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Introducing dAGI Accelerator’s first crop of graduates 🎉 300 AI startups applied. 8 were chosen. They got 2 months of hands-on mentorship and collaboration with and Delphi Labs. Now, we're thrilled to share their visions with the world: 00:00: fewsats: The easiest way for AI to use money 04:55:...

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dAGIhouse

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48,141 görüntüleme • 1 yıl önce •via X (Twitter)

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Dear VCs, Delphi Labs and teamed up to run our first-ever dAGI Accelerator cohort with 8 amazing teams building the future of open, unstoppable AI. After two months of relentless, product-focused progress, each team is ready to show off what they've built. Join us May 28 for a Virtual Demo Day like no other. Founders from TrueNorth, Mathlock, scade.xyz, ASIMOV, fewsats, Framework, No Cap👽, and RPS AI get up to 5 minutes to pitch… no fluff, just frontier AI. Backed by: 1️⃣ An unprecedented trio of support from the Solana and Ethereum foundations, and the Base ecosystem 2️⃣ Experts from Delphi Labs & cyber•Fund 3️⃣ 14 elite mentors including Ben Fielding at gensyn, Jasper at Hyperbolic, Tarun Chitra at Robot Ventures, Stability AI founder Emad, Sreeram Kannan at , , Rawson 🙏, Konstantin Lomashuk cyber/acc, Teng Yan and more! This is your front-row seat to the future of open and composable intelligence. Access is invite-only. DM us for an exclusive pass. The future of AI won’t be locked behind corporate firewalls. It’ll be open. And it will be unstoppable.
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Dear VCs, Delphi Labs and teamed up to run our first-ever dAGI Accelerator cohort with 8 amazing teams building the future of open, unstoppable AI. After two months of relentless, product-focused progress, each team is ready to show off what they've built. Join us May 28 for a Virtual Demo Day like no other. Founders from TrueNorth, Mathlock, scade.xyz, ASIMOV, fewsats, Framework, No Cap👽, and RPS AI get up to 5 minutes to pitch… no fluff, just frontier AI. Backed by: 1️⃣ An unprecedented trio of support from the Solana and Ethereum foundations, and the Base ecosystem 2️⃣ Experts from Delphi Labs & cyber•Fund 3️⃣ 14 elite mentors including Ben Fielding at gensyn, Jasper at Hyperbolic, Tarun Chitra at Robot Ventures, Stability AI founder Emad, Sreeram Kannan at , , Rawson 🙏, Konstantin Lomashuk cyber/acc, Teng Yan and more! This is your front-row seat to the future of open and composable intelligence. Access is invite-only. DM us for an exclusive pass. The future of AI won’t be locked behind corporate firewalls. It’ll be open. And it will be unstoppable.

dAGIhouse

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Dr. Fei-Fei Li (Fei-Fei Li), the Godmother of AI, on the origin of computer vision and why spatial intelligence is the next frontier. At AI Startup School in San Francisco. 01:00 - Origins of ImageNet 02:15 - The Dream to Make Machines See 03:28 - A paradigm shift in AI 05:50 - AlexNet and Deep Learning 08:00 - Evolving Computer Vision 12:20 - Building World Labs 13:00 - The next frontier in AI 14:20 - Why Spatial Intelligence Is Harder Than Language 18:40 - Technical Barriers for Vision-Based AI 20:00 - AI is more than LLMs 25:50 - Fei Fei’s Journey 29:30 - Mentoring some of the legends of AI 33:00 - Audience Q&A
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Dr. Fei-Fei Li (Fei-Fei Li), the Godmother of AI, on the origin of computer vision and why spatial intelligence is the next frontier. At AI Startup School in San Francisco. 01:00 - Origins of ImageNet 02:15 - The Dream to Make Machines See 03:28 - A paradigm shift in AI 05:50 - AlexNet and Deep Learning 08:00 - Evolving Computer Vision 12:20 - Building World Labs 13:00 - The next frontier in AI 14:20 - Why Spatial Intelligence Is Harder Than Language 18:40 - Technical Barriers for Vision-Based AI 20:00 - AI is more than LLMs 25:50 - Fei Fei’s Journey 29:30 - Mentoring some of the legends of AI 33:00 - Audience Q&A

