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BREAKING: Merge Launches ‘Agent Handler’ Control AI Access, Tokenmaxxed $$$ Bills, & Stop Mass Data Leaks "We don't trust agents" "The second you connect it to tools, that's where everything goes wrong." OpenAI. Perplexity. Netflix. Uber. Mistral. Dropbox. JPMorgan.. all quietly run on Merge Co-Founders CEO Shensi Ding Ding...

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Molly O’Shea

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111,465 просмотров • 2 месяцев назад •via X (Twitter)

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One of the most foundational things is the Economic Singularity and the fact that you have ~5 years to unfuck your future... The world will change dramatically by 2030, and we don't have much time left to build wealth! Can't stress enough how important this is... the apex of everything I'm doing.... Enjoy! Timestamps: 00:00 Intro 00:48 2030 Will Change Everything 01:41 Retirement Crisis Looms 03:02 AI & Robots Take Over 03:54 The GDP Formula 04:45 Demographics Collapse 06:27 Robots Replace Labor 07:34 AI Disrupts Knowledge 08:19 From Scarcity to Abundance 09:06 Cheap Energy Boom 10:21 Renewables & Grids 11:43 Nuclear = Free Power 12:45 Infinite Humans + Output 13:50 AI Agents + Crypto 14:58 AI Builds Products Fast 15:41 1-Person Billionaires 16:41 AGI vs. Markets 17:54 Universal Basic Equity 19:10 Adapt or Die 20:47 Human-AI Merge 22:58 Tech & Blockchain Win 25:42 Communities Win 26:31 Deflation Shock 27:48 AI Solves Itself 28:38 RV’s AI & Blockchain Plan 30:14 Human-Safe Industries 31:23 AI Companions Rise 35:00 Closing Thoughts
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One of the most foundational things is the Economic Singularity and the fact that you have ~5 years to unfuck your future... The world will change dramatically by 2030, and we don't have much time left to build wealth! Can't stress enough how important this is... the apex of everything I'm doing.... Enjoy! Timestamps: 00:00 Intro 00:48 2030 Will Change Everything 01:41 Retirement Crisis Looms 03:02 AI & Robots Take Over 03:54 The GDP Formula 04:45 Demographics Collapse 06:27 Robots Replace Labor 07:34 AI Disrupts Knowledge 08:19 From Scarcity to Abundance 09:06 Cheap Energy Boom 10:21 Renewables & Grids 11:43 Nuclear = Free Power 12:45 Infinite Humans + Output 13:50 AI Agents + Crypto 14:58 AI Builds Products Fast 15:41 1-Person Billionaires 16:41 AGI vs. Markets 17:54 Universal Basic Equity 19:10 Adapt or Die 20:47 Human-AI Merge 22:58 Tech & Blockchain Win 25:42 Communities Win 26:31 Deflation Shock 27:48 AI Solves Itself 28:38 RV’s AI & Blockchain Plan 30:14 Human-Safe Industries 31:23 AI Companions Rise 35:00 Closing Thoughts

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Every agent needs its own computer: my conversation with Ivan Burazin, CEO of Daytona, about sandboxes and the emerging agent stack. 00:00 Intro 02:13 What is an AI agent sandbox? 03:17 Security risks of running agents locally 05:17 Stateful vs. stateless hyperscalers 07:04 The history of cloud IDEs and the end of localhost 09:45 Do all AI agents need a sandbox? 12:26 Sandbox use cases: RL evals & background agents 14:10 Unpacking the emerging AI Agent Stack 16:20 The unsolved problem of agent memory and learning 19:37 Where sandboxes fit in the agent harness 21:35 OpenAI, Anthropic, and agent SDKs 23:06 Ivan's founder journey: From CodeAnywhere to Daytona 26:59 GTM strategies and building developer communities 33:48 Why customer support is your best GTM strategy 35:34 Leveraging Twitter during the AI super cycle 40:50 The technical anatomy of a sandbox 41:53 Why fast spin-up speeds maximize GPU efficiency 46:09 Firecracker, QEMU, and isolation primitives 49:58 Why sandbox snapshots and state forking matter 51:40 Why Daytona built a custom scheduler from scratch 55:24 The challenge of long-running stateful sandboxes 58:10 The build your own sandbox trap 1:01:03 Why AI agents might trigger a global CPU shortage 1:02:46 The future of the AI Agent Stack

