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$SPCX valuing Cursor at $60B proves durable value in AI is moving to the data layer because compute commoditizes as supply comes online while the application that owns daily workflow compounds as usage grows. $PLTR already owns that loop since every dataset, decision and process mapped into its ontology... show more

Shay Boloor

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61,460 views • 25 days ago •via X (Twitter)

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$SPCX spending $60B on Cursor validates the idea that real AI value accrues to the application layer that owns the workflow, proprietary data loop and enterprise distribution. $NOW is building exactly that as the orchestration layer for enterprise AI agents across business workflows. The Cursor deal is a reminder that the market will pay massive premiums for software that owns where work actually happens.

$SPCX spending $60B on Cursor validates the idea that real AI value accrues to the application layer that owns the workflow, proprietary data loop and enterprise distribution. $NOW is building exactly that as the orchestration layer for enterprise AI agents across business workflows. The Cursor deal is a reminder that the market will pay massive premiums for software that owns where work actually happens.

Shay Boloor

80,768 views • 26 days ago

$PLTR CEO Alex Karp argued that AI alone is not enough. The real value comes from combining models with domain expertise, workflows, and operational execution. His view is that enterprise AI is ultimately about solving business problems, not maximizing token usage. As models become commoditized, the winners may be the companies that combine taste, data, and execution rather than compute alone.

$PLTR CEO Alex Karp argued that AI alone is not enough. The real value comes from combining models with domain expertise, workflows, and operational execution. His view is that enterprise AI is ultimately about solving business problems, not maximizing token usage. As models become commoditized, the winners may be the companies that combine taste, data, and execution rather than compute alone.

Sam Badawi

36,546 views • 1 month ago

$SPCX ACQUIRES CURSOR FOR $60B. Months ago, Jensen Huang $NVDA said: "My favorite enterprise AI service is Cursor. Cursor is an AI coder. Every one of our engineers is now assisted by Cursor, and our productivity has gone up incredibly." Elon is playing to win.

$SPCX ACQUIRES CURSOR FOR $60B. Months ago, Jensen Huang $NVDA said: "My favorite enterprise AI service is Cursor. Cursor is an AI coder. Every one of our engineers is now assisted by Cursor, and our productivity has gone up incredibly." Elon is playing to win.

Daniel

515,767 views • 26 days ago

Software is getting repriced because the market doesn't trust which business models will matter a decade from now. The category grows but the winners concentrate with $PLTR emerging as the decision layer for AI agents & $NET as the connectivity layer.

Software is getting repriced because the market doesn't trust which business models will matter a decade from now. The category grows but the winners concentrate with $PLTR emerging as the decision layer for AI agents & $NET as the connectivity layer.

Shay Boloor

170,172 views • 4 months ago

The market is underappreciating that $MSFT already owns the enterprise workflow layer where AI adoption is likely to happen. Workers already live inside Outlook, Excel, PowerPoint, Teams, GitHub and Azure which gives Microsoft a built-in distribution advantage as AI gets embedded across the enterprise. Copilot is still early but the numbers are getting more meaningful with over 20M paid seats, paid seat additions up 250% YoY and customers with more than 50K seats quadrupling YoY Every 10M Copilot seats at ~$30 per user per month represents ~$3.6B of annualized revenue so if Copilot scales to 100M seats over the next several years then it becomes a major software revenue layer on top of Microsoft 365.

The market is underappreciating that $MSFT already owns the enterprise workflow layer where AI adoption is likely to happen. Workers already live inside Outlook, Excel, PowerPoint, Teams, GitHub and Azure which gives Microsoft a built-in distribution advantage as AI gets embedded across the enterprise. Copilot is still early but the numbers are getting more meaningful with over 20M paid seats, paid seat additions up 250% YoY and customers with more than 50K seats quadrupling YoY Every 10M Copilot seats at ~$30 per user per month represents ~$3.6B of annualized revenue so if Copilot scales to 100M seats over the next several years then it becomes a major software revenue layer on top of Microsoft 365.

Shay Boloor

117,204 views • 16 days ago

1/3 Zesh AI Layer is an advanced AI solution on SUI, powered by a library of data models that act as its engine. Zesh layer is designed for building cutting-edge AI products, giving every project on Zesh access to its expansive and ever-evolving library of data models. As more products, users, and activity takes place in the Zesh ecosystem, the data model library continually learns and grows. This is AI that evolves with you.

