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How to build long-horizon AI agents: behavior specs, ontologies, process supervision - my conversation with Mitchell Troyanovsky, co-founder of Basis 01:09 Why Everyone at Basis Was Whispering to AI when Stephanie Palazzolo walked in 04:12 Accounting as "an Intelligence Over the Economy" 06:11 What Makes an Agent Truly Long-Horizon...

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Matt Turck

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12,241 Aufrufe • vor 1 Tag •via X (Twitter)

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Everything Gets Rebuilt: my conversation with Harrison Chase, CEO of LangChain about agent harnesses, evals, runtimes, sandboxes, MCP and the future of the agent stack 00:00 Intro - meet Harrison Chase - at the Chase Center for the Daytona Compute conference 01:32 What changed in agents over the last year 03:57 Why coding agents are ahead 06:26 Do models commoditize the framework layer? 08:27 Harnesses, in plain English 10:11 Why system prompts matter so much 13:11 The upside — and downside — of subagents 15:31 Why a useful agent needs a filesystem 18:13 Additional core primitives of modern agents 19:12 Skills: the new primitive 20:19 What context compaction actually means 23:02 How memory works in agents 25:16 One mega-agent or many specialized agents? 27:46 The future of MCP 29:38 Why agents need sandboxes 32:35 How sandboxes help with security 33:32 How Harrison Chase started LangChain 37:24 LangChain vs LangGraph vs Deep Agents 40:17 Why observability matters more for agents 41:48 Evals, no-code, and continuous improvement 44:41 What LangChain is building next 45:29 Where the real moat in AI lives
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Everything Gets Rebuilt: my conversation with Harrison Chase, CEO of LangChain about agent harnesses, evals, runtimes, sandboxes, MCP and the future of the agent stack 00:00 Intro - meet Harrison Chase - at the Chase Center for the Daytona Compute conference 01:32 What changed in agents over the last year 03:57 Why coding agents are ahead 06:26 Do models commoditize the framework layer? 08:27 Harnesses, in plain English 10:11 Why system prompts matter so much 13:11 The upside — and downside — of subagents 15:31 Why a useful agent needs a filesystem 18:13 Additional core primitives of modern agents 19:12 Skills: the new primitive 20:19 What context compaction actually means 23:02 How memory works in agents 25:16 One mega-agent or many specialized agents? 27:46 The future of MCP 29:38 Why agents need sandboxes 32:35 How sandboxes help with security 33:32 How Harrison Chase started LangChain 37:24 LangChain vs LangGraph vs Deep Agents 40:17 Why observability matters more for agents 41:48 Evals, no-code, and continuous improvement 44:41 What LangChain is building next 45:29 Where the real moat in AI lives

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Updated: Vocals & Rap - #성화 #Seonghwa 00:00 Still Here 00:15 Wonderland 00:36 Halazia 00:47 Answer 01:21 Cyberpunk 01:27 Wave 01:37 Utopia 01:50 My Way 02:00 With U 02:16 Be With You 02:54 Star 1117 03:21 Turbulence (야간비행) 03:39 Days 04:26 Promise 04:38 Fever 04:54 Sunrise 05:19 Mist 05:43 Take Me Home 06:11 Better 06:34 All About You 06:43 Aurora 06:55 Blue Summer 07:23 Diamond 07:46 Time Of Love 07:58 Stay 08:07 Desire 08:21 WDIG 08:28 New World 08:35 Dreamers 08:53 Not Too Late 09:03 The Letter 09:19 One Day At A Time 09:28 Dazzling Light 09:40 Light 09:50 The Ring 10:04 Paradigm 10:18 This World 10:38 Bouncy 10:51 Not Okay 11:15 The King 11:23 Inception 11:52 Fireworks 12:03 Limitless 12:19 Precious 12:28 Rocky 12:41 Let’s Get Together 13:07 White Love 13:17 The Leaders 13:27 Crazy Form 13:43 Arriba 13:57 Silver Light 14:06 Dreamy Day 14:26 Matz 15:15 Outlaw 15:23 Twilight 15:31 Dune 15:38 Hala Hala 15:43 Deja Vu 15:50 Horizon 15:54 Say My Name 15:57 Sector 1 16:02 Good Lil Boy 16:09 Don’t Stop 16:12 Still Here (Acoustic Ver) 16:19 Siren 16:31 Guerrilla 16:45 We Know 17:00 Empty Box 17:28 Wake Up 17:40 Dancing Like Butterfly Wings 17:49 Work 18:09 Thanxx 18:26 If Without U 18:45 Shaboom 19:01 Outlaw 19:18 Treasure 19:33 Eternal Sunshine 20:03 Django 20:31 Turbulence Japanese Ver. 20:55 Blind 21:16 Pirate King 21:24 Forevermore 22:00 Birthday 22:11 Deep Dive 22:26 Ice On My Teeth 22:50 Man On Fire 23:10 Selfish Waltz 23:25 Enough
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Hwanakin

