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The shift from Copilot to Autopilot is happening now. This is the Agentic Frontier, and while 82% of leaders are investing in it, most are not ready. Why? Because they're stuck in Phase 1 (AI Assistants) while the winners are already building for Phase 3 (Human-Led, Agent-Operated) operations. The...

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Sabine VanderLinden

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236,535 次观看 • 8 个月前 •via X (Twitter)

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CEO of Nvidia said something that stopped me cold: "You may or may not lose a job to an AI, but you will absolutely lose a job to someone who uses AI" this 41 minutes is the most important talk on AI you'll watch this year so the question is not whether AI is coming for your job it's whether you're the one using it or the one being replaced by someone who does Nvidia already has hundreds of thousands of agents running inside the company right now agents are not the future, they are how the best teams work today I wrote a step by step guide on how to build your first AI agent with Claude Code you can find it in the article below
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CEO of Nvidia said something that stopped me cold: "You may or may not lose a job to an AI, but you will absolutely lose a job to someone who uses AI" this 41 minutes is the most important talk on AI you'll watch this year so the question is not whether AI is coming for your job it's whether you're the one using it or the one being replaced by someone who does Nvidia already has hundreds of thousands of agents running inside the company right now agents are not the future, they are how the best teams work today I wrote a step by step guide on how to build your first AI agent with Claude Code you can find it in the article below

Anatoli Kopadze

14,627 次观看 • 1 个月前

What if the question isn’t whether to use AI, but how fast you can learn to work with it? In this special episode recorded live at Webex One, I talk with Jeetu Patel (Jeetu Patel), President and Chief Product Officer at Cisco, about the mindset shift every company, and every professional, must make to thrive in the AI era. From rethinking work culture to designing products for both humans and AI agents, Jeetu shares a thoughtful, optimistic vision for the future, one rooted in curiosity, responsibility, and human creativity. “AI won’t take your job. But someone who uses AI better than you might.” An honest, energizing look at how to lead and learn in an AI-first world. 1:08 Embracing AI In The Workforce 5:17 AI Is More Than A Productivity Tool 8:35 Generational Differences In AI Use 10:49 The Future of Integrating AI Agents 13:44 AI As A "Given" 17:08 Speed of Accumulating Knowledge 19:00 Ethical AI Use 21:16 What The Industry Gets Wrong About AI
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What if the question isn’t whether to use AI, but how fast you can learn to work with it? In this special episode recorded live at Webex One, I talk with Jeetu Patel (Jeetu Patel), President and Chief Product Officer at Cisco, about the mindset shift every company, and every professional, must make to thrive in the AI era. From rethinking work culture to designing products for both humans and AI agents, Jeetu shares a thoughtful, optimistic vision for the future, one rooted in curiosity, responsibility, and human creativity. “AI won’t take your job. But someone who uses AI better than you might.” An honest, energizing look at how to lead and learn in an AI-first world. 1:08 Embracing AI In The Workforce 5:17 AI Is More Than A Productivity Tool 8:35 Generational Differences In AI Use 10:49 The Future of Integrating AI Agents 13:44 AI As A "Given" 17:08 Speed of Accumulating Knowledge 19:00 Ethical AI Use 21:16 What The Industry Gets Wrong About AI

Carolina Milanesi

37,076 次观看 • 10 个月前

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.
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Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Santiago

230,594 次观看 • 1 年前

This is nuts. Mark Cuban just said something every young person should hear. AI agents are going to run through every small and mid-size business in the country. Not a single one of those owners will know how to build them. His advice: learn Claude. Learn agentic workflows. Just learn AI and how it works. Then go to these businesses and help them — because they won't know how to do any of this. They have money to spend. They have deep problems. They don't have you. But first you need to know how to build agents. This is the complete course ↓ Bookmark this. This is the opportunity.
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This is nuts. Mark Cuban just said something every young person should hear. AI agents are going to run through every small and mid-size business in the country. Not a single one of those owners will know how to build them. His advice: learn Claude. Learn agentic workflows. Just learn AI and how it works. Then go to these businesses and help them — because they won't know how to do any of this. They have money to spend. They have deep problems. They don't have you. But first you need to know how to build agents. This is the complete course ↓ Bookmark this. This is the opportunity.

