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Every major shift in consumer tech has a moment when it suddenly becomes accessible to millions. Michael Mignano (Michael Mignano) helped spark one of those moments with Anchor, making podcast creation something anyone could do with a tap. Now at Lightspeed, he sees AI bringing a similar leap to... music, media, and everyday apps. In this conversation, Michael and Garry Tan trace the arc from the early days of social audio to today's consumer AI boom—and dig into what founders should focus on as the next generation of creative tools takes shape. 00:51 - Michael’s founder experience 06:43 - Consumer landscape and AI impact 08:26 - What makes consumer different from other spaces 10:00 - AI costs and distribution challenges 13:20 - Listening to the users, growth rules 16:40 - Ecosystem integration, distribution 19:52 - AI-generated content & social media 30:00 - Taste, craft, model energy 33:20 - Data opportunitiesshow more

Y Combinator

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134,448 次观看 • 7 个月前 •via X (Twitter)

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Where are all the consumer AI apps??? This is the question I posed to s-tier consumer investors scott belsky (Uber, Pinterest) and steve jang (Coinbase, Postmates). We're almost 3 years into the AI hype the we're still all mostly just talking about ChatGPT, Perplexity, and Claude. We explore the answer through the ways in which the entire consumer stack (input, memory, personalization, browsers, hardware) are being re-written by AI and how that may give birth to the consumer opportunity we've all been waiting for. Chapters: 00:00 Welcome and Introductions 00:43 The Current State of AI Products 02:48 Surprises and Challenges with LLMs 05:24 Future of Consumer AI and Personal AI 15:49 Memory and Personalization in AI 21:52 Potential Risks and Business Models 24:22 The Battle for User Data in AI 25:11 Optimism in AI Model Inference 27:00 The Role of Open Source Models 28:13 The Future of AI Hardware 28:54 Challenges and Opportunities in AI Hardware Startups 30:29 The Evolution of Consumer Hardware 38:36 The Reinvention of Browsers 46:23 The Potential of AI-Enhanced Browsers 47:54 Conclusion and Final Thoughts Many thanks to my good friends for joining me in this discussion 🙏

Where are all the consumer AI apps??? This is the question I posed to s-tier consumer investors scott belsky (Uber, Pinterest) and steve jang (Coinbase, Postmates). We're almost 3 years into the AI hype the we're still all mostly just talking about ChatGPT, Perplexity, and Claude. We explore the answer through the ways in which the entire consumer stack (input, memory, personalization, browsers, hardware) are being re-written by AI and how that may give birth to the consumer opportunity we've all been waiting for. Chapters: 00:00 Welcome and Introductions 00:43 The Current State of AI Products 02:48 Surprises and Challenges with LLMs 05:24 Future of Consumer AI and Personal AI 15:49 Memory and Personalization in AI 21:52 Potential Risks and Business Models 24:22 The Battle for User Data in AI 25:11 Optimism in AI Model Inference 27:00 The Role of Open Source Models 28:13 The Future of AI Hardware 28:54 Challenges and Opportunities in AI Hardware Startups 30:29 The Evolution of Consumer Hardware 38:36 The Reinvention of Browsers 46:23 The Potential of AI-Enhanced Browsers 47:54 Conclusion and Final Thoughts Many thanks to my good friends for joining me in this discussion 🙏

Michael Mignano

25,155 次观看 • 11 个月前

AI has ignited a consumer renaissance. My friend Kevin Rose is a legend in consumer tech. He founded a number of early internet startups, including Digg, where he invented an early predecessor to the now ubiquitous like button. He’s now a partner at True Ventures and recently relaunched Digg. We had a wide-ranging conversation on all things consumer tech, including why I think AI code will be an entire industry, why Kevin looks for “weird and working” products, Kevin’s dinners with Mark Zuckerberg, and how AI products will affect the human experience. 00:00 Intro 02:10 How we met 07:50 AI’s Renaissance for Consumer Products 11:48 Companionship apps and the future of human connection 14:01 The optimistic and pessimistic views on AI relationships 19:18 Poke and emotional primitives 21:05 Weird and working: how to spot great founders 30:05 AI companions and AI in relationships 40:08 The modern AI dev stack and building apps solo 47:25 AI music, creativity, and the next cultural wave 53:50 Curiosity, risk, and finding the next big thing 01:15:00 Always-on recording and social norms in tech