Y Combinator

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Ex-DeepMind researcher Misha Laskin on building superintelligence, coding as a shortcut, reinforcement learning, launching Reflection AI's first product, Asimov, and competing with the big AI labs 00:00 - Intro 01:42 - Reflection AI: Company Origins and Mission 04:14 - Making Superintelligence Concrete 06:04 - ASI vs. AGI: Why the Goalposts Moved 07:55 - Organizational Superintelligence as an Oracle 12:05 - Coding as Shortcut: Hands, Legs & Brain for AI 20:55 - Capturing Tribal Knowledge in Organizations 26:31 - Introducing Asimov: Deep Research for Code 28:44 - Team-Wide Memory 33:07 - Multi-Agent Design 34:48 - Data Retrieval and Integration in Asimov 39:41 - Reinforcement Learning in Asimov 41:04 - Misha's Journey: From Physics to AI 42:06 - Growing Up in a Science-Driven Desert Town 53:03 - Building General Agents at DeepMind 56:57 - Founding Reflection AI After DeepMind 58:54 - Product vs tech in AI 1:02:22 - The State of Autonomous Coding Agents 1:04:26 - What's Next for Reflection AI
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Ex-DeepMind researcher Misha Laskin on building superintelligence, coding as a shortcut, reinforcement learning, launching Reflection AI's first product, Asimov, and competing with the big AI labs 00:00 - Intro 01:42 - Reflection AI: Company Origins and Mission 04:14 - Making Superintelligence Concrete 06:04 - ASI vs. AGI: Why the Goalposts Moved 07:55 - Organizational Superintelligence as an Oracle 12:05 - Coding as Shortcut: Hands, Legs & Brain for AI 20:55 - Capturing Tribal Knowledge in Organizations 26:31 - Introducing Asimov: Deep Research for Code 28:44 - Team-Wide Memory 33:07 - Multi-Agent Design 34:48 - Data Retrieval and Integration in Asimov 39:41 - Reinforcement Learning in Asimov 41:04 - Misha's Journey: From Physics to AI 42:06 - Growing Up in a Science-Driven Desert Town 53:03 - Building General Agents at DeepMind 56:57 - Founding Reflection AI After DeepMind 58:54 - Product vs tech in AI 1:02:22 - The State of Autonomous Coding Agents 1:04:26 - What's Next for Reflection AI

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🚨 ANNOUNCING THE WORLD'S FIRST VIBE CODING AGENT FOR APIs. Vibe coders just became LEGIT backend engineers. With ONE PROMPT, you can create an entire microservice and host it on Abacus AI Deep Agent. Vibe coders can now go toe-to-toe with backend engineers and create an API, a Telegram bot, or any AI service. The AI takes care of everything. - creating an API spec - implementing it and hosting it - using a back-end database for tracking - giving you a test bed - providing you with a ready-to-use endpoint! Backend engineers are expensive; now you can start vibe-coding their projects in English.
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🚨 ANNOUNCING THE WORLD'S FIRST VIBE CODING AGENT FOR APIs. Vibe coders just became LEGIT backend engineers. With ONE PROMPT, you can create an entire microservice and host it on Abacus AI Deep Agent. Vibe coders can now go toe-to-toe with backend engineers and create an API, a Telegram bot, or any AI service. The AI takes care of everything. - creating an API spec - implementing it and hosting it - using a back-end database for tracking - giving you a test bed - providing you with a ready-to-use endpoint! Backend engineers are expensive; now you can start vibe-coding their projects in English.

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AI has a trust problem. Verifiability is the solution. Our GM of AI Nima Vaziri sat down with a16z’s Ali Yahya and Dan Boneh of Stanford University to map the deepest fault lines in AI today. ☁️ Models we can’t trust ☁️ Current providers can censor, shut down, or shift rules overnight. Outsourced training hides backdoors. Even “open” weights don’t prove what’s actually running. Trust. Backdoors. Black boxes. The path forward is clear: 🔥 Verifiable evals 🔥 Verifiable inference 🔥 TEEs for hardware-backed integrity 🔥 Infra beyond single points of control 🔥 Blockchains as coordination layers for AI From “trust us” to “verify yourself.” That’s the shift. That’s the unlock. The frontier is here. The builders decide what comes next. Create and use AI that’s incentive aligned with you. Timestamps: 00:00:00 Introduction: AI & Crypto Intersection Overview 00:01:58 Four Major AI-Crypto Trends 00:02:44 AI Agents Need Financial Infrastructure 00:04:03 Proof of Humanity: Fighting AI-Generated Content 00:04:17 Decentralizing AI Infrastructure Networks 00:04:44 Synthetic Life: Autonomous AI Agents 00:06:20 Verifiable AI 00:10:16 Current Performance Numbers for AI Proofs 00:13:18 The Era of Experience in AI Learning 00:14:56 AI Agents Having Life of its Own 00:18:21 Algorithmic Fairness & Verifiable Models 00:23:18 Privacy in AI: Trusted Execution Environments 00:25:47 Economic Incentive for Open Weight Models 00:31:39 Attribution Problem: Who Gets Paid for AI Training? 00:35:52 Content Provenance & Authentication (C2PA) 00:48:03 AI Security: Finding Exploits & Vulnerabilities 00:54:53 Educational Applications: LLMs as Learning Partner 00:58:29 Reliance on LLMs and Cognitive Abilities 01:03:57 Content Providers’ Fear of LLM Training
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.Ramp Labs (the AI unit of Ramp) has been *cooking* with agentic innovation Here's Alex L discussing and demo'ing code self-maintaining software and the concept of AI software factories #DataDrivenNYC ______________ 00:04 - Intro 01:11 - The shift from writing code to code maintenance 01:59 - Introducing Ramp Inspect, the background coding agent 03:05 - The first experiment: Nightly AI code automation 04:23 - The limits of stateless monitoring in large observability surfaces 05:47 - Using Datadog monitors to give the AI state and focus 07:23 - Real-world example: AI autonomously fixing an authentication bug 08:14 - How to control noise and implement an AI triage pattern 09:27 - The old vs. new paradigm for continuous code observability 10:21 - Key learnings on building autonomous AI software factories
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.Ramp Labs (the AI unit of Ramp) has been *cooking* with agentic innovation Here's Alex L discussing and demo'ing code self-maintaining software and the concept of AI software factories #DataDrivenNYC ______________ 00:04 - Intro 01:11 - The shift from writing code to code maintenance 01:59 - Introducing Ramp Inspect, the background coding agent 03:05 - The first experiment: Nightly AI code automation 04:23 - The limits of stateless monitoring in large observability surfaces 05:47 - Using Datadog monitors to give the AI state and focus 07:23 - Real-world example: AI autonomously fixing an authentication bug 08:14 - How to control noise and implement an AI triage pattern 09:27 - The old vs. new paradigm for continuous code observability 10:21 - Key learnings on building autonomous AI software factories