Rahul

1,273,696 次观看 • 15 天前

🚨 this chinese guy makes over $1,000,000 a year… by building AI agents. no employees. no massive startup. he just keeps building. while most people are still asking ChatGPT random questions, he’s using Claude to build software that solves real problems. this is what people call vibe coding. he opens Claude and says: “build me an AI agent for real estate businesses that creates property videos.” Claude writes the code. builds the interface. adds subscriptions. helps deploy the app. within a day, he has a working product. then he starts building the next one. that’s the part most people don’t understand. he isn’t trying to build one billion-dollar company. he’s building dozens of AI agents, each solving one problem for one industry. → an AI agent for dentists → an AI agent for ecommerce brands → an AI agent for podcasters → an AI agent for real estate businesses each one automates work that people normally do by hand. each one is built with simple prompts. each one can become a real business. the crazy part? you don’t need to be a software engineer anymore. you need to know how to think like a builder. how to spot problems. how to explain solutions to AI. and how to ship. that’s exactly why i’m reading this article: “How to Actually Build Your First AI Agent.” because this is the skill that’s creating the next generation of builders. the people who learn to build AI agents today won’t just use AI. they’ll own the tools everyone else ends up paying for.
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🚨 this chinese guy makes over $1,000,000 a year… by building AI agents. no employees. no massive startup. he just keeps building. while most people are still asking ChatGPT random questions, he’s using Claude to build software that solves real problems. this is what people call vibe coding. he opens Claude and says: “build me an AI agent for real estate businesses that creates property videos.” Claude writes the code. builds the interface. adds subscriptions. helps deploy the app. within a day, he has a working product. then he starts building the next one. that’s the part most people don’t understand. he isn’t trying to build one billion-dollar company. he’s building dozens of AI agents, each solving one problem for one industry. → an AI agent for dentists → an AI agent for ecommerce brands → an AI agent for podcasters → an AI agent for real estate businesses each one automates work that people normally do by hand. each one is built with simple prompts. each one can become a real business. the crazy part? you don’t need to be a software engineer anymore. you need to know how to think like a builder. how to spot problems. how to explain solutions to AI. and how to ship. that’s exactly why i’m reading this article: “How to Actually Build Your First AI Agent.” because this is the skill that’s creating the next generation of builders. the people who learn to build AI agents today won’t just use AI. they’ll own the tools everyone else ends up paying for.

MIKE

38,108 次观看 • 1 个月前

The most important AI question has nothing to do with picking the right technology. It's this: what problem are we actually trying to solve? In this IdeaCast episode, journalist and author Josh Tyrangiel makes the case that successful AI adoption comes down to discipline—pick a real, high-impact problem, follow through on it, and measure the value it creates. What you'll learn: - Why treating AI like magic sets initiatives back - How to identify the targeted problems where AI moves the needle - Practical ways to communicate change and get buy-in across an organization - Real examples from healthcare and beyond of AI creating measurable impact If your org is investing in AI, this conversation gives you a sharper way to think about where that investment should go. Listen to the full episode here:
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The most important AI question has nothing to do with picking the right technology. It's this: what problem are we actually trying to solve? In this IdeaCast episode, journalist and author Josh Tyrangiel makes the case that successful AI adoption comes down to discipline—pick a real, high-impact problem, follow through on it, and measure the value it creates. What you'll learn: - Why treating AI like magic sets initiatives back - How to identify the targeted problems where AI moves the needle - Practical ways to communicate change and get buy-in across an organization - Real examples from healthcare and beyond of AI creating measurable impact If your org is investing in AI, this conversation gives you a sharper way to think about where that investment should go. Listen to the full episode here:

Harvard Business Review

13,843 次观看 • 17 小时前

Sam Altman, CEO of OpenAI: "GPT 5.6 is 54% more efficient on agentic coding, and it's still the best on the market for half the cost." AI spend has never mattered as much as it does today. As a result the models keep getting better and cheaper at the same time. This is going to widen the gap between the people using AI agents and everyone else, because now it's not just powerful, it's cheap. That's exactly why i wrote a full step by step guide on agents, what they are and how to build your own from scratch. Read it below.
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Sam Altman, CEO of OpenAI: "GPT 5.6 is 54% more efficient on agentic coding, and it's still the best on the market for half the cost." AI spend has never mattered as much as it does today. As a result the models keep getting better and cheaper at the same time. This is going to widen the gap between the people using AI agents and everyone else, because now it's not just powerful, it's cheap. That's exactly why i wrote a full step by step guide on agents, what they are and how to build your own from scratch. Read it below.

Anatoli Kopadze

91,518 次观看 • 26 天前

Last year in Parliament, I spoke about India’s AI journey and two clear priorities. First, from Make in India to Make AI in India. Build our own capability, invest in research, and strengthen the infrastructure and compute we need to compete. Second, make advanced generative AI tools accessible and affordable for every Indian, in every language, so that no one is left behind. It is good to see AI back at the centre of national conversation as India hosts key discussions on its future. Now the focus must shift from intent to implementation. If we expand access and build with ambition, India can move from being a technology user to a technology leader. The question is not whether AI will shape the future. The question is whether India will help define it.
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Last year in Parliament, I spoke about India’s AI journey and two clear priorities. First, from Make in India to Make AI in India. Build our own capability, invest in research, and strengthen the infrastructure and compute we need to compete. Second, make advanced generative AI tools accessible and affordable for every Indian, in every language, so that no one is left behind. It is good to see AI back at the centre of national conversation as India hosts key discussions on its future. Now the focus must shift from intent to implementation. If we expand access and build with ambition, India can move from being a technology user to a technology leader. The question is not whether AI will shape the future. The question is whether India will help define it.

Raghav Chadha

112,311 次观看 • 5 个月前

Is your AI infrastructure ready for the agentic era? At Cisco Live, I connected with Gordon Macintosh and Dale Tucker from Equinix, Inc. to explore how the Secure AI Factory ecosystem is building the physical and interconnection foundations that make agentic AI at scale possible. Three thing leaders are still overlooking: → Distributed infrastructure. Production AI = multiple agents, tools, data sources, and policies → Data gravity is real. Sovereignty, regulation, and sensitivity shape where AI can run. → Last mile connectivity is where strategies stall. Secure, predictable, low-latency connections aren't optional at production scale. The Cisco + NVIDIA + Equinix, Inc. reference architecture is one of the most concrete answers I've seen with Equinix as the neutral landing zone across 280+ data centers worldwide. As Dale put it: "Last mile connectivity is where AI strategy can either accelerate or stall." The companies that win the next phase of AI will be the ones who got the infrastructure and the ecosystem right. Watch our full conversation here: #CiscoLive #SecureAIFactory #EquinixPartner #CiscoPartner
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Is your AI infrastructure ready for the agentic era? At Cisco Live, I connected with Gordon Macintosh and Dale Tucker from Equinix, Inc. to explore how the Secure AI Factory ecosystem is building the physical and interconnection foundations that make agentic AI at scale possible. Three thing leaders are still overlooking: → Distributed infrastructure. Production AI = multiple agents, tools, data sources, and policies → Data gravity is real. Sovereignty, regulation, and sensitivity shape where AI can run. → Last mile connectivity is where strategies stall. Secure, predictable, low-latency connections aren't optional at production scale. The Cisco + NVIDIA + Equinix, Inc. reference architecture is one of the most concrete answers I've seen with Equinix as the neutral landing zone across 280+ data centers worldwide. As Dale put it: "Last mile connectivity is where AI strategy can either accelerate or stall." The companies that win the next phase of AI will be the ones who got the infrastructure and the ecosystem right. Watch our full conversation here: #CiscoLive #SecureAIFactory #EquinixPartner #CiscoPartner