1/3 Zesh AI Layer is an advanced AI solution on SUI, powered by a library of data models that act as its engine. Zesh layer is designed for building cutting-edge AI products, giving every project on Zesh access to its expansive and ever-evolving library of data models. As more products, users, and activity takes place in the Zesh ecosystem, the data model library continually learns and grows. This is AI that evolves with you.

Zesh AI Layer

1,044,803 views • 1 year ago

Microsoft CEO Satya Nadella's new interivew: Explains how the next AI moat will not be the model you use, but the learning loop only your company can run. He is really asking what happens to the firm when intelligence becomes something you can rent. For a century, companies protected value through people, processes, data, routines, customer memory, and the tacit knowledge buried in daily operations. Foundation models threaten to flatten that advantage because the same general intelligence can be used by everyone. Nadella’s answer is that firms need their own “hill climbing machine,” a private loop where models learn from company-specific tasks, traces, evaluations, and outcomes. That means the real asset is not just the model. The asset is the environment that keeps improving the model in ways competitors cannot copy. Private evals become strategic memory. Workflow traces become training signal. Human judgment becomes a way to steer compounding, not just correct mistakes. This also reframes AI adoption: a company that only consumes a foundation model may gain productivity, but it may leak the deeper value of its operating knowledge. A company that builds a disciplined learning loop can turn everyday work into accumulating IP. The future firm may therefore be measured by how well it converts its unique activity into durable model improvement. The frontier will not belong only to whoever owns the largest model. It will belong to whoever owns the best loop. ---- From "Stanford Online" YouTube channel, (link in comment)

Microsoft CEO Satya Nadella's new interivew: Explains how the next AI moat will not be the model you use, but the learning loop only your company can run. He is really asking what happens to the firm when intelligence becomes something you can rent. For a century, companies protected value through people, processes, data, routines, customer memory, and the tacit knowledge buried in daily operations. Foundation models threaten to flatten that advantage because the same general intelligence can be used by everyone. Nadella’s answer is that firms need their own “hill climbing machine,” a private loop where models learn from company-specific tasks, traces, evaluations, and outcomes. That means the real asset is not just the model. The asset is the environment that keeps improving the model in ways competitors cannot copy. Private evals become strategic memory. Workflow traces become training signal. Human judgment becomes a way to steer compounding, not just correct mistakes. This also reframes AI adoption: a company that only consumes a foundation model may gain productivity, but it may leak the deeper value of its operating knowledge. A company that builds a disciplined learning loop can turn everyday work into accumulating IP. The future firm may therefore be measured by how well it converts its unique activity into durable model improvement. The frontier will not belong only to whoever owns the largest model. It will belong to whoever owns the best loop. ---- From "Stanford Online" YouTube channel, (link in comment)

Rohan Paul

79,900 views • 9 days ago

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

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

32,482 views • 10 days ago

$XDC owns the $19T supply chain market with barely any competition. As adoption grows, so does its dominance. The future of supply chain is on-chain—and $XDC is leading the charge.

$XDC owns the $19T supply chain market with barely any competition. As adoption grows, so does its dominance. The future of supply chain is on-chain—and $XDC is leading the charge.

Merlijn The Trader

77,504 views • 1 year ago

“Pointing an LLM at hundreds of disconnected, ungoverned databases gets you a system that hallucinates, is insecure, and unauditable. For something as consequential as our nation’s agricultural data, that is not just useless — it’s dangerous. The Ontology has been the key to delivering AI-enabled technology to every farmer in the country.” At AIPCon 10, the USDA demonstrates how the Ontology now underpins national food supply security.

“Pointing an LLM at hundreds of disconnected, ungoverned databases gets you a system that hallucinates, is insecure, and unauditable. For something as consequential as our nation’s agricultural data, that is not just useless — it’s dangerous. The Ontology has been the key to delivering AI-enabled technology to every farmer in the country.” At AIPCon 10, the USDA demonstrates how the Ontology now underpins national food supply security.

Palantir

2,199,311 views • 1 month ago

NeurochainAI is the all-in-one platform for developers to build AI dApps including GPU DePIN, Data Layer, and AI model layer. But what does it actually mean? AI is a $1.8 trillion industry, and NeurochainAI is tapping into 1% of that - as an infrastructure of interconnected GPUs, AI models, and data. Even simpler? Think of us as Ethereum for AI🧠🌐

NeurochainAI is the all-in-one platform for developers to build AI dApps including GPU DePIN, Data Layer, and AI model layer. But what does it actually mean? AI is a $1.8 trillion industry, and NeurochainAI is tapping into 1% of that - as an infrastructure of interconnected GPUs, AI models, and data. Even simpler? Think of us as Ethereum for AI🧠🌐