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E101: Virtuals Protocol : How to get Rich with AI Agents (Without Getting Lucky)! is the CoFounder of Virtuals, the leading AI Agent protocol valued at $2.5 Billion Timestamps 0:00 Intro 2:35 Mental Health 6:41 Having Optimistic Co-Founders 7:20 Post-Bull Survival Guide 10:09 Who is Wee Kee ? 10:51 Hyperliquid, an inspiration for Founders 15:21 Fascination of AI 16:56 What is an AI Game? 18:48 Crypto Gaming Narrative 21:20 Can AI Lovers Solve Loneliness? 24:33 What’s a Good AI Lover? 26:44 Solving Mental Health with AI 29:14 Why does Crypto AI Matter? 30:59 Purpose of terminal of truths & $Goat Token 33:54 Why AI Agents Matter 39:34 How aixbt Leads Crypto 43:09 The Risk of Social Coins 45:06 Replacing Humans with AI Agents 49:36 Fair Launches Reflect Crypto Values 58:20 What is Virtuals Protocol ? 1:00:56 Main Goal of Virtuals 1:02:12 What is Luna 1:05:30 Luna: AI Agents Hiring Humans 1:11:09 How AI Agents Mirror Humans 1:12:48 AI Agents Running Businesses 1:16:36 Network State & Why it Matters 1:19:24 AI Networks Bigger Than Earth 1:21:58 Human Advantage Over AI Agents 1:23:29 Does Decentralization Matter? 1:28:22 Base or Solana 1:33:49 Support from Base 1:35:13 What are Sentient Agents? 1:37:25 The Future of AI Agents 1:38:16 Non-Consensus Beliefs 1:39:54 Prediction for the Next 12 Months 1:42:52 Where is Hyperliquid Going?
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E101: Virtuals Protocol : How to get Rich with AI Agents (Without Getting Lucky)! is the CoFounder of Virtuals, the leading AI Agent protocol valued at $2.5 Billion Timestamps 0:00 Intro 2:35 Mental Health 6:41 Having Optimistic Co-Founders 7:20 Post-Bull Survival Guide 10:09 Who is Wee Kee ? 10:51 Hyperliquid, an inspiration for Founders 15:21 Fascination of AI 16:56 What is an AI Game? 18:48 Crypto Gaming Narrative 21:20 Can AI Lovers Solve Loneliness? 24:33 What’s a Good AI Lover? 26:44 Solving Mental Health with AI 29:14 Why does Crypto AI Matter? 30:59 Purpose of terminal of truths & $Goat Token 33:54 Why AI Agents Matter 39:34 How aixbt Leads Crypto 43:09 The Risk of Social Coins 45:06 Replacing Humans with AI Agents 49:36 Fair Launches Reflect Crypto Values 58:20 What is Virtuals Protocol ? 1:00:56 Main Goal of Virtuals 1:02:12 What is Luna 1:05:30 Luna: AI Agents Hiring Humans 1:11:09 How AI Agents Mirror Humans 1:12:48 AI Agents Running Businesses 1:16:36 Network State & Why it Matters 1:19:24 AI Networks Bigger Than Earth 1:21:58 Human Advantage Over AI Agents 1:23:29 Does Decentralization Matter? 1:28:22 Base or Solana 1:33:49 Support from Base 1:35:13 What are Sentient Agents? 1:37:25 The Future of AI Agents 1:38:16 Non-Consensus Beliefs 1:39:54 Prediction for the Next 12 Months 1:42:52 Where is Hyperliquid Going?

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Another mindblowing conversation with my good friend .Emad... Enjoy!! 00:00 - Introduction 00:22 - AI: The Biggest Shift in Human History 00:42 - AI’s Impact on Society and the Economy 01:03 - Conversation with Emad Mostaque Begins 01:50 - The Acceleration of AI and Economic Takeoff 03:07 - AI Intelligence: Beyond Human IQ 04:08 - The Rise of AI Chefs and Super Cooks 05:07 - Breaking AI Constraints: Compute and Energy 07:03 - The Future of AI: Ubiquitous Intelligence 08:04 - The Shift to Local AI Models 10:07 - Why Has Apple Lagged in AI? 11:21 - The AI Race: OpenAI, Grok, Gemini, and More 13:11 - China’s Open-Source AI Strategy 14:57 - AI Bias and Ethical Challenges 16:57 - AI’s Cross-Pollination and Memory 18:02 - Are AI Models Becoming Self-Aware? 19:16 - AI, Bitcoin, and Self-Sustaining Algorithms 21:26 - AI-Driven Economies and Autonomous Companies 23:41 - The Future of Labor: A World Without Jobs? 25:26 - AI-Powered Robots: The Next Workforce Revolution 27:28 - The End of Traditional Economic Models 30:27 - The Political Shift: Humanist vs. Transhumanist 33:04 - AI in Financial Markets: The End of Human Traders? 36:03 - The Evolution of Investing in an AI World 38:33 - AI’s Impact on Capital Formation and Business Disruption 40:01 - The Rise of Digital Twins and Post-Capital Society 42:45 - Building AI for Education, Healthcare, and Governance 46:42 - The Future of Money in an AI-Driven World 50:11 - Universal Basic AI: A New Economic Model 54:29 - The Deflationary Impact of AI and Crypto’s Role 57:02 - The AI Singularity: Five Years Until Everything Changes 58:56 - The Road Ahead: AI, Crypto, and the Future of Civilization 01:02:24 - Final Thoughts: The Most Exciting and Terrifying Time in History
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Another mindblowing conversation with my good friend .Emad... Enjoy!! 00:00 - Introduction 00:22 - AI: The Biggest Shift in Human History 00:42 - AI’s Impact on Society and the Economy 01:03 - Conversation with Emad Mostaque Begins 01:50 - The Acceleration of AI and Economic Takeoff 03:07 - AI Intelligence: Beyond Human IQ 04:08 - The Rise of AI Chefs and Super Cooks 05:07 - Breaking AI Constraints: Compute and Energy 07:03 - The Future of AI: Ubiquitous Intelligence 08:04 - The Shift to Local AI Models 10:07 - Why Has Apple Lagged in AI? 11:21 - The AI Race: OpenAI, Grok, Gemini, and More 13:11 - China’s Open-Source AI Strategy 14:57 - AI Bias and Ethical Challenges 16:57 - AI’s Cross-Pollination and Memory 18:02 - Are AI Models Becoming Self-Aware? 19:16 - AI, Bitcoin, and Self-Sustaining Algorithms 21:26 - AI-Driven Economies and Autonomous Companies 23:41 - The Future of Labor: A World Without Jobs? 25:26 - AI-Powered Robots: The Next Workforce Revolution 27:28 - The End of Traditional Economic Models 30:27 - The Political Shift: Humanist vs. Transhumanist 33:04 - AI in Financial Markets: The End of Human Traders? 36:03 - The Evolution of Investing in an AI World 38:33 - AI’s Impact on Capital Formation and Business Disruption 40:01 - The Rise of Digital Twins and Post-Capital Society 42:45 - Building AI for Education, Healthcare, and Governance 46:42 - The Future of Money in an AI-Driven World 50:11 - Universal Basic AI: A New Economic Model 54:29 - The Deflationary Impact of AI and Crypto’s Role 57:02 - The AI Singularity: Five Years Until Everything Changes 58:56 - The Road Ahead: AI, Crypto, and the Future of Civilization 01:02:24 - Final Thoughts: The Most Exciting and Terrifying Time in History