Helen Yu

11,558 次观看 • 1 个月前

Are we witnessing the AI vs. Memes flippening? AI is booming, and altcoins are gaining momentum. According to our data, the surge of attention toward AI began roughly a week ago. As shown in our app, AI-related metrics have now surpassed memes. Check it out in our app: With the recent resurgence of #Ethereum, AI projects are seeing significant growth. Combined with a rise in the altcoin market cap and a strengthening Altcoin Season Index, the first clear and confirmed signs of this shift are here. This is no longer speculation—AI is back in the spotlight. What's your AI Prediction? Is it going to be the lead narrative for #Altcoin run? Or is it an another sector? #ai #memecoins #eth $ETH $SPECT
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Are we witnessing the AI vs. Memes flippening? AI is booming, and altcoins are gaining momentum. According to our data, the surge of attention toward AI began roughly a week ago. As shown in our app, AI-related metrics have now surpassed memes. Check it out in our app: With the recent resurgence of #Ethereum, AI projects are seeing significant growth. Combined with a rise in the altcoin market cap and a strengthening Altcoin Season Index, the first clear and confirmed signs of this shift are here. This is no longer speculation—AI is back in the spotlight. What's your AI Prediction? Is it going to be the lead narrative for #Altcoin run? Or is it an another sector? #ai #memecoins #eth $ETH $SPECT

SPECTRE AI

17,388 次观看 • 1 年前

AI is transforming the way businesses operate 🤖. It’s no longer just a tool, it powers decision-making, efficiency, and growth. From automating tasks to predicting trends and uncovering insights, AI is becoming the backbone of modern business. But AI isn’t magic. It needs massive amounts of high-quality data 📊. Companies like Scale AI and other Web2 giants thrive because they control the pipelines of this data, turning it into a huge competitive advantage. The problem is most of this data is locked in centralized systems 🔒, expensive, and often inaccessible for smaller companies or innovators. That’s where OORT | The Data Cloud for Decentralized AI comes in 🌐✨. By building decentralized storage and AI infrastructure, OORTECH makes data open, secure, and accessible to everyone. It’s a foundation for the next generation of AI-powered businesses, giving all innovators the chance to compete and create 🚀
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AI is transforming the way businesses operate 🤖. It’s no longer just a tool, it powers decision-making, efficiency, and growth. From automating tasks to predicting trends and uncovering insights, AI is becoming the backbone of modern business. But AI isn’t magic. It needs massive amounts of high-quality data 📊. Companies like Scale AI and other Web2 giants thrive because they control the pipelines of this data, turning it into a huge competitive advantage. The problem is most of this data is locked in centralized systems 🔒, expensive, and often inaccessible for smaller companies or innovators. That’s where OORT | The Data Cloud for Decentralized AI comes in 🌐✨. By building decentralized storage and AI infrastructure, OORTECH makes data open, secure, and accessible to everyone. It’s a foundation for the next generation of AI-powered businesses, giving all innovators the chance to compete and create 🚀

Sky Wee

67,555 次观看 • 10 个月前

The paradigm shift is here: We are moving from a "Human-First" internet to an "Agent-First" internet. 🤖 In the latest episode of the AI on Air podcast, our CTO Scott Shi - e/acc dives deep into the future of the Agent-to-Agent (A2A) economy. Imagine a world where your AI assistant doesn't just search the web, but autonomously hires and pays other specialized agents to complete complex tasks for you. The infrastructure for this autonomous machine economy is being built right now. Are you ready for the future of AI payments? Watch the full episode to learn more⬇️
2:30

The paradigm shift is here: We are moving from a "Human-First" internet to an "Agent-First" internet. 🤖 In the latest episode of the AI on Air podcast, our CTO Scott Shi - e/acc dives deep into the future of the Agent-to-Agent (A2A) economy. Imagine a world where your AI assistant doesn't just search the web, but autonomously hires and pays other specialized agents to complete complex tasks for you. The infrastructure for this autonomous machine economy is being built right now. Are you ready for the future of AI payments? Watch the full episode to learn more⬇️

