulatory capture moving to enforce it from the top down. This is exactly why the Nvidia Palantir partnership is not just a product announcement but rather a strategic counter to that duopoly. The logic is straightforward from both sides because If you're Palantir, sitting at the application layer, the last thing you want is to be permanently beholden to Anthropic or OpenAI for the intelligence that powers your product. You want competitive model options, sovereignty and be able to tell enterprise customers they can run AI on their own infrastructure with their own data without any of it touching a frontier lab's servers. If you're Nvidia, sitting at the chip layer, an Anthropic-OpenAI duopoly is an existential concentration risk. Right now, Meta, Google, Microsoft, Amazon, and dozens of other companies buy Nvidia's hardware. If the model layer consolidates into two players, both of which are building their own chips Nvidia faces a monopsony where its best customers are building the tools to displace it. A healthy open source ecosystem where thousands of enterprises train, fine tune, and deploy their own models is Nvidia's ideal market structure. More buyers, more diversity, more demand, less pricing leverage from any single customer.
4:38

The most dangerous thing a company can do right now is rent intelligence from the same place as its competitors (Save this). You cannot rent intelligence from the same place that rents it to your competitor as Chamath Palihapitiya points out. If every company in an industry is feeding their workflows into the same frontier model, they are all converging on the same outputs, the same decisions, the same product improvements. The model becomes the equalizer and everyone pays a premium to become more mediocre. This is happening exactly as Chamath predicted, and the evidence is now concrete. Anthropic and OpenAI have established what analysts are now openly calling an emerging model layer duopoly. Anthropic crossed $45 billion ARR in may 2026, more than tripling from $9 billion at the end of 2025, OpenAI was at roughly $24 to $33 billion ARR at the same time. Together, the two companies combined could hit $160 to $240 billion ARR by end of 2026 and Anthropic and OpenAI now control 88% of enterprise LLM spend. That concentration is the structural problem Chamath is pointing at. And Anthropic isn't just winning on merit because it's actively lobbying for regulatory outcomes that would make that duopoly permanent. Dario Amodei has explicitly framed open source models as unsafe, pushing a safety agenda that, if enshrined in regulation, would effectively make it illegal for enterprises to use the cheaper, private, sovereign alternatives locking them into a closed model dependency by government decree rather than by choice. So you have market forces producing a duopoly, and potential regulatory capture moving to enforce it from the top down. This is exactly why the Nvidia Palantir partnership is not just a product announcement but rather a strategic counter to that duopoly. The logic is straightforward from both sides because If you're Palantir, sitting at the application layer, the last thing you want is to be permanently beholden to Anthropic or OpenAI for the intelligence that powers your product. You want competitive model options, sovereignty and be able to tell enterprise customers they can run AI on their own infrastructure with their own data without any of it touching a frontier lab's servers. If you're Nvidia, sitting at the chip layer, an Anthropic-OpenAI duopoly is an existential concentration risk. Right now, Meta, Google, Microsoft, Amazon, and dozens of other companies buy Nvidia's hardware. If the model layer consolidates into two players, both of which are building their own chips Nvidia faces a monopsony where its best customers are building the tools to displace it. A healthy open source ecosystem where thousands of enterprises train, fine tune, and deploy their own models is Nvidia's ideal market structure. More buyers, more diversity, more demand, less pricing leverage from any single customer.

Milk Road AI

34,385 просмотров • 1 месяц назад

FRIEDBERG: 2025 WILL BE THE YEAR OF THE ROBOT "We just placed an order today out of China called Unitree. Their Go2 robot is $1600, has an API. You can run a payload on it. It's got LiDAR on it. It's got kind of intelligence guidance systems on it. We're looking at using them on our test farms where it can wander the farm and take images and report data back to us." Source: david friedberg, The All-In Podcast
3:43

FRIEDBERG: 2025 WILL BE THE YEAR OF THE ROBOT "We just placed an order today out of China called Unitree. Their Go2 robot is $1600, has an API. You can run a payload on it. It's got LiDAR on it. It's got kind of intelligence guidance systems on it. We're looking at using them on our test farms where it can wander the farm and take images and report data back to us." Source: david friedberg, The All-In Podcast