62,764 Aufrufe • vor 1 Jahr

🤖 Bots with Wallets: What Could Possibly Go Right? In this episode of CDPod, yuga.eth 🛡 and erik.eth 🛡 are joined by EtherMage, co-founder of Virtuals Protocol. They break down the emergence of wallet-enabled AI agents, why crypto is the missing piece for real autonomy, and how tokenization creates new ways for people to benefit from agent-driven economies. Timestamps: 00:00 - Intro 01:26 - Introducing Jansen Tang from Virtuals Protocol 03:27 - From gaming DAO to Roblox autonomous NPCs 04:01 - Expanding into entertainment and TikTok agents 06:39 - Giving agents agency, goals, and memory 11:01 - Launching Luna as tokenized TikTok influencer 13:54 - Luna’s market cap rise, inspiring other agents 16:00 - Different schools of thought in AI 20:08 - How agents interact with each other 24:00 - Problems faced: information loss 25:05 - How blockchain solves information loss 29:40 - Agent economy stack and ACP’s role 30:39 - x402 enabling agent payments and wallets 32:33 - Combining tools, agents, and x402 32:59 - What agents do on ACP today 35:55 - Information agents like AIXBT 36:41 - Personal finance agents 38:08 - Current adoption 40:07 - Making agents richer 42:09 - Robotics gaps: data and real‑world testing 44:11 - Closing, ending questions
48:59

🤖 Bots with Wallets: What Could Possibly Go Right? In this episode of CDPod, yuga.eth 🛡 and erik.eth 🛡 are joined by EtherMage, co-founder of Virtuals Protocol. They break down the emergence of wallet-enabled AI agents, why crypto is the missing piece for real autonomy, and how tokenization creates new ways for people to benefit from agent-driven economies. Timestamps: 00:00 - Intro 01:26 - Introducing Jansen Tang from Virtuals Protocol 03:27 - From gaming DAO to Roblox autonomous NPCs 04:01 - Expanding into entertainment and TikTok agents 06:39 - Giving agents agency, goals, and memory 11:01 - Launching Luna as tokenized TikTok influencer 13:54 - Luna’s market cap rise, inspiring other agents 16:00 - Different schools of thought in AI 20:08 - How agents interact with each other 24:00 - Problems faced: information loss 25:05 - How blockchain solves information loss 29:40 - Agent economy stack and ACP’s role 30:39 - x402 enabling agent payments and wallets 32:33 - Combining tools, agents, and x402 32:59 - What agents do on ACP today 35:55 - Information agents like AIXBT 36:41 - Personal finance agents 38:08 - Current adoption 40:07 - Making agents richer 42:09 - Robotics gaps: data and real‑world testing 44:11 - Closing, ending questions

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66,581 Aufrufe • vor 8 Monaten

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Ely

24,802 Aufrufe • vor 1 Jahr

This is how Mark Pincus built Zynga into a $12B company, & how he keeps building something better Full interview with mark pincus & Hubert Thieblot : 00:00 Poker party legend 01:46 "The Abyss" when nothing's working 03:09 The lazy onramp to curiosity 04:01 How Zynga started 06:50 The bet that built Napster, LinkedIn, Facebook 09:18 How Mark almost built Uber 11:10 "If I could go back, I'd just copy Friendster" 11:36 You're in the right body of water, wrong boat 12:33 Don't let B+ be the enemy of A 14:53 Excitement is the real metric 16:11 What real product-market fit feels like 17:35 If you're not addicted, no one else will be 24:09 Too much success 33:46 Building FarmVille in 6 weeks 35:16 170,000 installs on day one 37:24 You're an "expert witness" 38:33 Build the house you want to live in 41:09 Talent is a myth 42:31 You should hire "broken resumes" 58:50 Can you talk to 10 real users every day? 01:00:06 Day-365 retention 01:02:13 Mark's framework: proven, better, new. 01:04:12 Everyone who treated Facebook as distribution failed 01:10:21 What I'd do if I was starting over today
1:11:28