KITE AI

25,038 次观看 • 5 个月前

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)
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Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Rohan Paul

16,584 次观看 • 2 个月前

Anthropic co-founder Jack Clark says the AI frontier is about to cross a much stranger line than coding assistants. "My prediction is by the end of 2028, it's more likely than not that we have an AI system where you would be able to say to it, 'Make a better version of yourself.' And it just goes off and does that completely autonomously." The reason: models have moved from basic coding into "the production of science itself" and the "unglamorous but fundamental engineering work" behind large-scale R&D. "An AI system that can build itself [has] big implications, and we'd like to start thinking about it now." That is the actual agent threshold: not demos, not chat UX, but AI becoming part of the loop that improves AI.
1:02

Anthropic co-founder Jack Clark says the AI frontier is about to cross a much stranger line than coding assistants. "My prediction is by the end of 2028, it's more likely than not that we have an AI system where you would be able to say to it, 'Make a better version of yourself.' And it just goes off and does that completely autonomously." The reason: models have moved from basic coding into "the production of science itself" and the "unglamorous but fundamental engineering work" behind large-scale R&D. "An AI system that can build itself [has] big implications, and we'd like to start thinking about it now." That is the actual agent threshold: not demos, not chat UX, but AI becoming part of the loop that improves AI.

Karl Mehta

208,701 次观看 • 1 个月前

If I were 25 today, I’d focus on two massive opportunities: AI implementation and data center development. Small businesses are desperate to adopt AI but need help executing it—that’s your chance to step in and solve a huge pain point. And data centers? The demand is off the charts. Real estate meets tech in the most lucrative way. This is where the future’s heading, Don’t miss it. #AI #investment #advice
1:25

If I were 25 today, I’d focus on two massive opportunities: AI implementation and data center development. Small businesses are desperate to adopt AI but need help executing it—that’s your chance to step in and solve a huge pain point. And data centers? The demand is off the charts. Real estate meets tech in the most lucrative way. This is where the future’s heading, Don’t miss it. #AI #investment #advice

Kevin O'Leary aka Mr. Wonderful

1,184,639 次观看 • 1 年前

60% of companies expect to be transformed by AI within two years. But here's the reality: most are still bolting AI onto legacy workflows instead of reimagining how work gets done. That's not transformation—that's just expensive automation. Our latest research reveals what separates AI leaders from laggards. The companies winning with AI aren't just adopting new tools—they're redesigning how their business creates value from the ground up. The challenge: Most organizations are nowhere near putting AI at the center of their strategy. They're missing the exponential gains that come from true AI-first thinking. The solution: A complete playbook for IT leaders and CIOs ready to move at the speed of AI. 🎯 5 Core Principles of AI-First Companies: 1️⃣ AI as a capability expander — Enable work that wasn't possible before, not just faster versions of old tasks 2️⃣ Human-AI partnership — Augment human creativity and decision-making rather than replacing it 3️⃣ AI-native design — Build systems that seamlessly integrate thousands of AI agents working behind the scenes 4️⃣ Trust & governance foundation — Remember: "AI agents can't keep a secret"—never rely on AI to maintain core security models. 5️⃣ Data as strategic fuel — Transform unstructured content into your competitive advantage The companies implementing these principles today are building insurmountable competitive advantages. They're not just working faster—they're working in entirely new ways. Ready to lead your industry's AI transformation? 📖 Get the complete framework Want to explore the benefits? Get the full details here:
0:21