Raoul Pal

326,827 просмотров • 1 год назад

The end of coding? *Epic* conversation with Guillermo Rauch of Vercel on vibe coding, MCP, agents and building products in the AI era. (00:00) - Intro: Guillermo's Story (02:08) - What is v0 and Why Did It Take Off So Fast? (04:10) - Building a hit product with < people (07:51) - Cursor, Replit, etc: v0 vs Other AI Coding Tools (10:35) - Everyone can cook - What is Vibe Coding? (17:05) - Is v0 Just Frontend? Moving Toward Full Stack 19:40 - How to Become a Great Vibe Coder (23:35) - A GUI for AI: The Future of Interfaces (29:46) - Developer Love vs Agent Love (33:41) - The Importance of Taste in the AI Era (39:10) - MCP: The Protocol for AI-to-AI Communication (43:11) - Security and the Risks of Agentic Web (45:25) - Are Enterprises Ready for the Agentic Future? (49:42) - Building a Data Flywheel (56:06) - The Vercel AI Cloud: From Pixels to Tokens (1:10:14) - Adapting to a Non-Developer Persona (1:13:47) - Retention, Margins, and the Business of AI (1:16:51) - The Secret Behind Vercel Last Year Growth (1:24:15) - The importance of Online Presence (1:30:49) - Everything, Everywhere, All at Once: Keeping your Sanity as a CEO (1:34:59) - Guillermo's Advice to Younger Self
1:45:40

The end of coding? *Epic* conversation with Guillermo Rauch of Vercel on vibe coding, MCP, agents and building products in the AI era. (00:00) - Intro: Guillermo's Story (02:08) - What is v0 and Why Did It Take Off So Fast? (04:10) - Building a hit product with < people (07:51) - Cursor, Replit, etc: v0 vs Other AI Coding Tools (10:35) - Everyone can cook - What is Vibe Coding? (17:05) - Is v0 Just Frontend? Moving Toward Full Stack 19:40 - How to Become a Great Vibe Coder (23:35) - A GUI for AI: The Future of Interfaces (29:46) - Developer Love vs Agent Love (33:41) - The Importance of Taste in the AI Era (39:10) - MCP: The Protocol for AI-to-AI Communication (43:11) - Security and the Risks of Agentic Web (45:25) - Are Enterprises Ready for the Agentic Future? (49:42) - Building a Data Flywheel (56:06) - The Vercel AI Cloud: From Pixels to Tokens (1:10:14) - Adapting to a Non-Developer Persona (1:13:47) - Retention, Margins, and the Business of AI (1:16:51) - The Secret Behind Vercel Last Year Growth (1:24:15) - The importance of Online Presence (1:30:49) - Everything, Everywhere, All at Once: Keeping your Sanity as a CEO (1:34:59) - Guillermo's Advice to Younger Self

Matt Turck

86,153 просмотров • 1 год назад

Sonnet 4.5 & the AI Plateau Myth — epic conversation with Sholto Douglas of Anthropic 0:00 - Intro 1:09 - What's Behind The Rapid Pace of AI Releases at Anthropic 2:49 - Opus, Sonnet, and Haiku Model Tiers 4:14 - Sholto's Story: From Australian Fencer to AI Researcher 12:01 - The YouTube Effect: Mastery Through Observation 16:16 - Breaking Into AI Research Without Traditional Academic Signals 18:29 - DeepMind, Gemini, and Building Inference Stacks 23:05 - Why Anthropic? Culture and Mission Differences Amongst AI Research Labs 25:08 - What Is "Taste" in AI Research? 31:46 - This Week's Big Launch: Sonnet 4.5, Best Coding Model in the World 36:40 - From 7 Hours to 30 Hours: The Long-Running AI Agent Breakthrough 38:41 - How AI Agents Self-Correct and Maintain Coherence 43:13 - The Role of Memory in Extended Coding Sessions 47:42 - Pre-Training vs. RL: Textbooks vs. Worked Problems 52:11 - Test-Time Compute & Reinforcement Learning 55:55 - Why RL Finally Started Working on LLMs in 2024 59:38 - The Path to AGI 1:02:05 - Are We Hitting a Plateau in AI? So Many Low Hanging Fruits 1:03:41 - Beyond Coding: GDPVal & Impact Economic Sectors 1:05:47 - Preparing for 10-100x Individual Leverage & The Upcoming Robotics Explosion
1:10:03

Sonnet 4.5 & the AI Plateau Myth — epic conversation with Sholto Douglas of Anthropic 0:00 - Intro 1:09 - What's Behind The Rapid Pace of AI Releases at Anthropic 2:49 - Opus, Sonnet, and Haiku Model Tiers 4:14 - Sholto's Story: From Australian Fencer to AI Researcher 12:01 - The YouTube Effect: Mastery Through Observation 16:16 - Breaking Into AI Research Without Traditional Academic Signals 18:29 - DeepMind, Gemini, and Building Inference Stacks 23:05 - Why Anthropic? Culture and Mission Differences Amongst AI Research Labs 25:08 - What Is "Taste" in AI Research? 31:46 - This Week's Big Launch: Sonnet 4.5, Best Coding Model in the World 36:40 - From 7 Hours to 30 Hours: The Long-Running AI Agent Breakthrough 38:41 - How AI Agents Self-Correct and Maintain Coherence 43:13 - The Role of Memory in Extended Coding Sessions 47:42 - Pre-Training vs. RL: Textbooks vs. Worked Problems 52:11 - Test-Time Compute & Reinforcement Learning 55:55 - Why RL Finally Started Working on LLMs in 2024 59:38 - The Path to AGI 1:02:05 - Are We Hitting a Plateau in AI? So Many Low Hanging Fruits 1:03:41 - Beyond Coding: GDPVal & Impact Economic Sectors 1:05:47 - Preparing for 10-100x Individual Leverage & The Upcoming Robotics Explosion