AI has ignited a consumer renaissance. My friend Kevin Rose is a legend in consumer tech. He founded a number of early internet startups, including Digg, where he invented an early predecessor to the now ubiquitous like button. He’s now a partner at True Ventures and recently relaunched Digg. We had a wide-ranging conversation on all things consumer tech, including why I think AI code will be an entire industry, why Kevin looks for “weird and working” products, Kevin’s dinners with Mark Zuckerberg, and how AI products will affect the human experience. 00:00 Intro 02:10 How we met 07:50 AI’s Renaissance for Consumer Products 11:48 Companionship apps and the future of human connection 14:01 The optimistic and pessimistic views on AI relationships 19:18 Poke and emotional primitives 21:05 Weird and working: how to spot great founders 30:05 AI companions and AI in relationships 40:08 The modern AI dev stack and building apps solo 47:25 AI music, creativity, and the next cultural wave 53:50 Curiosity, risk, and finding the next big thing 01:15:00 Always-on recording and social norms in tech

Anish Acharya

38,002 次观看 • 8 个月前

What our consumer team expects in 2026 for AI: - Enterprise usage drives consumer usage - More app generation - More multimodality: Anything-in, anything-out - Better models enable startups to fill niches with opinionated products a16z's Anish Acharya, Bryan Kim, Olivia Moore, and Justine Moore sat down for a conversation on the state of consumer AI, including what we saw in 2025 and what's coming in 2026. They cover the “winner-take-most” trend for general-purpose LLMs, the role of brand in distribution, great products that flew under the radar in 2025, and more. 00:00 Introduction & market overview 00:35 Who won consumer AI in 2025? 02:24 Image and video model innovations 09:11 Underhyped products and productivity apps 10:21 Prosumer tools and power user workflows 12:56 Distribution and brand 14:04 Product nuances: Onboarding and engagement 16:09 Social features 26:54 Looking to 2026: Enterprise, apps, and multimodality 32:02 Startup opportunities and app generation 36:27 Favorite products and recommendations 42:19 Building consumer products in 2026 Anish Acharya Bryan Kim Olivia Moore Justine Moore

a16z

66,374 次观看 • 6 个月前

BREAKING: Lightspeed’s Bets on xAI, Neuralink, Suno, Pika, Granola, Macroscope Michael Mignano (Michael Mignano), Lightspeed We cover: - Why Lightspeed invested in 'competing' LLMs (xAI, Anthropic, Mistral, Stability AI) - Current ~$7B investment strategy - Lessons from Spotify’s Daniel Ek - "The End of the Creator" re: Sora - Founding Oboe w/ Anchor Co-Founder Nir Zicherman (Nir Zicherman) - Thoughts on 2026’s potential IPO candidates. Michael Mignano (Michael Mignano), Partner at ~$30B megafund Lightspeed, & Co-Founder of Anchor, a podcast creation, hosting, & monetization platform acquired by Spotify in 2019 Highlights: (00:00) Michael Mignano (01:06) Anchor’s pivot & podcasting’s breakout moment (02:32) Spotify’s Talk: podcasts, video, & live audio (02:55) Why synchronous (live) formats fail online (03:27) Joining Lightspeed & portfolio overview (03:47) Investment thesis: creativity, product taste, founders (05:24) How xAI & Neuralink fit Lightspeed’s strategy (06:56) Is OpenAI “Sherlocking” ? (08:37) Granola & retention as the real AI moat (09:52) Why ARR can be FAKE in AI startups (11:20) Seed vs Series A check sizes & AI valuation premiums (19:34) Sora, avatars, recommendation media, & creator economics (33:37) Oboe: AI education & human intelligence (40:01) Lessons from Daniel Ek (Daniel Ek) & Spotify’s long-term strategy (42:55) IPO predictions

