Podcast appearances and mentions of dharmesh shah

Jason Cohen is a four-time founder (including two unicorns, one being WP Engine) and an investor in over 60 startups, and has been sharing his lessons on company building at A Smart Bear for nearly 20 years. In this episode, Jason shares his methodical five-step framework for diagnosing stalled growth—a problem that faces almost every team.We discuss:1. Jason's five-step framework: logo retention, pricing, NRR, marketing channels, target market2. A small tweak that'll double response rates on your cancellation surveys3. Why “it's too expensive” is almost never the real reason customers cancel4. The “elephant curve” of growth5. How repositioning the same product can increase revenue 8x6. When to reconsider if growth is even the right goal for your business—Brought to you by:10Web—Vibe coding platform as an APIStrella—The AI-powered customer research platformBrex—The banking solution for startups—Episode transcript: https://www.lennysnewsletter.com/p/why-your-product-stopped-growing—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Jason Cohen:• Preorder Jason's book: https://preorder.hiddenmultipliers.com/• X: https://x.com/asmartbear• LinkedIn: https://www.linkedin.com/in/jasoncohen• Blog: https://longform.asmartbear.com• Website: https://wpengine.com—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction to Jason Cohen(05:19) Jason's writing journey(08:25) Questions to ask when your product stops growing(18:17) Getting real customer feedback(20:27) Analyzing cancellation reasons(26:54) Onboarding and activation(29:35) Quick summary(35:46) Revisiting pricing strategies(41:46) Positioning strategies(47:52) Why pricing is inseparable from your strategy(52:06) The importance of net revenue retention (NRR)(01:00:25) Asking whether or not this is good for the customer(01:04:34) Leveraging existing customers(01:06:42) Are your acquisition channels saturated? The “elephant curve”(1:09:41) Why all marketing channels eventually decline(01:12:04) Direct vs. indirect marketing channels(1:13:36) Getting creative with new channels(01:19:04) Do you actually need to grow?(01:25:57) Deciding when to quit(01:29:27) Book announcement(01:33:21) AI corner(01:34:35) Contrarian corner(01:37:43) Lightning round and final thoughts—Referenced:• Tyler Cowen's website: https://tylercowen.com• How to Perform a Customer Churn Analysis (and Why You Should): https://www.groovehq.com/blog/learn-from-customer-churn• Linear: https://linear.app• Jira: https://www.atlassian.com/software/jira• Patrick Campbell's post on X about pricing: https://x.com/Patticus/status/1702313260547006942• The art and science of pricing | Madhavan Ramanujam (Monetizing Innovation, Simon-Kucher): https://www.lennysnewsletter.com/p/the-art-and-science-of-pricing-madhavan• Pricing your AI product: Lessons from 400+ companies and 50 unicorns | Madhavan Ramanujam: https://www.lennysnewsletter.com/p/pricing-and-scaling-your-ai-product-madhavan-ramanujam• Pricing your SaaS product: https://www.lennysnewsletter.com/p/saas-pricing-strategy• M&A, competition, pricing, and investing | Julia Schottenstein (dbt Labs): https://www.lennysnewsletter.com/p/m-and-a-competition-pricing-and-investing• “Sell the alpha, not the feature”: The enterprise sales playbook for $1M to $10M ARR | Jen Abel: https://www.lennysnewsletter.com/p/the-enterprise-sales-playbook-1m-to-10m-arr• Buffer: https://buffer.com• AG1: https://drinkag1.com• How to find hidden growth opportunities in your product | Albert Cheng (Duolingo, Grammarly, Chess.com): https://www.lennysnewsletter.com/p/how-to-find-hidden-growth-opportunities-albert-cheng• How Duolingo reignited user growth: https://www.lennysnewsletter.com/p/how-duolingo-reignited-user-growth• The Elephant in the room: The myth of exponential hypergrowth: https://longform.asmartbear.com/exponential-growth• HubSpot: https://www.hubspot.com• Zigging vs. zagging: How HubSpot built a $30B company | Dharmesh Shah (co-founder/CTO): https://www.lennysnewsletter.com/p/lessons-from-30-years-of-building• Adjacency Matrix: How to expand after PMF: https://longform.asmartbear.com/adjacency/• Ecosystem is the next big growth channel: https://www.lennysnewsletter.com/p/ecosystem-is-the-next-big-growth• ChatGPT apps are about to be the next big distribution channel: Here's how to build one: https://www.lennysnewsletter.com/p/chatgpt-apps-are-about-to-be-the• 10 contrarian leadership truths every leader needs to hear | Matt MacInnis (Rippling): https://www.lennysnewsletter.com/p/10-contrarian-leadership-truths• Breaking the rules of growth: Why Shopify bans KPIs, optimizes for churn, prioritizes intuition, and builds toward a 100-year vision | Archie Abrams (VP Product, Head of Growth at Shopify): https://www.lennysnewsletter.com/p/shopifys-growth-archie-abrams• Geoffrey Moore on finding your beachhead, crossing the chasm, and dominating a market: https://www.lennysnewsletter.com/p/geoffrey-moore-on-finding-your-beachhead• ER on Prime Video: https://www.amazon.com/ER-Season-1/dp/B0FWK5WJQ4• The Pitt on Prime Video: https://www.amazon.com/The-Pitt-Season-1/dp/B0DNRR8QWD• Wispr Flow: https://wisprflow.ai• Anker: https://www.anker.com—Recommended books:• Will: https://www.amazon.com/Will-Smith/dp/1984877925• Monetizing Innovation: How Smart Companies Design the Product Around the Price: https://www.amazon.com/Monetizing-Innovation-Companies-Design-Product/dp/1119240867• Hidden Multipliers: Small Things That Accelerate Growth: https://preorder.hiddenmultipliers.com• On Writing Well: The Essential Guide to Mastering Nonfiction Writing and Effective Communication: https://www.amazon.com/Writing-Well-Classic-Guide-Nonfiction/dp/0060891548• Crossing the Chasm, 3rd Edition: The Updated Version of the Insightful Guide on Bringing Cutting-Edge Products to the Mainstream: https://www.amazon.com/Crossing-Chasm-3rd-Disruptive-Mainstream/dp/0062292986—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. To hear more, visit www.lennysnewsletter.com

Rachel Lockett is a sought-after executive coach and former HR leader at Stripe and Pinterest who now works with CEOs, founders, and tech leaders on emotional intelligence, resilience, and leadership skills. In this episode, Rachel shares powerful frameworks for coaching reports, having difficult conversations, avoiding burnout, and strengthening co-founder relationships. She also demonstrates these techniques through a live coaching session with me.We discuss:* When to coach and when to just tell people what to do [09:00]* The GROW technique for helping people figure out a solution for themselves [18:37]* Techniques for making difficult conversations less difficult [01:20:28]* Avoiding burnout and designing a more energizing career [41:55]* Building and sustaining a healthy co-founder relationship [01:06:50]* Creating a one-page plan that aligns your entire company [01:31:47]* Practical ways AI is transforming executive coaching and leadership development [01:36:50]* Why you should ask, “Would I enthusiastically rehire this person?” to clarify talent decisions [23:55]Also on Spotify and Apple PodcastsBrought to you by:Stripe—Helping companies of all sizes grow revenueVanta—Automate compliance. Simplify security.Persona—A global leader in digital identity verificationWhere to find Rachel Lockett:• LinkedIn: https://www.linkedin.com/in/rhlockett/• Website: https://www.lockettcoaching.comReferenced:• One-page plan template: https://www.lockettcoaching.com/#resources• Lockett Coaching Leadership Toolkit: https://www.dropbox.com/scl/fi/s74a9cn1ka1ebz6pglypf/Leadership-Toolkit_-Coaching-Rachel-Lockett.pdf?rlkey=yg2m9df2ziwy0fa6p0dt4gcfu&st=dgzvnf76&dl=0• Renew Your Co-Founder Vows—and Other Tactics for Strengthening the Most Important Relationship in Your Startup: https://review.firstround.com/five-practices-to-strengthen-your-co-founder-relationship/• First Round Guide to Co-Founder Check-Ins: https://docs.google.com/document/d/1yUosmfMuE-8-sAwPrEPDcGqkJLVLWg5dC2_8lcXm7U4/edit?tab=t.0• Coinbase: https://www.coinbase.com• Management Time: Who's Got the Monkey?: https://hbr.org/1999/11/management-time-whos-got-the-monkey• Chuck Palahniuk's quote from Fight Club: https://www.goodreads.com/quotes/1338270-people-don-t-listen-they-just-wait-for-their-turn-to• Patrick Collison on X: https://x.com/patrickc• Stripe: https://stripe.com• Remind: https://www.remind.com• Zach Abrams on LinkedIn: https://www.linkedin.com/in/zacharyabrams• Brex: https://www.brex.com• Bridge: https://www.bridge.xyz• 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/superhumans-secret-to-success-rahul-vohra• Zigging vs. zagging: How HubSpot built a $30B company | Dharmesh Shah (co-founder/CTO): https://www.lennysnewsletter.com/p/lessons-from-30-years-of-building• The Enneagram Institute: https://www.enneagraminstitute.com• How to build deeper, more robust relationships | Carole Robin (Stanford GSB professor, “Touchy Feely”): https://www.lennysnewsletter.com/p/build-robust-relationships-carole-robin• How have I been complicit in creating the conditions I say I don't want? | Jerry Colonna (CEO of Reboot, executive coach, former VC): https://www.lennysnewsletter.com/p/jerry-colonna• How Netflix builds a culture of excellence | Elizabeth Stone (CTO): https://www.lennysnewsletter.com/p/how-netflix-builds-a-culture-of-excellence• What Is PeopleFirst?: https://alpineinvestors.com/story/what-is-peoplefirst• How to break out of autopilot and create the life you want | Graham Weaver (Stanford GSB professor, founder of Alpine Investors): https://www.lennysnewsletter.com/p/how-to-break-out-of-autopilot-graham-weaver• Granola: https://www.granola.ai• KPop Demon Hunters on Netflix: https://www.netflix.com/title/81498621• Loom: https://www.loom.com• Joseph Campbell's quote: https://www.goodreads.com/quotes/21396-if-you-can-see-your-path-laid-out-in-front• Wes Anderson's short films (Roald Dahl) on Netflix: https://www.netflix.com/tudum/articles/wes-anderson-netflix-short-filmsRecommended books:• Nonviolent Communication: A Language of Life: Life-Changing Tools for Healthy Relationships: https://www.amazon.com/Nonviolent-Communication-Language-Life-Changing-Relationships/dp/189200528X• The 15 Commitments of Conscious Leadership: A New Paradigm for Sustainable Success: https://www.amazon.com/15-Commitments-Conscious-Leadership-Sustainable/dp/0990976904• Designing Your Life: How to Build a Well-Lived, Joyful Life: https://www.amazon.com/Designing-Your-Life-Well-Lived-Joyful/dp/1101875321• Roald Dahl books: https://www.amazon.com/Roald-Dahl-Collection-Books-Box/dp/0241377293Production 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.My biggest takeaways from this conversation: To hear more, visit www.lennysnewsletter.com