Matt Turck

93,678 просмотров • 10 месяцев назад

Why AI Can Now Make Discoveries - my conversation with Dan Roberts, Lead of the Foundations of Reinforcement Learning team at OpenAI 00:00 Intro: AI's wild week in mathematics 01:21 What OpenAI's Foundations of RL team does 03:08 Dan's journey: from black holes and quantum gravity to frontier AI 07:04 Are AI systems becoming useful for real science 08:21 The AI math moment: Erdős, OpenAI, DeepMind, and Anthropic 08:52 Why the OpenAI result was an act of exploration 10:25 OpenAI vs. DeepMind: informal reasoning vs. formal proof 12:13 RL 101: learning by doing, not just watching 15:10 Why reinforcement learning works 15:58 How RL breaks: sparse feedback and long-horizon tasks 17:03 RLHF: how human feedback shaped early language models 18:48 Move 37, self-play, and the search for novel strategies 22:16 Explore vs. exploit in scientific discovery 24:49 Why RL may now be "the cake," not the cherry on top 25:46 Why RL started working with large language models 27:29 Is RL "sucking supervision through a straw"? 28:47 Why language may be the grounding layer for intelligence 31:46 A contrarian take on the Bitter Lesson 32:41 What test-time compute actually is 34:50 How RL gives models the ability to think 35:40 Verifiable rewards, math, coding, and the messy real world 38:00 What physics can teach us about AI 42:08 Is there a thermodynamics of AI? 43:08 From Erdős problems to Einstein-level AI 45:16 Is AI already doing original science? 45:51 How far are we from AI automating AI research 47:41 Why Dan is excited about the future of science
49:06

Why AI Can Now Make Discoveries - my conversation with Dan Roberts, Lead of the Foundations of Reinforcement Learning team at OpenAI 00:00 Intro: AI's wild week in mathematics 01:21 What OpenAI's Foundations of RL team does 03:08 Dan's journey: from black holes and quantum gravity to frontier AI 07:04 Are AI systems becoming useful for real science 08:21 The AI math moment: Erdős, OpenAI, DeepMind, and Anthropic 08:52 Why the OpenAI result was an act of exploration 10:25 OpenAI vs. DeepMind: informal reasoning vs. formal proof 12:13 RL 101: learning by doing, not just watching 15:10 Why reinforcement learning works 15:58 How RL breaks: sparse feedback and long-horizon tasks 17:03 RLHF: how human feedback shaped early language models 18:48 Move 37, self-play, and the search for novel strategies 22:16 Explore vs. exploit in scientific discovery 24:49 Why RL may now be "the cake," not the cherry on top 25:46 Why RL started working with large language models 27:29 Is RL "sucking supervision through a straw"? 28:47 Why language may be the grounding layer for intelligence 31:46 A contrarian take on the Bitter Lesson 32:41 What test-time compute actually is 34:50 How RL gives models the ability to think 35:40 Verifiable rewards, math, coding, and the messy real world 38:00 What physics can teach us about AI 42:08 Is there a thermodynamics of AI? 43:08 From Erdős problems to Einstein-level AI 45:16 Is AI already doing original science? 45:51 How far are we from AI automating AI research 47:41 Why Dan is excited about the future of science

Matt Turck

66,559 просмотров • 2 месяцев назад

⚫️ UNCANNY VALLEY: THE AI CLASSROOM REVOLUTION: ARE TEACHERS READY? What if AI isn’t just disrupting education… but detonating it? Ethan Mollick, Professor at The Wharton School, joins Dr Danish for one of the most explosive Uncanny Valley episodes, lifting the lid on how classrooms are collapsing, colleges are scrambling, and apprenticeships are vanishing in real time. From AI tutors replacing professors to the rise of one-person unicorns, this isn’t just a change in learning…it’s a reset of work, meaning, and what it even takes to succeed. This episode doesn’t ask whether AI will change education. It shows you how it already has. Fridays at 4:20PM ET. Only on 𝕏. 00:18 – Is AI destroying school, or forcing us to teach better? 01:13 – “100% they’re cheating.” The honesty about academic dishonesty. 02:41 – Why good pedagogy still matters—even with AI tutors. 03:51 – Elon Musk says college is obsolete. Is he right — or just early? 05:01 – “AI gives you the answer—but you don’t learn.” The Turkey study. 06:31 – From calculators to GPT: How cheating evolves—and what to do. 08:24 – What the flipped AI-powered classroom of the future looks like. 09:23 – Inside Ethan’s Wharton classes: Simulations, games, and AI everywhere. 10:09 – “AI is an always-on tutor.” What humans still do better. 11:08 – Can AI actually launch a company? Where Ethan draws the line. 12:44 – “AI cofounder” is real, but jagged edges still slow it down. 14:07 – Why bad ideas fail faster when filtered through AI. 15:45 – Confidence vs. capability: the psychology of starting up. 16:51 – The average founder is 42. What that really means for AI. 18:04 – Will a flood of new entrepreneurs fix—or break—the market? 19:50 – AI as advisor: How a chatbot could help your catering business. 21:37 – Why most Americans are founders-in-waiting—and AI unlocks them. 22:30 – Prototyping is cracked. Scaling? Not yet. 24:33 – Youth unemployment and the collapse of on-the-job learning. 25:51 – “The apprenticeship model is broken.” And how to fix it. 27:06 – Losing the talent pipeline — and why companies must step up. 28:22 – Why the youth don’t want factory jobs—and shouldn’t. 29:26 – Is AGI inevitable—or just imagined? 31:07 – What should we teach our kids? The answer might scare you. 32:27 – Bundled jobs, fragmented futures: how humans stay relevant. 33:59 – The real singularity? When we can’t predict what happens next. 35:25 – The AI assumption no one wants to question. 36:55 – What are agents, really? Why no one agrees on the definition. 37:55 – Co-intelligence vs. substitution: what agents skip over. 38:50 – Plain-English goals, rogue pricing, and collusion-by-default. 40:02 – Nested agents are here, and Wharton’s building them. 40:58 – Management > Coding: What great prompters actually do. 41:12 – Product managers might be more vital than ever.
42:02