This is how Mark Pincus built Zynga into a $12B company, & how he keeps building something better Full interview with mark pincus & Hubert Thieblot : 00:00 Poker party legend 01:46 "The Abyss" when nothing's working 03:09 The lazy onramp to curiosity 04:01 How Zynga started 06:50 The bet that built Napster, LinkedIn, Facebook 09:18 How Mark almost built Uber 11:10 "If I could go back, I'd just copy Friendster" 11:36 You're in the right body of water, wrong boat 12:33 Don't let B+ be the enemy of A 14:53 Excitement is the real metric 16:11 What real product-market fit feels like 17:35 If you're not addicted, no one else will be 24:09 Too much success 33:46 Building FarmVille in 6 weeks 35:16 170,000 installs on day one 37:24 You're an "expert witness" 38:33 Build the house you want to live in 41:09 Talent is a myth 42:31 You should hire "broken resumes" 58:50 Can you talk to 10 real users every day? 01:00:06 Day-365 retention 01:02:13 Mark's framework: proven, better, new. 01:04:12 Everyone who treated Facebook as distribution failed 01:10:21 What I'd do if I was starting over today

Founders Inc

48,756 Aufrufe • vor 2 Monaten

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

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

University of Austin (UATX)

27,770 Aufrufe • vor 6 Monaten

E180: KAST Founder: Most crypto neobanks will be gone in 12 months raagulanpathy is the founder and CEO of KAST , a global stablecoin neobank, and a former Circle exec. He raised $80 million at a $600 million valuation on the thesis that the real prize isn't the stablecoin - it's the bank you build on top of it. We get into the money, the grind, and the token decision that pissed a chunk of his community off. Timestamps 00:00 Introduction 01:58 How Raagulan Decides What Gets Done At KAST 04:35 The Chaos KAST Employees Deal With Daily 05:38 Raagulan's Hiring Philosophy At KAST 07:02 Why Firing Is Harder Than Hiring 08:35 The One Error That Could Kill KAST 09:52 How Raagulan Convinces Stablecoin Skeptics 10:46 What Outsiders Miss About The Payment Industry 12:06 Why KAST Needs So Many Different Departments 18:32 Partnerships: Variational & Bitwise 19:24 Raagulan's Real Take On Fees 21:55 KAST's Best Type Of Customer 23:53 The Thing Raagulan Can't Say Publicly 26:54 Founders Can't Chase All These Three Things At Once 29:04 Raagulan's Experience With GLP-1s 31:39 How KAST Kept Growing When Bitcoin Crashed 50% 34:05 KAST Is On Track For $100 Million In Revenue 36:55 Why KAST Hasn't Blown Up From Overspending 41:04 Why Everyone's Racing To Build Neobanks 42:52 What Makes Neobanks So Hard To Build 44:54 Why Neobanks Keep Shutting Down 45:57 What KAST Offers That Exchanges Can't 49:14 KAST Isn't A Card Business 50:43 How KAST Is Building Momentum 54:57 Raagulan On His Competitors 56:29 Partnerships: KAST & Trezor 57:33 Kevin's Honest Take On KAST 58:59 What KAST Is Doing With the $80 Million they raised 01:01:55 Would Raagulan Ever Sell Equity? 01:06:57 Who Buys In At A $3B Valuation Next? 01:08:39 Is Your Money Actually Yours Inside KAST 01:10:49 What Happens To Your Money If KAST Collapses 01:17:38 Custodial Vs Self-Custodial: Pros And Cons 01:19:52 Why KAST Obsesses Over Design And Brand 01:22:42 Partnerships: Jupiter & Ethena 01:23:26 KAST Points & Token: Should The KAST Community Feel Cheated? 01:34:13 What's Actually Behind This Tokenized Stock? 01:35:25 The Hill Raagulan Will Die On 01:36:41 One Prediction That Comes True In 5 Years 01:37:59 Is The Worst Behind Us In Crypto? 01:42:57 The One Thing To Remember From This Conversation 01:45:16 Closing Thoughts
1:46:06