In this episode of OnBase, host Chris Moody sits down with Jasmeet Sawhney to explore what it means to lead marketing in an AI-driven world. Jasmeet shares his unconventional journey from engineer to marketing executive, emphasizing how technical fluency and creativity are now inseparable in leadership roles.They dive deep into the evolving responsibilities of marketing leaders, how AI is reshaping strategy, execution, and team structures, and why the biggest risk is failing to evolve. From scaling personalization to rethinking attribution and ROI, Jasmeet offers a candid and forward-looking perspective on how leaders can guide their teams through this transformation.This episode is a must-listen for marketing, sales, and business leaders navigating the AI revolution and seeking actionable insights for long-term success.Key TakeawaysAI is no longer optional: AI is no longer a buzzword, it's a business necessity. Marketing leaders must integrate it across every function, from data analytics to customer engagement.Leadership must get technical: Future marketing leaders can't avoid data or tech. Understanding AI, automation, and analytics is critical for setting effective goals and strategies.Don't just hire AI experts, build internal fluency: Instead of creating isolated “AI teams,” leaders should train and empower existing staff to integrate AI into daily workflows.Personalization at scale is the new standard: AI enables hyper-personalization down to the stakeholder level, not just the account level. This is where real competitive advantage lies.Measure what matters: AI offers new opportunities to track touchpoints across the customer journey, finally making ROI and attribution measurable with greater accuracy.Change requires courage: Creativity, experimentation, and risk-taking are essential to unlocking AI's potential, leaders must champion innovation even when outcomes are uncertain.Quotes“This is the biggest opportunity of our generation. If we don't leverage AI, that's what's really at stake.”Tech RecommendationsClaude (Anthropic) – For content creation and ideation.Veo (Google LLM) – For AI-driven media and video content.Lovable – For AI-powered design support.Figma – For creating lightweight AI agents and workflows.Resource RecommendationsBook:Nexus: The History of Information Networks by Yuval Noah HarariPodcast:Marketing Against the Grain by HubSpotShout-OutsMohanbir Sawhney, Northwestern University - Kellogg School of Management – mentor and thought leader in marketing innovation.Dharmesh Shah, Co-founder & CTO of HubSpot – admired for bridging strategy, culture, and technology.Gary Vaynerchuk, Chairman of VaynerX, CEO of VaynerMedia – inspiration for fearless creativity and constant evolution.About the GuestJasmeet is a marketer with deep roots in technology, data analytics, and AI. He is currently Global Head of Marketing at Axtria. Earlier, Jasmeet was CEO of YibLab, which was one of the fastest growing marketing technology and solutions providers, ranked Top 50 among the fastest growing companies in NJ. Jasmeet has 20+ years of experience building and scaling marketing operations for both small and large companies. He is an investor, advisor, and mentor to multiple firms, and has received several company and individual awards - Inc. 500, Deloitte 500, Crain's Fast 50, SmartCEO Future 50, Red Herring, NJBiz Business of the Year, Top CMO, and Forty Under 40, among others.Connect with Jasmeet.

Want to rank #1 in ChatGPT? Get the Prompt Library: https://clickhubspot.com/dpm Get HubSpot's new Loop playbook here: https://clickhubspot.com/cd63b7 Episode 745: Sam Parr ( https://x.com/theSamParr ) and Shaan Puri ( https://x.com/ShaanVP ) talk to Dharmesh Shah about the early days of SEO and how to jack the algorithm today to show up in ChatGPT responses. — Show Notes: (0:00) The origin of inbound (15:55) Algorithm jacking (22:43) Old Way: SEO (32:45) New Way: AEO (36:21) Step 1: Enable chatbot crawlers (37:55) Step 2: Restructure your content as Q&A (39:05) Step 3: White hat linking (43:44) Step 4: Structured product catalogues (44:27)Step 5: Human generated answered (46:57) How Dharmesh goes from 0 to 1 (52:26) How Dharmesh uses ChatGPT (59:30) The sport of business — Links: • Inbound - http://inbound.com/ • On Startups - https://www.onstartups.com/ • ClickFunnels - https://www.clickfunnels.com/ • Loop Marketing - https://www.hubspot.com/loop-marketing • ImageGen.ai - https://imagegen.ai/imagegen • DadJoke.ai - https://agent.ai/agent/dadjoke • Agent.ai - https://agent.ai/ — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Need a bank for your company? Go check out Mercury (mercury.com). Shaan uses it for all of his companies! Mercury is a financial technology company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N.A., and Evolve Bank & Trust, Members FDIC — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth • Sam's List - http://samslist.co/ My First Million is a HubSpot Original Podcast // Brought to you by HubSpot Media // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano

Brian 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 platform3. The exact signals that ChatGPT will launch a third-party platform within six months4. Why you have six months (not years) to make your platform bet5. Why companies that don't integrate with ChatGPT will lose to competitors that do6. 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 now—Brought 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/lenny—Transcript: https://www.lennysnewsletter.com/p/why-chatgpt-will-be-the-next-big-growth-channel-brian-balfour—My biggest takeaways (for paid newsletter subscribers): https://www.lennysnewsletter.com/i/170294620/my-biggest-takeaways-from-this-conversation—Where to find Brian Balfour:• X: https://twitter.com/bbalfour• LinkedIn: https://www.linkedin.com/in/bbalfour/• Website: https://brianbalfour.com/• Substack: https://blog.brianbalfour.com/• Podcast: https://www.reforge.com/podcast/unsolicited-feedback—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/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 thoughts—Referenced:• The Next Great Distribution Shift: https://blog.brianbalfour.com/p/the-next-great-distribution-shift• Brian Balfour: 10 lessons on career, growth, and life: https://www.lennysnewsletter.com/p/brian-balfour-10-lessons-on-career• This Week #9: Breaking into growth, leading with influence, and (not) stepping on toes: https://www.lennysnewsletter.com/p/this-week-9-breaking-into-growth• Distribution vs. Innovation: https://a16z.com/distribution-vs-innovation/• On Platform Shifts and AI: https://caseyaccidental.com/on-platform-shifts-and-ai/• How to sell your ideas and rise within your company | Casey Winters, Eventbrite: https://www.lennysnewsletter.com/p/how-to-sell-your-ideas-and-rise-within• Thinking beyond frameworks | Casey Winters (Pinterest, Eventbrite, Airbnb, Tinder, Canva, Reddit, Grubhub): https://www.lennysnewsletter.com/p/thinking-beyond-frameworks-casey• ChatGPT: https://chatgpt.com/• Claude: https://claude.ai/• Gemini: https://gemini.google.com/• Vine: https://en.wikipedia.org/wiki/Vine_(service)• Periscope: https://en.wikipedia.org/wiki/Periscope_(service)• 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: https://www.linkedin.com/in/debarghyadas/• ChatGPT's product retention curves are a product manager's wet dream: https://www.linkedin.com/posts/debarghyadas_chatgpts-product-retention-curves-are-a-activity-7338384752393035776-ice1/• 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/the-untold-story-of-windsurf-varun-mohan• Anthropic's CPO on what comes next | Mike Krieger (co-founder of Instagram): https://www.lennysnewsletter.com/p/anthropics-cpo-heres-what-comes-next• Udemy: https://www.udemy.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/the-rise-of-cursor-michael-truell• Notion: https://www.notion.com/• Airtable: https://www.airtable.com/• Monday: monday.com• Sierra: http://sierra.ai• 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-saved-openai-bret-taylor• Introducing ChatGPT agent: bridging research and action: https://openai.com/index/introducing-chatgpt-agent/• Zigging vs. zagging: How HubSpot built a $30B company | Dharmesh Shah (co-founder/CTO): https://www.lennysnewsletter.com/p/lessons-from-30-years-of-building• Marc Andreessen on Why Optimism Is the Safest Bet: https://nymag.com/marc-andressen-2014-10-20/• Reforge: https://www.reforge.com• Reforge Insights: https://www.reforge.com/insights• Shopify: https://www.shopify.com/• 25 proven tactics to accelerate AI adoption at your company: https://www.lennysnewsletter.com/p/25-proven-tactics-to-accelerate-ai• Clouded Judgement: https://cloudedjudgement.substack.com/• NFX: https://www.nfx.com/news• James Currier: https://www.nfx.com/team/james-currier• Hallway Chat: https://www.hallwaychat.co/• Bryan Johnson on LinkedIn: https://www.linkedin.com/in/bryanrjohnson/• Silicon Valley on HBO: https://www.hbomax.com/shows/silicon-valley/b4583939-e39f-4b5c-822d-5b6cc186172d• Stick: https://tv.apple.com/us/show/stick/umc.cmc.52w04zy67tiv11p8xvbc57wmc• Ergonofis standing desks: https://ergonofis.com/en-us/collections/standing-desks• Coping with the loss of a child and protecting your time | Brian Balfour (father of 2, CEO and founder Reforge, venture partner): https://www.startupdadpod.com/coping-with-the-loss-of-a-child-and-protecting-your-time-brian-balfour-father-of-2-ceo-and-found/—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. To hear more, visit www.lennysnewsletter.com

Want Sam's playbook to turn ChatGPT into your executive coach? Get it here: https://clickhubspot.com/sfb Episode 726: Sam Parr ( https://x.com/theSamParr ) and Shaan Puri ( https://x.com/ShaanVP ) talk to Dharmesh Shah ( https://x.com/dharmesh ) about how he's using ChatGPT. — Show Notes: (0:00) Intro (2:00) Context windows (5:26) Vector embeddings (17:20) Automation and orchestration (21:03) Tool calling (28:14) Dharmesh's hot takes on AI (33:06) Agentic managers (39:41) Zuck poaches OpenAI talent w/ 9-figures (49:33) Shaan makes a video game — Links: • Agent.ai - https://agent.ai/ • Andrej Karpathy - https://www.youtube.com/andrejkarpathy — Check Out Shaan's Stuff: • Shaan's weekly email - https://www.shaanpuri.com • Visit https://www.somewhere.com/mfm to hire worldwide talent like Shaan and get $500 off for being an MFM listener. Hire developers, assistants, marketing pros, sales teams and more for 80% less than US equivalents. • Mercury - Need a bank for your company? Go check out Mercury (mercury.com). Shaan uses it for all of his companies! Mercury is a financial technology company, not an FDIC-insured bank. Banking services provided by Choice Financial Group, Column, N.A., and Evolve Bank & Trust, Members FDIC — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth • Sam's List - http://samslist.co/ My First Million is a HubSpot Original Podcast // Brought to you by HubSpot Media // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano

From a 350-square-foot home in South India to leading HubSpot, a $30B CRM powerhouse, Yamini Rangan's journey is nothing short of remarkable. In this episode, Yamini shares how she's guiding HubSpot through a post-pandemic shift toward product-led growth, the hard-won lessons behind building go-to-market alignment, and why human-centric leadership is her edge in an AI-first world. Plus, her take on why data is the new battleground in tech.Chapters: 00:00 Trailer00:52 Introduction02:22 Fire in my belly10:06 Constraints12:19 Peak performance16:38 Helping while in sheer panic21:43 The general ethos30:14 Customer value36:08 Excited and scared47:25 Becoming CEO54:19 Feeling behind1:01:51 Very lonely1:05:34 Losing credibility1:08:42 Slowing down, sitting still1:12:31 No patience to finish a book1:15:39 Who HubSpot is hiring1:15:54 What “grit” means to Yamini1:16:45 OutroMentioned in this episode: Sequoia Capital, Carl Pieri, Brian Halligan, Zoom Workplace, Meta Platforms, Google, Anthropic, Microsoft, Salesforce, Blockbuster Video, BlackBerry Limited, Axon Enterprise, Netflix, Snapchat, Harvey, Dharmesh Shah, Gödel, Escher, Bach: an Eternal Golden Braid, Sapiens: A Brief History of HumankindLinks:Connect with YaminiXLinkedInConnect with JoubinXLinkedInEmail: grit@kleinerperkins.comLearn more about Kleiner Perkins

Empowering Marketers with AI – Sam Mallikarjunan – agent.ai Discover how Sam Mallikarjunan, Growth Lead at agent.ai transitioned from being an AI skeptic to an advocate, and learn about the innovative platform that allows anyone to build and customize AI agents, regardless of their technical skills. Mike and Sam explore what AI agents are, share real-world examples of how marketers can use them for tasks like research and content creation, and discuss how AI is reshaping the future of marketing roles. About agent.ai Agent.ai is the #1 professional marketplace where users can build, discover, and deploy trustworthy AI agents that deliver real-world value. Founded in 2024 by Dharmesh Shah, co-founder and CTO of HubSpot, and led by Sam Mallikarjunan, Agent.ai empowers professionals to revolutionize their workflow across sales, marketing, and customer service through intelligent automation. Since its launch at HubSpot's INBOUND 2024, the platform has experienced explosive growth, amassing over 1.5 million users and hosting more than 1,200 public agents by early 2025. The platform distinguishes itself with its intuitive low-code agent builder, access to cutting-edge AI models, and a vibrant developer ecosystem. About Sam Mallikarjunan Sam Mallikarjunan is a growth strategist, entrepreneur, and the Growth Lead at agent.ai. He is the former CEO and co-founder of OneScreen.ai, a marketplace for out-of-home advertising, and previously served as Chief Revenue Officer at Flock.com and Head of Growth at HubSpot Labs, where he drove significant customer acquisition and revenue growth. Sam is a former professor at Harvard University, where he taught Advanced Digital Marketing and Innovation, and he currently shares his expertise as a LinkedIn Learning Instructor. He is also the co-author of the bestseller Inbound Commerce - How to Sell Better than Amazon and frequently offers insights on AI, marketing, and business strategy Time Stamps 00:00:18 - Guest Introduction: Sam Mallikarjanan from Agent.ai 00:01:41 - Overview of Agent.ai and Its Features 00:02:45 - Understanding AI Agents in Marketing 00:04:10 - Practical Applications of Agents for Marketers 00:10:34 - Target Audience: Individuals vs. Enterprises 00:12:57 - The Importance of AI Confidence in Marketing 00:17:27 - Future Changes in Marketing Roles Due to AI 00:19:59 - The Shift from Performance to Brand Marketing 00:22:44 - Best Marketing Advice Received by Sam 00:24:07 - Career Advice for Aspiring Marketers 00:27:15 - Conclusion and Closing Remarks Quotes "The more focused you try and make an AI, the more effective it's gonna be at whatever the task is that you're trying to have it do." Sam Mallikarjunan, Growth Lead at agent.ai "The biggest challenge is getting people to become AI curious and AI confident." Sam Mallikarjunan, Growth Lead at agent.ai "It was an interesting project because it's what helped turn me from an AI doomer into an AI boomer." Sam Mallikarjunan, Growth Lead at agent.ai   Follow Sam: Sam Mallikarjunan on LinkedIn: https://www.linkedin.com/in/mallikarjunan/ agent.ai's website: https://agent.ai/ agent.ai's on LinkedIn: https://www.linkedin.com/company/pulsar-platform/ Follow Mike: Mike Maynard on LinkedIn: https://www.linkedin.com/in/mikemaynard/ Napier website: https://www.napierb2b.com/ Napier LinkedIn: https://www.linkedin.com/company/napier-partnership-limited/   If you enjoyed this episode, be sure to subscribe to our podcast for more discussions about the latest in Marketing B2B Tech and connect with us on social media to stay updated on upcoming episodes. We'd also appreciate it if you could leave us a review on your favourite podcast platform. Want more? Check out Napier's other podcast - The Marketing Automation Moment: https://podcasts.apple.com/ua/podcast/the-marketing-automation-moment-podcast/id1659211547

We are happy to announce that there will be a dedicated MCP track at the 2025 AI Engineer World's Fair, taking place Jun 3rd to 5th in San Francisco, where the MCP core team and major contributors and builders will be meeting. Join us and apply to speak or sponsor!When we first wrote Why MCP Won, we had no idea how quickly it was about to win.In the past 4 weeks, OpenAI and now Google have now announced the MCP support, effectively confirming our prediction that MCP was the presumptive winner of the agent standard wars. MCP has now overtaken OpenAPI, the incumbent option and most direct alternative, in GitHub stars (3 months ahead of conservative trendline):We have explored the state of MCP at AIE (now the first ever >100k views workshop):And since then, we've added a 7th reason why MCP won - this team acts very quickly on feedback, with the 2025-03-26 spec update adding support for stateless/resumable/streamable HTTP transports, and comprehensive authz capabilities based on OAuth 2.1.This bodes very well for the future of the community and project. For protocol and history nerds, we also asked David and Justin to tell the origin story of MCP, which we leave to the reader to enjoy (you can also skim the transcripts, or, the changelogs of a certain favored IDE). It's incredible the impact that individual engineers solving their own problems can have on an entire industry.Full video episodeLike and subscribe on YouTube!Show Links* David* Justin* MCP* Why MCP WonTimestamps* 00:00 Introduction and Guest Welcome* 00:37 What is MCP?* 02:00 The Origin Story of MCP* 05:18 Development Challenges and Solutions* 08:06 Technical Details and Inspirations* 29:45 MCP vs Open API* 32:48 Building MCP Servers* 40:39 Exploring Model Independence in LLMs* 41:36 Building Richer Systems with MCP* 43:13 Understanding Agents in MCP* 45:45 Nesting and Tool Confusion in MCP* 49:11 Client Control and Tool Invocation* 52:08 Authorization and Trust in MCP Servers* 01:01:34 Future Roadmap and Stateless Servers* 01:10:07 Open Source Governance and Community Involvement* 01:18:12 Wishlist and Closing RemarksTranscriptAlessio [00:00:02]: Hey, everyone. Welcome back to Latent Space. This is Alessio, partner and CTO at Decibel, and I'm joined by my co-host Swyx, founder of Small AI.swyx [00:00:10]: Hey, morning. And today we have a remote recording, I guess, with David and Justin from Anthropic over in London. Welcome. Hey, good You guys have created a storm of hype because of MCP, and I'm really glad to have you on. Thanks for making the time. What is MCP? Let's start with a crisp what definition from the horse's mouth, and then we'll go into the origin story. But let's start off right off the bat. What is MCP?Justin/David [00:00:43]: Yeah, sure. So Model Context Protocol, or MCP for short, is basically something we've designed to help AI applications extend themselves or integrate with an ecosystem of plugins, basically. The terminology is a bit different. We use this client-server terminology, and we can talk about why that is and where that came from. But at the end of the day, it really is that. It's like extending and enhancing the functionality of AI application.swyx [00:01:05]: David, would you add anything?Justin/David [00:01:07]: Yeah, I think that's actually a good description. I think there's like a lot of different ways for how people are trying to explain it. But at the core, I think what Justin said is like extending AI applications is really what this is about. And I think the interesting bit here that I want to highlight, it's AI applications and not models themselves that this is focused on. That's a common misconception that we can talk about a bit later. But yeah. Another version that we've used and gotten to like is like MCP is kind of like the USB-C port of AI applications and that it's meant to be this universal connector to a whole ecosystem of things.swyx [00:01:44]: Yeah. Specifically, an interesting feature is, like you said, the client and server. And it's a sort of two-way, right? Like in the same way that said a USB-C is two-way, which could be super interesting. Yeah, let's go into a little bit of the origin story. There's many people who've tried to make statistics. There's many people who've tried to build open source. I think there's an overall, also, my sense is that Anthropic is going hard after developers in the way that other labs are not. And so I'm also curious if there was any external influence or was it just you two guys just in a room somewhere riffing?Justin/David [00:02:18]: It is actually mostly like us two guys in a room riffing. So this is not part of a big strategy. You know, if you roll back time a little bit and go into like July 2024. I was like, started. I started at Anthropic like three months earlier or two months earlier. And I was mostly working on internal developer tooling, which is what I've been doing for like years and years before. And as part of that, I think there was an effort of like, how do I empower more like employees at Anthropic to use, you know, to integrate really deeply with the models we have? Because we've seen these, like, how good it is, how amazing it will become even in the future. And