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"This is not a product category." "They're not actually going to work on this." "They're going to acquihire themselves to somebody." When Christina Cacioppo (Christina Cacioppo) first pitched her startup in 2018, investors couldn't believe anyone would want to build compliance software. Eight years later, Vanta works with 16K+...

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Alex Konrad

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57,500 views • 2 months ago •via X (Twitter)

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MR SHIFT 🦁

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Salespeople have a problem: they only spend 21% of their time actually selling to customers 🤝 Mutiny CEO Jaleh Rezaei (Jaleh Rezaei) thought she'd found a way to fix it. She worked with customers like Snowflake and Uber. Revenue reached 8-figures 📈 Which makes what happened next all the more shocking: she burned it all down 🔥 On The Upstarts Podcast, Jaleh shares why she took the tough decision to fire her customers, slash headcount and re-found her startup around an AI agent. We go into AI's disruption of SaaS; her favorite advice from Fin's Des Traynor on pivoting and from Y Combinator's Garry Tan on showing the chart you don't want people to see; how to get over "Claude Spookies," and why speed is (mostly) all you need. This season of the show is presented by Rippling 🫡 CHAPTERS 00:00 Introduction 2:41 An AI agent for sales 7:04 Why an AI ‘blank canvas’ doesn’t work 10:38 Jaleh’s founder journey and Gusto lessons 17:01 Mutiny’s early software success 22:51 Jaleh’s Upstart Moment: tearing it down 24:42 Why you can’t rebuild a business halfway 27:15 Intercom’s founders share valuable advice 30:44 Focus on the business, not the optics 34:53 ‘Speed is the only thing that matters’ 37:40 ‘Claude spookies’ in the AI app layer 43:59 Second-time founder advantage Thanks for watching!
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Alex Konrad

99,147 views • 2 months ago

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Y Combinator

69,478 views • 1 month ago

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claire vo 🖤

19,127 views • 1 year ago

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
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Dan Shipper 📧

186,985 views • 1 year ago

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Gergely Orosz

17,126 views • 8 months ago

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1:12:54

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Matt Turck

49,647 views • 3 months ago

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30:54

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Y Combinator

102,871 views • 1 month ago

Palantir CEO Alex Karp says people think we’re in an AI bubble because a lot of AI just doesn’t work: “If you just buy LLMs off the shelf and try to do any of this, it won’t work.” “It’s not precise enough. You can’t do underwriting. You can’t do these things that are regulated.” “People have tried things that just can never work. You buy a LLM, put it on your stack, and wonder why it’s not working.” “What you’re going to see, especially in America, is people trying to do something like Ontology by hand.” “Once you build a software layer to orchestrate and manage the LLMs in a language your enterprise understands, you actually can create value.” “There’s a lot of discussion on if we’re in an AI bubble. What is the meaning of this bubble? If anything, we’re just in a lag. There’s a lot of AI, some of it works.” “Go back to the battlefield context: everybody in the world assumed this would not work. But now it does work. Now the question is, ‘How can I get it to work for my country?’” “Palantir barely has a sales force. In fact, it seems to be getting smaller and smaller every time I go see them.”
3:13

Palantir CEO Alex Karp says people think we’re in an AI bubble because a lot of AI just doesn’t work: “If you just buy LLMs off the shelf and try to do any of this, it won’t work.” “It’s not precise enough. You can’t do underwriting. You can’t do these things that are regulated.” “People have tried things that just can never work. You buy a LLM, put it on your stack, and wonder why it’s not working.” “What you’re going to see, especially in America, is people trying to do something like Ontology by hand.” “Once you build a software layer to orchestrate and manage the LLMs in a language your enterprise understands, you actually can create value.” “There’s a lot of discussion on if we’re in an AI bubble. What is the meaning of this bubble? If anything, we’re just in a lag. There’s a lot of AI, some of it works.” “Go back to the battlefield context: everybody in the world assumed this would not work. But now it does work. Now the question is, ‘How can I get it to work for my country?’” “Palantir barely has a sales force. In fact, it seems to be getting smaller and smaller every time I go see them.”