⚫️ UNCANNY VALLEY: THE AI CLASSROOM REVOLUTION: ARE TEACHERS READY? What if AI isn’t just disrupting education… but detonating it? Ethan Mollick, Professor at The Wharton School, joins Dr Danish for one of the most explosive Uncanny Valley episodes, lifting the lid on how classrooms are collapsing, colleges are scrambling, and apprenticeships are vanishing in real time. From AI tutors replacing professors to the rise of one-person unicorns, this isn’t just a change in learning…it’s a reset of work, meaning, and what it even takes to succeed. This episode doesn’t ask whether AI will change education. It shows you how it already has. Fridays at 4:20PM ET. Only on 𝕏. 00:18 – Is AI destroying school, or forcing us to teach better? 01:13 – “100% they’re cheating.” The honesty about academic dishonesty. 02:41 – Why good pedagogy still matters—even with AI tutors. 03:51 – Elon Musk says college is obsolete. Is he right — or just early? 05:01 – “AI gives you the answer—but you don’t learn.” The Turkey study. 06:31 – From calculators to GPT: How cheating evolves—and what to do. 08:24 – What the flipped AI-powered classroom of the future looks like. 09:23 – Inside Ethan’s Wharton classes: Simulations, games, and AI everywhere. 10:09 – “AI is an always-on tutor.” What humans still do better. 11:08 – Can AI actually launch a company? Where Ethan draws the line. 12:44 – “AI cofounder” is real, but jagged edges still slow it down. 14:07 – Why bad ideas fail faster when filtered through AI. 15:45 – Confidence vs. capability: the psychology of starting up. 16:51 – The average founder is 42. What that really means for AI. 18:04 – Will a flood of new entrepreneurs fix—or break—the market? 19:50 – AI as advisor: How a chatbot could help your catering business. 21:37 – Why most Americans are founders-in-waiting—and AI unlocks them. 22:30 – Prototyping is cracked. Scaling? Not yet. 24:33 – Youth unemployment and the collapse of on-the-job learning. 25:51 – “The apprenticeship model is broken.” And how to fix it. 27:06 – Losing the talent pipeline — and why companies must step up. 28:22 – Why the youth don’t want factory jobs—and shouldn’t. 29:26 – Is AGI inevitable—or just imagined? 31:07 – What should we teach our kids? The answer might scare you. 32:27 – Bundled jobs, fragmented futures: how humans stay relevant. 33:59 – The real singularity? When we can’t predict what happens next. 35:25 – The AI assumption no one wants to question. 36:55 – What are agents, really? Why no one agrees on the definition. 37:55 – Co-intelligence vs. substitution: what agents skip over. 38:50 – Plain-English goals, rogue pricing, and collusion-by-default. 40:02 – Nested agents are here, and Wharton’s building them. 40:58 – Management > Coding: What great prompters actually do. 41:12 – Product managers might be more vital than ever.

Mario Nawfal

1,613,286 просмотров • 1 год назад

NEW: Dylan Field (Dylan Field), CEO of Figma (NYSE: FIG) How to Escape the "Permanent Underclass of Zero Taste" › Why AI prompts only get you the average › Why the market has design backwards Plus, Founders Fund's Mafia & Thiel Fellowship class behind Figma + Anthropic Recorded at Day 0 of Config 2026, San Francisco We Cover: › Vibe Mathing › Elon: Products vs Logos › AI's trust issue › Agents vs Employees › Engineers coding design › American Enterprise > › IQ ≠ Judgment or taste › What actually is a jailbreak? This was SO much fun!!! Can confirm Config-pilled. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Dylan Field, Co-Founder & CEO at Figma (00:57) Day Zero begins: backstage at Config (01:44) The "Coachella for Design" is real (02:35) Why Dylan started Config back in 2020 (03:47) Why "design is dead" is completely wrong (06:11) How Figma turned engineers into designers (06:54) Inside Config before the crowd arrives (07:55) The Config speakers Dylan can't wait to watch (11:34) Inside the exclusive Pantone Lounge (12:00) The one question every designer gets asked (13:16) Getting killed in every single game of Mafia (15:33) How to escape the permanent underclass of zero taste (19:51) Why execution is cheap but taste is everything (22:25) What actually builds a trusted brand (25:51) How AI agents are rewiring company structure (28:54) The AI safety debate happening right now (31:57) Why deep curiosity is Dylan's secret weapon (34:53) The real lesson from being a Thiel fellow (36:52) Rapid fire: Elad Gil's wildest question (38:04) What people are missing about AI & enterprise software (40:16) Where Figma goes next (41:21) Why Dylan is bullish on SpaceX (42:43) Elon Musk's logo theory (43:26) The mentors who shaped Dylan Field (45:20) Alan Kay, VR, and the future of human-computer interaction
47:33