of course, you know, just dogfoot your own model as much as you can. And as part of that. From my development tooling background, I quickly got frustrated by the idea that, you know, on one hand side, I have Cloud Desktop, which is this amazing tool with artifacts, which I really enjoyed. But it was very limited to exactly that feature set. And it was there was no way to extend it. And on the other hand side, I like work in IDEs, which could greatly like act on like the file system and a bunch of other things. But then they don't have artifacts or something like that. And so what I constantly did was just copy. Things back and forth on between Cloud Desktop and the IDE, and that quickly got me, honestly, just very frustrated. And part of that frustration wasn't like, how do I go and fix this? What, what do we need? And back to like this development developer, like focus that I have, I really thought about like, well, I know how to build all these integrations, but what do I need to do to let these applications let me do this? And so it's very quickly that you see that this is clearly like an M times N problem. Like you have multiple like applications. And multiple integrations you want to build and like, what that is better there to fix this than using a protocol. And at the same time, I was actually working on an LSP related thing internally that didn't go anywhere. But you put these things together in someone's brain and let them wait for like a few weeks. And out of that comes like the idea of like, let's build some, some protocol. And so back to like this little room, like it was literally just me going to a room with Justin and go like, I think we should build something like this. Uh, this is a good idea. And Justin. Lucky for me, just really took an interest in the idea, um, and, and took it from there to like, to, to build something, together with me, that's really the inception story is like, it's us to, from then on, just going and building it over, over the course of like, like a month and a half of like building the protocol, building the first integration, like Justin did a lot of the, like the heavy lifting of the first integrations in cloud desktop. I did a lot of the first, um, proof of concept of how this can look like in an IDE. And if you, we could talk about like some of. All the tidbits you can find way before the inception of like before the official release, if you were looking at the right repositories at the right time, but there you go. That's like some of the, the rough story.Alessio [00:05:12]: Uh, what was the timeline when, I know November 25th was like the official announcement date. When did you guys start working on it?Justin/David [00:05:19]: Justin, when did we start working on that? I think it, I think it was around July. I think, yeah, I, as soon as David pitched this initial idea, I got excited pretty quickly and we started working on it, I think. I think almost immediately after that conversation and then, I don't know, it was a couple, maybe a few months of, uh, building the really unrewarding bits, if we're being honest, because for, for establishing something that's like this communication protocol has clients and servers and like SDKs everywhere, there's just like a lot of like laying the groundwork that you have to do. So it was a pretty, uh, that was a pretty slow couple of months. But then afterward, once you get some things talking over that wire, it really starts to get exciting and you can start building. All sorts of crazy things. And I think this really came to a head. And I don't remember exactly when it was, maybe like approximately a month before release, there was an internal hackathon where some folks really got excited about MCP and started building all sorts of crazy applications. I think the coolest one of which was like an MCP server that can control a 3d printer or something. And so like, suddenly people are feeling this power of like cloud connecting to the outside world in a really tangible way. And that, that really added some, uh, some juice to us and to the release.Alessio [00:06:32]: Yeah. And we'll go into the technical details, but I just want to wrap up here. You mentioned you could have seen some things coming if you were looking in the right places. We always want to know what are the places to get alpha, how, how, how to find MCP early.Justin/David [00:06:44]: I'm a big Zed user. I liked the Zed editor. The first MCP implementation on an IDE was in Zed. It was written by me and it was there like a month and a half before the official release. Just because we needed to do it in the open because it's an open source project. Um, and so it was, it was not, it was named slightly differently because we. We were not set on the name yet, but it was there.swyx [00:07:05]: I'm happy to go a little bit. Anthropic also had some preview of a model with Zed, right? Some kind of fast editing, uh, model. Um, uh, I, I'm con I confess, you know, I'm a cursor windsurf user. Haven't tried Zed. Uh, what's, what's your, you know, unrelated or, you know, unsolicited two second pitch for, for Zed. That's a good question.Justin/David [00:07:28]: I, it really depends what you value in editors. For me. I, I wouldn't even say I like, I love Zed more than others. I like them all like complimentary in, in a way or another, like I do use windsurf. I do use Zed. Um, but I think my, my main pitch for Zed is low latency, super smooth experience editor with a decent enough AI integration.swyx [00:07:51]: I mean, and maybe, you know, I think that's, that's all it is for a lot of people. Uh, I think a lot of people obviously very tied to the VS code paradigm and the extensions that come along with it. Okay. So I wanted to go back a little bit. You know, on, on, on some of the things that you mentioned, Justin, uh, which was building MCP on paper, you know, obviously we only see the end result. It just seems inspired by LSP. And I, I think both of you have acknowledged that. So how much is there to build? And when you say build, is it a lot of code or a lot of design? Cause I felt like it's a lot of design, right? Like you're picking JSON RPC, like how much did you base off of LSP and, and, you know, what, what, what was the sort of hard, hard parts?Justin/David [00:08:29]: Yeah, absolutely. I mean, uh, we, we definitely did take heavy inspiration from LSP. David had much more prior experience with it than I did working on developer tools. So, you know, I've mostly worked on products or, or sort of infrastructural things. LSP was new to me. But as a, as a, like, or from design principles, it really makes a ton of sense because it does solve this M times N problem that David referred to where, you know, in the world before LSP, you had all these different IDEs and editors, and then all these different languages that each wants to support or that their users want them to support. And then everyone's just building like one. And so, like, you use Vim and you might have really great support for, like, honestly, I don't know, C or something, and then, like, you switch over to JetBrains and you have the Java support, but then, like, you don't get to use the great JetBrains Java support in Vim and you don't get to use the great C support in JetBrains or something like that. So LSP largely, I think, solved this problem by creating this common language that they could all speak and that, you know, you can have some people focus on really robust language server implementations, and then the IDE developers can really focus on that side. And they both benefit. So that was, like, our key takeaway for MCP is, like, that same principle and that same problem in the space of AI applications and extensions to AI applications. But in terms of, like, concrete particulars, I mean, we did take JSON RPC and we took this idea of bidirectionality, but I think we quickly took it down a different route after that. I guess there is one other principle from LSP that we try to stick to today, which is, like, this focus on how features manifest. More than. The semantics of things, if that makes sense. David refers to it as being presentation focused, where, like, basically thinking and, like, offering different primitives, not because necessarily the semantics of them are very different, but because you want them to show up in the application differently. Like, that was a key sort of insight about how LSP was developed. And that's also something we try to apply to MCP. But like I said, then from there, like, yeah, we spent a lot of time, really a lot of time, and we could go into this more separately, like, thinking about each of the primitives that we want to offer in MCP. And why they should be different, like, why we want to have all these different concepts. That was a significant amount of work. That was the design work, as you allude to. But then also already out of the gate, we had three different languages that we wanted to at least support to some degree. That was TypeScript, Python, and then for the Z integration, it was Rust. So there was some SDK building work in those languages, a mixture of clients and servers to build out to try to create this, like, internal ecosystem that we could start playing with. And then, yeah, I guess just trying to make everything, like, robust over, like, I don't know, this whole, like, concept that we have for local MCP, where you, like, launch subprocesses and stuff and making that robust took some time as well. Yeah, maybe adding to that, I think the LSP inference goes even a little bit further. Like, we did take actually quite a look at criticisms on LSP, like, things that LSP didn't do right and things that people felt they would love to have different and really took that to heart to, like, see, you know, what are some of the things. that we wish, you know, we should do better. We took a, you know, like, a lengthy, like, look at, like, their very unique approach to JSON RPC, I may say, and then we decided that this is not what we do. And so there's, like, these differences, but it's clearly very, very inspired. Because I think when you're trying to build and focus, if you're trying to build something like MCP, you kind of want to pick the areas you want to innovate in, but you kind of want to be boring about the other parts in pattern matching LSP. So the problem allows you to be boring in a lot of the core pieces that you want to be boring in. Like, the choice of JSON RPC is very non-controversial to us because it's just, like, it doesn't matter at all, like, what the action, like, bites on the bar that you're speaking. It makes no difference to us. The innovation is on the primitives you choose and