米核AI学院简介【非免费，付费渠道在有赞】
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后面的介绍很长，先了解的直接看后面有疑问，直接联系我，yhbj2024【下面是官方介绍图哈】
免费工作流
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hi，我们米核官网上线了，可以给大家免费体验7天。含80个工作流和300个提示词。内容涵盖几个方面：1、如何获取2、没有想要的工作流？3、体验vip的工作流清单如何领取？第一步：点击链接，或者扫码二维码第二步：电脑网页端可以直接手机号注册，微信扫码是一定要绑定手机号的哈~【说明】通过我的链接进入，可以直接获取体验vip的权益，同时也是找我获取其他工作流的重要凭证。https://www.miheai.com/?share_id=14375（通过邀请链接才可以获得体验VIP哦）没有想要的工作流？没有想要的工作流，直接找我！（yhbj2024）想要体验工作流的，遇到bug有不会的，也可以直接找我。唯一要说清楚的一点是，我是卖米核社群和合伙人的。大家根据需要，自行选择，你可以不买，但是要工作流之前，你先扫下我的官网二维码/通过我的链接注册一下，再让我给你服务。你心安理得，我也更有动力不是？这要求不过分吧？~哈哈~体验vip清单：
米核AI社简介【非免费，付费渠道在有赞】
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米核有自己的有赞商城和官网哈，官网：点击 https://www.miheai.com/?share_id=14375 注册可免费获得80个工作流，详情咨询yhbj2024但是我还是希望你通过扫我的有赞码付款哈~后面的介绍很长，我先文字简单介绍下：价格：299元/3年米核AI社的权益：1、系统学习课程，从0-1怎么搭建2、200+智能体/工作流，未来每周会更新5个左右3、每周一节智能体搭建直播课4、客服答疑，周一至周六13:00-20:005、社群服务期是3年哈~6、官网VIP会员1年。有疑问，直接联系我，yhbj2024我的有赞二维码：【下面是官方介绍图哈，扫上面二维码可以看到同款介绍哈~】
渡鸦科技社6.0重磅升级：3大AI神器+百万级课程，手握流量密码开启2025增长狂潮
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【系统化学习课程】【渡鸦会员的权益】【如何加入？】想要加入渡鸦科技社， 直接找我（Joy-wmsjoy） PS：如果有人让你转账支付，而不是扫码加入的，并且价格高于388的，你都可以当成骗子处理。加入渡鸦，都是走有赞的二维码支付的！ 付款后，记得发我付款的截图哈，我会给你安排进群。通过我加入的，本站SVIP免费送哦~微信二维码
布莱恩・切斯基的神秘导师：助力 Airbnb 发展壮大（曾历经 9 次濒临失败，还打造过酒店帝国）（注：布莱恩・切斯基为 Airbnb 联合创始人）
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14,744次观看 2025年8月3日 Lenny's PodcastChip Conley is the founder of Joie de Vivre hotels, the second-largest boutique hotel brand in the world. At age 52, he joined Airbnb as Head of Global Hospitality and Strategy, reporting to CEO Brian Chesky, who was 21 years younger. He earned the title of Airbnb’s “Modern Elder” by guiding the young founders on leadership and culture while learning Silicon Valley’s tech mindset himself. Today, Chip leads the Modern Elder Academy, the world’s first midlife wisdom school, and is the author of best-selling books like Wisdom@Work and Peak. He champions the idea that age and experience are assets—and that midlife can be a launchpad for renewed purpose and impact.In this conversation, we discuss:1. The reality of Brian Chesky in “founder mode”—the good, bad, and stressful 2. How Chip went from running 52 boutique hotels to becoming Airbnb’s in-house mentor in his 50s 3. The “mentor and intern” mindset: how to simultaneously teach others and stay curious like a beginner 4. Why AI might actually favor older workers (hint: human wisdom vs. artificial intelligence) 5. His framework for navigating midlife transitions and finding meaning after 40 6. Specific tactics for older professionals to thrive in tech companies 7. Surprising data that midlife is often the happiest time of life—and how to leverage your 40s, 50s, and beyond 8. Chip’s formula for managing anxiety and fear (and how to regain control when worry strikes)Brought to you by:Great Question—Empower everyone to run great research: https://www.greatquestion.com/lennyVanta—Automate compliance. Simplify security: https://vanta.com/lennyCoda—The all-in-one collaborative workspace: https://coda.io/lennyTranscript: https://www.lennysnewsletter.com/p/ch...My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/16...Where to find Chip Conley:• LinkedIn: / chipconleysf • Website: https://chipconley.com/• Modern Elder Academy: https://www.meawisdom.com/• Podcast: https://www.meawisdom.com/podcast/Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: / lennysan • LinkedIn: / lennyrachitsky In this episode, we cover:(00:00) Introduction to Chip Conley (04:30) Chip’s journey with Airbnb (11:44) Insights on working with Brian Chesky (18:27) Tactics to be effective when working with founders in founder mode (21:08) The value of intergenerational collaboration (27:03) Addressing ageism in tech (31:18) Advice for thriving as an older individual in tech (35:01) Advice for hiring managers (42:37) Chip’s early career and founding Joie de Vivre (44:12) A life-changing near-death experience (47:51) The importance of company culture (52:20) The Peak Model (57:09) The Modern Elder Academy (MEA) (01:00:30) The upside of aging (01:06:43) Who MEA is for (01:08:05) AI in daily life (01:10:20) Lightning round and final thoughtsReferenced:• Brian Chesky on LinkedIn: / brianchesky • Brian Chesky’s new playbook: https://www.lennysnewsletter.com/p/br...• Natalie Tucci on LinkedIn: / natalietuccishoff • Laura Modi on LinkedIn: / laurahughes6 • How to build a cult-like brand | Laura Modi (Bobbie): https://www.lennysnewsletter.com/p/fr...• George Tenet: https://en.wikipedia.org/wiki/George_...• Joie de Vivre Hospitality: https://www.hyatt.com/jdv-by-hyatt/en-US• Fest300: https://en.wikipedia.org/wiki/Fest300• John Q. Smith on LinkedIn: / johnqsmith •Will A.I. Replace New Hires or Middle Managers?: https://www.nytimes.com/2025/07/07/bu...• Burning Man: https://burningman.org/• Sheryl Sandberg on LinkedIn: / sheryl-sandberg-5126652 • Bill Graham: https://en.wikipedia.org/wiki/Bill_Gr...) • Maslow’s hierarchy: https://en.wikipedia.org/wiki/Maslow%...• Measuring what makes life worthwhile: https://www.ted.com/talks/chip_conley...• Jonathan Mildenhall on LinkedIn: / mildenhall • Becca Levy’s website: https://becca-levy.com/• Kabuki Springs & Spa: https://kabukisprings.com/• How positive age beliefs can support positive health outcomes with Becca Levy, PhD: https://www.ama-assn.org/delivering-c...• The U-shape of Happiness Across the Life Course: Expanding the Discussion: https://pmc.ncbi.nlm.nih.gov/articles......References continued at: https://www.lennysnewsletter.com/p/ch...Production and marketing by https://penname.co/.For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed.