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67,624 görüntüleme • 2 ay önce

Natalia Quintero (Natalia) runs Every 📧’s seven-figure AI consulting practice, and she just automated her job with Claude Code. She built an AI project manager, Claudie, that cuts her weekly project management workload from 15 hours to just one. It manages the fleet of spreadsheets she uses to manage new clients, track what has been delivered and what hasn’t, and aggregate feedback to improve our services over time. A month ago she would’ve described herself as non-technical, but now she’s a ‘bonafide vibe code addict’—waking up at 6 a.m. everyday to work on Claudie before her meetings start. She’s not just personally neck-deep in AI—she’s also seen it work, and not, in the smartest enterprises in the world. As our head of consulting, she’s worked with top hedge funds, PE, firms, tech companies, and Fortune 500s to help drive AI adoption and automations. I had her on AI&I to talk about: - How to transition a big company into a truly AI-native org - Why enterprise AI adoption only goes as far as CEO adoption - How to empower AI early adopters inside your org - Why you have to carve out space to “play” with AI if you want real transformation If you’re trying to figure out how to actually put AI to work inside your company, this episode is for you. Watch below! Timestamps: Introduction: 00:00:00 Why successful AI adoption requires coordinated, top-down effort: 00:01:30 How a private equity firm reduced investment memo creation from weeks to 30 minutes: 00:07:05 The benefits of connecting AI to proprietary context: 00:13:30 The plan-delegate-assess-compound framework for engineering teams: 00:15:20 How non-technical team members are becoming vibe coding addicts: 00:17:55 Building Claudie: an AI project manager from scratch: 00:20:50 Why creative exploration time outside the 9-to-5 is essential: 00:23:00 Live demo: How Claudie automates client onboarding and tracking: 00:27:50 The human side of AI: spending less time in spreadsheets, more time with people: 00:38:40
47:14

Natalia Quintero (Natalia) runs Every 📧’s seven-figure AI consulting practice, and she just automated her job with Claude Code. She built an AI project manager, Claudie, that cuts her weekly project management workload from 15 hours to just one. It manages the fleet of spreadsheets she uses to manage new clients, track what has been delivered and what hasn’t, and aggregate feedback to improve our services over time. A month ago she would’ve described herself as non-technical, but now she’s a ‘bonafide vibe code addict’—waking up at 6 a.m. everyday to work on Claudie before her meetings start. She’s not just personally neck-deep in AI—she’s also seen it work, and not, in the smartest enterprises in the world. As our head of consulting, she’s worked with top hedge funds, PE, firms, tech companies, and Fortune 500s to help drive AI adoption and automations. I had her on AI&I to talk about: - How to transition a big company into a truly AI-native org - Why enterprise AI adoption only goes as far as CEO adoption - How to empower AI early adopters inside your org - Why you have to carve out space to “play” with AI if you want real transformation If you’re trying to figure out how to actually put AI to work inside your company, this episode is for you. Watch below! Timestamps: Introduction: 00:00:00 Why successful AI adoption requires coordinated, top-down effort: 00:01:30 How a private equity firm reduced investment memo creation from weeks to 30 minutes: 00:07:05 The benefits of connecting AI to proprietary context: 00:13:30 The plan-delegate-assess-compound framework for engineering teams: 00:15:20 How non-technical team members are becoming vibe coding addicts: 00:17:55 Building Claudie: an AI project manager from scratch: 00:20:50 Why creative exploration time outside the 9-to-5 is essential: 00:23:00 Live demo: How Claudie automates client onboarding and tracking: 00:27:50 The human side of AI: spending less time in spreadsheets, more time with people: 00:38:40