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Molly O’Shea

107,084 次观看 • 6 个月前

Sarah Tavel (Sarah Tavel) thinks it's criminal that ChatGPT isn’t inherently social. There’s no easy way to discover great prompts or share the ones that worked. As a venture partner Benchmark, Sarah believes that the next wave of consumer AI will be built on this missing social layer—by product-driven founders who understand people, not just models. Sarah has seen this shift before. As one of Pinterest’s first product managers, she saw the company grow from a niche consumer tool to a beloved global community. On this episode of Every 📧’s podcast AI & I, we talk about how she’s applying the lessons she learned to AI—and what it takes to build a breakout consumer AI app today. We get into: - Why product geniuses win as new tech matures. In the early days of a new technology, companies win by wrangling raw innovation into something usable. But as the infrastructure matures, Sarah says the edge shifts to product thinkers—founders who turn new capabilities into delightful user experiences. - The future of prompting is social. When Sarah had to dig through Reddit to find a prompt to help her interpret her blood test results, she saw a gap: The best prompt creators are invisible. Sarah bets that a social AI product that makes them discoverable and followable would gain traction. - Sarah’s method to spot exceptional founders. Sarah backs founders for whom building a company feels like a calling—or even an affliction. These are people who have fallen in love with the process and are obsessed with learning how to grow alongside their companies. -How LLMs change the way the best VCs invest. Sarah thinks the future of venture will be shaped by how well VCs can turn the decisions they make into training data. After every pitch, she logs what she liked, what she didn’t, the deal terms, and her reasoning. Over time, she’s building a dataset of her own judgment—one an LLM could help her use to pressure-test decisions and avoid past mistakes. This is a must-watch for if you’re building a consumer AI product and want to see ahead of the curve. Watch below! Timestamps: Introduction: 00:01:10 Why the future of consumer AI belongs to founders with product intuition: 00:02:26 What Sarah sees as ChatGPT’s biggest weakness: 00:11:09 How Sarah would design a consumer AI app with social DNA: 00:18:45 The kind of founders Sarah invests in: 00:24:10 How to know if your startup’s network-effects are real: 00:28:33 What’s catching Sarah’s eye beyond AI: 00:35:40 How AI will change the way top venture capitalists invest: 00:40:41

Sarah Tavel (Sarah Tavel) thinks it's criminal that ChatGPT isn’t inherently social. There’s no easy way to discover great prompts or share the ones that worked. As a venture partner Benchmark, Sarah believes that the next wave of consumer AI will be built on this missing social layer—by product-driven founders who understand people, not just models. Sarah has seen this shift before. As one of Pinterest’s first product managers, she saw the company grow from a niche consumer tool to a beloved global community. On this episode of Every 📧’s podcast AI & I, we talk about how she’s applying the lessons she learned to AI—and what it takes to build a breakout consumer AI app today. We get into: - Why product geniuses win as new tech matures. In the early days of a new technology, companies win by wrangling raw innovation into something usable. But as the infrastructure matures, Sarah says the edge shifts to product thinkers—founders who turn new capabilities into delightful user experiences. - The future of prompting is social. When Sarah had to dig through Reddit to find a prompt to help her interpret her blood test results, she saw a gap: The best prompt creators are invisible. Sarah bets that a social AI product that makes them discoverable and followable would gain traction. - Sarah’s method to spot exceptional founders. Sarah backs founders for whom building a company feels like a calling—or even an affliction. These are people who have fallen in love with the process and are obsessed with learning how to grow alongside their companies. -How LLMs change the way the best VCs invest. Sarah thinks the future of venture will be shaped by how well VCs can turn the decisions they make into training data. After every pitch, she logs what she liked, what she didn’t, the deal terms, and her reasoning. Over time, she’s building a dataset of her own judgment—one an LLM could help her use to pressure-test decisions and avoid past mistakes. This is a must-watch for if you’re building a consumer AI product and want to see ahead of the curve. Watch below! Timestamps: Introduction: 00:01:10 Why the future of consumer AI belongs to founders with product intuition: 00:02:26 What Sarah sees as ChatGPT’s biggest weakness: 00:11:09 How Sarah would design a consumer AI app with social DNA: 00:18:45 The kind of founders Sarah invests in: 00:24:10 How to know if your startup’s network-effects are real: 00:28:33 What’s catching Sarah’s eye beyond AI: 00:35:40 How AI will change the way top venture capitalists invest: 00:40:41