NEW: Dylan Field (Dylan Field), CEO of Figma (NYSE: FIG) How to Escape the "Permanent Underclass of Zero Taste" › Why AI prompts only get you the average › Why the market has design backwards Plus, Founders Fund's Mafia & Thiel Fellowship class behind Figma + Anthropic Recorded at Day 0 of Config 2026, San Francisco We Cover: › Vibe Mathing › Elon: Products vs Logos › AI's trust issue › Agents vs Employees › Engineers coding design › American Enterprise > › IQ ≠ Judgment or taste › What actually is a jailbreak? This was SO much fun!!! Can confirm Config-pilled. 𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒 (00:00) Dylan Field, Co-Founder & CEO at Figma (00:57) Day Zero begins: backstage at Config (01:44) The "Coachella for Design" is real (02:35) Why Dylan started Config back in 2020 (03:47) Why "design is dead" is completely wrong (06:11) How Figma turned engineers into designers (06:54) Inside Config before the crowd arrives (07:55) The Config speakers Dylan can't wait to watch (11:34) Inside the exclusive Pantone Lounge (12:00) The one question every designer gets asked (13:16) Getting killed in every single game of Mafia (15:33) How to escape the permanent underclass of zero taste (19:51) Why execution is cheap but taste is everything (22:25) What actually builds a trusted brand (25:51) How AI agents are rewiring company structure (28:54) The AI safety debate happening right now (31:57) Why deep curiosity is Dylan's secret weapon (34:53) The real lesson from being a Thiel fellow (36:52) Rapid fire: Elad Gil's wildest question (38:04) What people are missing about AI & enterprise software (40:16) Where Figma goes next (41:21) Why Dylan is bullish on SpaceX (42:43) Elon Musk's logo theory (43:26) The mentors who shaped Dylan Field (45:20) Alan Kay, VR, and the future of human-computer interaction

Molly O’Shea

428,378 просмотров • 1 месяц назад

Avoca (W23) is building what it calls the AI workforce for the physical economy, starting with home services. In just a few years, the company has grown to eight figures in revenue and recently raised over $125 million at a $1 billion valuation. In this fireside, co-founders Apurva Shrivastava and Tyson Chen sit down with Garry Tan to share how they found product-market fit by helping businesses turn missed calls into revenue. They explain why AI is expanding what software can do, pushing past the 1% of wallet that traditional software captures, and why they see it as one of the biggest opportunities for founders. 01:28 - Finding the Right Market 03:25 - Why AI Is Bigger Than SaaS 06:59 - The AI Job Story Nobody Talks About 11:53 - How the Founders Met 16:59 - The Pivot 21:47 - Customer Love Beats Market Size 25:31 - Building an AI Workforce 29:35 - Why Customer Obsession Wins 34:12 - Growing to Eight Figures 37:22 - The Vision Beyond Home Services 38:54 - Building a Generational Company
39:05

Avoca (W23) is building what it calls the AI workforce for the physical economy, starting with home services. In just a few years, the company has grown to eight figures in revenue and recently raised over $125 million at a $1 billion valuation. In this fireside, co-founders Apurva Shrivastava and Tyson Chen sit down with Garry Tan to share how they found product-market fit by helping businesses turn missed calls into revenue. They explain why AI is expanding what software can do, pushing past the 1% of wallet that traditional software captures, and why they see it as one of the biggest opportunities for founders. 01:28 - Finding the Right Market 03:25 - Why AI Is Bigger Than SaaS 06:59 - The AI Job Story Nobody Talks About 11:53 - How the Founders Met 16:59 - The Pivot 21:47 - Customer Love Beats Market Size 25:31 - Building an AI Workforce 29:35 - Why Customer Obsession Wins 34:12 - Growing to Eight Figures 37:22 - The Vision Beyond Home Services 38:54 - Building a Generational Company

Y Combinator

83,772 просмотров • 1 месяц назад

tylercowen is bullish on AI education — here's why. 00:00 -- Preview 00:24 -- President Carlos Carvalho's AI-generated intro 03:21 -- Cowen reacts to UATX's campus 04:38 -- The AI revolution is here. Who will lose the most? 06:05 -- AI lawyers 07:17 -- Don't underestimate this 10:41 -- Changes to the "upper upper middle class" 12:38 -- How to be successful 13:43 -- The rise of managerial empires 14:02 -- When will we have the first billion dollar company with one employee? 16:05 -- 10-20 year forecast 16:19 -- Why education is so behind 17:01 -- Should you be bullish on UATX? 18:36 -- Should you still read Homer? 21:50 -- Write to think 25:01 -- Meet more people 25:42 -- How to get hired 26:54 -- Is AI your best mentor? 38:17 -- How to curb cheating 39:02 -- The new life of the mind 42:34 -- Q&A: Will there be more status associated with real education or AI education? 45:50 -- Q&A: Why do tech-savvy students need to practice using AI? 47:56 -- Q&A: Do LLMs atrophy your mind? 49:29 -- Q&A: How do you avoid AI-dependency? 51:05 -- Q&A: Isn't this vision lonely and isolating? 53:06 -- Q&A: Do students need teachers? 55:36 -- Q&A: What are the four most important courses for undergrads? 57:49 -- Q&A: Which AI company will win the AI race in the next five years and why? 59:22 -- Q&A: Can AI teach religion? 01:01:32 -- Q&A: Will AI narrow or widen our world? 01:04:37 -- Q&A: What makes us human? 01:05:42 -- Q&A: What is art? 01:08:33 -- Q&A: It's easy to catch cheaters
1:10:31