60% of companies expect to be transformed by AI within two years. But here's the reality: most are still bolting AI onto legacy workflows instead of reimagining how work gets done. That's not transformation—that's just expensive automation. Our latest research reveals what separates AI leaders from laggards. The companies winning with AI aren't just adopting new tools—they're redesigning how their business creates value from the ground up. The challenge: Most organizations are nowhere near putting AI at the center of their strategy. They're missing the exponential gains that come from true AI-first thinking. The solution: A complete playbook for IT leaders and CIOs ready to move at the speed of AI. 🎯 5 Core Principles of AI-First Companies: 1️⃣ AI as a capability expander — Enable work that wasn't possible before, not just faster versions of old tasks 2️⃣ Human-AI partnership — Augment human creativity and decision-making rather than replacing it 3️⃣ AI-native design — Build systems that seamlessly integrate thousands of AI agents working behind the scenes 4️⃣ Trust & governance foundation — Remember: "AI agents can't keep a secret"—never rely on AI to maintain core security models. 5️⃣ Data as strategic fuel — Transform unstructured content into your competitive advantage The companies implementing these principles today are building insurmountable competitive advantages. They're not just working faster—they're working in entirely new ways. Ready to lead your industry's AI transformation? 📖 Get the complete framework Want to explore the benefits? Get the full details here:

Box

128,566 次观看 • 1 年前

We're winning the AI browser wars, and we're not even trying. Our mission isn't to build a browser. We're an agent company, not a browser company. We've seen firsthand how teams struggle to get started with AI. The tools they tried are too complex and lack the context you need. We decided to build a browser since it's already the tool you work in. We all know how to use a browser. You can pick up Strawberry and start using AI agents from day one. By building a browser we are also positioning ourselves to build towards the internet of the future. An internet where trillions of agents will be communicating with each other. This is the biggest opportunity of our lifetime. But someone has to make sure it is safe, effective and accessible to teams across the world. That is our mission.
0:52

We're winning the AI browser wars, and we're not even trying. Our mission isn't to build a browser. We're an agent company, not a browser company. We've seen firsthand how teams struggle to get started with AI. The tools they tried are too complex and lack the context you need. We decided to build a browser since it's already the tool you work in. We all know how to use a browser. You can pick up Strawberry and start using AI agents from day one. By building a browser we are also positioning ourselves to build towards the internet of the future. An internet where trillions of agents will be communicating with each other. This is the biggest opportunity of our lifetime. But someone has to make sure it is safe, effective and accessible to teams across the world. That is our mission.

Charles Maddock

38,357 次观看 • 1 个月前

The AI boom just hit a wall nobody saw coming. And it's not software. It's not regulation. It's not even energy... It's memory chips. Right now, Dell is raising PC prices by 30%. Intel can't ship chips. Nvidia is slashing GPU production by 40%. And almost nobody understands why. Here's the "hidden" crisis the AI industry is trying to hide: AI data centers are hoarding memory. Not GPUs. Not processors. MEMORY. Every AI server needs massive amounts of high-bandwidth memory (HBM) to run those models everyone's hyping. One problem: There are only 3 companies in the world that can make it. Samsung. SK Hynix. Micron. That's it. And all 3 just diverted their entire production capacity away from normal RAM to feed AI data centers. The math that breaks everything: 1 gigabyte of HBM takes 4X the manufacturing capacity of regular DRAM. AI will consume 20% of global DRAM production in 2026. But the thing is, consumer demand for RAM didn't disappear. PCs still need memory. Phones still need memory. Cars still need memory. But there's no capacity left to make it. The price explosion: RAM prices are up 246% in the last 6 months. DDR5 contract prices jumped 100% month-over-month in some cases. Dell's CFO said he's "never witnessed costs escalating at this pace." SK Hynix and Micron? Sold out through all of 2026. Micron straight up EXITED the consumer memory market entirely to focus on AI customers. If you're not building an AI data center, you're not getting memory chips. AI data centers pay 3-5X margins compared to consumer products. So memory manufacturers are rationally choosing: Serve Microsoft and Google's AI buildout, or serve Dell's laptop business? Easy choice. Every wafer allocated to an Nvidia H100 GPU is a wafer DENIED to your next laptop. It's a zero-sum game. And consumers are losing. The dangerous cascade effect: Nvidia is cutting RTX 50-series GPU production by 30-40% because they can't get GDDR7 memory. Dell, Lenovo, HP are all raising PC prices 15-30% in early 2026. Xiaomi and other smartphone makers are cutting shipment targets. Even Intel's crash last week? Partially driven by memory shortages limiting chip production. This is a PERMANENT reallocation of the world's silicon capacity. Not a temporary supply hiccup. For decades, consumer electronics (phones, PCs, laptops) drove memory production. Now? AI data centers are the priority customer. And that priority shift is reshaping the entire tech economy. The timeline Is worse than you think: Industry analysts project shortages lasting through 2027, maybe 2028. Why? Because building new memory fabs takes 3-5 YEARS. Micron's new Idaho fab won't meaningfully impact supply until 2028. Samsung and SK Hynix are too busy ramping up HBM4 production to expand consumer DRAM. So we're stuck. AI companies need memory to scale. But producing that memory DESTROYS the supply chain for everything else. My question here: Everyone's betting on AI scaling infinitely. But what if the AI boom STALLS because there's not enough memory to support it? What if we're not in an "AI supercycle" but a "memory shortage that kills the AI buildout"? Intel crashed 17% because they can't manufacture enough chips. The root cause though? Memory shortages limiting what they can even produce. Nvidia is cutting GPU production by 40%. AMD is struggling to get GDDR6 for Radeon cards. This isn't just a consumer problem. It's an AI infrastructure problem. And if memory doesn't scale, AI doesn't scale. The AI industry sold you on infinite scaling. But they forgot to mention the part where there's only 3 companies making the memory chips that power everything. And all 3 just chose AI data centers over you. Even Nvidia can't make enough GPUs to meet demand. Not because of energy. Not because of regulation... But because the memory supply chain is BROKEN. And it won't be fixed until 2028.
0:58