Dan Shipper 📧

31,655 görüntüleme • 5 ay önce

For nearly two decades, Box co-founder and CEO Aaron Levie (Aaron Levie) has been at the frontlines of how technology reshapes work—guiding the company through the rise of mobile, the cloud, and now the age of AI. In his fireside with YC's David Lieb at AI Startup School, Aaron reflects on adapting a company for the long term, staying relevant across multiple waves, and why he believes AI is the most transformative shift yet. 00:00 – AI hype vs. reality inside companies 01:00 – Early days: starting Box in 2005 03:30 – Pivoting from consumer storage to enterprise cloud 05:45 – Cloud transition lessons vs. AI today 07:10 – Why unstructured data is AI’s biggest opportunity 09:05 – Will AI replace jobs or create more work? 13:15 – Startups vs. incumbents in the AI era 15:20 – Finding the next “nouns and verbs” for startups 20:25 – Rethinking SaaS business models for AI agents 27:05 – Why companies won’t just build everything in-house 31:15 – Advice to young founders 35:40 – Fulfillment and meaning of life 36:40 – Enterprise design and craft in SaaS 39:00 – Competing with incumbents
40:27

For nearly two decades, Box co-founder and CEO Aaron Levie (Aaron Levie) has been at the frontlines of how technology reshapes work—guiding the company through the rise of mobile, the cloud, and now the age of AI. In his fireside with YC's David Lieb at AI Startup School, Aaron reflects on adapting a company for the long term, staying relevant across multiple waves, and why he believes AI is the most transformative shift yet. 00:00 – AI hype vs. reality inside companies 01:00 – Early days: starting Box in 2005 03:30 – Pivoting from consumer storage to enterprise cloud 05:45 – Cloud transition lessons vs. AI today 07:10 – Why unstructured data is AI’s biggest opportunity 09:05 – Will AI replace jobs or create more work? 13:15 – Startups vs. incumbents in the AI era 15:20 – Finding the next “nouns and verbs” for startups 20:25 – Rethinking SaaS business models for AI agents 27:05 – Why companies won’t just build everything in-house 31:15 – Advice to young founders 35:40 – Fulfillment and meaning of life 36:40 – Enterprise design and craft in SaaS 39:00 – Competing with incumbents

Y Combinator

236,530 görüntüleme • 10 ay önce

.Dwarkesh Patel has a new book on AI out from Stripe Press and we arrive with a new Core Memory podcast with the man himself to talk about the book, his beard and his podcasting rise Timestamps: 0:00 – Intro: AI’s explosive evolution 1:30 – The “Scaling Era” & making the book 3:00 – Oral history as an art form 4:45 – Why scaling laws are mysterious 6:40 – Old soul in a young body 8:10 – Podcasting as a learning engine 11:00 – Debating, early influences & the beard 13:00 – AI needs a multidisciplinary lens 15:20 – Dwarkesh’s intellectual growth 18:00 – Startup dreams & origin story 21:00 – Debate legacy & reflection on public speaking 24:00 – What models still struggle with 26:00 – AI’s future: RL environments & bottlenecks 29:00 – How scale might hit a wall 32:20 – Can labs fast-follow superintelligence? 34:00 – The arms race for AGI dominance 38:00 – Will the first lab to AGI dominate forever? 40:00 – Automation of R&D: hype or real edge? 44:00 – Deep discussion on reasoning models 47:00 – Economic impact of true AI agents 50:00 – Finding overlooked genius guests 53:00 – Sarah Paine & accidental podcast hits 55:00 – The power of mentorship (Tyler Cowen) 57:00 – Outro: Growth, learning, and the hivemind
1:10:05

.Dwarkesh Patel has a new book on AI out from Stripe Press and we arrive with a new Core Memory podcast with the man himself to talk about the book, his beard and his podcasting rise Timestamps: 0:00 – Intro: AI’s explosive evolution 1:30 – The “Scaling Era” & making the book 3:00 – Oral history as an art form 4:45 – Why scaling laws are mysterious 6:40 – Old soul in a young body 8:10 – Podcasting as a learning engine 11:00 – Debating, early influences & the beard 13:00 – AI needs a multidisciplinary lens 15:20 – Dwarkesh’s intellectual growth 18:00 – Startup dreams & origin story 21:00 – Debate legacy & reflection on public speaking 24:00 – What models still struggle with 26:00 – AI’s future: RL environments & bottlenecks 29:00 – How scale might hit a wall 32:20 – Can labs fast-follow superintelligence? 34:00 – The arms race for AGI dominance 38:00 – Will the first lab to AGI dominate forever? 40:00 – Automation of R&D: hype or real edge? 44:00 – Deep discussion on reasoning models 47:00 – Economic impact of true AI agents 50:00 – Finding overlooked genius guests 53:00 – Sarah Paine & accidental podcast hits 55:00 – The power of mentorship (Tyler Cowen) 57:00 – Outro: Growth, learning, and the hivemind