E180: KAST Founder: Most crypto neobanks will be gone in 12 months raagulanpathy is the founder and CEO of KAST , a global stablecoin neobank, and a former Circle exec. He raised $80 million at a $600 million valuation on the thesis that the real prize isn't the stablecoin - it's the bank you build on top of it. We get into the money, the grind, and the token decision that pissed a chunk of his community off. Timestamps 00:00 Introduction 01:58 How Raagulan Decides What Gets Done At KAST 04:35 The Chaos KAST Employees Deal With Daily 05:38 Raagulan's Hiring Philosophy At KAST 07:02 Why Firing Is Harder Than Hiring 08:35 The One Error That Could Kill KAST 09:52 How Raagulan Convinces Stablecoin Skeptics 10:46 What Outsiders Miss About The Payment Industry 12:06 Why KAST Needs So Many Different Departments 18:32 Partnerships: Variational & Bitwise 19:24 Raagulan's Real Take On Fees 21:55 KAST's Best Type Of Customer 23:53 The Thing Raagulan Can't Say Publicly 26:54 Founders Can't Chase All These Three Things At Once 29:04 Raagulan's Experience With GLP-1s 31:39 How KAST Kept Growing When Bitcoin Crashed 50% 34:05 KAST Is On Track For $100 Million In Revenue 36:55 Why KAST Hasn't Blown Up From Overspending 41:04 Why Everyone's Racing To Build Neobanks 42:52 What Makes Neobanks So Hard To Build 44:54 Why Neobanks Keep Shutting Down 45:57 What KAST Offers That Exchanges Can't 49:14 KAST Isn't A Card Business 50:43 How KAST Is Building Momentum 54:57 Raagulan On His Competitors 56:29 Partnerships: KAST & Trezor 57:33 Kevin's Honest Take On KAST 58:59 What KAST Is Doing With the $80 Million they raised 01:01:55 Would Raagulan Ever Sell Equity? 01:06:57 Who Buys In At A $3B Valuation Next? 01:08:39 Is Your Money Actually Yours Inside KAST 01:10:49 What Happens To Your Money If KAST Collapses 01:17:38 Custodial Vs Self-Custodial: Pros And Cons 01:19:52 Why KAST Obsesses Over Design And Brand 01:22:42 Partnerships: Jupiter & Ethena 01:23:26 KAST Points & Token: Should The KAST Community Feel Cheated? 01:34:13 What's Actually Behind This Tokenized Stock? 01:35:25 The Hill Raagulan Will Die On 01:36:41 One Prediction That Comes True In 5 Years 01:37:59 Is The Worst Behind Us In Crypto? 01:42:57 The One Thing To Remember From This Conversation 01:45:16 Closing Thoughts

MR SHIFT 🦁

170,665 Aufrufe • vor 15 Tagen

Cursor Complete Guide for AI Coding... 1. The Basics, Composer, Cursor 2.0, Why use Cursor? 2. Multiple Agent Testing, Adding Database, Deploying to Vercel 3. Comparing the big 4: v0, Replit, Lovable, Cursor And more... with Senior Software Engineer Kehan Zhang TIME STAMPS --------------- 1. BASICS: 00:00 Introduction 01:01 Overview of Cursor and Its Features 01:47 Getting Started with Cursor 02:39 Understanding IDE and Vibe Coding 06:00 Cursor For Mobile Apps 10:26 Downloading and Installing Cursor 11:17 Creating and Managing Projects in Cursor 15:14 Building a Simple Game with Cursor 19:10 Advanced Features and Customization 40:28 Fixing Styling Rules 40:53 Redesigning the App 42:17 Exploring Cursor 2.0 Features 43:22 Setting Up the Project Structure 44:17 Adding and Testing Meme Templates 46:08 Debugging Text Issues 2. ADVANCED 49:46 Using Multiple Agents 01:10:40 Creating Custom Commands 01:14:15 Creating Commands in Settings Tab 01:15:11 Introduction to Instant DB 01:16:04 Setting Up Instant DB in Your Project 01:18:24 Building a Full Stack Application 01:19:04 Using the Agent to Plan and Build 01:26:06 Testing and Debugging the Application 01:53:02 Deploying the Application with Vercel 01:55:35 Setting Up the CLI 01:56:15 Understanding Command Line Interfaces (CLI) 01:57:32 Deploying Code to Vercel 01:58:07 Handling Environment Variables 01:58:44 Interacting with the Vercel Deployment 02:00:34 Exploring Cursor's Capabilities 3. COMPARING VIBE CODING TOOLS 02:09:48 Comparing Vibe Coding Tools 02:31:04 Final Thoughts and Recommendations
2:34:13