Dan Shipper 📧

72,543 次观看 • 1 年前

NEW EP: The Massive 'Infra to Apps' Shift in Crypto Investing with Wei Dai For today's episode, & Wayne Sim had Wei Dai, a research partner of 1kx, on to cover: > The shift from infra to apps > Investing in blockchain apps > Rollup clusters and interop > Consumer apps and brands Full episode links below. Timestamps: 00:00 Intro 01:26 Wei’s Intro To Crypto 05:30 Technical Valuation Metrics 13:33 New Chain Network Effects 21:14 What Are Rollup Clusters? 27:06 Next Iteration of Consumer Apps

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The Rollup

31,595 次观看 • 1 年前

Alex Elias (Alex Elias), CEO & Founder of Qloo, joined us on the SourceForge Podcast to discuss AI and how AI can be used to predict and decode consumer taste. Qloo is a taste AI company that offers a unique and privacy-centric solution for understanding consumer taste across various industries, and discusses the evolution of Qloo and the AI industry.

Alex Elias (Alex Elias), CEO & Founder of Qloo, joined us on the SourceForge Podcast to discuss AI and how AI can be used to predict and decode consumer taste. Qloo is a taste AI company that offers a unique and privacy-centric solution for understanding consumer taste across various industries, and discusses the evolution of Qloo and the AI industry.

SourceForge

13,167 次观看 • 2 年前

Kirsten Green (Kirsten Green), founder of Forerunner Ventures, has backed some of the most iconic consumer brands of the past two decades — from Warby Parker to Chime to Dollar Shave Club. She sat down with Garry Tan to share how great products (not marketing tricks) still win, why AI is unlocking a new kind of emotional relationship between consumers and technology, and what founders can learn from the messy creative stage we're in right now. Kirsten also breaks down how shifts in distribution, wellness, and digital behavior are reshaping what it means to build for real human needs. 01:05 - What will the consumer AI wave look like? 04:54 - The ability to have memory 07:35 - Data personalization 08:58 - Voice as an unlock 11:07 - The messy creative stage of consumer AI 12:07 - How to nail distribution 14:58 - Don’t just do things for the sake of marketing 16:09 - Why the Dollar Shave Club ad worked so well 17:39 - What convinced Kirsten to invest in Dollar Shave Club 20:16 - What large companies are realizing about search & marketing 23:02 - How will we use different AI tools as consumers? 26:20 - Forerunner’s latest trend report on health, wellness, security 32:16 - How do you compete against ChatGPT? 33:52 - Advice for new founders

Kirsten Green (Kirsten Green), founder of Forerunner Ventures, has backed some of the most iconic consumer brands of the past two decades — from Warby Parker to Chime to Dollar Shave Club. She sat down with Garry Tan to share how great products (not marketing tricks) still win, why AI is unlocking a new kind of emotional relationship between consumers and technology, and what founders can learn from the messy creative stage we're in right now. Kirsten also breaks down how shifts in distribution, wellness, and digital behavior are reshaping what it means to build for real human needs. 01:05 - What will the consumer AI wave look like? 04:54 - The ability to have memory 07:35 - Data personalization 08:58 - Voice as an unlock 11:07 - The messy creative stage of consumer AI 12:07 - How to nail distribution 14:58 - Don’t just do things for the sake of marketing 16:09 - Why the Dollar Shave Club ad worked so well 17:39 - What convinced Kirsten to invest in Dollar Shave Club 20:16 - What large companies are realizing about search & marketing 23:02 - How will we use different AI tools as consumers? 26:20 - Forerunner’s latest trend report on health, wellness, security 32:16 - How do you compete against ChatGPT? 33:52 - Advice for new founders

Y Combinator

176,034 次观看 • 1 年前

We want to make AI accessible for everyone, so we're reducing our API prices by ~50%. Consumer AI growth is still blocked by model costs. 97% of consumer AI users will never pay. But every session still consumes tokens. This is the math we've found every consumer AI developer is stuck with. The model pricing they're forced to use, was built for $300/mo enterprise seats, not $10/month consumer subscriptions. So we're taking a step to solve this with reduced pricing across TTS, STT and LLMs. Teams like Wishroll, Biblechat, Talkpal, and Luvu are already seeing 40-95% reductions in their AI costs. Full breakdown on our blog: Pricing details in bio link.