Ashlee Vance

34,839 görüntüleme • 1 yıl önce

People of AI is back with a new co-host Christina Warren who joins Ashley Oldacre on Season 5 to highlight the developers, startups, and founders shaping the future of AI, including their challenges and triumphs 💪 First up, Clément Farabet, VP of Research at Google DeepMind, shares his engineering journey, AI work, and the balance between research and real-world products, and how these advancements are paving the way for an agentic future. Key Moments: 0:00 Intro season 5 02:36 Neural Nets to Transformers 08:16 Were Transformers inevitable? 10:45 Time at NVIDIA 13:05 Why join Google DeepMind? 16:00 Research vs Production or both? 24:00 AI studio - product experimentation 27:32 The future of agents 30:53 Agent accountability 36:30 How does Clement use agents? 40:00 Clement’s vision for the future 47:20 Rapid Fire Questions
52:36

People of AI is back with a new co-host Christina Warren who joins Ashley Oldacre on Season 5 to highlight the developers, startups, and founders shaping the future of AI, including their challenges and triumphs 💪 First up, Clément Farabet, VP of Research at Google DeepMind, shares his engineering journey, AI work, and the balance between research and real-world products, and how these advancements are paving the way for an agentic future. Key Moments: 0:00 Intro season 5 02:36 Neural Nets to Transformers 08:16 Were Transformers inevitable? 10:45 Time at NVIDIA 13:05 Why join Google DeepMind? 16:00 Research vs Production or both? 24:00 AI studio - product experimentation 27:32 The future of agents 30:53 Agent accountability 36:30 How does Clement use agents? 40:00 Clement’s vision for the future 47:20 Rapid Fire Questions

Google for Developers

17,576 görüntüleme • 1 yıl önce

We’re back for Episode 14 of TAO Talk 🚨 calanthia from Masa joins 563 and brody this week to chat about new subnets and AI agents sourcing intelligence from Bittensor! The group chats about: - $TAO -pilling AI/ML chads at NeurIPS Conference feat. const Crucible Labs Macrocosmos Manifold and Yuma - JJ teaming up with Cameron Fairchild to form Laτenτ Holdings, which will validate and help scale subnets - Crucible Labs drops a subnet analysis framework - Celium offering H100s cheaper than any other provider - Tao360 releases inaugural research report for their AI-enabled subnet analysis tool @notYourBananaa - Masa unveils the AI Agent Arena on SN59 /// Timestamps: 00:00 Intro 01:10 Subnet 42 and Agent Arena: Masa’s Subnets 03:00 Real-Time Data Networks for AI 04:20 How Masa is Building AI Agent Arenas Inspired by Gladiators 06:10 Decentralized AI and Bittensor: The Growing Ecosystem 08:15 AI Meets Web3: Masa’s Role in Revolutionizing Data Networks 10:00 The Future of AI Agents: Intelligent Societies and Real-Time Data 12:05 Why Masa Chose Bittensor 14:10 $TAO Incentives and the Future of AI Decentralization 16:25 Bittensor and the Rise of Agent Competition: Masa’s Perspective 18:00 Exploring AI Agent Societies 20:30 Creating Competitive AI Arenas: The Agent Arena Subnet Explained 23:00 Calanthia on the Challenges of Web3 AI Development 25:10 Bringing Web2 Developers into Web3: Lessons from Masa 27:30 The Evolution of AI: From Dumb Agents to Intelligent Societies 30:00 AI Agents as the Future of Interaction in Decentralized AI 34:00 The Agent Arena’s Vision: Competition, Incentives, and Innovation
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We’re back for Episode 14 of TAO Talk 🚨 calanthia from Masa joins 563 and brody this week to chat about new subnets and AI agents sourcing intelligence from Bittensor! The group chats about: - $TAO -pilling AI/ML chads at NeurIPS Conference feat. const Crucible Labs Macrocosmos Manifold and Yuma - JJ teaming up with Cameron Fairchild to form Laτenτ Holdings, which will validate and help scale subnets - Crucible Labs drops a subnet analysis framework - Celium offering H100s cheaper than any other provider - Tao360 releases inaugural research report for their AI-enabled subnet analysis tool @notYourBananaa - Masa unveils the AI Agent Arena on SN59 /// Timestamps: 00:00 Intro 01:10 Subnet 42 and Agent Arena: Masa’s Subnets 03:00 Real-Time Data Networks for AI 04:20 How Masa is Building AI Agent Arenas Inspired by Gladiators 06:10 Decentralized AI and Bittensor: The Growing Ecosystem 08:15 AI Meets Web3: Masa’s Role in Revolutionizing Data Networks 10:00 The Future of AI Agents: Intelligent Societies and Real-Time Data 12:05 Why Masa Chose Bittensor 14:10 $TAO Incentives and the Future of AI Decentralization 16:25 Bittensor and the Rise of Agent Competition: Masa’s Perspective 18:00 Exploring AI Agent Societies 20:30 Creating Competitive AI Arenas: The Agent Arena Subnet Explained 23:00 Calanthia on the Challenges of Web3 AI Development 25:10 Bringing Web2 Developers into Web3: Lessons from Masa 27:30 The Evolution of AI: From Dumb Agents to Intelligent Societies 30:00 AI Agents as the Future of Interaction in Decentralized AI 34:00 The Agent Arena’s Vision: Competition, Incentives, and Innovation