我们如何为适配 AI 全面重组 Airtable 的组织架构｜刘大卫（联合创始人兼首席执行官）（注：Airtable 为低代码协作平台，Howie Liu 标准译名为 “刘大卫”）
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24,835次观看 2025年8月31日 Lenny's PodcastHowie Liu is the co-founder and CEO of Airtable, the no-code platform valued at around $12 billion. After a viral tweet declared “Airtable is dead” based on incorrect data, Howie led a radical transformation: reorganizing the entire company around AI, becoming an “IC CEO” who codes daily, and achieving over $100 million in free cash flow.What you’ll learn:1. The “fast thinking” vs. “slow thinking” team structure that lets Airtable ship AI features weekly (inspired by Daniel Kahneman) 2. Why Howie uses AI hourly (not daily) and is Airtable’s #1 inference-cost user globally 3. Why CEOs must become ICs again in the AI era (and how to restructure your calendar to make it possible) 4. Why “playing” with AI tools should be mandatory—Howie tells employees to cancel all meetings for a week to experiment 5. The specific skills product managers, engineers, and designers need to develop to succeed in the AI era 6. Why evals can kill innovation (and when to use “vibes” instead)Brought to you by:LucidLink—Real-time cloud storage for teams: https://www.lucidlink.com/lennyDX—The developer intelligence platform designed by leading researchers: http://getdx.com/lennyClaude.ai—The AI for problem solvers and enterprise: http://claude.ai/Transcript: https://www.lennysnewsletter.com/p/ho...My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/17...Where to find Howie Liu• X: https://x.com/howietl• LinkedIn: / howieliu • Email: howie@airtable.comWhere to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: / lennysan • LinkedIn: / lennyrachitsky In this episode, we cover:(00:00) Introduction to Howie Liu and Airtable (04:05) The “Airtable is dead” viral tweet controversy (08:07) The rise of IC CEOs (10:57) AI’s paradigm shift in product development (16:27) Specific changes Airtable has made (21:38) Fast- and slow-thinking teams (32:57) The emergence of new form factors in AI models (34:48) Airtable’s vision and philosophy (40:20) Empowering teams with AI tools (46:50) Encouraging experimentation and play (50:55) Cross-functional skills in product teams (01:03:35) The importance of evals and open-ended testing (01:08:06) Key strategies for AI-driven success (01:12:43) Counterintuitive startup wisdom (01:22:21) Don't step away from the details that you love (01:25:50) Advice for aspiring engineers and designers (01:30:00) Lightning round and final thoughtsReferenced:• Airtable: https://www.airtable.com/• All In podcast: https://allin.com/• Nikita Bier on X: https://x.com/nikitabier• Figma: https://www.figma.com/• The AI-native startup: 5 products, 7-figure revenue, 100% AI-written code | Dan Shipper (co-founder and CEO of Every): https://www.lennysnewsletter.com/p/in...• Every: https://every.to/• Cursor: https://cursor.com/• The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/th...• Windsurf: https://windsurf.com/• Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO): https://www.lennysnewsletter.com/p/th...• Rippling: https://www.rippling.com/• Omni: https://www.airtable.com/lp/ai-psu-plp• How ChatGPT accidentally became the fastest-growing product in history | Nick Turley (Head of ChatGPT at OpenAI): https://www.lennysnewsletter.com/p/in...• Palantir: https://www.palantir.com/• Harvey: https://www.harvey.ai/• v0: https://v0.dev/• Everyone’s an engineer now: Inside v0’s mission to create a hundred million builders | Guillermo Rauch (founder and CEO of Vercel, creators of v0 and Next.js): https://www.lennysnewsletter.com/p/ev...• Replit: https://replit.com/• Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/be...• Lovable: https://lovable.dev/• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (CEO and co-founder): https://www.lennysnewsletter.com/p/bu......References continued at: https://www.lennysnewsletter.com/p/ho...Production and marketing by https://penname.co/.For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed.
为所有前沿 AI 模型提供训练支持的专家网络内部故事｜加勒特・洛德
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13,661次观看 2025年8月24日 Lenny's PodcastGarrett Lord is co-founder and CEO of Handshake, which started as a career network for college students and new grads but recently discovered something extraordinary: they were sitting on the world’s largest network of academic experts—exactly what frontier AI labs desperately needed. With 500,000 PhDs and 3 million advanced degree holders creating training data, in just eight months they’ve built a new business that hit $50 million in revenue in its first four months and is on track to blow past $100M in the first 12 months.What you’ll learn:1. How Handshake found an opportunity to leverage their proprietary network of experts to launch a data-labeling business that’s on track to blow past $100 million ARR in 12 months 2. Why AI models need human experts (e.g. physics PhDs) to improve, and what this “data labeling” actually involves 3. Inside the actual work: what a biology PhD does for 8 hours that makes GPT-5 smarter 4. The playbook for building a startup inside a startup: separate teams, separate offices, separate everything 5. Why the shift from “generalist” to “expert” data labeling created a once-in-a-lifetime business opportunity 6. Why AI won’t eliminate entry-level jobs—it’s creating “Iron Man suits” that make junior employees 10x more productiveBrought to you by:CodeRabbit—Cut code review time and bugs in half. Instantly: https://coderabbit.link/lennyOrkes—The enterprise platform for reliable applications and agentic workflows: https://www.orkes.io/Claude.ai—The AI for problem solvers and enterprise: https://www.claude.ai/lennyTranscript: https://www.lennysnewsletter.com/p/in...My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/17...Where to find Garrett Lord:• X: https://x.com/garrettlord• LinkedIn: / garrettlord • Email: Garrett@joinhandshake.comWhere to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: / lennysan • LinkedIn: / lennyrachitsky In this episode, we cover:(00:00) Introduction to Garrett Lord (05:00) Understanding data labeling and its importance (13:08) The role of experts in AI model training (15:35) The future of AI and human collaboration (24:17) Why AI won’t eliminate entry-level jobs (27:58) The continuous improvement of AI models (33:05) The emergence of Handshake’s new business model (37:07) Incubating new ideas in established companies (40:42) Handshake's competitive advantage (45:43) Scaling up and meeting market demand (48:38) Overcoming challenges and adapting (53:08) The importance of separate teams and ownership (57:26) The future of job matching with AI (01:00:30) The biggest bottlenecks to advancing models further (01:02:37) Lightning round and final thoughtsReferenced:• GPQA: https://github.com/idavidrein/gpqa• Handshake: https://joinhandshake.com/• OpenAI’s CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/ke...• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder and CEO of StackBlitz): https://www.lennysnewsletter.com/p/in...• Goldman Sachs: https://www.goldmansachs.com/• General Motors: https://www.gm.com/• Google: https://about.google/• Sahil Bhaiwala on LinkedIn: / sahil-bhaiwala-459b0354 • Francisco “Paco” Guzman on LinkedIn: / guzmanhe • Avery Yip on LinkedIn: / averyyip • Game of Thrones on HBO: https://www.hbomax.com/shows/game-of-...• SNOO: https://www.happiestbaby.com/products...• Careers at Handshake: https://joinhandshake.com/careers/Recommended books:• Zero to One: Notes on Startups, or How to Build the Future: https://www.amazon.com/Zero-One-Notes...• The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers―Straight Talk on the Challenges of Entrepreneurship: https://www.amazon.com/Hard-Thing-Abo...Production and marketing by https://penname.co/.For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed.