Mario Nawfal

172,113 просмотров • 1 год назад

David Sacks says the data kills the open-source-is-winning narrative, closed models just went from 81% to 89% of enterprise spend. "This is why the share of wallet of closed models actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing... Anyone who's saying these closed models are somehow losing, you're just not seeing it in the data." "Nikesh Arora said enterprises would like what he called model fungibility. They would love to commoditize these models and just hot swap them, headless. But then what do you do about memory, context, history? No one's really figured out a way to abstract that stuff away from the model yet."
0:58

David Sacks says the data kills the open-source-is-winning narrative, closed models just went from 81% to 89% of enterprise spend. "This is why the share of wallet of closed models actually increased. I think that open source went from 19% last year to 11% this year. So open source as a share of enterprise spending is actually decreasing... Anyone who's saying these closed models are somehow losing, you're just not seeing it in the data." "Nikesh Arora said enterprises would like what he called model fungibility. They would love to commoditize these models and just hot swap them, headless. But then what do you do about memory, context, history? No one's really figured out a way to abstract that stuff away from the model yet."

Fireside Alpha

54,383 просмотров • 1 месяц назад

FRIEDBERG: VIDEO DATA WILL POWER THE NEXT GENERATION OF AI Friedberg broke down the scale shift coming to artificial intelligence, arguing that text based models like GPT are just the beginning, and that the real revolution will come from video-trained systems: “The internet and all these LLMs are language models trained on text from the internet, around 50 billion words total, maybe one to five terabytes of data in their training sets. But if you look at the video data out there, there are hundreds of billions of hours, much of it on YouTube. By some estimates, there’s a thousand exabytes of video data on the internet, about a billion times more than text data. I think we just saw that play out with the new video model that launched yesterday. Google has all this YouTube data, whether or not they’re using it to train, I don’t know. I’ve heard from insiders they’re not allowed to yet and would have to redo the terms of service.” Source: AIFinInsights david friedberg
2:12

FRIEDBERG: VIDEO DATA WILL POWER THE NEXT GENERATION OF AI Friedberg broke down the scale shift coming to artificial intelligence, arguing that text based models like GPT are just the beginning, and that the real revolution will come from video-trained systems: “The internet and all these LLMs are language models trained on text from the internet, around 50 billion words total, maybe one to five terabytes of data in their training sets. But if you look at the video data out there, there are hundreds of billions of hours, much of it on YouTube. By some estimates, there’s a thousand exabytes of video data on the internet, about a billion times more than text data. I think we just saw that play out with the new video model that launched yesterday. Google has all this YouTube data, whether or not they’re using it to train, I don’t know. I’ve heard from insiders they’re not allowed to yet and would have to redo the terms of service.” Source: AIFinInsights david friedberg

Mario Nawfal

15,855 просмотров • 8 месяцев назад

Anthropic is running the oldest predatory playbook in Big Tech (Save this). Here is what actually happened. Anthropic's own Chief Product Officer, Mike Krieger, was sitting on Figma's board and he resigned on April 14, 2026. Three days later, Anthropic launched Claude Design, a direct competitor to Figma's core product that allows users to generate prototypes, slide decks, and visual assets through conversation. Figma's stock dropped 7% the day of the launch and the stock has shed approximately 80% from its all-time high, erasing nearly $50 billion in market cap. Anthropic's valuation surged toward $800 billion in the same period. This is not an accident but rather a deliberate, systematic strategy and once you see the pattern, you cannot unsee it. Anthropic watched Cursor build the coding assistant category on top of Claude's models, Cursor became one of Anthropic's biggest customers. Cursor's usage patterns and product insights flowed through Anthropic's infrastructure every single day then Anthropic launched Claude Code, entering the exact category Cursor had created armed with every data point it needed to know the market size, the use cases, and the user behavior. The same pattern has now repeated across Claude Science, Claude Security, Claude Legal, and Claude Financial, every single one a vertical that was previously served by companies building on top of Anthropic's own models. The companies that trusted Anthropic's platform were simultaneously handing Anthropic the product roadmap for what to build next. Every company currently building on top of a closed frontier model is in the same position Figma was in before April 14, 2026. The only question is which category Anthropic targets next. David Sacks
5:11