Jawwwn

695,479 views • 7 months ago

The AI OS. Talking with Phanindra Reddy, founder/CEO of AI is moving from "ask it a question" to "it does 90% of your work for you." Most people still use ChatGPT like a search engine. But a new wave of tools watches your email, calendar, and screen — then automates your actual workflow. I sat down with Phanindra, founder of Magic Teams AI OS, to unpack this new genre of AI tools. We covered: • How AI went from answering questions to end-to-end automation • The privacy debate — should an AI watch everything you do? • Why local-first storage matters for founders • What happens when AI tells YOU what to do next (not the other way around) • The future of SaaS when everyone can build their own tools Less than 0.1% of people even know this category exists. Worth paying attention. Watch the full conversation 👇
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The AI OS. Talking with Phanindra Reddy, founder/CEO of AI is moving from "ask it a question" to "it does 90% of your work for you." Most people still use ChatGPT like a search engine. But a new wave of tools watches your email, calendar, and screen — then automates your actual workflow. I sat down with Phanindra, founder of Magic Teams AI OS, to unpack this new genre of AI tools. We covered: • How AI went from answering questions to end-to-end automation • The privacy debate — should an AI watch everything you do? • Why local-first storage matters for founders • What happens when AI tells YOU what to do next (not the other way around) • The future of SaaS when everyone can build their own tools Less than 0.1% of people even know this category exists. Worth paying attention. Watch the full conversation 👇

Robert Scoble

20,051 views • 13 days ago

AI INTERVIEW: OPENAI'S SECRET WEAPON AI agents are no longer just hype—they're here to revolutionize automation, Web3, and beyond. SwarmNode.ai is building a serverless AI agent platform for scalability, efficiency, and real-world impact. In this exclusive interview, he reveals how AI swarms can outperform single models, why OpenAI’s Operator is just the beginning, and how crypto is fueling AI innovation. Plus, he breaks down DeepSeek’s game-changing AI breakthrough, the future of agent monetization, and why serverless AI could be the next frontier in automation. 01:37 – From Engineering to AI: The journey into artificial intelligence. 02:43 – The GPT-3 Moment: How OpenAI’s tech pulled him in. 04:10 – AI’s Biggest Challenge: Why real-world use cases lag behind. 05:05 – OpenAI’s Operator: Why it’s “rudimentary” (for now). 06:25 – Crypto & AI: How tokens help bootstrap AI startups. 08:15 – Can You Bootstrap a Startup with a Token? The trade-offs. 09:56 – 90% of AI Token Holders Don’t Use the Product—Does It Matter? 11:18 – What is SwarmNode?: AI agents, hosted serverlessly. 14:23 – AI Swarms: Why multiple agents outperform single models. 16:08 – What is a Swarm? A simple definition of collaborative AI. 17:32 – “How Can I Make Money with AI?”: Real-world use cases. 18:41 – AI Bounties: Hiring devs to build your custom agent. 20:50 – The Future of AI Marketplaces: Monetizing pre-built agents. 23:15 – DeepSeek’s Disruption: Why it’s good news for AI. 24:46 – Is SwarmNode Compatible with DeepSeek? How it integrates. 26:17 – SwarmNode vs. AI Launchpads: What makes it different? 27:42 – Why Serverless Matters: Cost savings & efficiency. 29:53 – AI Agents in the Real World: Booking flights, managing workflows, and more. 31:11 – Building SwarmNode for Developers: Why it started as a personal project. 32:27 – Explosive Growth: 200,000 AI agent executions in 5 weeks. 34:41 – Why SwarmNode Agents Aren’t Visible on 𝕏 Yet. 36:46 – Startup Hiring Lessons: Finding top AI talent. 39:15 – Why SwarmNode is Built in Python (and What’s Next). 40:32 – Scaling AI Workloads: Handling traffic surges. 41:42 – AWS & Cost Challenges: The biggest monetization hurdle. 42:58 – 2025: The Year of Mass AI Adoption. 45:22 – Should We Be Worried About AI’s Rapid Growth? 46:46 – The Most Underrated AI Tools Right Now. 47:34 – What’s Next for SwarmNode?: Making AI accessible to everyone.
49:12