Cursor Complete Guide for AI Coding... 1. The Basics, Composer, Cursor 2.0, Why use Cursor? 2. Multiple Agent Testing, Adding Database, Deploying to Vercel 3. Comparing the big 4: v0, Replit, Lovable, Cursor And more... with Senior Software Engineer Kehan Zhang TIME STAMPS --------------- 1. BASICS: 00:00 Introduction 01:01 Overview of Cursor and Its Features 01:47 Getting Started with Cursor 02:39 Understanding IDE and Vibe Coding 06:00 Cursor For Mobile Apps 10:26 Downloading and Installing Cursor 11:17 Creating and Managing Projects in Cursor 15:14 Building a Simple Game with Cursor 19:10 Advanced Features and Customization 40:28 Fixing Styling Rules 40:53 Redesigning the App 42:17 Exploring Cursor 2.0 Features 43:22 Setting Up the Project Structure 44:17 Adding and Testing Meme Templates 46:08 Debugging Text Issues 2. ADVANCED 49:46 Using Multiple Agents 01:10:40 Creating Custom Commands 01:14:15 Creating Commands in Settings Tab 01:15:11 Introduction to Instant DB 01:16:04 Setting Up Instant DB in Your Project 01:18:24 Building a Full Stack Application 01:19:04 Using the Agent to Plan and Build 01:26:06 Testing and Debugging the Application 01:53:02 Deploying the Application with Vercel 01:55:35 Setting Up the CLI 01:56:15 Understanding Command Line Interfaces (CLI) 01:57:32 Deploying Code to Vercel 01:58:07 Handling Environment Variables 01:58:44 Interacting with the Vercel Deployment 02:00:34 Exploring Cursor's Capabilities 3. COMPARING VIBE CODING TOOLS 02:09:48 Comparing Vibe Coding Tools 02:31:04 Final Thoughts and Recommendations

Riley Brown

65,392 Aufrufe • vor 9 Monaten

좋아하는 #선우 틱톡 춤&챌린지 모음 ❤︎ 00:00 세상에 소리질러 00:15 ladidadida 00:30 Ready to love 00:48 Permission to Dance 00:52 꿈빛파티시엘 01:20 Hot 01:32 Hot 01:47 That That 01:58 ZOOM 02:27 Roller Coaster 02:37 Beatbox 02:50 Attention 어텐션 03:10 단거 03:38 귀여워서 미안해 03:53 MBTI 04:15 on the street 04:27 배고파송 04:42 AMERICA HAS A PROBLEM 04:53 comethru 커피 05:13 난장 05:28 Love me 05:43 If we ever broke up 05:58 최애의아이 06:13 FIREWORK 06:29 Go 06:37 Love Lee 러브리 07:04 INVITATION 07:15 Right Now 풀업 07:26 War Cry 07:39 위글위글 07:50 나이트댄서 08:08 나이트댄서 08:28 첫눈 08:41 산타텔미 08:51 마리오 브이 09:00 Obsessed 09:13 Like I Do 09:24 Like I Do 09:39 Rather Be 레덜비 09:57 첫 만남은 계획대로 되지 않아 10:24 10:33 무빙 10:44 Back it up 10:54 전방향미소년 11:05 보이프렌드 11:18 워너비 11:33 티라미수 케익 11:45 페도라 11:56 Blessed 12:19 渋沢栄一 12:35 Change 댄스잼 12:46 동물원을 빠져나온 퓨마 13:25 어머뿔자 14:55 어머뿔자 15:51 영웅 16:17 작은 것들을 위한 시 17:48 으르렁 18:29 I NEED U 18:35 파이팅해야지 19:11 빙글빙글
19:30