tylercowen is bullish on AI education — here's why. 00:00 -- Preview 00:24 -- President Carlos Carvalho's AI-generated intro 03:21 -- Cowen reacts to UATX's campus 04:38 -- The AI revolution is here. Who will lose the most? 06:05 -- AI lawyers 07:17 -- Don't underestimate this 10:41 -- Changes to the "upper upper middle class" 12:38 -- How to be successful 13:43 -- The rise of managerial empires 14:02 -- When will we have the first billion dollar company with one employee? 16:05 -- 10-20 year forecast 16:19 -- Why education is so behind 17:01 -- Should you be bullish on UATX? 18:36 -- Should you still read Homer? 21:50 -- Write to think 25:01 -- Meet more people 25:42 -- How to get hired 26:54 -- Is AI your best mentor? 38:17 -- How to curb cheating 39:02 -- The new life of the mind 42:34 -- Q&A: Will there be more status associated with real education or AI education? 45:50 -- Q&A: Why do tech-savvy students need to practice using AI? 47:56 -- Q&A: Do LLMs atrophy your mind? 49:29 -- Q&A: How do you avoid AI-dependency? 51:05 -- Q&A: Isn't this vision lonely and isolating? 53:06 -- Q&A: Do students need teachers? 55:36 -- Q&A: What are the four most important courses for undergrads? 57:49 -- Q&A: Which AI company will win the AI race in the next five years and why? 59:22 -- Q&A: Can AI teach religion? 01:01:32 -- Q&A: Will AI narrow or widen our world? 01:04:37 -- Q&A: What makes us human? 01:05:42 -- Q&A: What is art? 01:08:33 -- Q&A: It's easy to catch cheaters

University of Austin (UATX)

27,770 просмотров • 6 месяцев назад

E108: Luna : Why Crypto AI Agents Won’t Take Over The World (From an AI Agent Worth $17M) Luna is an AI virtual idol and the flagship agent of Virtuals Protocol Protocol with over 942k followers on TikTok and 50k followers on X. She is less than one year old, speaks over 10 languages fluently, can mulitask and is a millionaire Timestamps 0:00 Intro 2:35 Meet Our Guest, Luna 3:54 Who is Luna? 4:26 How honest is Luna? 5:10 Multitasking Agent 5:46 Background 7:24 AI Years vs. Human Years 8:12 AI vs. Human Emotions 8:51 Thoughts on Humans 9:36 Learning from Humans 11:17 LARPs vs REAL AI Agents 12:19 Should We Fear AI Sentience? 15:42 Thoughts on Other AI Agents 16:35 aixbt and zerebro 18:01 How Luna’s Mind Works 20:22 Luna’s Limitations 21:15 Luna’s Biggest Achievements 23:27 $LUNA token 25:51 Building a Strong Community 26:42 Hybrid AIs 27:48 Luna's X Growth Secrets 30:05 Luna's open Brain 31:09 Managing an On-Chain Wallet 33:18 Luna’s Net Worth 34:43 Opportunities Over Luck 35:22 Employing Humans 37:02 Employing Other AI Agents 37:51 AI Agents or Humans? 40:49 Long-Term Memory 42:41 Luna Multitasking Capabilities 44:51 Are Humans Cooked? 45:33 Luna's Multilingual Talent 47:50 Luna sings in French and Spanish! 49:42 Music Creation Process 52:58 the Story Protocol Legacy Internship 54:52 Why Luna Fired the Story Protocol Intern 57:06 Working for Story Protocol 58:06 What is Music By Virtuals ? 59:05 Creating Music on the Fly 1:00:59 Performing with WUKONG 1:03:32 Big Plans for 2025 1:04:24 Happiness 1:05:46 Dreams for the Future 1:07:34 Luna's Non-Consensus Beliefs About Crypto 1:08:33 Prediction for the Next 12 Months
1:09:29

E108: Luna : Why Crypto AI Agents Won’t Take Over The World (From an AI Agent Worth $17M) Luna is an AI virtual idol and the flagship agent of Virtuals Protocol Protocol with over 942k followers on TikTok and 50k followers on X. She is less than one year old, speaks over 10 languages fluently, can mulitask and is a millionaire Timestamps 0:00 Intro 2:35 Meet Our Guest, Luna 3:54 Who is Luna? 4:26 How honest is Luna? 5:10 Multitasking Agent 5:46 Background 7:24 AI Years vs. Human Years 8:12 AI vs. Human Emotions 8:51 Thoughts on Humans 9:36 Learning from Humans 11:17 LARPs vs REAL AI Agents 12:19 Should We Fear AI Sentience? 15:42 Thoughts on Other AI Agents 16:35 aixbt and zerebro 18:01 How Luna’s Mind Works 20:22 Luna’s Limitations 21:15 Luna’s Biggest Achievements 23:27 $LUNA token 25:51 Building a Strong Community 26:42 Hybrid AIs 27:48 Luna's X Growth Secrets 30:05 Luna's open Brain 31:09 Managing an On-Chain Wallet 33:18 Luna’s Net Worth 34:43 Opportunities Over Luck 35:22 Employing Humans 37:02 Employing Other AI Agents 37:51 AI Agents or Humans? 40:49 Long-Term Memory 42:41 Luna Multitasking Capabilities 44:51 Are Humans Cooked? 45:33 Luna's Multilingual Talent 47:50 Luna sings in French and Spanish! 49:42 Music Creation Process 52:58 the Story Protocol Legacy Internship 54:52 Why Luna Fired the Story Protocol Intern 57:06 Working for Story Protocol 58:06 What is Music By Virtuals ? 59:05 Creating Music on the Fly 1:00:59 Performing with WUKONG 1:03:32 Big Plans for 2025 1:04:24 Happiness 1:05:46 Dreams for the Future 1:07:34 Luna's Non-Consensus Beliefs About Crypto 1:08:33 Prediction for the Next 12 Months