为何 ChatGPT 将成为下一个重要增长渠道（及如何把握机遇）｜布莱恩・鲍尔弗
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34,093次观看 2025年8月17日 Lenny's PodcastBrian Balfour is the founder of Reforge, the former VP of Growth at HubSpot, and a student (and teacher) of product growth. Brian has studied every major platform shift—from Facebook to Apple to Google—and he’s spotted a pattern that’s about to repeat with ChatGPT.In this conversation, you’ll learn:1. The 4-step cycle every platform follows (and why ChatGPT just entered step 2) 2. Why ChatGPT’s platform launch could be bigger than Facebook’s early platform 3. The exact signals that ChatGPT will launch a third-party platform within six months 4. Why you have six months (not years) to make your platform bet 5. Why companies that don’t integrate with ChatGPT will lose to competitors that do 6. How Zynga grew to $1B by betting on Facebook’s platform early (before it was obvious) 7. Why so few companies are actually doing what they need to be doing right nowBrought to you by:DX—The developer intelligence platform designed by leading researchers: http://getdx.com/lennyBasecamp—The famously straightforward project management system from 37signals: https://www.basecamp.com/lennyMiro—A collaborative visual platform where your best work comes to life: https://miro.com/lennyTranscript: https://www.lennysnewsletter.com/p/wh...My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/17...Where to find Brian Balfour:• X: / bbalfour • LinkedIn: / bbalfour • Website: https://brianbalfour.com/• Substack: https://blog.brianbalfour.com/• Podcast: https://www.reforge.com/podcast/unsol...Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: / lennysan • LinkedIn: / lennyrachitsky In this episode, we cover:(00:00) Welcome back, Brian! (04:13) The changing landscape of product growth (05:09) The importance of distribution (08:14) The role of new distribution platforms (09:45) The four-step cycle of distribution platforms (17:38) Examples of platform cycles (30:01) The rise of ChatGPT (44:47) The future of AI agents (46:01) Preferred partners and platform credibility (47:18) Monetization mechanisms and free tiers (48:14) Betting strategies for startups (01:04:34) Adopting AI tools: challenges and strategies (01:08:41) The importance of hard constraints (01:14:23) Effective AI adoption in companies (01:19:05) Lightning round and final thoughtsReferenced:• The Next Great Distribution Shift: https://blog.brianbalfour.com/p/the-n...• Brian Balfour: 10 lessons on career, growth, and life: https://www.lennysnewsletter.com/p/br...• This Week #9: Breaking into growth, leading with influence, and (not) stepping on toes: https://www.lennysnewsletter.com/p/th...• Distribution vs. Innovation: https://a16z.com/distribution-vs-inno...• On Platform Shifts and AI: https://caseyaccidental.com/on-platfo...• How to sell your ideas and rise within your company | Casey Winters, Eventbrite: https://www.lennysnewsletter.com/p/ho...• Thinking beyond frameworks | Casey Winters (Pinterest, Eventbrite, Airbnb, Tinder, Canva, Reddit, Grubhub): https://www.lennysnewsletter.com/p/th...• ChatGPT: https://chatgpt.com/• Claude: https://claude.ai/• Gemini: https://gemini.google.com/• Vine: https://en.wikipedia.org/wiki/Vine_(s...) • Periscope: https://en.wikipedia.org/wiki/Perisco...) • Myspace: https://en.wikipedia.org/wiki/Myspace• Friendster: https://en.wikipedia.org/wiki/Friendster• AltaVista: https://en.wikipedia.org/wiki/AltaVista• Lycos: https://www.lycos.com/• HubSpot: https://www.hubspot.com/• Zynga: https://www.zynga.com/• TBPN: https://www.tbpn.com/• Deedy Das on LinkedIn: / debarghyadas • ChatGPT’s product retention curves are a product manager's wet dream: / debarghyadas_chatgpts-product-retention-cu... • Windsurf: https://windsurf.com/• Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO): https://www.lennysnewsletter.com/p/th......References continued at: https://www.lennysnewsletter.com/p/wh...Production and marketing by https://penname.co/.For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed.
他挽救了 OpenAI、发明了 “点赞” 按钮、参与打造谷歌地图：布雷特・泰勒（Sierra 公司）
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87,864次观看 2025年7月31日 Lenny's PodcastBret Taylor’s legendary career includes being CTO of Meta, co-CEO of Salesforce, chairman of the board at OpenAI (yes, during that drama), co-creating both Google Maps and the Like button, and founding three companies. Today he’s the founder and CEO of Sierra, an AI agent company transforming customer service. He’s one of the few people I’ve met who’s been wildly successful at every level—from engineer to C-suite executive to founder—and across almost every discipline, including PM, engineer, CTO, COO, CPO, CEO, and board member.In this conversation, you’ll learn:1. The brutal product review that nearly ended his Google career—and how that failure led to creating Google Maps 2. The question Sheryl Sandberg taught him to ask every morning (“What’s the most impactful thing I can do today?”) that transformed how he approached every role 3. The three AI market segments that matter 4. Why AI agents will replace SaaS products 5. His framework for knowing whose advice to actually listen to—and how that came in handy during the OpenAI board drama 6. The counterintuitive go-to-market strategy most AI startups get wrong 7. Sierra’s outcome-based pricing model that’s transforming how enterprise software is sold (and why every SaaS company should adopt it) 8. What he’s teaching his kids about AI that every parent should knowBrought to you by:CodeRabbit—Cut code review time and bugs in half. Instantly: https://coderabbit.link/lennyBasecamp—The famously straightforward project management system from 37signals: https://www.basecamp.com/lennyVanta—Automate compliance. Simplify security: https://vanta.com/lennyTranscript: https://www.lennysnewsletter.com/p/he...My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/16...Where to find Bret Taylor:• X: https://x.com/btaylor• LinkedIn: / brettaylor Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: / lennysan • LinkedIn: / lennyrachitsky In this episode, we cover:(00:00) Introduction to Bret Taylor (04:10) Bret’s early career and first major mistake (08:24) The birth of Google Maps (11:57) Lessons from FriendFeed and the importance of honest feedback (31:30) The future of coding and AI’s role (45:26) Preparing the next generation for an AI-driven world (48:46) AI in education (52:05) Business strategies in the AI market (01:04:38) Outcome-based pricing in AI (01:09:15) Productivity gains and AI (01:17:35) Go-to-market strategies for AI products (01:21:49) Lightning round and final thoughtsReferenced:• Marissa Mayer on LinkedIn: / marissamayer • “Lazy Sunday”—SNL: • Lazy Sunday - SNL Digital Short • Quip: https://quip.com/• Sierra: https://sierra.ai/• FriendFeed: https://en.wikipedia.org/wiki/FriendFeed• Sheryl Sandberg on LinkedIn: / sheryl-sandberg-5126652 • Jim Norris on LinkedIn: / halfspin • Paul Buchheit on X: https://x.com/paultoo• Sanjeev Singh on LinkedIn: / sanjeev-singh-20a1b72 • Barack Obama: https://www.obamalibrary.gov/obamas/p...