Anthropic is running the oldest predatory playbook in Big Tech (Save this). Here is what actually happened. Anthropic's own Chief Product Officer, Mike Krieger, was sitting on Figma's board and he resigned on April 14, 2026. Three days later, Anthropic launched Claude Design, a direct competitor to Figma's core product that allows users to generate prototypes, slide decks, and visual assets through conversation. Figma's stock dropped 7% the day of the launch and the stock has shed approximately 80% from its all-time high, erasing nearly $50 billion in market cap. Anthropic's valuation surged toward $800 billion in the same period. This is not an accident but rather a deliberate, systematic strategy and once you see the pattern, you cannot unsee it. Anthropic watched Cursor build the coding assistant category on top of Claude's models, Cursor became one of Anthropic's biggest customers. Cursor's usage patterns and product insights flowed through Anthropic's infrastructure every single day then Anthropic launched Claude Code, entering the exact category Cursor had created armed with every data point it needed to know the market size, the use cases, and the user behavior. The same pattern has now repeated across Claude Science, Claude Security, Claude Legal, and Claude Financial, every single one a vertical that was previously served by companies building on top of Anthropic's own models. The companies that trusted Anthropic's platform were simultaneously handing Anthropic the product roadmap for what to build next. Every company currently building on top of a closed frontier model is in the same position Figma was in before April 14, 2026. The only question is which category Anthropic targets next. David Sacks

Milk Road AI

69,499 просмотров • 1 месяц назад

The entire AI industry is racing to build the smartest model. Satya Nadella just admitted that is not where the money is. The model is not the product. The harness is. That is the exact line. And it changes what Microsoft is actually competing on. OpenAI, Anthropic, Google, xAI, Meta every frontier lab is pouring hundreds of billions into training compute, chasing the next capability jump. Each betting that raw model intelligence is the moat. Microsoft is doing the opposite. It is building the harness the orchestration layer that sits above the model, connecting it to tools, data, permissions, sub-agents, and enterprise workflows. And it is letting OpenAI, Anthropic, and MAI compete to plug into it. "You need the model. But the model is not the product. The harness is." So do the math on what a harness actually does. A raw model dropped into an enterprise answers questions. That is a chatbot. A harness turns that same model into an agent that reads the SharePoint, edits the ERP entry, pulls the GitHub PR, updates Salesforce, and files the Excel report with the right permissions, the right audit trail, and the right sub-agent for each sub-task. The model provides the intelligence. The harness converts intelligence into work. Now here's where it gets interesting. "Even the best model in the world will feel broken without a great harness. And an okay model with a great harness can feel like magic." If that is true, the enterprise buyer is not buying model quality. The enterprise buyer is buying the harness. Which means model quality becomes a commodity input over time, and harness quality becomes the sustainable moat. Compare that to the strategy the entire frontier lab industry is executing. Everyone else is chasing the numerator raw intelligence. Almost nobody at scale is racing to build the denominator the orchestration layer that determines whether that intelligence can actually be deployed profitably inside a real company. The frontier model race has a 10 to 20 percent chance of producing a single dominant winner. Nadella just told the industry he does not need to be that winner. If OpenAI wins, Microsoft wins. If Anthropic wins, Microsoft wins. If MAI wins, Microsoft wins. If someone Microsoft has never heard of trains a better model in 2027, Microsoft still wins. Because the compute they train on, the harness they get plugged into, the enterprise contracts they get delivered through, and the products they sit inside are all Microsoft. He is not building the best AI model. He is building the layer that the best AI model has to run on to make anyone money. I wonder which position looks more valuable in ten years.
3:19