We want to make AI accessible for everyone, so we're reducing our API prices by ~50%. Consumer AI growth is still blocked by model costs. 97% of consumer AI users will never pay. But every session still consumes tokens. This is the math we've found every consumer AI developer is stuck with. The model pricing they're forced to use, was built for $300/mo enterprise seats, not $10/month consumer subscriptions. So we're taking a step to solve this with reduced pricing across TTS, STT and LLMs. Teams like Wishroll, Biblechat, Talkpal, and Luvu are already seeing 40-95% reductions in their AI costs. Full breakdown on our blog: Pricing details in bio link.

Inworld AI

617,699 次观看 • 28 天前

In 2026, I believe we'll see a Consumer AI Renaissance. Consumer spending is the lifeblood of the US economy – representing more than 65% of US GDP. AI is already rapidly transforming how we spend both our money and time. In just the past 3 years, ChatGPT has become the fastest growing consumer product in history – reaching billions of users with engagement levels similar to social media apps like WhatsApp and Instagram. And with recent advancement in AI capabilities, I predict we’ll see a new wave of breakout consumer AI applications. We’ve seen major advances in three key areas: 1. Real-time voice AI - which allows users to engage with AI products in a natural, hands-free way 2. Advanced reasoning models - which improves the complexity of questions AI products can answer 3. Embedded Memory - which allows AI products to remember context between conversations, enabling more personalized responses With these new capabilities, we can now build AI products that are 10x better than before. I’m especially excited about products that use AI to make previously expensive services cheaper and more accessible, sometimes using human-in-the-loop to start. This includes things like AI travel agents, personal assistants, matchmakers, therapists, tutors, and more. We’ve already seen a number of early-stage teams working on these at a16z a16z speedrun 🧊 – and we’re excited to meet more. If you’re building the next generation of consumer AI, we’d love to hear from you! h/t to Theresa Horne Avenir whose excellent research helped inspire some of these insights.

In 2026, I believe we'll see a Consumer AI Renaissance. Consumer spending is the lifeblood of the US economy – representing more than 65% of US GDP. AI is already rapidly transforming how we spend both our money and time. In just the past 3 years, ChatGPT has become the fastest growing consumer product in history – reaching billions of users with engagement levels similar to social media apps like WhatsApp and Instagram. And with recent advancement in AI capabilities, I predict we’ll see a new wave of breakout consumer AI applications. We’ve seen major advances in three key areas: 1. Real-time voice AI - which allows users to engage with AI products in a natural, hands-free way 2. Advanced reasoning models - which improves the complexity of questions AI products can answer 3. Embedded Memory - which allows AI products to remember context between conversations, enabling more personalized responses With these new capabilities, we can now build AI products that are 10x better than before. I’m especially excited about products that use AI to make previously expensive services cheaper and more accessible, sometimes using human-in-the-loop to start. This includes things like AI travel agents, personal assistants, matchmakers, therapists, tutors, and more. We’ve already seen a number of early-stage teams working on these at a16z a16z speedrun 🧊 – and we’re excited to meet more. If you’re building the next generation of consumer AI, we’d love to hear from you! h/t to Theresa Horne Avenir whose excellent research helped inspire some of these insights.