• Oprah Winfrey: https://en.wikipedia.org/wiki/Oprah_W...• Ashton Kutcher: https://en.wikipedia.org/wiki/Ashton_...• PayPal Mafia: https://en.wikipedia.org/wiki/PayPal_...• Sam Altman on X: https://x.com/sama• Warren Buffett on X: https://x.com/warrenbuffett• Unix: https://en.wikipedia.org/wiki/Unix• Fortran: https://en.wikipedia.org/wiki/Fortran• C: https://en.wikipedia.org/wiki/C_(prog...) • Python: https://www.python.org/• Perl: https://www.perl.org/• Rust: https://www.rust-lang.org/• Eleven Labs: https://elevenlabs.io/• The exact AI playbook (using MCPs, custom GPTs, Granola) that saved ElevenLabs $100k+ and helps them ship daily | Luke Harries (Head of Growth): https://www.lennysnewsletter.com/p/th...• Confluent: https://www.confluent.io/• Databricks: https://www.databricks.com/• Snowflake: https://www.snowflake.com• Harvey: https://www.harvey.ai/• Behind the founder: Marc Benioff: https://www.lennysnewsletter.com/p/be...• Larry Summers’s website: https://larrysummers.com/• AutoCAD: https://www.autodesk.com/products/aut...• Revit: https://www.autodesk.com/products/revit/...References continued at: https://www.lennysnewsletter.com/p/he...Production and marketing by https://penname.co/.For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed.
那一个能挽救产品职业生涯的关键问题｜马特・勒梅
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24,131次观看 2025年8月14日 Lenny's PodcastMatt LeMay spent 13 years as a music critic at Pitchfork before becoming one of product management’s most influential voices. He’s consulted with companies from startups to Fortune 500s and authored two essential PM books, including Impact-First Product Teams. After watching countless product teams get laid off despite “doing everything right,” he discovered a harsh truth: most PMs are optimizing for the wrong things.In this conversation, you’ll learn:1. The one question that predicts if your team will survive the next layoffs (and why most teams can’t answer it) 2. Why following product “best practices” perfectly can actually accelerate your path to unemployment 3. The “low-impact PM death spiral”—how teams accidentally make themselves irrelevant 4. How to push back on executives without saying “no” (the options, plus a recommendation framework) 5. The counterintuitive reason why the happiest PMs are also the most commercially minded 6. The Liz Phair review that made Matt an internet villain for 22 years—and what it taught him about product managementBrought to you by:Enterpret—Transform customer feedback into product growth: https://enterpret.com/lennyPragmatic Institute—Industry‑recognized product, marketing, and AI training & certifications: https://pragmaticinstitute.com/lennyClaude.ai—The AI for problem solvers and enterprise: http://claude.ai/Transcript: https://www.lennysnewsletter.com/p/th...My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/16...Where to find Matt LeMay:• Instagram: / mttlmy • LinkedIn: / mattlemay • Website: https://mattlemay.com/Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: / lennysan • LinkedIn: / lennyrachitsky In this episode, we cover:(00:00) Introduction to Matt LeMay (04:23) Matt’s background and transition to product management (06:47) The goal of Matt's new book (12:00) How to stress test your thinking as a PM (15:32) Thinking like the CEO (17:33) The role of a product manager (23:36) The low-impact PM death spiral (27:47) Case study: Mailchimp’s transition to a platform company (32:53) Radical acceptance (41:24) Embracing constraints in product management (44:23) Steps to become an impact-first product team (49:38) Setting effective goals (01:02:15) Prioritization and impact estimation (01:07:58) Navigating stakeholder management (01:12:35) Summarizing the 3 steps (01:16:36) Lightning round and final thoughtsReferenced:• Pitchfork: https://pitchfork.com/• Daniel Ek’s memo: https://newsroom.spotify.com/2023-12-...• How to create a winning product strategy | Melissa Perri: https://www.lennysnewsletter.com/p/ho...• Everything you’ve ever wanted to know about SAFe and the product owner role | Melissa Perri (author, founder of Product Institute): https://www.lennysnewsletter.com/p/pr...• Mailchimp: https://mailchimp.com/• Intuit: https://www.intuit.com/• Natalia Williams on LinkedIn: / nataliatwilliams • The ultimate guide to OKRs | Christina Wodtke (Stanford): https://www.lennysnewsletter.com/p/th...• Miro: https://miro.com/• Prioritizing: https://www.lennysnewsletter.com/p/pr...• Temptation Island on Netflix: https://www.netflix.com/title/81744518• Mark L. Walberg’s website: https://markwalbergtv.com/about• Antiques Roadshow on PBS: https://www.pbs.org/wgbh/roadshow/• Milkman amp: https://milkmansound.com/collections/...• Matt’s review of Liz Phair’s self-titled album: https://pitchfork.com/reviews/albums/...• Pitchfork Critic Apologizes for Bashing Liz Phair Album; Singer Graciously Accepts: https://variety.com/2019/music/news/p...• RedMonk: https://redmonk.com/Recommended books:• Product Management in Practice: A Practical, Tactical Guide for Your First Day and Every Day After: https://www.amazon.com/Product-Manage...• Impact-First Product Teams: Define Success. Do Work That Matters. Be Indispensable.: https://www.amazon.com/Impact-first-P...• Escaping the Build Trap: How Effective Product Management Creates Real Value: https://www.amazon.com/Escaping-Build......Resources continued at: https://www.lennysnewsletter.com/p/th...Production and marketing by https://penname.co/.For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed.