The AI boom just hit a wall nobody saw coming. And it's not software. It's not regulation. It's not even energy... It's memory chips. Right now, Dell is raising PC prices by 30%. Intel can't ship chips. Nvidia is slashing GPU production by 40%. And almost nobody understands why. Here's the "hidden" crisis the AI industry is trying to hide: AI data centers are hoarding memory. Not GPUs. Not processors. MEMORY. Every AI server needs massive amounts of high-bandwidth memory (HBM) to run those models everyone's hyping. One problem: There are only 3 companies in the world that can make it. Samsung. SK Hynix. Micron. That's it. And all 3 just diverted their entire production capacity away from normal RAM to feed AI data centers. The math that breaks everything: 1 gigabyte of HBM takes 4X the manufacturing capacity of regular DRAM. AI will consume 20% of global DRAM production in 2026. But the thing is, consumer demand for RAM didn't disappear. PCs still need memory. Phones still need memory. Cars still need memory. But there's no capacity left to make it. The price explosion: RAM prices are up 246% in the last 6 months. DDR5 contract prices jumped 100% month-over-month in some cases. Dell's CFO said he's "never witnessed costs escalating at this pace." SK Hynix and Micron? Sold out through all of 2026. Micron straight up EXITED the consumer memory market entirely to focus on AI customers. If you're not building an AI data center, you're not getting memory chips. AI data centers pay 3-5X margins compared to consumer products. So memory manufacturers are rationally choosing: Serve Microsoft and Google's AI buildout, or serve Dell's laptop business? Easy choice. Every wafer allocated to an Nvidia H100 GPU is a wafer DENIED to your next laptop. It's a zero-sum game. And consumers are losing. The dangerous cascade effect: Nvidia is cutting RTX 50-series GPU production by 30-40% because they can't get GDDR7 memory. Dell, Lenovo, HP are all raising PC prices 15-30% in early 2026. Xiaomi and other smartphone makers are cutting shipment targets. Even Intel's crash last week? Partially driven by memory shortages limiting chip production. This is a PERMANENT reallocation of the world's silicon capacity. Not a temporary supply hiccup. For decades, consumer electronics (phones, PCs, laptops) drove memory production. Now? AI data centers are the priority customer. And that priority shift is reshaping the entire tech economy. The timeline Is worse than you think: Industry analysts project shortages lasting through 2027, maybe 2028. Why? Because building new memory fabs takes 3-5 YEARS. Micron's new Idaho fab won't meaningfully impact supply until 2028. Samsung and SK Hynix are too busy ramping up HBM4 production to expand consumer DRAM. So we're stuck. AI companies need memory to scale. But producing that memory DESTROYS the supply chain for everything else. My question here: Everyone's betting on AI scaling infinitely. But what if the AI boom STALLS because there's not enough memory to support it? What if we're not in an "AI supercycle" but a "memory shortage that kills the AI buildout"? Intel crashed 17% because they can't manufacture enough chips. The root cause though? Memory shortages limiting what they can even produce. Nvidia is cutting GPU production by 40%. AMD is struggling to get GDDR6 for Radeon cards. This isn't just a consumer problem. It's an AI infrastructure problem. And if memory doesn't scale, AI doesn't scale. The AI industry sold you on infinite scaling. But they forgot to mention the part where there's only 3 companies making the memory chips that power everything. And all 3 just chose AI data centers over you. Even Nvidia can't make enough GPUs to meet demand. Not because of energy. Not because of regulation... But because the memory supply chain is BROKEN. And it won't be fixed until 2028.