these type of things. And so there's way more focus on that that we wanted to do. So having some prior art is good there, basically.swyx [00:12:26]: It does. I wanted to double click. I mean, there's so many things you can go into. Obviously, I am passionate about protocol design. I wanted to show you guys this. I mean, I think you guys know, but, you know, you already referred to the M times N problem. And I can just share my screen here about anyone working in developer tools has faced this exact issue where you see the God box, basically. Like, the fundamental problem and solution of all infrastructure engineering is you have things going to N things, and then you put the God box and they'll all be better, right? So here is one problem for Uber. One problem for... GraphQL, one problem for Temporal, where I used to work at, and this is from React. And I was just kind of curious, like, you know, did you solve N times N problems at Facebook? Like, it sounds like, David, you did that for a living, right? Like, this is just N times N for a living.Justin/David [00:13:16]: David Pérez- Yeah, yeah. To some degree, for sure. I did. God, what a good example of this, but like, I did a bunch of this kind of work on like source control systems and these type of things. And so there were a bunch of these type of problems. And so you just shove them into something that everyone can read from and everyone can write to, and you build your God box somewhere, and it works. But yeah, it's just in developer tooling, you're absolutely right. In developer tooling, this is everywhere, right?swyx [00:13:47]: And that, you know, it shows up everywhere. And what was interesting is I think everyone who makes the God box then has the same set of problems, which is also you now have like composability off and remotes versus local. So, you know, there's this very common set of problems. So I kind of want to take a meta lesson on how to do the God box, but, you know, we can talk about the sort of development stuff later. I wanted to double click on, again, the presentation that Justin mentioned of like how features manifest and how you said some things are the same, but you just want to reify some concepts so they show up differently. And I had that sense, you know, when I was looking at the MCP docs, I'm like, why do these two things need to be the difference in other? I think a lot of people treat tool calling as the solution to everything, right? And sometimes you can actually sort of view kinds of different kinds of tool calls as different things. And sometimes they're resources. Sometimes they're actually taking actions. Sometimes they're something else that I don't really know yet. But I just want to see, like, what are some things that you sort of mentally group as adjacent concepts and why were they important to you to emphasize?Justin/David [00:14:58]: Yeah, I can chat about this a bit. I think fundamentally we every sort of primitive that we thought through, we thought from the perspective of the application developer first, like if I'm building an application, whether it is an IDE or, you know, call a desktop or some agent interface or whatever the case may be, what are the different things that I would want to receive from like an integration? And I think once you take that lens, it becomes quite clear that that tool calling is necessary, but very insufficient. Like there are many other things you would want to do besides just get tools. And plug them into the model and you want to have some way of differentiating what those different things are. So the kind of core primitives that we started MCP with, we've since added a couple more, but the core ones are really tools, which we've already talked about. It's like adding, adding tools directly to the model or function calling is sometimes called resources, which is basically like bits of data or context that you might want to add to the context. So excuse me, to the, to the model context. And this, this is the first primitive where it's like, we, we. Decided this could be like application controlled, like maybe you want a model to automatically search through and, and find relevant resources and bring them into context. But maybe you also want that to be an explicit UI affordance in the application where the user can like, you know, pick through a dropdown or like a paperclip menu or whatever, and find specific things and tag them in. And then that becomes part of like their message to the LLM. Like those are both use cases for resources. And then the third one is prompts. Which are deliberately meant to be like user initiated or. Like. User substituted. Text or messages. So like the analogy here would be like, if you're an editor, like a slash command or something like that, or like an at, you know, auto completion type thing where it's like, I have this kind of macro effectively that I want to drop in and use. And we have sort of expressed opinions through MCP about the different ways that these things could manifest, but ultimately it is for application developers to decide, okay, you, you get these different concepts expressed differently. Um, and it's very useful as an application developer because you can decide. The appropriate experience for each, and actually this can be a point of differentiation to, like, we were also thinking, you know, from the application developer perspective, they, you know, application developers don't want to be commoditized. They don't want the application to end up the same as every other AI application. So like, what are the unique things that they could do to like create the best user experience even while connecting up to this big open ecosystem of integration? I, yeah. And I think to add to that, the, I think there are two, two aspects to that, that I want to. I want to mention the first one is that interestingly enough, like while nowadays tool calling is obviously like probably like 95% plus of the integrations, and I wish there would be, you know, more clients doing tool resources, doing prompts. The, the very first implementation in that is actually a prompt implementation. It doesn't deal with tools. And, and it, we found this actually quite useful because what it allows you to do is, for example, build an MCP server that takes like a backtrack. So it's, it's not necessarily like a tool that literally just like rawizes from Sentry or any other like online platform that, that tracks your, your crashes. And just lets you pull this into the context window beforehand. And so it's quite nice that way that it's like a user driven interaction that you does the user decide when to pull this in and don't have to wait for the model to do it. And so it's a great way to craft the prompt in a way. And I think similarly, you know, I wish, you know, more MCP servers today would bring prompts as examples of, like how to even use the tools. Yeah. at the same time. The resources bits are quite interesting as well. And I wish we would see more usage there because it's very easy to envision, but yet nobody has really implemented it. A system where like an MCP server exposes, you know, a set of documents that you have, your database, whatever you might want to as a set of resources. And then like a client application would build a full rack index around this, right? This is definitely an application use case we had in mind as to why these are exposed in such a way that they're not model driven, because you might want to have way more resource content than is, you know, realistically usable in a context window. And so I think, you know, I wish applications and I hope applications will do this in the next few months, use these primitives, you know, way better, because I think there's way more rich experiences to be created that way. Yeah, completely agree with that. And I would also add that I would go into it if I haven't.Alessio [00:19:30]: I think that's a great point. And everybody just, you know, has a hammer and wants to do tool calling on everything. I think a lot of people do tool calling to do a database query. They don't use resources for it. What are like the, I guess, maybe like pros and cons or like when people should use a tool versus a resource, especially when it comes to like things that do have an API interface, like for a database, you can do a tool that does a SQL query versus when should you do that or a resource instead with the data? Yeah.Justin/David [00:20:00]: The way we separate these is like tools are always meant to be initiated by the model. It's sort of like at the model's discretion that it will like find the right tool and apply it. So if that's the interaction you want as a server developer, where it's like, okay, this, you know, suddenly I've given the LLM the ability to run a SQL queries, for example, that makes sense as a tool. But resources are more flexible, basically. And I think, to be completely honest, the story here is practically a bit complicated today. Because many clients don't support resources yet. But like, I think in an ideal world where all these concepts are fully realized, and there's like full ecosystem support, you would do resources for things like the schemas of your database tables and stuff like that, as a way to like either allow the user to say like, okay, now, you know, cloud, I want to talk to you about this database table. Here it is. Let's have this conversation. Or maybe the particular AI application that you're using, like, you know, could be something agentic, like cloud code. is able to just like agentically look up resources and find the right schema of the database table you're talking about, like both those interactions are possible. But I think like, anytime you have this sort of like, you want to list a bunch of entities, and then read any of them, that makes sense to model as resources. Resources are also, they're uniquely identified by a URI, always. And so you can also think of them as like, you know, sort of general purpose transformers, even like, if you want to support an interaction where a user just like drops a URI in, and then you like automatically figure out how to interpret that, you could use MCP servers to do that interpretation. One of the interesting side notes here, back to the Z example of resources, is that has like a prompt library that you can do, that people can interact with. And we just exposed a set of default prompts that we want everyone to have as part of that prompt library. Yeah, resources for a while so that like, you boot up Zed and Zed will just populate the prompt library from an MCP server, which was quite a cool interaction. And that was, again, a very specific, like, both sides needed to