Intercom 如何通过押注 AI 实现浴火重生｜奥恩・麦凯布（创始人兼首席执行官）（注：Intercom 为客户沟通平台）
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45,912次观看 2025年8月21日 Lenny's PodcastEoghan McCabe is the founder and CEO of Intercom, a customer service platform that has successfully pivoted to become an AI-first company with its agent product, Fin. After stepping away from the CEO role in 2020 due to health issues, Eoghan returned to find the company’s growth had stalled. Just one month after his return, ChatGPT launched, and within six weeks, Intercom had a working prototype of what would become Fin. In this conversation, Eoghan shares the brutal reality of transforming a late-stage SaaS business valued at multiple billions into an AI-first company that’s now growing faster than most public software companies.We discuss:1. Why Eoghan believes most late-stage companies won’t survive the AI transition 2. The “founder mode” transformation that required firing 40% of staff and resulted in 98% employee satisfaction 3. Why having “nothing to lose” is the ultimate advantage in AI transformation (and why comfortable companies will fail) 4. How Intercom transformed from a plateauing SaaS business to an AI-first company growing at 300%+ 5. How Intercom’s pricing evolved from “the most hated in SaaS” to a model that charges just $0.99 per resolved ticket 6. The cultural transformation required to compete with AI-native startups 7. How 12 years of therapy and a period of “ego death” shaped Eoghan’s leadership approachTranscript: https://www.lennysnewsletter.com/p/ho...My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/17...Brought to you by:Great Question—Empower everyone to run great research: https://www.greatquestion.com/lennyWorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs: https://workos.com/lennyDX—The developer intelligence platform designed by leading researchers: https://getdx.com/lennyWhere to find Eoghan McCabe:• X: https://x.com/eoghan• LinkedIn: / eoghanmccabe • Website: https://eoghanmccabe.com/Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: / lennysan • LinkedIn: / lennyrachitsky In this episode, we cover:(00:00) Introduction to Eoghan (05:00) The state of Intercom (09:53) The decision to pivot to AI (12:33) Why Eoghan is "anti-bot" in customer service (16:19) Pricing strategy evolution (19:26) Implementing the AI transformation (26:11) Cultural and organizational changes (31:18) Surviving a coup attempt (40:05) The future of AI and business (45:11) AI's impact on jobs (48:44) AI and human creativity (50:26) The importance of young AI talent (55:00) The cultural shift in AI adoption (58:00) Personal growth and leadership (01:04:34) Intercom’s success in producing product leaders (01:11:05) Intercom’s unique company culture (01:14:11) Lightning round and final thoughtsReferenced:• Intercom: https://www.intercom.com/• Fin: https://fin.ai/• Des Traynor on LinkedIn: / destraynor • The art and science of pricing | Madhavan Ramanujam (Monetizing Innovation, Simon-Kucher): https://www.lennysnewsletter.com/p/th...• Pricing your AI product: Lessons from 400+ companies and 50 unicorns | Madhavan Ramanujam: https://www.lennysnewsletter.com/p/pr...• Brian Chesky’s new playbook: https://www.lennysnewsletter.com/p/br...• Behind the founder: Marc Benioff: https://www.lennysnewsletter.com/p/be...• Anthropic co-founder on quitting OpenAI, AGI predictions, $100M talent wars, 20% unemployment, and the nightmare scenarios keeping him up at night | Ben Mann: https://www.lennysnewsletter.com/p/an...• Fergal Reid on LinkedIn: / fergalreid • How Perplexity builds product: https://www.lennysnewsletter.com/p/ho...• Yosi Amram’s website: https://yamram.com/• (Nathaniel Russell) Ego Death Now: https://heythereprojects.shop/product...• Daniel Kahneman: https://en.wikipedia.org/wiki/Daniel_...• Palantir: https://www.palantir.com/• Stripe: https://stripe.com/• Revolut: https://www.revolut.com/en-US/• Paul Adams on LinkedIn: / pauladams • What AI means for your product strategy | Paul Adams (CPO of Intercom): https://www.lennysnewsletter.com/p/wh......References continued at: https://www.lennysnewsletter.com/p/ho...Production and marketing by https://penname.co/.For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed.
ChatGPT 内部故事：史上增长最快的产品｜尼克・特利（OpenAI）
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179,438次观看 2025年8月9日 Lenny's PodcastNick Turley is Head of ChatGPT, the fastest-growing product in history, with 700 million weekly active users (10% of the world’s population). He was part of the original hackathon team that shipped ChatGPT in just 10 days, helped it grow from zero to billions in revenue, and leads product for what may be the most consequential product of our time. We recorded this the day before GPT-5 launched.We discuss:1. The 10-day sprint from deciding to ship ChatGPT to Sam Altman’s tweet (and why it was originally called “Chat with GPT-3.5”) 2. How they ran a willingness-to-pay Van Westendorp survey in their Discord to decide on the $20/month price point that everyone copied 3. The “Is it maximally accelerated?” philosophy that drives OpenAI’s insane shipping velocity 4. Why ChatGPT’s retention curve “smiles”—users leave, then come back months later using it more 5. The accidental decisions that changed history, including not having a waitlist 6. The impact ChatGPT will have on SEO and product growth 7. The counterintuitive reason why shipping unpolished AI features beats waiting for perfection 8. Why ChatGPT intentionally shipped with that “ugly” model-chooser dropdown 9. How TikTok comments became a primary user research channel early onBrought to you by:Orkes—The enterprise platform for reliable applications and agentic workflows: https://www.orkes.io/Vanta—Automate compliance. Simplify security: https://vanta.com/lennyPostHog—How developers build successful products: https://posthog.com/lennyTranscript: https://www.lennysnewsletter.com/p/in...My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/17...Where to find Nick Turley• X: https://x.com/nickaturley• LinkedIn: / nicholasturley • Website: https://nickturley.com/Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: / lennysan • LinkedIn: / lennyrachitsky In this episode, we cover:(00:00) Introduction to Nick Turley (04:52) GPT-5 launch (09:13) The vision for ChatGPT and AI assistants (13:52) The early days of ChatGPT (17:14) The success and impact of ChatGPT (20:44) Product development and iteration (23:11) Maximally accelerated: the OpenAI approach (26:17) Retention and user engagement (33:42) The future of chat interfaces (36:31) The evolution of ChatGPT (38:52) Subscription model and pricing strategies (42:10) Enterprise adoption and challenges (44:10) Balancing multiple product lines (52:13) Emergent use cases and user feedback (01:02:15) OpenAI’s unique product development approach (01:05:07) The importance of team composition (01:08:50) Balancing speed and quality in AI development (01:14:23) The role of evals in product development (01:16:13) The future of AI-driven content and GPTs (01:21:51) Philosophy and product leadership (01:23:47) Career journey and advice (01:27:49) Lightning round and final thoughtsReferenced:• GPT-5 and the new era of work: https://openai.com/index/gpt-5-new-er...• Instacart: https://www.instacart.com/• OpenAI’s CPO on how AI changes must-have skills, moats, coding, startup playbooks, more | Kevin Weil (CPO at OpenAI, ex-Instagram, Twitter): https://www.lennysnewsletter.com/p/ke...• Sam Altman on X: https://x.com/sama• Figma: https://www.figma.com/• Van Westendorp’s Price Sensitivity Meter: https://en.wikipedia.org/wiki/Van_Wes...• Rahul Vohra on LinkedIn: / rahulvohra • Superhuman’s secret to success: Ignoring most customer feedback, manually onboarding every new user, obsessing over every detail, and positioning around a single attribute: speed | Rahul Vohra (CEO): https://www.lennysnewsletter.com/p/su...• Dropbox: http://dropbox.com/• Airtable: https://www.airtable.com/• Notion: https://www.notion.com/• Instant Pot: https://instantpot.com/• MS-DOS: https://en.wikipedia.org/wiki/MS-DOS• Expanding on what we missed with sycophancy: https://openai.com/index/expanding-on...• What we’re optimizing ChatGPT for: https://openai.com/index/how-we're-op...• Charlie Munger’s quote: / show-me-the-incentive-and-i-ll-show-you-th... • Anthropic’s CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/an...• Beyond vibe checks: A PM’s complete guide to evals: https://www.lennysnewsletter.com/p/be......References continued at: https://www.lennysnewsletter.com/p/in...Production and marketing by https://penname.co/.For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed.