Neurochain.AI

105,336 views • 2 years ago

HERE’S TODAY’S FOX BUSINESS SEGMENT • The “SaaSpocalypse” 2026: legacy SaaS gets repriced as the plumbing layer in an agentic AI stack • Where value is migrating in the Agentic AI Stack: orchestration, security, connectivity, and data • Cyber picks for the agentic era: $CRWD as the interaction layer for agents, $RBRK as the “undo button” for agents & $ZS as the control plane for agent traffic • Why AI systems can’t function without clean, well-organized data: $SNOW, $MDB • The enterprise AI bottleneck: nobody is better positioned than $PLTR sitting between cheap, powerful models & messy, valuable enterprise data • Picks-and-shovels winner in agentic AI: $NET

HERE’S TODAY’S FOX BUSINESS SEGMENT • The “SaaSpocalypse” 2026: legacy SaaS gets repriced as the plumbing layer in an agentic AI stack • Where value is migrating in the Agentic AI Stack: orchestration, security, connectivity, and data • Cyber picks for the agentic era: $CRWD as the interaction layer for agents, $RBRK as the “undo button” for agents & $ZS as the control plane for agent traffic • Why AI systems can’t function without clean, well-organized data: $SNOW, $MDB • The enterprise AI bottleneck: nobody is better positioned than $PLTR sitting between cheap, powerful models & messy, valuable enterprise data • Picks-and-shovels winner in agentic AI: $NET

Shay Boloor

191,754 views • 4 months ago

Satya Nadella says “if you're going to use energy, you better have social permission to use energy.” Compute is electricity. And as usage grows, so will the burden of proof. Not just benchmarks. But visible value. Measurable impact. “That means you've got to make sure that the output of this AI is socially useful.”

Satya Nadella says “if you're going to use energy, you better have social permission to use energy.” Compute is electricity. And as usage grows, so will the burden of proof. Not just benchmarks. But visible value. Measurable impact. “That means you've got to make sure that the output of this AI is socially useful.”

vitrupo

67,328 views • 1 year ago

Elon Musk Elon owns Twitter, owns Tesla, owns SpaceX and so much more. This man is a modern day genius. I’m honored to share the earth at the same time as him!

Elon Musk Elon owns Twitter, owns Tesla, owns SpaceX and so much more. This man is a modern day genius. I’m honored to share the earth at the same time as him!

Camilo Sandoval

727,242 views • 3 years ago

"What I was betting on was the jockey and not the horse. I was betting on them as extraordinary people," says early investor of Cursor Michael Fertik following its $60B deal with $SPCX.

"What I was betting on was the jockey and not the horse. I was betting on them as extraordinary people," says early investor of Cursor Michael Fertik following its $60B deal with $SPCX.

Squawk Box

14,400 views • 24 days ago

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.

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

31,447 views • 7 days ago

Why is $NVDA letting NemoClaw run on any chip? Because Jensen is no longer trying to win only at the silicon layer against $AMD, $GOOGL TPUs or $AMZN Trainium but trying to own the orchestration layer above the hardware. NemoClaw decides how AI agents are deployed, what tasks they take on & how work flows across an enterprise. If those agents run through its system then it still owns the workflow even when it doesn’t own the chip. That is how Nvidia turns agentic AI orchestration into Workforce-as-a-Service.

Why is $NVDA letting NemoClaw run on any chip? Because Jensen is no longer trying to win only at the silicon layer against $AMD, $GOOGL TPUs or $AMZN Trainium but trying to own the orchestration layer above the hardware. NemoClaw decides how AI agents are deployed, what tasks they take on & how work flows across an enterprise. If those agents run through its system then it still owns the workflow even when it doesn’t own the chip. That is how Nvidia turns agentic AI orchestration into Workforce-as-a-Service.

Shay Boloor

77,857 views • 4 months ago

Copilot versus Cursor: (This is so embarrassing for Copilot) I opened the same project in Visual Studio Code and Cursor. I asked both agents to complete the same task: • Cursor: 34 seconds • Visual Studio Code: 122 seconds (4x slower!) At this point, Copilot is so behind Cursor that it's sad to even remember they were once ahead.

Copilot versus Cursor: (This is so embarrassing for Copilot) I opened the same project in Visual Studio Code and Cursor. I asked both agents to complete the same task: • Cursor: 34 seconds • Visual Studio Code: 122 seconds (4x slower!) At this point, Copilot is so behind Cursor that it's sad to even remember they were once ahead.

Santiago

154,094 views • 1 year ago