AI INTERVIEW: OPENAI'S SECRET WEAPON AI agents are no longer just hype—they're here to revolutionize automation, Web3, and beyond. SwarmNode.ai is building a serverless AI agent platform for scalability, efficiency, and real-world impact. In this exclusive interview, he reveals how AI swarms can outperform single models, why OpenAI’s Operator is just the beginning, and how crypto is fueling AI innovation. Plus, he breaks down DeepSeek’s game-changing AI breakthrough, the future of agent monetization, and why serverless AI could be the next frontier in automation. 01:37 – From Engineering to AI: The journey into artificial intelligence. 02:43 – The GPT-3 Moment: How OpenAI’s tech pulled him in. 04:10 – AI’s Biggest Challenge: Why real-world use cases lag behind. 05:05 – OpenAI’s Operator: Why it’s “rudimentary” (for now). 06:25 – Crypto & AI: How tokens help bootstrap AI startups. 08:15 – Can You Bootstrap a Startup with a Token? The trade-offs. 09:56 – 90% of AI Token Holders Don’t Use the Product—Does It Matter? 11:18 – What is SwarmNode?: AI agents, hosted serverlessly. 14:23 – AI Swarms: Why multiple agents outperform single models. 16:08 – What is a Swarm? A simple definition of collaborative AI. 17:32 – “How Can I Make Money with AI?”: Real-world use cases. 18:41 – AI Bounties: Hiring devs to build your custom agent. 20:50 – The Future of AI Marketplaces: Monetizing pre-built agents. 23:15 – DeepSeek’s Disruption: Why it’s good news for AI. 24:46 – Is SwarmNode Compatible with DeepSeek? How it integrates. 26:17 – SwarmNode vs. AI Launchpads: What makes it different? 27:42 – Why Serverless Matters: Cost savings & efficiency. 29:53 – AI Agents in the Real World: Booking flights, managing workflows, and more. 31:11 – Building SwarmNode for Developers: Why it started as a personal project. 32:27 – Explosive Growth: 200,000 AI agent executions in 5 weeks. 34:41 – Why SwarmNode Agents Aren’t Visible on 𝕏 Yet. 36:46 – Startup Hiring Lessons: Finding top AI talent. 39:15 – Why SwarmNode is Built in Python (and What’s Next). 40:32 – Scaling AI Workloads: Handling traffic surges. 41:42 – AWS & Cost Challenges: The biggest monetization hurdle. 42:58 – 2025: The Year of Mass AI Adoption. 45:22 – Should We Be Worried About AI’s Rapid Growth? 46:46 – The Most Underrated AI Tools Right Now. 47:34 – What’s Next for SwarmNode?: Making AI accessible to everyone.

Mario Nawfal

338,265 views • 1 year ago

Nicholas Thorne (Nicholas Thorne) is building Squarespace for the AI age. It’s called Audos, and it’s an AI chatbot to help any entrepreneur go from idea to: - Pitch deck - Working website - Custom GPT - User interviews with real customers All in just a few minutes. And he did it using @ChatGPTapp. It’s AI all the way down—and it’s one of the most impressive early AI businesses I’ve ever seen. Nicholas is a good friend of mine and a general partner at Prehype, an incubator that launched BarkBox and Ro. It’s also where I started Every 🧱, so it was great to come full circle. Nicholas’s job at Prehype is to launch new companies. He’s taken everything he’s learned running an incubator and is using it to help entrepreneurs start businesses at scale—with AI. Nicholas tells me that he used @ChatGPTapp to prototype most of Audos’s features—despite being non-technical himself. He shares exactly how he did this by showing me how he’s using AI to create a new feature for the product. We get into: - Ways AI can make you a more effective founder - How to use ChatGPT to build your prototype - Strategies to refine problem statements with AI - Using GPTs to gather and synthesize customer feedback This episode is a must-watch for anyone who has ever toyed with the idea of starting a business—and wants to do it with AI. Watch! ___ Timestamps: Introduction: 00:48 How AI can make you a more effective founder: 12:10 Live demo of Audos! 17:03 Why Nicholas built an AI tool to enable entrepreneurs: 24:07 How Audos puts you in “edit mode” instead of “create mode”: 25:35 Tools to gather customer feedback, generated by Audos: 28:12 How Audos actually works: 32:58 Nicholas uses ChatGPT to prototype a new feature: 35:07 How to establish checks and balances while using ChatGPT: 42:37 AI as a force for pushing entrepreneurship to new heights: 57:20
1:00:48