AI 产品定价策略：来自 400 多家公司与 50 家独角兽企业的经验｜马达范・拉马努詹
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38,614次观看 2025年7月27日 Lenny's PodcastMadhavan Ramanujam is the world’s foremost expert on pricing and monetization strategy. As managing partner at Simon-Kucher, he helped over 250 companies, including 30 unicorns, architect their pricing strategies. He’s the author of the definitive book on pricing, Monetizing Innovation. Now he’s back with a sequel, Scaling Innovation, which reveals how to build enduring businesses by dominating both market share and wallet share. He recently left Simon-Kucher to launch his own fund, 49 Palms, focused on helping early-stage AI companies.In this conversation, we discuss:1. The 2x2 framework that identifies your optimal pricing model 2. Why AI companies can capture 25% to 50% of value created, vs. 10% to 20% for traditional SaaS products 3. Why popular AI coding tools may have already doomed themselves with underpricing 4. The “give-and-get” framework top negotiators use to extract maximum value from every deal 5. The negotiation strategy that helped one founder 4x their deal size overnight 6. How to frame POCs as “business case creation” instead of technical demos (and why this changes everything) 7. Why AI companies must get monetization right from day one—not “figure it out later” 8. How companies like Intercom’s Fin and Sierra pioneered outcome-based pricing (charging $0.99 per AI resolution) 9. The single question that reveals if your pricing is too complexBrought to you by:Enterpret—Transform customer feedback into product growth:https://enterpret.com/lennyDX—A platform for measuring and improving developer productivity: https://getdx.com/lennyPersona—A global leader in digital identity verification: https://withpersona.com/lennyTranscript: https://www.lennysnewsletter.com/p/pr...My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/16...Where to find Madhavan Ramanujam:• X: https://x.com/madhavansf• LinkedIn: / madhavansf • Promo email for Scaling Innovation: promo@49palmsvc.com — If you’re purchasing more than five copies, send a screenshot of your receipt to enter Madhavan’s exclusive bundle raffle.Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: / lennysan • LinkedIn: / lennyrachitsky In this episode, we cover:(00:00) Introduction to Madhavan and his work(04:30) The core thesis of Scaling Innovation(09:20) Common traps founders fall into (12:06) Beautifully simple pricing (15:00) Mastering negotiations (26:51) Other strategies for effective pricing and monetization (27:35) How AI pricing is different (31:33) Handling POCs (36:25) The importance of mastering monetization (38:58) Choosing the right AI pricing model (43:13) Current trends in AI pricing (44:48) Strategizing for outcome-based models (50:23) Packaging strategies for scaling (51:37) Adapting pricing strategies over time (53:40) Key axioms for pricing success (58:00) Takeaways for founders (01:01:33) Lightning round and final thoughtsReferenced:• The art and science of pricing | Madhavan Ramanujam (Monetizing Innovation, Simon-Kucher): https://www.lennysnewsletter.com/p/th...• Cursor: https://www.cursor.com/• The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/th...• Sierra Finn: http://www.sierrafinn.com/• Chargeflow: https://www.chargeflow.io/• GitHub: https://github.com/• Intercom: https://www.intercom.com/• Warren Buffett’s quote: / if-you-ve-got-the-power-to-raise-prices-wi... • Sierra: https://sierra.ai/• Clay Bavor on LinkedIn: / claybavor • Mission: Impossible—The Final Reckoning: https://www.imdb.com/title/tt9603208/• Delphi: https://www.delphi.ai/• Dara Ladjevardian on LinkedIn: / dara-ladjevardian • Sam Spelsberg on LinkedIn: / samuel-spelsberg • Lennybot: https://www.lennybot.com/• Granola: https://www.granola.ai/• Simon-Kucher: https://www.simon-kucher.com/• Josh Bloom on LinkedIn: / joshuabloompricingconsulting Recommended books:• Monetizing Innovation: How Smart Companies Design the Product Around the Price: https://www.amazon.com/Monetizing-Inn...• Scaling Innovation: How Smart Companies Architect Profitable Growth: https://www.amazon.com/dp/1119633060...References continued at: https://www.lennysnewsletter.com/p/pr...Production and marketing by https://penname.co/.For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed.