Kenan Saleh

15,846 次观看 • 6 个月前

Most people experience AI through apps. Those apps run on infrastructure owned by a handful of companies. Ben Fielding and Harry Grieve of gensyn on why that needs to change, and what it's going to take to rebuild AI as crypto-native open infrastructure. 00:00 – Intro 00:29 – Misconceptions about AI infrastructure 01:20 – Why centralization in AI is a deeper problem than people realize 04:19 – Why AI needs crypto 05:51 – How AI models are trained 08:15 – The rise of autonomous AI agents with onchain identities 10:37 – Lightning round

Most people experience AI through apps. Those apps run on infrastructure owned by a handful of companies. Ben Fielding and Harry Grieve of gensyn on why that needs to change, and what it's going to take to rebuild AI as crypto-native open infrastructure. 00:00 – Intro 00:29 – Misconceptions about AI infrastructure 01:20 – Why centralization in AI is a deeper problem than people realize 04:19 – Why AI needs crypto 05:51 – How AI models are trained 08:15 – The rise of autonomous AI agents with onchain identities 10:37 – Lightning round

a16z crypto

24,109 次观看 • 2 个月前

As ever, a fascinating chat with my friend Jordi Visser on AI, crypto, and hedge funds' future... Enjoy! 00:00:00 Introduction 00:00:54 The Big Picture: AI, Crypto, and Macro 00:02:25 Jordie Visser’s Background in Macro and Finance 00:03:30 AI’s Disruptive Impact on the Economy 00:06:32 Rethinking GDP and Productivity 00:08:59 The Future of Labor and Profit Margins 00:10:49 The Rise of the Speculative Economy 00:14:41 Generational Shifts in Investing and Risk-taking 00:16:18 AI and Crypto: A Global Network Effect 00:19:38 Stablecoins and AI-Driven Market Volume Growth 00:24:28 The End of Traditional Hedge Funds? 00:31:16 Deep Research and the Power of AI Analysis 00:35:29 The Acceleration of AI and its Economic Impact 00:41:02 The Growing Crypto Adoption and Its Role in the Future Economy 00:44:22 Shifting from Fear to Optimism in Markets 00:50:27 The Political and Economic Challenges Ahead 00:56:01 Quantum Computing and the Next Leap in AI 01:02:06 Closing Thoughts: Preparing for a Radical Future

As ever, a fascinating chat with my friend Jordi Visser on AI, crypto, and hedge funds' future... Enjoy! 00:00:00 Introduction 00:00:54 The Big Picture: AI, Crypto, and Macro 00:02:25 Jordie Visser’s Background in Macro and Finance 00:03:30 AI’s Disruptive Impact on the Economy 00:06:32 Rethinking GDP and Productivity 00:08:59 The Future of Labor and Profit Margins 00:10:49 The Rise of the Speculative Economy 00:14:41 Generational Shifts in Investing and Risk-taking 00:16:18 AI and Crypto: A Global Network Effect 00:19:38 Stablecoins and AI-Driven Market Volume Growth 00:24:28 The End of Traditional Hedge Funds? 00:31:16 Deep Research and the Power of AI Analysis 00:35:29 The Acceleration of AI and its Economic Impact 00:41:02 The Growing Crypto Adoption and Its Role in the Future Economy 00:44:22 Shifting from Fear to Optimism in Markets 00:50:27 The Political and Economic Challenges Ahead 00:56:01 Quantum Computing and the Next Leap in AI 01:02:06 Closing Thoughts: Preparing for a Radical Future

Raoul Pal

280,145 次观看 • 1 年前

A former lawyer turned founder, Jake Heller set out to make legal work faster, fairer, and more accessible through AI with Casetext (acquired by Thomson Reuters for $650M in 2023). On the Social Radars, he shares how a weekend with an early version of GPT-4 convinced him to pivot the entire company, what it means to be in founder mode during moments of extreme technological change, and how a decade of grinding led to one of the biggest exits in legal tech. 01:20 – Founding Casetext 03:10 – Early Struggles in Legal Tech 06:00 – The Decade-Long Grind to PMF 08:15 – A Weekend with GPT-4 That Changed Everything 11:30 – Pivoting the Company Around AI 14:40 – Building Trust in AI for Legal Work 17:50 – Scaling Casetext to Thousands of Firms 21:10 – Acquisition by Thomson Reuters for $650M 24:00 – What It Means to Stay in Founder Mode 26:20 – Lessons for Founders in Highly Regulated Industries 28:10 – The Future of AI and the Law