agree upon the URI format and the underlying data format. And but that was a nice and kind of like neat little application of resources. There's also going back to that perspective of like, as an application developer, what are the things that I would want? Yeah. We also applied this thinking to like, you know, like, we can do this, we can do this, we can do this, we can do this. Like what existing features of applications could conceivably be kind of like factored out into MCP servers if you were to take that approach today. And so like basically any IDE where you have like an attachment menu that I think naturally models as resources. It's just, you know, those implementations already existed.swyx [00:22:49]: Yeah, I think the immediate like, you know, when you introduced it for cloud desktop and I saw the at sign there, I was like, oh, yeah, that's what Cursor has. But this is for everyone else. And, you know, I think like that that is a really good design target because it's something that already exists and people can map on pretty neatly. I was actually featuring this chart from Mahesh's workshop that presumably you guys agreed on. I think this is so useful that it should be on the front page of the docs. Like probably should be. I think that's a good suggestion.Justin/David [00:23:19]: Do you want to do you want to do a PR for this? I love it.swyx [00:23:21]: Yeah, do a PR. I've done a PR for just Mahesh's workshop in general, just because I'm like, you know. I know.SPEAKER_03 [00:23:28]: I approve. Yeah.swyx [00:23:30]: Thank you. Yeah. I mean, like, but, you know, I think for me as a developer relations person, I always insist on having a map for people. Here are all the main things you have to understand. We'll spend the next two hours going through this. So some one image that kind of covers all this, I think is pretty helpful. And I like your emphasis on prompts. I would say that it's interesting that like I think, you know, in the earliest early days of like chat GPT and cloud, people. Often came up with, oh, you can't really follow my screen, can you? In the early days of chat of, of chat, GPT and all that, like a lot, a lot of people started like, you know, GitHub for prompts, like we'll do prop manager libraries and, and like those never really took off. And I think something like this is helpful and important. I would say like, I've also seen prompt file from human loop, I think, as, as other ways to standardize how people share prompts. But yeah, I agree that like, there should be. There should be more innovation here. And I think probably people want some dynamicism, which I think you, you afford, you allow for. And I like that you have multi-step that this was, this is the main thing that got me like, like these guys really get it. You know, I think you, you maybe have a published some research that says like, actually sometimes to get, to get the model working the right way, you have to do multi-step prompting or jailbreaking to, to, to behave the way that you want. And so I think prompts are not just single conversations. They're sometimes chains of conversations. Yeah.Alessio [00:25:05]: Another question that I had when I was looking at some server implementations, the server builders kind of decide what data gets eventually returned, especially for tool calls. For example, the Google maps one, right? If you just look through it, they decide what, you know, attributes kind of get returned and the user can not override that if there's a missing one. That has always been my gripe with like SDKs in general, when people build like API wrapper SDKs. And then they miss one parameter that maybe it's new and then I can not use it. How do you guys think about that? And like, yeah, how much should the user be able to intervene in that versus just letting the server designer do all the work?Justin/David [00:25:41]: I think we probably bear responsibility for the Google maps one, because I think that's one of the reference servers we've released. I mean, in general, for things like for tool results in particular, we've actually made the deliberate decision, at least thus far, for tool results to be not like sort of structured JSON data, not matching a schema, really, but as like a text or images or basically like messages that you would pass into the LLM directly. And so I guess the correlation that is, you really should just return a whole jumble of data and trust the LLM to like sort through it and see. I mean, I think we've clearly done a lot of work. But I think we really need to be able to shift and like, you know, extract the information it cares about, because that's what that's exactly what they excel at. And we really try to think about like, yeah, how to, you know, use LLMs to their full potential and not maybe over specify and then end up with something that doesn't scale as LLMs themselves get better and better. So really, yeah, I suppose what should be happening in this example server, which again, will request welcome. It would be great. It's like if all these result types were literally just passed through from the API that it's calling, and then the API would be able to pass through automatically.Alessio [00:26:50]: Thank you for joining us.Alessio [00:27:19]: It's a hard to sign decisions on where to draw the line.Justin/David [00:27:22]: I'll maybe throw AI under the bus a little bit here and just say that Claude wrote a lot of these example servers. No surprise at all. But I do think, sorry, I do think there's an interesting point in this that I do think people at the moment still to mostly still just apply their normal software engineering API approaches to this. And I think we're still need a little bit more relearning of how to build something for LLMs and trust them, particularly, you know, as they are getting significantly better year to year. Right. And I think, you know, two years ago, maybe that approach would have been very valid. But nowadays, just like just throw data at that thing that is really good at dealing with data is a good approach to this problem. And I think it's just like unlearning like 20, 30, 40 years of software engineering practices that go a little bit into this to some degree. If I could add to that real quickly, just one framing as well for MCP is thinking in terms of like how crazily fast AI is advancing. I mean, it's exciting. It's also scary. Like thinking, us thinking that like the biggest bottleneck to, you know, the next wave of capabilities for models might actually be their ability to like interact with the outside world to like, you know, read data from outside data sources or like take stateful actions. Working at Anthropic, we absolutely care about doing that. Safely and with the right control and alignment measures in place and everything. But also as AI gets better, people will want that. That'll be key to like becoming productive with AI is like being able to connect them up to all those things. So MCP is also sort of like a bet on the future and where this is all going and how important that will be.Alessio [00:29:05]: Yeah. Yeah, I would say any API attribute that says formatted underscore should kind of be gone and we should just get the raw data from all of them. Because why, you know, why are you formatting? For me, the, the model is definitely smart enough to format an address. So I think that should go to the end user.swyx [00:29:23]: Yeah. I have, I think Alessio is about to move on to like server implementation. I wanted to, I think we were talking, we're still talking about sort of MCP design and goals and intentions. And we've, I think we've indirectly identified like some problems that MCP is really trying to address. But I wanted to give you the spot to directly take on MCP versus open API, because I think obviously there's a, this is a top question. I wanted to sort of recap everything we just talked about and give people a nice little segment that, that people can say, say, like, this is a definitive answer on MCP versus open API.Justin/David [00:29:56]: Yeah, I think fundamentally, I mean, open API specifications are a very great tool. And like I've used them a lot in developing APIs and consumers of APIs. I think fundamentally, or we think that they're just like too granular for what you want to do with LLMs. Like they don't express higher level AI specific concepts like this whole mental model. Yeah. But we've talked about with the primitives of MCP and thinking from the perspective of the application developer, like you don't get any of that when you encode this information into an open API specification. So we believe that models will benefit more from like the purpose built or purpose design tools, resources, prompts, and the other primitives than just kind of like, here's our REST API, go wild. I do think there, there's another aspect. I think that I'm not an open API expert, so I might, everything might not be perfectly accurate. But I do think that we're... Like there's been, and we can talk about this a bit more later. There's a deliberate design decision to make the protocol somewhat stateful because we do really believe that AI applications and AI like interactions will become inherently more stateful and that we're the current state of like, like need for statelessness is more a temporary point in time that will, you know, to some degree that will always exist. But I think like more statefulness will become increasingly more popular, particularly when you think about additional modalities that go beyond just pure text-based, you know, interactions with models, like it might be like video, audio, whatever other modalities exist and out there already. And so I do think that like having something a bit more stateful is just inherently useful in this interaction pattern. I do think they're actually more complimentary open API and MCP than if people wanted to make it out. Like people look. For these, like, you know, A versus B and like, you know, have, have all the, all the developers of these things go in a room and fist fight it out. But that's rarely what's going on. I think it's actually, they're very complimentary and they have their little space where they're very, very strong. And I think, you know, just use the best tool for the job. And if you want to have a rich interaction between an AI application, it's probably like, it's probably MCP. That's the right choice. And if, if you want to have like an API spec somewhere that is very easy and like a model can read. And to interpret, and that's what, what worked for you, then open API is the way to go. One more thing to add here is that we've already seen people, I mean, this happened very early. People