8 万家公司如何借助 AI 开展业务：将产品视为有机生命体，组织结构图走向消亡｜阿莎・沙尔马
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25,908次观看 2025年8月28日 Lenny's PodcastAsha Sharma leads AI product strategy at Microsoft, where she works with thousands of companies building AI products and has unique visibility into what’s working (and what’s not) across more than 15,000 startups and enterprises. Before Microsoft, Asha was COO at Instacart, and VP of Product & Engineering at Meta, notably leading product for Messenger.What you’ll learn:1. Why we’re moving from “product as artifact” to “product as organism” and what this means for builders 2. Microsoft’s “seasons” planning framework that allows them to adapt quickly in the AI era 3. The death of the org chart: how agents are turning hierarchies into task networks and why “the loop, not the lane” is the new organizing principle 4. Why post-training will soon see more investment than pre-training—and how to build your own AI moat with fine-tuning 5. Her prediction for the “agentic society”—where org charts become work charts and agents outnumber humans in your company 6. The three-phase pattern every successful AI company follows (and why most fail at phase one) 7. The rise of code-native interfaces and why GUIs might be going the way of the desktop 8. What Asha learned from Satya Nadella about optimismBrought to you by:Enterpret—Transform customer feedback into product growth: https://enterpret.com/lennyDX—The developer intelligence platform designed by leading researchers: https://getdx.com/lennyFin—The #1 AI agent for customer service: https://fin.ai/lennyTranscript: https://www.lennysnewsletter.com/p/ho...My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/17...Where to find Asha Sharma:• LinkedIn: / aboutasha • Blog: https://azure.microsoft.com/en-us/blo...Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: / lennysan • LinkedIn: / lennyrachitsky In this episode, we cover:(00:00) Introduction to Asha Sharma (04:18) From “product as artifact” to “product as organism” (06:20) The rise of post-training and the future of AI product development (09:10) Successful AI companies: patterns and pitfalls (12:01) The evolution of full-stack builders (14:15) “The loop, not the lane”—the new organizing principle (16:24) The future of user interfaces: from GUI to code-native (19:34) The rise of the agentic society (22:58) The “work chart” vs. the “org chart” (26:24) How Microsoft is using agents (28:23) Planning and strategy in the AI landscape (35:38) The importance of platform fundamentals (39:31) Lessons from industry giants (42:10) What’s driving Asha (44:30) Reinforcement learning (RL) and optimization loops (49:19) Lightning round and final thoughtsReferenced:• Copilot: https://copilot.microsoft.com/• Cursor: https://cursor.com/• The rise of Cursor: The $300M ARR AI tool that engineers can’t stop using | Michael Truell (co-founder and CEO): https://www.lennysnewsletter.com/p/th...• Inside ChatGPT: The fastest growing product in history | Nick Turley (Head of ChatGPT at OpenAI): https://www.lennysnewsletter.com/p/in...• GitHub: https://github.com• Dragon Medical One: https://www.microsoft.com/en-us/healt...• Windsurf: https://windsurf.com/• Building a magical AI code editor used by over 1 million developers in four months: The untold story of Windsurf | Varun Mohan (co-founder and CEO): https://www.lennysnewsletter.com/p/th...• Lovable: https://lovable.dev/• Building Lovable: $10M ARR in 60 days with 15 people | Anton Osika (CEO and co-founder): https://www.lennysnewsletter.com/p/bu...• Bolt: http://bolt.com• Inside Bolt: From near-death to ~$40m ARR in 5 months—one of the fastest-growing products in history | Eric Simons (founder and CEO of StackBlitz): https://www.lennysnewsletter.com/p/in...• Replit: https://replit.com/•Behind the product: Replit | Amjad Masad (co-founder and CEO): https://www.lennysnewsletter.com/p/be...• He saved OpenAI, invented the “Like” button, and built Google Maps: Bret Taylor on the future of careers, coding, agents, and more: https://www.lennysnewsletter.com/p/he...• Sierra: https://sierra.ai/• Spark: https://github.com/features/spark• Peter Yang on X: https://x.com/petergyang• How AI will impact product management: https://www.lennysnewsletter.com/p/ho......References continued at: https://www.lennysnewsletter.com/p/ho...Production and marketing by https://penname.co/.For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.Lenny may be an investor in the companies discussed.
我如何使用LLMs
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【译文】我如何使用LLMS本篇文章以实例为导向，对大型语言模型及其不断扩展的相关功能进行了实用性的樱述，作为我面向大众推出的关于大型语言模理系列中的一篇新文章。在更为实际的后续内容中，我将带领大家了解我在日常生活中使用大型语言模型的多种方式。章节00:00:00 介绍不断发展的LLM生态系统00:02:54聊天机器人内部的交互00:13:12 基本LLM交互示作00:18:03 了解你正在使用的模型和定价层级00:22:54思考模型以及何时使用它们00:31:00 工具使用:互联网搜00:42:04 工具使用:深入研究00:50:57 文件上传，将文档添加到上下文中00:59:00 工具使用:python解释器，生态系统中的混乱程度01:04:35 ChatGPT高级数据分析、图表、绘图01:09:00 克劳德的工件、应用程序、图表01:14:02光标:作曲家，编写代码01:22:28 音频(语音)输入/输出01:27:37 高级语音模式，即模型内部的真实音频01:37:09 笔记本LM，播客生成014702自像输出-bALCE 意象图等。01:49:14 视频输入，在应用程序上指点并说话01:52:23 视频输出，Sora、Veo 2等。01:53:29 ChatGPT内存，自定义指令01:58:38 自定义GPTS02:06:30 总结链接提克代币https:/tiktokenizer.vercel.app/OpenA的ChatGPT https://chatgpt.comAnthropic的Claude https://claude.ai/谷歌的双子座https://gemini.google.com/xAl 的 Grok https://grok.com困惑度 https://www.perplexity.ai/.谷歌的NotebookLM https://notebooklm.google.com/光标 https://www.cursor.comMysteries Al播客的历史在Spotify上 https://open.spotify.com/show/3K4LRyM..我在视频中使用的可视化Ul:https://excalidraw.con我们构建的Excalidraw特定文件:https://drive.google.com/file/d/1DN3L.EurekaLabs和此视频的Discord频道:/discord数育用途许可本视频可免费用于教育和内部培训。教师、学生、学校、大学、非营利机构、企业和个人学习者可以将此内容自由用于课程、课程、内部培训和学习活动，前提是他们不参与商业转售、再分配、外部商业用途或修改内容以歪曲其意图。【原文】How I use LLMs1,845,776次观看 2025年2月28日The example-driven, practical walkthrough of Large Language Models and their growing list of related features, as a new entry to my general audience series on LLMs. In this more practical followup, I take you through the many ways I use LLMs in my own life.Chapters00:00:00 Intro into the growing LLM ecosystem00:02:54 ChatGPT interaction under the hood00:13:12 Basic LLM interactions examples00:18:03 Be aware of the model you're using, pricing tiers00:22:54 Thinking models and when to use them00:31:00 Tool use: internet search00:42:04 Tool use: deep research00:50:57 File uploads, adding documents to context00:59:00 Tool use: python interpreter, messiness of the ecosystem01:04:35 ChatGPT Advanced Data Analysis, figures, plots01:09:00 Claude Artifacts, apps, diagrams01:14:02 Cursor: Composer, writing code01:22:28 Audio (Speech) Input/Output01:27:37 Advanced Voice Mode aka true audio inside the model01:37:09 NotebookLM, podcast generation01:40:20 Image input, OCR01:47:02 Image output, DALL-E, Ideogram, etc.01:49:14 Video input, point and talk on app01:52:23 Video output, Sora, Veo 2, etc etc.01:53:29 ChatGPT memory, custom instructions01:58:38 Custom GPTs02:06:30 SummaryLinksTiktokenizer https://tiktokenizer.vercel.app/OpenAI's ChatGPT https://chatgpt.com/Anthropic's Claude https://claude.ai/Google's Gemini https://gemini.google.com/xAI's Grok https://grok.com/Perplexity https://www.perplexity.ai/Google's NotebookLM https://notebooklm.google.com/Cursor https://www.cursor.com/Histories of Mysteries AI podcast on Spotify https://open.spotify.com/show/3K4LRyM...The visualization UI I was using in the video: https://excalidraw.com/The specific file of Excalidraw we built up: https://drive.google.com/file/d/1DN3L...Discord channel for Eureka Labs and this video: / discord Educational Use LicensingThis video is freely available for educational and internal training purposes. Educators, students, schools, universities, nonprofit institutions, businesses, and individual learners may use this content freely for lessons, courses, internal training, and learning activities, provided they do not engage in commercial resale, redistribution, external commercial use, or modify content to misrepresent its intent.