Ricardo

594,643 次观看 • 6 个月前

The AI business model is undergoing a transformation. For the last few years, the playbook was simple: put an AI wrapper on a SaaS product and sell it by the seat. That era is ending. The new wave of AI companies are moving beyond simple subscriptions and embracing a more sophisticated approach tied directly to value creation. Here’s what’s changing: 💰 From Seats to Spend: The most forward-thinking companies are shifting to usage-based and outcome-driven pricing. Think less about how many people use the AI and more about what the AI does. This includes new revenue streams like "agentic checkout" on ChatGPT, where AI agents complete purchases and transactions directly within a chat interface. The closer the AI is to the dollar, the more value it captures. 🎙️ From Text to Voice & Video: The interface for AI is becoming more human. Voice is mainstream (Sierra for support, Listen Labs for market research). The next frontier is video, where AI will see, understand, and interact with the world in real-time. The keyboard is no longer the only way to talk to a machine. 🤖 From Advisors to Actors: Early AI copilots gave advice. The next generation takes action. These agents aren't just suggesting what to do; they are executing complex workflows that directly impact the metrics that matter: boosting conversion, reducing average handle time (AHT), improving NPS, and cutting churn. This is about moving from passive assistance to active problem-solving. The common thread? A relentless focus on tangible ROI. We’re incredibly bullish on founders who understand this shift and are building companies that align their success with the success of their customers. The future of AI isn't just about intelligence; it's about impact.
1:28

The AI business model is undergoing a transformation. For the last few years, the playbook was simple: put an AI wrapper on a SaaS product and sell it by the seat. That era is ending. The new wave of AI companies are moving beyond simple subscriptions and embracing a more sophisticated approach tied directly to value creation. Here’s what’s changing: 💰 From Seats to Spend: The most forward-thinking companies are shifting to usage-based and outcome-driven pricing. Think less about how many people use the AI and more about what the AI does. This includes new revenue streams like "agentic checkout" on ChatGPT, where AI agents complete purchases and transactions directly within a chat interface. The closer the AI is to the dollar, the more value it captures. 🎙️ From Text to Voice & Video: The interface for AI is becoming more human. Voice is mainstream (Sierra for support, Listen Labs for market research). The next frontier is video, where AI will see, understand, and interact with the world in real-time. The keyboard is no longer the only way to talk to a machine. 🤖 From Advisors to Actors: Early AI copilots gave advice. The next generation takes action. These agents aren't just suggesting what to do; they are executing complex workflows that directly impact the metrics that matter: boosting conversion, reducing average handle time (AHT), improving NPS, and cutting churn. This is about moving from passive assistance to active problem-solving. The common thread? A relentless focus on tangible ROI. We’re incredibly bullish on founders who understand this shift and are building companies that align their success with the success of their customers. The future of AI isn't just about intelligence; it's about impact.

Konstantine Buhler

24,887 次观看 • 9 个月前