좋아하는 #선우 틱톡 춤&챌린지 모음 ❤︎ 00:00 세상에 소리질러 00:15 ladidadida 00:30 Ready to love 00:48 Permission to Dance 00:52 꿈빛파티시엘 01:20 Hot 01:32 Hot 01:47 That That 01:58 ZOOM 02:27 Roller Coaster 02:37 Beatbox 02:50 Attention 어텐션 03:10 단거 03:38 귀여워서 미안해 03:53 MBTI 04:15 on the street 04:27 배고파송 04:42 AMERICA HAS A PROBLEM 04:53 comethru 커피 05:13 난장 05:28 Love me 05:43 If we ever broke up 05:58 최애의아이 06:13 FIREWORK 06:29 Go 06:37 Love Lee 러브리 07:04 INVITATION 07:15 Right Now 풀업 07:26 War Cry 07:39 위글위글 07:50 나이트댄서 08:08 나이트댄서 08:28 첫눈 08:41 산타텔미 08:51 마리오 브이 09:00 Obsessed 09:13 Like I Do 09:24 Like I Do 09:39 Rather Be 레덜비 09:57 첫 만남은 계획대로 되지 않아 10:24 10:33 무빙 10:44 Back it up 10:54 전방향미소년 11:05 보이프렌드 11:18 워너비 11:33 티라미수 케익 11:45 페도라 11:56 Blessed 12:19 渋沢栄一 12:35 Change 댄스잼 12:46 동물원을 빠져나온 퓨마 13:25 어머뿔자 14:55 어머뿔자 15:51 영웅 16:17 작은 것들을 위한 시 17:48 으르렁 18:29 I NEED U 18:35 파이팅해야지 19:11 빙글빙글

라기

55,782 Aufrufe • vor 1 Jahr

Netflix pays AI PMs up to $900K/year. How do you become (and succeed) as one? Marily Nika Marily Nika is an AI PM at Google, and was an AI PM at Meta. In today's episode, she breaks it down: How AI PM Roles Differ at Big Tech Companies – 06:56 How Technical an AI PM Needs to Be – 08:08 Data Handling Responsibilities for AI PMs – 13:10 How PMs Can Improve Collaboration with Researchers – 18:06 Interviewing for AI PM Roles at Big Tech Companies – 22:08 The Role of a PhD in AI Product Management – 26:03 Optimizing LinkedIn for Aspiring AI PMs – 31:55 Roadmap to Becoming an AI PM – 37:05 Transitioning into AI Product Management – 40:52 The Process of Boomeranging Back to a Company – 44:00 AI Tools Every PM Should Know – 48:08 What It’s Like to Be an AI PM at Google – 57:46 How to Develop a Strong Product Strategy – 01:01:21 The Evolution of PM Roles in the Age of AI – 01:05:11 How PMs Can Stay Relevant in an AI-Driven World – 01:08:12 Balancing a Side Business with a Full-Time Job – 01:13:42 The Process of Creating a Course – 01:17:12 LinkedIn Tips for Aspiring AI PM Creators – 01:21:21 Lessons from Product Failures – 01:25:27 Paid promotions included
1:27:33

Netflix pays AI PMs up to $900K/year. How do you become (and succeed) as one? Marily Nika Marily Nika is an AI PM at Google, and was an AI PM at Meta. In today's episode, she breaks it down: How AI PM Roles Differ at Big Tech Companies – 06:56 How Technical an AI PM Needs to Be – 08:08 Data Handling Responsibilities for AI PMs – 13:10 How PMs Can Improve Collaboration with Researchers – 18:06 Interviewing for AI PM Roles at Big Tech Companies – 22:08 The Role of a PhD in AI Product Management – 26:03 Optimizing LinkedIn for Aspiring AI PMs – 31:55 Roadmap to Becoming an AI PM – 37:05 Transitioning into AI Product Management – 40:52 The Process of Boomeranging Back to a Company – 44:00 AI Tools Every PM Should Know – 48:08 What It’s Like to Be an AI PM at Google – 57:46 How to Develop a Strong Product Strategy – 01:01:21 The Evolution of PM Roles in the Age of AI – 01:05:11 How PMs Can Stay Relevant in an AI-Driven World – 01:08:12 Balancing a Side Business with a Full-Time Job – 01:13:42 The Process of Creating a Course – 01:17:12 LinkedIn Tips for Aspiring AI PM Creators – 01:21:21 Lessons from Product Failures – 01:25:27 Paid promotions included