The entire AI industry is racing to build the smartest model. Satya Nadella just admitted that is not where the money is. The model is not the product. The harness is. That is the exact line. And it changes what Microsoft is actually competing on. OpenAI, Anthropic, Google, xAI, Meta every frontier lab is pouring hundreds of billions into training compute, chasing the next capability jump. Each betting that raw model intelligence is the moat. Microsoft is doing the opposite. It is building the harness the orchestration layer that sits above the model, connecting it to tools, data, permissions, sub-agents, and enterprise workflows. And it is letting OpenAI, Anthropic, and MAI compete to plug into it. "You need the model. But the model is not the product. The harness is." So do the math on what a harness actually does. A raw model dropped into an enterprise answers questions. That is a chatbot. A harness turns that same model into an agent that reads the SharePoint, edits the ERP entry, pulls the GitHub PR, updates Salesforce, and files the Excel report with the right permissions, the right audit trail, and the right sub-agent for each sub-task. The model provides the intelligence. The harness converts intelligence into work. Now here's where it gets interesting. "Even the best model in the world will feel broken without a great harness. And an okay model with a great harness can feel like magic." If that is true, the enterprise buyer is not buying model quality. The enterprise buyer is buying the harness. Which means model quality becomes a commodity input over time, and harness quality becomes the sustainable moat. Compare that to the strategy the entire frontier lab industry is executing. Everyone else is chasing the numerator raw intelligence. Almost nobody at scale is racing to build the denominator the orchestration layer that determines whether that intelligence can actually be deployed profitably inside a real company. The frontier model race has a 10 to 20 percent chance of producing a single dominant winner. Nadella just told the industry he does not need to be that winner. If OpenAI wins, Microsoft wins. If Anthropic wins, Microsoft wins. If MAI wins, Microsoft wins. If someone Microsoft has never heard of trains a better model in 2027, Microsoft still wins. Because the compute they train on, the harness they get plugged into, the enterprise contracts they get delivered through, and the products they sit inside are all Microsoft. He is not building the best AI model. He is building the layer that the best AI model has to run on to make anyone money. I wonder which position looks more valuable in ten years.

Vikram M

21,463 просмотров • 1 месяц назад

🚨NEW: David Friedberg explains why people have lost interest in the Democratic party (MUST WATCH) "I think the Democratic party has split into two parties: the democratic party *with* beliefs and the democratic party *without* beliefs. The Democratic party with beliefs is very far left and their beliefs are fundamentally rooted in socialism and marxism... The rest of the Democratic party, the "moderate party," really don't know what their beliefs are. Republicans know clearly what their beliefs are. Every member of the cabinet in DC we met with had the exact same message and exact same set of beliefs as to what this admin stands for and what they're trying to do... Because the moderates in the Democratic party have not stated a set of beliefs for their country/party, the party is effectively being represented by the part of the party that *does* have beliefs: the deeply socialist/marxist beliefs. They have subsumed the message and as a result this is why people have lost interest in the Democratic party..." 📸: david friedberg The All-In Podcast
2:35

🚨NEW: David Friedberg explains why people have lost interest in the Democratic party (MUST WATCH) "I think the Democratic party has split into two parties: the democratic party *with* beliefs and the democratic party *without* beliefs. The Democratic party with beliefs is very far left and their beliefs are fundamentally rooted in socialism and marxism... The rest of the Democratic party, the "moderate party," really don't know what their beliefs are. Republicans know clearly what their beliefs are. Every member of the cabinet in DC we met with had the exact same message and exact same set of beliefs as to what this admin stands for and what they're trying to do... Because the moderates in the Democratic party have not stated a set of beliefs for their country/party, the party is effectively being represented by the part of the party that *does* have beliefs: the deeply socialist/marxist beliefs. They have subsumed the message and as a result this is why people have lost interest in the Democratic party..." 📸: david friedberg The All-In Podcast

Autism Capital 🧩

2,317,500 просмотров • 1 год назад

This is the best take I have heard around the existing AI landscape today Fantastic explanation around the constraints at OpenAI and Anthropic, focus on enterprise business models, and the doomerism narrative in AI From former AI czar David Sacks "Even though Anthropic's revenue has followed this exponential graph very predictably, it cannot do that ever. The reason is that as you hit new levels of scale, you encounter new problems. You are simply going to run out of compute, electricity, data centers, and infrastructure. There are limits to the physical world you are going to hit. And there is already evidence that Anthropic is hitting some of those limits."
4:27

This is the best take I have heard around the existing AI landscape today Fantastic explanation around the constraints at OpenAI and Anthropic, focus on enterprise business models, and the doomerism narrative in AI From former AI czar David Sacks "Even though Anthropic's revenue has followed this exponential graph very predictably, it cannot do that ever. The reason is that as you hit new levels of scale, you encounter new problems. You are simply going to run out of compute, electricity, data centers, and infrastructure. There are limits to the physical world you are going to hit. And there is already evidence that Anthropic is hitting some of those limits."