in the community built like bridges between the two as well. So like, if what you have is an open API specification and no one's, you know, building a custom MCP server for it, there are already like translators that will take that and re-expose it as MCP. And you could do the other direction too. Awesome.Alessio [00:32:43]: Yeah. I think there's the other side of MCPs that people don't talk as much. Okay. I think there's the other side of MCPs that people don't talk as much about because it doesn't go viral, which is building the servers. So I think everybody does the tweets about like connect the cloud desktop to XMCP. It's amazing. How would you guys suggest people start with building servers? I think the spec is like, so there's so many things you can do that. It's almost like, how do you draw the line between being very descriptive as a server developer versus like going back to our discussion before, like just take the data and then let them auto manipulate it later. Do you have any suggestions for people?Justin/David [00:33:16]: I. I think there, I have a few suggestions. I think that one of the best things I think about MCP and something that we got right very early is that it's just very, very easy to build like something very simple that might not be amazing, but it's pretty, it's good enough because models are very good and get this going within like half an hour, you know? And so I think that the best part is just like pick the language of, you know, of your choice that you love the most, pick the SDK for it, if there's an SDK for it, and then just go build a tool of the thing that matters to you personally. And that you want to use. You want to see the model like interact with, build the server, throw the tool in, don't even worry too much about the description just yet, like do a bit of like, write your little description as you think about it and just give it to the model and just throw it to standard IO protocol transport wise into like an application that you like and see it do things. And I think that's part of the magic that, or like, you know, empowerment and magic for developers to get so quickly to something that the model does. Or something that you care about. That I think really gets you going and gets you into this flow of like, okay, I see this thing can do cool things. Now I go and, and can expand on this and now I can go and like really think about like, which are the different tools I want, which are the different raw resources and prompts I want. Okay. Now that I have that. Okay. Now do I, what do my evals look like for how I want this to go? How do I optimize my prompts for the evals using like tools like that? This is infinite depth so that you can do. But. Okay. Just start. As simple as possible and just go build a server in like half an hour in the language of your choice and how the model interacts with the things that matter to you. And I think that's where the fun is at. And I think people, I think a lot of what MCP makes great is it just adds a lot of fun to the development piece to just go and have models do things quickly. I also, I'm quite partial, again, to using AI to help me do the coding. Like, I think even during the initial development process, we realized it was quite easy to basically just take all the SDK code. Again, you know, what David suggested, like, you know, pick the language you care about, and then pick the SDK. And once you have that, you can literally just drop the whole SDK code into an LLM's context window and say, okay, now that you know MCP, build me a server that does that. This, this, this. And like, the results, I think, are astounding. Like, I mean, it might not be perfect around every single corner or whatever. And you can refine it over time. But like, it's a great way to kind of like one shot something that basically does what you want, and then you can iterate from there. And like David said, there has been a big emphasis from the beginning on like making servers as easy and simple to build as possible, which certainly helps with LLMs doing it too. We often find that like, getting started is like, you know, 100, 200 lines of code in the last couple of years. It's really quite easy. Yeah. And if you don't have an SDK, again, give the like, give the subset of the spec that you care about to the model, and like another SDK and just have it build you an SDK. And it usually works for like, that subset. Building a full SDK is a different story. But like, to get a model to tool call in Haskell or whatever, like language you like, it's probably pretty straightforward.swyx [00:36:32]: Yeah. Sorry.Alessio [00:36:34]: No, I was gonna say, I co-hosted a hackathon at the AGI house. I'm a personal agent, and one of the personal agents somebody built was like an MCP server builder agent, where they will basically put the URL of the API spec, and it will build an MCP server for them. Do you see that today as kind of like, yeah, most servers are just kind of like a layer on top of an existing API without too much opinion? And how, yeah, do you think that's kind of like how it's going to be going forward? Just like AI generated, exposed to API that already exists? Or are we going to see kind of like net new MCP experiences that you... You couldn't do before?Justin/David [00:37:10]: I think, go for it. I think both, like, I, I think there, there will always be value in like, oh, I have, you know, I have my data over here, and I want to use some connector to bring it into my application over here. That use case will certainly remain. I think, you know, this, this kind of goes back to like, I think a lot of things today are maybe defaulting to tool use when some of the other primitives would be maybe more appropriate over time. And so it could still be that connector. It could still just be that sort of adapter layer, but could like actually adapt it onto different primitives, which is one, one way to add more value. But then I also think there's plenty of opportunity for use cases, which like do, you know, or for MCP servers that kind of do interesting things in and out themselves and aren't just adapters. Some of the earliest examples of this were like, you know, the memory MCP server, which gives the LLM the ability to remember things across conversations or like someone who's a close coworker built the... I shouldn't have said that, not a close coworker. Someone. Yeah. Built the sequential thinking MCP server, which gives a model the ability to like really think step-by-step and get better at its reasoning capabilities. This is something where it's like, it really isn't integrating with anything external. It's just providing this sort of like way of thinking for a model.Justin/David [00:38:27]: I guess either way though, I think AI authorship of the servers is totally possible. Like I've had a lot of success in prompting, just being like, Hey, I want to build an MCP server that like does this thing. And even if this thing is not. Adapting some other API, but it's doing something completely original. It's usually able to figure that out too. Yeah. I do. I do think that the, to add to that, I do think that a good part of, of what MCP servers will be, will be these like just API wrapper to some degree. Um, and that's good to be valid because that works and it gets you very, very far. But I think we're just very early, like in, in exploring what you can do. Um, and I think as client support for like certain primitives get better, like we can talk about sampling. I'm playing with my favorite topic and greatest frustration at the same time. Um, I think you can just see it very easily see like way, way, way richer experiences and we have, we have built them internally for as prototyping aspects. And I think you see some of that in the community already, but there's just, you know, things like, Hey, summarize my, you know, my, my, my, my favorite subreddits for the morning MCP server that nobody has built yet, but it's very easy to envision. And the protocol can totally do this. And these are like slightly richer experiences. And I think as people like go away from like the, oh, I just want to like, I'm just in this new world where I can hook up the things that matter to me, to the LLM, to like actually want a real workflow, a real, like, like more richer experience that I, I really want exposed to the model. I think then you will see these things pop up, but again, that's a, there's a little bit of a chicken and egg problem at the moment with like what a client supported versus, you know, what servers like authors want to do. Yeah.Alessio [00:40:10]: That, that, that was. That's kind of my next question on composability. Like how, how do you guys see that? Do you have plans for that? What's kind of like the import of MCPs, so to speak, into another MCP? Like if I want to build like the subreddit one, there's probably going to be like the Reddit API, uh, MCP, and then the summarization MCP. And then how do I, how do I do a super MCP?Justin/David [00:40:33]: Yeah. So, so this is an interesting topic and I think there, um, so there, there are two aspects to it. I think that the one aspect is like, how can I build something? I think agentically that you requires an LLM call and like a one form of fashion, like for summarization or so, but I'm staying model independent and for that, that's where like part of this by directionality comes in, in this more rich experience where we do have this facility for servers to ask the client again, who owns the LLM interaction, right? Like we talk about cursor, who like runs the, the, the loop with the LLM for you there that for the server author to ask the client for a completion. Um, and basically have it like summarize something for the server and return it back. And so now what model summarizes this depends on which one you have selected in cursor and not depends on what the author brings. The author doesn't bring an SDK. It doesn't have, you had an API key. It's completely model independent, how you can build this. There's just one aspect to that. The second aspect to building richer, richer systems with MCP is that you can easily envision an MCP server that serves something to like something like cursor or win server. For a cloud desktop, but at the same time, also is an MCP client at the same time and itself can use MCP servers to create a rich experience. And now you have a recursive property, which we actually quite carefully in the design principles, try to retain. You, you know, you see it all over the place and authorization and other aspects, um, to the spec that we retain this like recursive pattern. And now you can think about like, okay, I have, I have this