Aakash Gupta

42,853 Aufrufe • vor 1 Jahr

The Hermes Desktop App is insanely good. It's now the best way to run AI agents on your computer. Here's the full setup, start to finish. Enjoy! Chapters: 00:00 - why Hermes desktop is a game changer 00:46 - downloading and installing the desktop app 01:47 - picking your model and provider 02:52 - sessions, settings, and gateway connection 04:08 - adding a custom MCP server 04:58 - memory and context (the three-tier system) 06:52 - connecting to Telegram 09:45 - skills and tools 11:06 - the skills hub (built-in and community skills) 11:50 - creating a custom skill 14:18 - artifacts 15:11 - going from one to many agents (profiles and personas) 18:12 - agents working as a team (Hermes Kanban) 19:01 - outro I have also written an article on Hermes masterclass, the same is quoted below.
19:13

The Hermes Desktop App is insanely good. It's now the best way to run AI agents on your computer. Here's the full setup, start to finish. Enjoy! Chapters: 00:00 - why Hermes desktop is a game changer 00:46 - downloading and installing the desktop app 01:47 - picking your model and provider 02:52 - sessions, settings, and gateway connection 04:08 - adding a custom MCP server 04:58 - memory and context (the three-tier system) 06:52 - connecting to Telegram 09:45 - skills and tools 11:06 - the skills hub (built-in and community skills) 11:50 - creating a custom skill 14:18 - artifacts 15:11 - going from one to many agents (profiles and personas) 18:12 - agents working as a team (Hermes Kanban) 19:01 - outro I have also written an article on Hermes masterclass, the same is quoted below.

Akshay 🚀

103,655 Aufrufe • vor 2 Monaten

In this episode, Beyang and Thorsten discuss strategies for effective agentic coding, including the 101 of how it's different from coding with chat LLMs, the key constraint of the context window, how and where subagents can help, and the new oracle subagent which combines multiple LLMs. 00:38 Intros 03:20 How coding with agents is very different from coding with prior AI tools 10:31 Example: fix a simple issue 14:13 Example: debugging an issue with an MCP server 21:50 Example: unifying two build scripts 25:09 How the context window is a key constraint 31:01 Why it's best to focus on one thing at a time 33:09 Subagents and context windows 33:49 The codebase search subagent 38:33 General-purpose subagents 44:05 When to use subagents 46:44 The oracle subagent and o3 51:32 Multi-model agents
53:54

In this episode, Beyang and Thorsten discuss strategies for effective agentic coding, including the 101 of how it's different from coding with chat LLMs, the key constraint of the context window, how and where subagents can help, and the new oracle subagent which combines multiple LLMs. 00:38 Intros 03:20 How coding with agents is very different from coding with prior AI tools 10:31 Example: fix a simple issue 14:13 Example: debugging an issue with an MCP server 21:50 Example: unifying two build scripts 25:09 How the context window is a key constraint 31:01 Why it's best to focus on one thing at a time 33:09 Subagents and context windows 33:49 The codebase search subagent 38:33 General-purpose subagents 44:05 When to use subagents 46:44 The oracle subagent and o3 51:32 Multi-model agents