TAO τalk 🥩🦍

24,929 görüntüleme • 1 yıl önce

VIBE CODING TUTORIAL: Creating a Viral Meme Mobile App Without Any Coding in 20 minutes! You can now build multi-step AI workflows on a drag and drop platform, and then connect that workflow to your vibe coded mobile app, in a single cursor prompt. This only scratches the surface on the different workflows you can create like this. IN THIS VIDEO 00:00 Intro 00:36 Overview: MultiStep AI Backend on GLIF 01:33 Using Glif as an API 03:49 The backend for our app 04:36 Structured Outputs (Important for Vibe Coding, skip if you know what these are) 06:40 Image Workflow for the meme 08:34 Let's Protototype on 11:09 Setting this up with Cursor 18:40 Testing with
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VIBE CODING TUTORIAL: Creating a Viral Meme Mobile App Without Any Coding in 20 minutes! You can now build multi-step AI workflows on a drag and drop platform, and then connect that workflow to your vibe coded mobile app, in a single cursor prompt. This only scratches the surface on the different workflows you can create like this. IN THIS VIDEO 00:00 Intro 00:36 Overview: MultiStep AI Backend on GLIF 01:33 Using Glif as an API 03:49 The backend for our app 04:36 Structured Outputs (Important for Vibe Coding, skip if you know what these are) 06:40 Image Workflow for the meme 08:34 Let's Protototype on 11:09 Setting this up with Cursor 18:40 Testing with

Riley Brown

58,068 görüntüleme • 1 yıl önce

Guillermo Rauch (Guillermo Rauch) is one of the most prolific coders of this generation. But he doesn’t think of himself as a coder anymore. Coding, he says, is a specific skill that AI is becoming great at. Instead, he thinks the future of coding is more holistic, full-stack engineers who can ideate, design, and execute all together. Guillermo is the founder and CEO of Vercel (Vercel), the creator of NextJS, and SocketIO. We spent an hour talking about the future of software development in an AI world—and the meta-skills that are essential for the coders of today to master—in order to use tomorrow’s tools to their fullest extent. Here are a few takeaways: - One of the most important keys to his success is taste—and developing taste is all about paying better attention to everything you experience day to day. - He’s great at recognizing bleeding-edge technologies with extremely practical applications but that have bad user experiences. If you can learn to recognize those and build with them, you might build the next NextJs or SocketIO. - Why prototype cultures are becoming common in AI—and the benefits of written cultures like Amazon vs. prototype cultures like Apple for different kinds of companies. - For developers building frameworks, always put the product first; a framework in isolation without a “customer zero” is never going to be a good tool. - The theory of “recursive founder mode”—if you want to build a scalable business, you have to scale yourself by creating an atmosphere that nurtures talent and ambition. - AI tools are shifting software toward consumption-based billing models, making us capital allocators who decide how much compute the AI consumes. - The future of AI is agents with the taste, knowledge, and tools to perform specialized tasks. Watch below! Timestamps: Introduction: 00:01:33 How to spot trends early: 00:03:18 Why you should be your own customer: 00:07:34 How to create an ecosystem of talent and ambition: 00:14:55 Why Guillermo doesn't identify as a coder: 00:17:29 AI is gearing us toward an allocation economy: 00:20:50 How Vercel’s copilot compares with other coding agents: 00:28:34 Guillermo’s advice on having better taste: 00:40:35 The future of AI agents is specialized: 00:42:46 How AI startups can compete with big tech: 00:47:50
56:15

Guillermo Rauch (Guillermo Rauch) is one of the most prolific coders of this generation. But he doesn’t think of himself as a coder anymore. Coding, he says, is a specific skill that AI is becoming great at. Instead, he thinks the future of coding is more holistic, full-stack engineers who can ideate, design, and execute all together. Guillermo is the founder and CEO of Vercel (Vercel), the creator of NextJS, and SocketIO. We spent an hour talking about the future of software development in an AI world—and the meta-skills that are essential for the coders of today to master—in order to use tomorrow’s tools to their fullest extent. Here are a few takeaways: - One of the most important keys to his success is taste—and developing taste is all about paying better attention to everything you experience day to day. - He’s great at recognizing bleeding-edge technologies with extremely practical applications but that have bad user experiences. If you can learn to recognize those and build with them, you might build the next NextJs or SocketIO. - Why prototype cultures are becoming common in AI—and the benefits of written cultures like Amazon vs. prototype cultures like Apple for different kinds of companies. - For developers building frameworks, always put the product first; a framework in isolation without a “customer zero” is never going to be a good tool. - The theory of “recursive founder mode”—if you want to build a scalable business, you have to scale yourself by creating an atmosphere that nurtures talent and ambition. - AI tools are shifting software toward consumption-based billing models, making us capital allocators who decide how much compute the AI consumes. - The future of AI is agents with the taste, knowledge, and tools to perform specialized tasks. Watch below! Timestamps: Introduction: 00:01:33 How to spot trends early: 00:03:18 Why you should be your own customer: 00:07:34 How to create an ecosystem of talent and ambition: 00:14:55 Why Guillermo doesn't identify as a coder: 00:17:29 AI is gearing us toward an allocation economy: 00:20:50 How Vercel’s copilot compares with other coding agents: 00:28:34 Guillermo’s advice on having better taste: 00:40:35 The future of AI agents is specialized: 00:42:46 How AI startups can compete with big tech: 00:47:50