Nicholas Thorne (Nicholas Thorne) is building Squarespace for the AI age. It’s called Audos, and it’s an AI chatbot to help any entrepreneur go from idea to: - Pitch deck - Working website - Custom GPT - User interviews with real customers All in just a few minutes. And he did it using @ChatGPTapp. It’s AI all the way down—and it’s one of the most impressive early AI businesses I’ve ever seen. Nicholas is a good friend of mine and a general partner at Prehype, an incubator that launched BarkBox and Ro. It’s also where I started Every 🧱, so it was great to come full circle. Nicholas’s job at Prehype is to launch new companies. He’s taken everything he’s learned running an incubator and is using it to help entrepreneurs start businesses at scale—with AI. Nicholas tells me that he used @ChatGPTapp to prototype most of Audos’s features—despite being non-technical himself. He shares exactly how he did this by showing me how he’s using AI to create a new feature for the product. We get into: - Ways AI can make you a more effective founder - How to use ChatGPT to build your prototype - Strategies to refine problem statements with AI - Using GPTs to gather and synthesize customer feedback This episode is a must-watch for anyone who has ever toyed with the idea of starting a business—and wants to do it with AI. Watch! ___ Timestamps: Introduction: 00:48 How AI can make you a more effective founder: 12:10 Live demo of Audos! 17:03 Why Nicholas built an AI tool to enable entrepreneurs: 24:07 How Audos puts you in “edit mode” instead of “create mode”: 25:35 Tools to gather customer feedback, generated by Audos: 28:12 How Audos actually works: 32:58 Nicholas uses ChatGPT to prototype a new feature: 35:07 How to establish checks and balances while using ChatGPT: 42:37 AI as a force for pushing entrepreneurship to new heights: 57:20

Dan Shipper 📧

36,351 views • 2 years ago

Nat Eliason’s (Nat Eliason) career arc is borderline absurd—but it works. He’ll spot a new tool or trend, master it, build a business around it, and move on. Nat’s pulled it off with the note-taking wave ($600k in sales from a Roam Research course), real estate (6x return flipping property in Austin), and crypto (published his insider story with Random House). Now it’s AI: he’s running a viral course on building apps with AI—$200k in pre-sales in just a week, 800 students and counting. I’ve known Nat for a long time and I think he has a great sense for where the puck is headed. He was one of the first guests I had on the podcast and I was delighted to have him on again. Here are a few takeaways from our conversation: - Coding with AI has become orders of magnitude easier for non-technical people over the last 2 years—Nat rarely has to help students fix bugs; they troubleshoot in Cursor on their own. - AI coding assistants are creating new behaviours in programming, like using a speech-to-text model to talk to an agent and having it write code for you. - The traditional learning curve of coding is flattening because AI tools let beginners build and iterate in faster feedback loops. - AI has given Nat leverage in spades—it increases his ability to be a creator while also building a robust business with as few people to manage as possible. He demos an AI book editor he coded for his sci-fi novel. - In the age of AI, software is becoming content and the barriers to create are lower than ever—but custom software for everything isn’t the answer. Nat’s model is that personalized tools make sense for that one thing you care the most about. - Nat believes that the future of writing with AI is a Cursor-style interface with a model that’s trained on your style and voice. This episode is a must-watch for writers, creators, and anyone interested in the future of product building. Watch below! Timestamps: Introduction: 00:01:45 The origins of Nat’s viral course on building apps with AI: 00:11:45 How coding with AI has evolved over the last two years: 00:18:46 Nat creates an app using Composer, Cursor’s AI assistant: 00:22:22 Tactical tips for coding with Cursor: 00:26:06 How coding with AI is creating new behaviours in programming: 00:29:06 What excites Nat the most about the future of AI: 00:32:41 A demo of Hubbard, the AI editor Nat built for his science fiction writing: 00:38:58 When does it makes sense to build custom software: 00:44:52 Nat’s take on the future of writing with AI: 00:49:18
1:00:52