Boring_Business

236,448 просмотров • 3 месяцев назад

Jensen Huang was asked whether AI's future is open source or proprietary the question the whole industry keeps fighting over. He didn't pick a side. He said something that quietly ends the fight. "models is a technology, not a product. Model is a technology, not a service" "For the vast majority of consumers, the horizontal layer, the general intelligence, I would really, really love not to go fine-tune my own" "all these industries, their domain expertise, their specialization has to be channeled, has to be captured in a way that they can control, and that it can only come from open models" "the open model industry we're contributing tremendously to it is near the frontier" Everyone else is arguing about which lab wins OpenAI or Anthropic, who has the smartest frontier model this quarter. Jensen is standing on stage saying that's the sideshow. The proprietary model is the convenience layer you rent when you don't care. The open model is the thing you own when the work is yours. Two different products for two different needs not two horses in one race. open models are the second-biggest in the room. Ahead of Anthropic. Behind only OpenAI.
2:51

Jensen Huang was asked whether AI's future is open source or proprietary the question the whole industry keeps fighting over. He didn't pick a side. He said something that quietly ends the fight. "models is a technology, not a product. Model is a technology, not a service" "For the vast majority of consumers, the horizontal layer, the general intelligence, I would really, really love not to go fine-tune my own" "all these industries, their domain expertise, their specialization has to be channeled, has to be captured in a way that they can control, and that it can only come from open models" "the open model industry we're contributing tremendously to it is near the frontier" Everyone else is arguing about which lab wins OpenAI or Anthropic, who has the smartest frontier model this quarter. Jensen is standing on stage saying that's the sideshow. The proprietary model is the convenience layer you rent when you don't care. The open model is the thing you own when the work is yours. Two different products for two different needs not two horses in one race. open models are the second-biggest in the room. Ahead of Anthropic. Behind only OpenAI.

Vikram M

12,078 просмотров • 26 дней назад

Alex Karp went on CNBC and absolutely torched Anthropic & OpenAI. He is a bit biased, but he isnt totally wrong here either. Many enterprises went all-in on AI tokens thinking usage as it meant progress. More prompts, more agents, more tokens, more and more tokens. Real question still remains: What actual workflow changed? How much was the cost? What decision got better? What alpha stayed inside the company? Was the data cached on the model provider’s servers? That is where the frustration seems to be building among enterprise CEOs. The problem is enterprises are paying more and more to rent intelligence, while still worrying about their data, IP, workflows, and overall control. Karp is calling it a “wealth tax on business” The next phase of enterprise AI in his words is by reading between the lines is, Deployment, Security, Data control, Workflow integration, Actual ROI. Model + Application layer (Ontology) + compute Reason why Palantir is pushing for a model agnostic sovereign AI on top of their ontology in partnership with Nvidia $NVDA This essentially means enterprises and customers will, 1. Own their data 2 Control their data. 3. Keep their alpha rather than transferring it to the model providers. Karp is talking his book. But the points he made aren’t wrong either. Must watch! 🍿 $PLTR
19:45

Alex Karp went on CNBC and absolutely torched Anthropic & OpenAI. He is a bit biased, but he isnt totally wrong here either. Many enterprises went all-in on AI tokens thinking usage as it meant progress. More prompts, more agents, more tokens, more and more tokens. Real question still remains: What actual workflow changed? How much was the cost? What decision got better? What alpha stayed inside the company? Was the data cached on the model provider’s servers? That is where the frustration seems to be building among enterprise CEOs. The problem is enterprises are paying more and more to rent intelligence, while still worrying about their data, IP, workflows, and overall control. Karp is calling it a “wealth tax on business” The next phase of enterprise AI in his words is by reading between the lines is, Deployment, Security, Data control, Workflow integration, Actual ROI. Model + Application layer (Ontology) + compute Reason why Palantir is pushing for a model agnostic sovereign AI on top of their ontology in partnership with Nvidia $NVDA This essentially means enterprises and customers will, 1. Own their data 2 Control their data. 3. Keep their alpha rather than transferring it to the model providers. Karp is talking his book. But the points he made aren’t wrong either. Must watch! 🍿 $PLTR

Anand

33,114 просмотров • 1 месяц назад