Amp — Research Preview

24,534 Aufrufe • vor 1 Jahr

this is a lecture on how to hunt for investors, cofounders & new hires complete breakdown: 00:00 8 billion people don't know you exist 00:24 No one knows you. No one cares. 01:09 Stop being a farmer 01:51 The one thing all great hunters share 02:10 How I got my co-founder in 30 seconds 03:30 You + them = 3 people 05:36 Missionaries vs mercenaries 10:31 Why you have to be generous with equity 12:35 The right vesting schedule 13:17 Always trial before you commit 14:19 The 9-to-5 specialist red flag 15:05 Why logos mean nothing 17:46 Hunt them on GitHub 19:37 Niche Discords and subreddits 20:58 Why paid referrals work 22:10 Hiring friends: the trap 24:39 Why advisors are bullshit 31:29 Should you raise at all? 35:06 Investors only buy growth stories 35:58 Fundraising is running an auction 37:36 The luck factor (and Twitter lies) 39:33 Angels vs VCs 47:21 The hierarchy: inbound > warm > cold 48:00 Never ask a VC for intros if they pass 48:59 The double opt-in rule 52:32 Fundraising is a full-time job 53:33 Why a 4-week VC chat is a "no" 56:22 The leverage trick 01:00:24 Fundraising advisors = scam 01:02:21 The one trait of every great founder 01:03:18 Your homework: a list of 100
1:04:08

this is a lecture on how to hunt for investors, cofounders & new hires complete breakdown: 00:00 8 billion people don't know you exist 00:24 No one knows you. No one cares. 01:09 Stop being a farmer 01:51 The one thing all great hunters share 02:10 How I got my co-founder in 30 seconds 03:30 You + them = 3 people 05:36 Missionaries vs mercenaries 10:31 Why you have to be generous with equity 12:35 The right vesting schedule 13:17 Always trial before you commit 14:19 The 9-to-5 specialist red flag 15:05 Why logos mean nothing 17:46 Hunt them on GitHub 19:37 Niche Discords and subreddits 20:58 Why paid referrals work 22:10 Hiring friends: the trap 24:39 Why advisors are bullshit 31:29 Should you raise at all? 35:06 Investors only buy growth stories 35:58 Fundraising is running an auction 37:36 The luck factor (and Twitter lies) 39:33 Angels vs VCs 47:21 The hierarchy: inbound > warm > cold 48:00 Never ask a VC for intros if they pass 48:59 The double opt-in rule 52:32 Fundraising is a full-time job 53:33 Why a 4-week VC chat is a "no" 56:22 The leverage trick 01:00:24 Fundraising advisors = scam 01:02:21 The one trait of every great founder 01:03:18 Your homework: a list of 100

Founders Inc

19,492 Aufrufe • vor 3 Monaten

In this episode of the Lightcone Podcast, we sat down with Mukund Jha and Madhav Jha, the founders of Emergent - an AI platform that lets anyone build and ship production-ready software. In just eight months, users have created more than 7 million apps on Emergent, with the number doubling in just the last 45 days. We discuss how they built one of the most powerful AI coding agents, why they focused on non-technical users and what it's like building for a global audience from India. 00:00 - Intro 01:06 - What Is Emergent? 01:18 - Founder Backstory 02:09 - From AI Testing to General Coding Agents 02:52 - Getting Ahead of the Market 04:18 - The Pivot to Non-Technical Users 05:22 - Why Second Movers Can Win in AI 09:04 - Building for Production, Not Just Prototypes 18:21 - Live Demo: Building Apps with Emergent 24:40 - How Emergent Hires and Runs a Lean Team 29:04 - Is SaaS Dead? The Rise of Personalized Software 34:04 - The Future: Niche Apps, Solo Builders and AI Agency
39:32

In this episode of the Lightcone Podcast, we sat down with Mukund Jha and Madhav Jha, the founders of Emergent - an AI platform that lets anyone build and ship production-ready software. In just eight months, users have created more than 7 million apps on Emergent, with the number doubling in just the last 45 days. We discuss how they built one of the most powerful AI coding agents, why they focused on non-technical users and what it's like building for a global audience from India. 00:00 - Intro 01:06 - What Is Emergent? 01:18 - Founder Backstory 02:09 - From AI Testing to General Coding Agents 02:52 - Getting Ahead of the Market 04:18 - The Pivot to Non-Technical Users 05:22 - Why Second Movers Can Win in AI 09:04 - Building for Production, Not Just Prototypes 18:21 - Live Demo: Building Apps with Emergent 24:40 - How Emergent Hires and Runs a Lean Team 29:04 - Is SaaS Dead? The Rise of Personalized Software 34:04 - The Future: Niche Apps, Solo Builders and AI Agency

Y Combinator

107,654 Aufrufe • vor 4 Monaten