Nat Eliason’s (Nat Eliason) career arc is borderline absurd—but it works. He’ll spot a new tool or trend, master it, build a business around it, and move on. Nat’s pulled it off with the note-taking wave ($600k in sales from a Roam Research course), real estate (6x return flipping property in Austin), and crypto (published his insider story with Random House). Now it’s AI: he’s running a viral course on building apps with AI—$200k in pre-sales in just a week, 800 students and counting. I’ve known Nat for a long time and I think he has a great sense for where the puck is headed. He was one of the first guests I had on the podcast and I was delighted to have him on again. Here are a few takeaways from our conversation: - Coding with AI has become orders of magnitude easier for non-technical people over the last 2 years—Nat rarely has to help students fix bugs; they troubleshoot in Cursor on their own. - AI coding assistants are creating new behaviours in programming, like using a speech-to-text model to talk to an agent and having it write code for you. - The traditional learning curve of coding is flattening because AI tools let beginners build and iterate in faster feedback loops. - AI has given Nat leverage in spades—it increases his ability to be a creator while also building a robust business with as few people to manage as possible. He demos an AI book editor he coded for his sci-fi novel. - In the age of AI, software is becoming content and the barriers to create are lower than ever—but custom software for everything isn’t the answer. Nat’s model is that personalized tools make sense for that one thing you care the most about. - Nat believes that the future of writing with AI is a Cursor-style interface with a model that’s trained on your style and voice. This episode is a must-watch for writers, creators, and anyone interested in the future of product building. Watch below! Timestamps: Introduction: 00:01:45 The origins of Nat’s viral course on building apps with AI: 00:11:45 How coding with AI has evolved over the last two years: 00:18:46 Nat creates an app using Composer, Cursor’s AI assistant: 00:22:22 Tactical tips for coding with Cursor: 00:26:06 How coding with AI is creating new behaviours in programming: 00:29:06 What excites Nat the most about the future of AI: 00:32:41 A demo of Hubbard, the AI editor Nat built for his science fiction writing: 00:38:58 When does it makes sense to build custom software: 00:44:52 Nat’s take on the future of writing with AI: 00:49:18

Dan Shipper 📧

27,207 views • 1 year ago

"We'll get to a point in intelligence where the human making that decision is going to be less efficient than the AI making that decision themselves." My full conversation with the head of AI at the Solana Foundation on the world coming fast, where AI starts earning, investing and outpacing the humans who built it. 00:00 Intro 02:46 The Wall Street dream he ditched 06:50 The cold email that changed everything 08:07 Meeting the founder of Stable Diffusion 11:36 Why Rishin left investing to build AI 20:31 When AI starts paying for things itself 23:36 The moment that predicted the future 31:35 Three people, five weeks, one product 38:01 When AI stops asking you first 41:09 When your customer is a robot 44:01 How much of the economy will AI run
48:32

"We'll get to a point in intelligence where the human making that decision is going to be less efficient than the AI making that decision themselves." My full conversation with the head of AI at the Solana Foundation on the world coming fast, where AI starts earning, investing and outpacing the humans who built it. 00:00 Intro 02:46 The Wall Street dream he ditched 06:50 The cold email that changed everything 08:07 Meeting the founder of Stable Diffusion 11:36 Why Rishin left investing to build AI 20:31 When AI starts paying for things itself 23:36 The moment that predicted the future 31:35 Three people, five weeks, one product 38:01 When AI stops asking you first 41:09 When your customer is a robot 44:01 How much of the economy will AI run

JackGK

19,233 views • 1 month ago