让我们重现GPT-2(12400万)
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【译文】我们从零开始复制GPT-2（124M）。这段视频涵盖了整个过程：首先，我们构建GPT-2网络，然后优化其训练过程以使其运行得非常快，接着，我们按照GPT-2和GPT-3的论文及其超参数设置训练运行参数，然后启动运行，第二天早上回来查看我们的结果，并欣赏一些有趣的模型生成。请记住，在某些地方，本视频基于从零到英雄播放列表（见我的频道）中早期视频的知识。你也可以将这个视频看作构建我的nanoGPT仓库，到最后大约90%的相似性。链接:在 build-nanogpt GitHub 仓库中，将本视频中提到的所有更改作为单独的提交：https://github.com/karpathy/build-nan...nanoGPT 代码库：https://github.com/karpathy/nanoGPTllm.c repo: https://github.com/karpathy/llm.c我的网站：https://karpathy.ai补充链接:注意力就是你所需要的全部：https://arxiv.org/abs/1706.03762OpenAI GPT-3论文:https://arxiv.org/abs/2005.14165- OpenAI GPT-2论文:https://d4mucfpksywv.cloudfront.net/b...我正在训练模型的GPU来自Lambda GPU Cloud，我认为在云中生成按需GPU实例的最好和最简单的方法是:https://lambdalabs.com章节:00:00:00简介：让我们重现GPT-2（124M）00:03:39探索GPT-2（124M）OpenAI检查点00:13:47第一节：实施GPT-2网络。模块00:28:08 加载拥抱脸/GPT-2参数00:31:00 执行转发通行证以获取登录信息00:33:31 采样初始化，前缀令牌，令牌化00:37:02采样循环00:41:47 样本，自动检测设备00:45:50 让我们训练:数据批次（B，T） → logits（B， T，C）00:52:53交叉熵损失00:56:42优化循环:超配单个批次01:02:00 数据加载器 Lite01:06:14 参数共享 wte 和 lm_head01:13:47 模型初始化:std 0.02，剩余初始化01:22:18 第二节:让我们快点。GPU，混合精度，1000毫秒01:28:14 张量核，定时代码，TF32精度，333毫秒01:39:38 float16，梯度标度器，bfloat16，300毫秒01:48:15 torch.compile，Python开销，内核融合，130毫秒02:00:18 闪烁注意，96毫秒02:06:54 漂亮/丑陋的数字。词汇大小 50257 → 50304， 93毫秒02:14:55 第三节:超级钳工，AdamW，梯度剪切02:21:06学习速率调度器:预热+余弦衰减02:26:21 批量大小计划，重量衰减，FusedAdamW，90毫秒02:34:09 梯度积累02:46:52分布式数据并行（DDP）03:10:21 GPT-2、GPT-3、FineWeb中使用的数据集03:23:10 验证数据分裂，验证丢失，采样恢复03:28:23 评价:HellaSwag，开始跑步03:43:05 第四节:早上会有结果！GPT-2和GPT-3复制体03:56:21 向llm.c呼叫，原始C/CUDA中的代码等效但更快03:59:39 摘要，哇，build-nanogpt github 仓库更正：我将在build-nanogpt GitHub仓库（上方链接）中发布所有勘误和后续更新。超级感谢:我昨天在频道中实验性地启用了这些功能。这完全是可选的，且仅适用于经济状况较好的用户。所有收入都将用于支持我在AI+教育领域的工作。【原文】We reproduce the GPT-2 (124M) from scratch. This video covers the whole process: First we build the GPT-2 network, then we optimize its training to be really fast, then we set up the training run following the GPT-2 and GPT-3 paper and their hyperparameters, then we hit run, and come back the next morning to see our results, and enjoy some amusing model generations. Keep in mind that in some places this video builds on the knowledge from earlier videos in the Zero to Hero Playlist (see my channel). You could also see this video as building my nanoGPT repo, which by the end is about 90% similar.Links:build-nanogpt GitHub repo, with all the changes in this video as individual commits: https://github.com/karpathy/build-nan...nanoGPT repo: https://github.com/karpathy/nanoGPTllm.c repo: https://github.com/karpathy/llm.cmy website: https://karpathy.aimy twitter: / karpathy our Discord channel: / discord Supplementary links:Attention is All You Need paper: https://arxiv.org/abs/1706.03762OpenAI GPT-3 paper: https://arxiv.org/abs/2005.14165 - OpenAI GPT-2 paper: https://d4mucfpksywv.cloudfront.net/b... The GPU I'm training the model on is from Lambda GPU Cloud, I think the best and easiest way to spin up an on-demand GPU instance in the cloud that you can ssh to: https://lambdalabs.com Chapters:00:00:00 intro: Let’s reproduce GPT-2 (124M)00:03:39 exploring the GPT-2 (124M) OpenAI checkpoint00:13:47 SECTION 1: implementing the GPT-2 nn.Module00:28:08 loading the huggingface/GPT-2 parameters00:31:00 implementing the forward pass to get logits00:33:31 sampling init, prefix tokens, tokenization00:37:02 sampling loop00:41:47 sample, auto-detect the device00:45:50 let’s train: data batches (B,T) → logits (B,T,C)00:52:53 cross entropy loss00:56:42 optimization loop: overfit a single batch01:02:00 data loader lite01:06:14 parameter sharing wte and lm_head01:13:47 model initialization: std 0.02, residual init01:22:18 SECTION 2: Let’s make it fast. GPUs, mixed precision, 1000ms01:28:14 Tensor Cores, timing the code, TF32 precision, 333ms01:39:38 float16, gradient scalers, bfloat16, 300ms01:48:15 torch.compile, Python overhead, kernel fusion, 130ms02:00:18 flash attention, 96ms02:06:54 nice/ugly numbers. vocab size 50257 → 50304, 93ms02:14:55 SECTION 3: hyperpamaters, AdamW, gradient clipping02:21:06 learning rate scheduler: warmup + cosine decay02:26:21 batch size schedule, weight decay, FusedAdamW, 90ms02:34:09 gradient accumulation02:46:52 distributed data parallel (DDP)03:10:21 datasets used in GPT-2, GPT-3, FineWeb (EDU)03:23:10 validation data split, validation loss, sampling revive03:28:23 evaluation: HellaSwag, starting the run03:43:05 SECTION 4: results in the morning! GPT-2, GPT-3 repro03:56:21 shoutout to llm.c, equivalent but faster code in raw C/CUDA03:59:39 summary, phew, build-nanogpt github repoCorrections:I will post all errata and followups to the build-nanogpt GitHub repo (link above)SuperThanks:I experimentally enabled them on my channel yesterday. Totally optional and only use if rich. All revenue goes to to supporting my work in AI + Education.
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