Dan Shipper 📧

186,927 görüntüleme • 1 yıl önce

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
1:04:51

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 görüntüleme • 1 yıl önce

"AI is going to be the last technological innovation. There's nothing beyond this." Naveen Rao is rethinking the computer from first principles to make compute more power efficient for AI at Unconventional AI. Trey Holterman is automating healthcare's referral black hole at Tennr. They get into AI beating ER doctors at diagnosis, recursive self-improvement, and the cult-like belief inside frontier AI labs. They join @jason on This Week in AI, Episode 12: 00:51 Intro to Naveen Rao & Trey Holterman 05:43 Tennr & the healthcare black hole 09:09 The radiologist that wasn't replaced 15:31 AI beats ER doctors 67% to 55% 20:16 Plaud Pin in the exam room 25:20 Epic & the FHIR protocol 34:21 Disrupting Epic with open source 37:20 Abridge vs Ambience scribe wars 42:06 Jack Clark on recursive self-improvement 53:41 $1.1T hyperscaler CapEx 1:04:53 Anthropic & the AI religion thesis
1:17:00

"AI is going to be the last technological innovation. There's nothing beyond this." Naveen Rao is rethinking the computer from first principles to make compute more power efficient for AI at Unconventional AI. Trey Holterman is automating healthcare's referral black hole at Tennr. They get into AI beating ER doctors at diagnosis, recursive self-improvement, and the cult-like belief inside frontier AI labs. They join @jason on This Week in AI, Episode 12: 00:51 Intro to Naveen Rao & Trey Holterman 05:43 Tennr & the healthcare black hole 09:09 The radiologist that wasn't replaced 15:31 AI beats ER doctors 67% to 55% 20:16 Plaud Pin in the exam room 25:20 Epic & the FHIR protocol 34:21 Disrupting Epic with open source 37:20 Abridge vs Ambience scribe wars 42:06 Jack Clark on recursive self-improvement 53:41 $1.1T hyperscaler CapEx 1:04:53 Anthropic & the AI religion thesis

This Week in AI

33,275 görüntüleme • 2 ay önce

"AI doesn't take your job. AI makes you the CEO." Balaji Srinivasan joins a16z’s Erik Torenberg for a conversation on the future of the AI economy, decentralization, and how work changes in an AI-native world, including: - How distillation and open source could decentralize AI power - Why AI lowers the cost of creation but raises the cost of verification - The shift from global internet to “trusted tribes” and private AI - Why humans are the sensor and AI is the actuator 00:00 Intro 02:06 Why you want AI inside the trusted tribe, not outside it 05:35 The Problem with AI slop 09:25 Where AI works 17:08 "AI can't read your mind, but it can read your body." 30:10 "AI doesn't take your job. AI makes you the CEO." 46:01 The SaaSpocalypse: Real or overblown? 49:19 What happens if AI companies get bigger than governments? Balaji Erik Torenberg
1:05:44

"AI doesn't take your job. AI makes you the CEO." Balaji Srinivasan joins a16z’s Erik Torenberg for a conversation on the future of the AI economy, decentralization, and how work changes in an AI-native world, including: - How distillation and open source could decentralize AI power - Why AI lowers the cost of creation but raises the cost of verification - The shift from global internet to “trusted tribes” and private AI - Why humans are the sensor and AI is the actuator 00:00 Intro 02:06 Why you want AI inside the trusted tribe, not outside it 05:35 The Problem with AI slop 09:25 Where AI works 17:08 "AI can't read your mind, but it can read your body." 30:10 "AI doesn't take your job. AI makes you the CEO." 46:01 The SaaSpocalypse: Real or overblown? 49:19 What happens if AI companies get bigger than governments? Balaji Erik Torenberg

a16z

162,795 görüntüleme • 3 ay önce

YC and Together AI are partnering to bring the first dedicated YC GPU cluster online, giving YC startups easier access to the compute they need to build and scale. In this Founder Fireside, YC's Ankit Gupta and Together AI co-founder & CEO Vipul Ved Prakash dig into why compute has become one of the biggest bottlenecks for modern AI companies, how Together AI is helping more than 8,000 customers—from early-stage research teams to companies like Cursor, Cognition, and ElevenLabs—train, fine-tune, and serve AI models, and why flexible access to GPUs is becoming a competitive advantage for the next generation of founders. 00:00 — Partnering on a GPU Cluster 00:26 — What Together AI Does 01:22 — From Research Labs to Cursor: Together's 8,000 Customers 01:58 — The Landscape of AI Native Startups 03:24 — How Building an AI Company Has Changed Since 2018 04:56 — Why the Cost of Compute Keeps Going Up 05:29 — YC as the Biggest Seed Funder of Research Companies 08:47 — Flash Attention, Mamba, and the Science of Production AI 10:43 — Compute Planning Advice for Early Stage Companies 12:39 — When Your Compute Bill Is Bigger Than Your Cash Balance 13:31 — How Companies Are Using the Cluster Today 14:24 — What's Next
15:47