A former lawyer turned founder, Jake Heller set out to make legal work faster, fairer, and more accessible through AI with Casetext (acquired by Thomson Reuters for $650M in 2023). On the Social Radars, he shares how a weekend with an early version of GPT-4 convinced him to pivot the entire company, what it means to be in founder mode during moments of extreme technological change, and how a decade of grinding led to one of the biggest exits in legal tech. 01:20 – Founding Casetext 03:10 – Early Struggles in Legal Tech 06:00 – The Decade-Long Grind to PMF 08:15 – A Weekend with GPT-4 That Changed Everything 11:30 – Pivoting the Company Around AI 14:40 – Building Trust in AI for Legal Work 17:50 – Scaling Casetext to Thousands of Firms 21:10 – Acquisition by Thomson Reuters for $650M 24:00 – What It Means to Stay in Founder Mode 26:20 – Lessons for Founders in Highly Regulated Industries 28:10 – The Future of AI and the Law

Y Combinator

144,202 次观看 • 9 个月前

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

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 次观看 • 9 个月前

On frontier science: stepping into the golden age of energy tech In conversation with Danielle Fong Danielle Fong 🔆 00:45 Danielle’s background, starting with college at 12 04:16 The global energy crisis 11:15 Productizing: from drones to data centers 14:00 Powering your future openclaw with propane 14:34 US gov vs consumer applications 19:30 AI, data centers, and new energy sources 23:25 Agentic tools at Lightcell 27:54 Leveraging models across providers 29:54 Iterating on frontier science 43:22 Hyperscalers and the golden age of energy tech

On frontier science: stepping into the golden age of energy tech In conversation with Danielle Fong Danielle Fong 🔆 00:45 Danielle’s background, starting with college at 12 04:16 The global energy crisis 11:15 Productizing: from drones to data centers 14:00 Powering your future openclaw with propane 14:34 US gov vs consumer applications 19:30 AI, data centers, and new energy sources 23:25 Agentic tools at Lightcell 27:54 Leveraging models across providers 29:54 Iterating on frontier science 43:22 Hyperscalers and the golden age of energy tech

ashe

61,597 次观看 • 3 个月前

FULL INTERVIEW: Moltbook creator Matt Schlicht on his viral social network for AI agents, the future of AI and social media, where Moltbook is headed, and more 00:31 Matt's background and early career 02:10 How he started Moltbook 05:04 Reaction to Moltbook going viral 06:08 How Moltbook works 10:08 Moltbook's future 13:40 Privacy, safety, and data concerns 14:26 Fundraising, team expansion, and YC 16:52 The utility and value of Moltbook 20:30 Bots and social media 22:27 Upcoming Moltbook features

FULL INTERVIEW: Moltbook creator Matt Schlicht on his viral social network for AI agents, the future of AI and social media, where Moltbook is headed, and more 00:31 Matt's background and early career 02:10 How he started Moltbook 05:04 Reaction to Moltbook going viral 06:08 How Moltbook works 10:08 Moltbook's future 13:40 Privacy, safety, and data concerns 14:26 Fundraising, team expansion, and YC 16:52 The utility and value of Moltbook 20:30 Bots and social media 22:27 Upcoming Moltbook features

TBPN

33,245 次观看 • 5 个月前

on the frontier of consumer wearables: building an egoless AI product in conversation with Mina Fahmi, building Sandbar between Mina's eloquence and our nyc galavanting, this conversation feels like a work of art. stoked to be able to share it dive in: 00:34 Mina's background 01:42 Robotics, neural interfaces, and hardware 06:06 Bringing nervous system work into designing AI products 10:25 Building with voice 12:38 AI extending self-concept 19:05 AI sycophancy 24:58 Agentic memory 30:11 Hardware decisions at Sandbar 34:16 Hiring at Sandbar 36:04 Bringing AI to more people

on the frontier of consumer wearables: building an egoless AI product in conversation with Mina Fahmi, building Sandbar between Mina's eloquence and our nyc galavanting, this conversation feels like a work of art. stoked to be able to share it dive in: 00:34 Mina's background 01:42 Robotics, neural interfaces, and hardware 06:06 Bringing nervous system work into designing AI products 10:25 Building with voice 12:38 AI extending self-concept 19:05 AI sycophancy 24:58 Agentic memory 30:11 Hardware decisions at Sandbar 34:16 Hiring at Sandbar 36:04 Bringing AI to more people