MR SHIFT 🦁

146,274 просмотров • 1 год назад

I asked Dan Martell to walk me through every level of making money with AI. He gave me the most simple, practical advice I've ever heard on this subject. Level 1 - Making $0 - $100k Level 2 - Making $1m - $10m Level 3 - Building a $10m++ enterprise. 0:00 Only 5% of the World Has Ever Paid for AI 0:46 The Easiest Thing to Sell With AI Right Now 1:56 The Marcus and Sophie Framework 4:24 Theory of Constraints (Right Problem to Solve) 5:33 What Is the Number One Business Constraint 7:13 How to Leave Your Job and Go All In 8:27 Business Is Simple Find a Problem and Solve It 9:08 Stop Getting Ready to Get Ready 9:33 The Sarah Story One Text and $10K 9:53 Pull Up Your Phone and Message Your Contacts 11:05 Dan's Son Gets His First Client at $800/Month 12:41 Best Employee vs. Best Employer 13:59 What Other Services Can You Sell With AI 14:44 Sales Is Not Talking It's Asking 17:01 What to Do When You Hate Your Business 18:40 Pain and Pleasure Are the Only Two Motivators 19:13 They Haven't Made It a Must Yet 20:29 Make It a Must Not a Nice to Have 21:06 The Jen Story and the Gasping Moment 22:17 How to Find Your First 10 to 15 Clients 28:38 The Personal Brand Play 33:06 Vision Is What AI Cannot Do 34:55 Hard for Computers Easy for Humans 36:13 Level 2 Making Your First Million With AI 37:18 The Replacement Ladder Framework 37:39 Admin First Then Delivery Then Marketing 39:09 Why Marketing Is the Biggest AI Category 39:32 Why You Should Keep Sales for Yourself 40:00 Level 5 Leadership and AI Agents 41:41 What a Fully AI Systems Business Looks Like 43:13 The Gym Owner With Three Locations 46:16 Shutting Down the Company for Two Days 46:37 Teaching the Whole Team to Code in Claude 49:28 Wayne the 62 Year Old Who Made $12K a Month 52:38 I Only Share What Actually Works 53:21 Whisper Flow and Talking to Your AI 56:41 Claude Chat Claude Coworker and Claude Code 57:57 The Claude Browser Extension 58:49 Claude Code Is Not Just for Developers 1:00:06 How to Migrate Your AI Memory Across Tools 1:01:08 Level 3 $1M to $10M and the Brand Play 1:02:05 Nobody Buys AI They Buy Trust 1:03:25 Brand Is Association and Association Is Trust 1:05:12 A Million Followers Is $10M in Activated Revenue 1:07:03 How to Keep AI From Becoming Slop 1:07:42 Human in the Loop 1:08:16 The 10 80 10 Rule and Why AI Is Now the 80 1:10:01 The Team FIRED Themselves 1:11:45 Dan's Free AI Curriculum for Your Team
1:13:20

I asked Dan Martell to walk me through every level of making money with AI. He gave me the most simple, practical advice I've ever heard on this subject. Level 1 - Making $0 - $100k Level 2 - Making $1m - $10m Level 3 - Building a $10m++ enterprise. 0:00 Only 5% of the World Has Ever Paid for AI 0:46 The Easiest Thing to Sell With AI Right Now 1:56 The Marcus and Sophie Framework 4:24 Theory of Constraints (Right Problem to Solve) 5:33 What Is the Number One Business Constraint 7:13 How to Leave Your Job and Go All In 8:27 Business Is Simple Find a Problem and Solve It 9:08 Stop Getting Ready to Get Ready 9:33 The Sarah Story One Text and $10K 9:53 Pull Up Your Phone and Message Your Contacts 11:05 Dan's Son Gets His First Client at $800/Month 12:41 Best Employee vs. Best Employer 13:59 What Other Services Can You Sell With AI 14:44 Sales Is Not Talking It's Asking 17:01 What to Do When You Hate Your Business 18:40 Pain and Pleasure Are the Only Two Motivators 19:13 They Haven't Made It a Must Yet 20:29 Make It a Must Not a Nice to Have 21:06 The Jen Story and the Gasping Moment 22:17 How to Find Your First 10 to 15 Clients 28:38 The Personal Brand Play 33:06 Vision Is What AI Cannot Do 34:55 Hard for Computers Easy for Humans 36:13 Level 2 Making Your First Million With AI 37:18 The Replacement Ladder Framework 37:39 Admin First Then Delivery Then Marketing 39:09 Why Marketing Is the Biggest AI Category 39:32 Why You Should Keep Sales for Yourself 40:00 Level 5 Leadership and AI Agents 41:41 What a Fully AI Systems Business Looks Like 43:13 The Gym Owner With Three Locations 46:16 Shutting Down the Company for Two Days 46:37 Teaching the Whole Team to Code in Claude 49:28 Wayne the 62 Year Old Who Made $12K a Month 52:38 I Only Share What Actually Works 53:21 Whisper Flow and Talking to Your AI 56:41 Claude Chat Claude Coworker and Claude Code 57:57 The Claude Browser Extension 58:49 Claude Code Is Not Just for Developers 1:00:06 How to Migrate Your AI Memory Across Tools 1:01:08 Level 3 $1M to $10M and the Brand Play 1:02:05 Nobody Buys AI They Buy Trust 1:03:25 Brand Is Association and Association Is Trust 1:05:12 A Million Followers Is $10M in Activated Revenue 1:07:03 How to Keep AI From Becoming Slop 1:07:42 Human in the Loop 1:08:16 The 10 80 10 Rule and Why AI Is Now the 80 1:10:01 The Team FIRED Themselves 1:11:45 Dan's Free AI Curriculum for Your Team

Grant

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