YC and Together AI are partnering to bring the first dedicated YC GPU cluster online, giving YC startups easier access to the compute they need to build and scale. In this Founder Fireside, YC's Ankit Gupta and Together AI co-founder & CEO Vipul Ved Prakash dig into why compute has become one of the biggest bottlenecks for modern AI companies, how Together AI is helping more than 8,000 customers—from early-stage research teams to companies like Cursor, Cognition, and ElevenLabs—train, fine-tune, and serve AI models, and why flexible access to GPUs is becoming a competitive advantage for the next generation of founders. 00:00 — Partnering on a GPU Cluster 00:26 — What Together AI Does 01:22 — From Research Labs to Cursor: Together's 8,000 Customers 01:58 — The Landscape of AI Native Startups 03:24 — How Building an AI Company Has Changed Since 2018 04:56 — Why the Cost of Compute Keeps Going Up 05:29 — YC as the Biggest Seed Funder of Research Companies 08:47 — Flash Attention, Mamba, and the Science of Production AI 10:43 — Compute Planning Advice for Early Stage Companies 12:39 — When Your Compute Bill Is Bigger Than Your Cash Balance 13:31 — How Companies Are Using the Cluster Today 14:24 — What's Next

Y Combinator

155,300 görüntüleme • 7 gün önce

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 görüntüleme • 1 yıl önce

At 23, with no legal background, Max Junestrand co-founded Legora to transform how lawyers work. Today, Legora’s AI workspace is used by tens of thousands of lawyers across Europe—valued at $675M just 13 months after launch. From due diligence grids that turn days of work into minutes, to Word integrations that renegotiate contracts, Max sat down with Gustaf Alströmer to share how Legora won over skeptical firms, scaled from 10 to 100 people, and built a new category in legal AI. 00:45 – Legora's Origin Story 01:00 – Building an AI Workspace for Lawyers 02:20 – The GPT Unlock 04:10 – The “Aha Moment” with Law Firms 06:15 – Raising $80M and Scaling Fast 06:30 – How Legora Works 09:40 – How It Transforms Legal Work 11:40 – Selling To AI Skeptics 14:40 – Creative Use Cases: From Court Battles to NDAs 17:30 – Starting Without Industry Expertise 18:40 – Interviewing 100 Lawyers 20:30 – Competing with Legacy Legal Tech Giants 23:50 – Tech Stack and Model Strategy 25:00 – Who Actually Buys AI inside a Law Firm? 27:00 – Cracking Sales in Conservative Industries 28:00 – Max’s Background: From eSports to Startups 30:50 – Hypergrowth: 10 → 100 People in 13 Months 34:00 – Why Hiring Ex-Founders Works 36:45 – The Future Job of a Lawyer 38:35 – What PMF Felt Like 39:45 – Why They Stayed in Stockholm (Not SF) 41:00 – Becoming the Category Leader in Legal AI 42:00 – Advice for Founders Building Vertical AI Companies 43:20 – What It’s Like to Work at Legora
45:25

At 23, with no legal background, Max Junestrand co-founded Legora to transform how lawyers work. Today, Legora’s AI workspace is used by tens of thousands of lawyers across Europe—valued at $675M just 13 months after launch. From due diligence grids that turn days of work into minutes, to Word integrations that renegotiate contracts, Max sat down with Gustaf Alströmer to share how Legora won over skeptical firms, scaled from 10 to 100 people, and built a new category in legal AI. 00:45 – Legora's Origin Story 01:00 – Building an AI Workspace for Lawyers 02:20 – The GPT Unlock 04:10 – The “Aha Moment” with Law Firms 06:15 – Raising $80M and Scaling Fast 06:30 – How Legora Works 09:40 – How It Transforms Legal Work 11:40 – Selling To AI Skeptics 14:40 – Creative Use Cases: From Court Battles to NDAs 17:30 – Starting Without Industry Expertise 18:40 – Interviewing 100 Lawyers 20:30 – Competing with Legacy Legal Tech Giants 23:50 – Tech Stack and Model Strategy 25:00 – Who Actually Buys AI inside a Law Firm? 27:00 – Cracking Sales in Conservative Industries 28:00 – Max’s Background: From eSports to Startups 30:50 – Hypergrowth: 10 → 100 People in 13 Months 34:00 – Why Hiring Ex-Founders Works 36:45 – The Future Job of a Lawyer 38:35 – What PMF Felt Like 39:45 – Why They Stayed in Stockholm (Not SF) 41:00 – Becoming the Category Leader in Legal AI 42:00 – Advice for Founders Building Vertical AI Companies 43:20 – What It’s Like to Work at Legora

Y Combinator

185,285 görüntüleme • 11 ay önce