ashe

33,638 次观看 • 2 个月前

"A week is 2% of the year. The cadence we operate on is: A week is not the shortest timeline. It's the longest timeline. What can we decide by tomorrow?" - Michael Grinich. Michael Grinich. Founder and CEO of WorkOS. The company powering the enterprise adoption of AI. Knuckle Up ↓ -- 00:00 Introduction 01:33 From design-obsessed founder to enterprise infrastructure 04:20 Michael’s year off and what made the WorkOS bet obvious 06:54 Why a great startup idea has to look bad first 09:46 Minimum awesome product beats MVP 11:09 The org with no CRO, no VP of sales, and one PM 13:29 Hiring for curiosity, not credentials 16:25 The "AI pilled" interview red flag 18:25 A week is 2% of the year 26:00 How WorkOS approaches brand 33:00 The future shape of engineering orgs 43:20 Why senior engineers benefit most from AI 44:45 Micro-leadership over micromanagement 49:10 Tough times in the early days 59:04 The reverse Peter principle 1:04:38 Quickfire: red flags, hires too early, and biggest fears 1:10:30 Michael's advice to his 25-year-old self

Nakul Mandan

671,022 次观看 • 2 个月前

Michael Truell (Michael Truell), co-founder and CEO of Anysphere, the company behind Cursor, joined Garry Tan to talk about building one of the fastest-growing startups of all time—and why he's betting everything on a world beyond code. He walks through the early insights that led him and his co-founders to leave a promising AI-powered CAD project and instead chase a bigger dream: reinventing how software is written. From the hard years of false starts and rewrites to Cursor's breakthrough moment, Michael explains what it really takes to build a tool that could eventually replace programming as we know it. He also reflects on their first 10 hires, why taste still matters, and how the decade ahead will unlock a new kind of creativity for builders everywhere. 01:00 - A new way to build software 04:50 - Two ways to view LLMs 05:50 - Bottlenecks to superhuman agents 08:30 - New approaches to coding UI 09:40 - Why taste still matters 12:15 - Niche software opportunities 13:30 - Cursor origin story 16:00 - The first problem they tried solving 17:20 - Why they abandoned the CAD idea 21:00 - Pivoting to Cursor 23:00 - Following the scaling laws 27:00 - Getting to PMF 30:00 - “Dogfooding” 31:00 - First 10 hires 32:50 - How to evaluate great engineers 33:45 - Maintaining the hacker mindset 35:00 - What are the moats for AI coding tools? 37:00 - Looking ahead

Michael Truell (Michael Truell), co-founder and CEO of Anysphere, the company behind Cursor, joined Garry Tan to talk about building one of the fastest-growing startups of all time—and why he's betting everything on a world beyond code. He walks through the early insights that led him and his co-founders to leave a promising AI-powered CAD project and instead chase a bigger dream: reinventing how software is written. From the hard years of false starts and rewrites to Cursor's breakthrough moment, Michael explains what it really takes to build a tool that could eventually replace programming as we know it. He also reflects on their first 10 hires, why taste still matters, and how the decade ahead will unlock a new kind of creativity for builders everywhere. 01:00 - A new way to build software 04:50 - Two ways to view LLMs 05:50 - Bottlenecks to superhuman agents 08:30 - New approaches to coding UI 09:40 - Why taste still matters 12:15 - Niche software opportunities 13:30 - Cursor origin story 16:00 - The first problem they tried solving 17:20 - Why they abandoned the CAD idea 21:00 - Pivoting to Cursor 23:00 - Following the scaling laws 27:00 - Getting to PMF 30:00 - “Dogfooding” 31:00 - First 10 hires 32:50 - How to evaluate great engineers 33:45 - Maintaining the hacker mindset 35:00 - What are the moats for AI coding tools? 37:00 - Looking ahead

Y Combinator

337,015 次观看 • 1 年前