little bundle of applications, both a server and a client. And I can add. Add these in chains and build basically graphs like, uh, DAGs out of MCP servers, um, uh, that can just richly interact with each other. A agentic MCP server can also use the whole ecosystem of MCP servers available to themselves. And I think that's a really cool environment, cool thing you can do. And people have experimented with this. And I think you see hopefully more of this, particularly when you think about like auto-selecting, auto-installing, there's a bunch of these things you can do that make, uh, make a really fun experience. I, I think practically there are some niceties we still need to add to the SDKs to make this really simple and like easy to execute on like this kind of recursive MCP server that is also a client or like kind of multiplexing together the behaviors of multiple MCP servers into one host, as we call it. These are things we definitely want to add. We haven't been able to yet, but like, uh, I think that would go some way to showcasing these things that we know are already possible, but not necessarily taken up that much yet. Okay.swyx [00:43:08]: This is, uh, very exciting. And very, I'm sure, I'm sure a lot of people get very, very, uh, a lot of ideas and inspiration from this. Is an MCP server that is also a client, is that an agent?Justin/David [00:43:19]: What's an agent? There's a lot of definitions of agents.swyx [00:43:22]: Because like you're, in some ways you're, you're requesting something and it's going off and doing stuff that you don't necessarily know. There's like a layer of abstraction between you and the ultimate raw source of the data. You could dispute that. Yeah. I just, I don't know if you have a hot take on agents.Justin/David [00:43:35]: I do think, I do think that you can build an agent that way. For me, I think you need to define the difference between. An MCP server plus client that is just a proxy versus an agent. I think there's a difference. And I think that difference might be in, um, you know, for example, using a sample loop to create a more richer experience to, uh, to, to have a model call tools while like inside that MCP server through these clients. I think then you have a, an actual like agent. Yeah. I do think it's very simple to build agents that way. Yeah. I think there are maybe a few paths here. Like it definitely feels like there's some relationship. Between MCP and agents. One possible version is like, maybe MCP is a great way to represent agents. Maybe there are some like, you know, features or specific things that are missing that would make the ergonomics of it better. And we should make that part of MCP. That's one possibility. Another is like, maybe MCP makes sense as kind of like a foundational communication layer for agents to like compose with other agents or something like that. Or there could be other possibilities entirely. Maybe MCP should specialize and narrowly focus on kind of the AI application side. And not as much on the agent side. I think it's a very live question and I think there are sort of trade-offs in every direction going back to the analogy of the God box. I think one thing that we have to be very careful about in designing a protocol and kind of curating or shepherding an ecosystem is like trying to do too much. I think it's, it's a very big, yeah, you know, you don't want a protocol that tries to do absolutely everything under the sun because then it'll be bad at everything too. And so I think the key question, which is still unresolved is like, to what degree are agents. Really? Really naturally fitting in to this existing model and paradigm or to what degree is it basically just like orthogonal? It should be something.swyx [00:45:17]: I think once you enable two way and once you enable client server to be the same and delegation of work to another MCP server, it's definitely more agentic than not. But I appreciate that you keep in mind simplicity and not trying to solve every problem under the sun. Cool. I'm happy to move on there. I mean, I'm going to double click on a couple of things that I marked out because they coincide with things that we wanted to ask you. Anyway, so the first one is, it's just a simple, how many MCP things can one implementation support, you know, so this is the, the, the sort of wide versus deep question. And, and this, this is direct relevance to the nesting of MCPs that we just talked about in April, 2024, when, when Claude was launching one of its first contexts, the first million token context example, they said you can support 250 tools. And in a lot of cases, you can't do that. You know, so to me, that's wide in, in the sense that you, you don't have tools that call tools. You just have the model and a flat hierarchy of tools, but then obviously you have tool confusion. It's going to happen when the tools are adjacent, you call the wrong tool. You're going to get the bad results, right? Do you have a recommendation of like a maximum number of MCP servers that are enabled at any given time?Justin/David [00:46:32]: I think be honest, like, I think there's not one answer to this because to some extent, it depends on the model that you're using. To some extent, it depends on like how well the tools are named and described for the model and stuff like that to avoid confusion. I mean, I think that the dream is certainly like you just furnish all this information to the LLM and it can make sense of everything. This, this kind of goes back to like the, the future we envision with MCP is like all this information is just brought to the model and it decides what to do with it. But today the reality or the practicalities might mean that like, yeah, maybe you, maybe in your client application, like the AI application, you do some fill in the blanks. Maybe you do some filtering over the tool set or like maybe you, you run like a faster, smaller LLM to like filter to what's most relevant and then only pass those tools to the bigger model. Or you could use an MCP server, which is a proxy to other MCP servers and does some filtering at that level or something like that. I think hundreds, as you referenced, is still a fairly safe bet, at least for Claude. I can't speak to the other models, but yeah, I don't know. I think over time we should just expect this to get better. So we're wary of like constraining anything and preventing that. Sort of long. Yeah, and obviously it highly, it highly depends on the overlap of the description, right? Like if you, if you have like very separate servers that do very separate things and the tools have very clear unique names, very clear, well-written descriptions, you know, your mileage might be more higher than if you have a GitLab and a GitHub server at the same time in your context. And, and then the overlap is quite significant because they look very similar to the model and confusion becomes easier. There's different considerations too. Depending on the AI application, if you're, if you're trying to build something very agentic, maybe you are trying to minimize the amount of times you need to go back to the user with a question or, you know, minimize the amount of like configurability in your interface or something. But if you're building other applications, you're building an IDE or you're building a chat application or whatever, like, I think it's totally reasonable to have affordances that allow the user to say like, at this moment, I want this feature set or at this different moment, I want this different feature set or something like that. And maybe not treat it as like always on. The full list always on all the time. Yeah.swyx [00:48:42]: That's where I think the concepts of resources and tools get to blend a little bit, right? Because now you're saying you want some degree of user control, right? Or application control. And other times you want the model to control it, right? So now we're choosing just subsets of tools. I don't know.Justin/David [00:49:00]: Yeah, I think it's a fair point or a fair concern. I guess the way I think about this is still like at the end of the day, and this is a core MCP design principle is like, ultimately, the concept of a tool is not a tool. It's a client application, and by extension, the user. Ultimately, they should be in full control of absolutely everything that's happening via MCP. When we say that tools are model controlled, what we really mean is like, tools should only be invoked by the model. Like there really shouldn't be an application interaction or a user interaction where it's like, okay, as a user, I now want you to use this tool. I mean, occasionally you might do that for prompting reasons, but like, I think that shouldn't be like a UI affordance. But I think the client application or the user deciding to like filter out the user, it's not a tool. I think the client application or the user deciding to like filter out things that MCP servers are offering, totally reasonable, or even like transform them. Like you could imagine a client application that takes tool descriptions from an MCP server and like enriches them, makes them better. We really want the client applications to have full control in the MCP paradigm. That in addition, though, like I think there, one thing that's very, very early in my thinking is there might be a addition to the protocol where you want to give the server author the ability to like logically group certain primitives together, potentially. Yeah. To inform that, because they might know some of these logical groupings better, and that could like encompasses prompts, resources, and tools at the same time. I mean, personally, we can have a design discussion on there. I mean, personally, my take would be that those should be separate MCP servers, and then the user should be able to compose them together. But we can figure it out.Alessio [00:50:31]: Is there going to be like a MCP standard library, so to speak, of like, hey, these are like the canonical servers, do not build this. We're just going to take care of those. And those can be maybe the building blocks that people can compose. Or do you expect people to just rebuild their own MCP servers for like a lot of things?Justin/David [00:50:49]: I think we will not be prescriptive in that sense. I think there will be inherently, you know, there's a lot of power. Well, let me rephrase it. Like, I have a long history in open source, and I feel the bizarre approach to this problem is somewhat useful, right? And I think so that the best and most interesting option wins. And I don't think we want to be very prescriptive. I will definitely foresee, and this already exists, that there will be like 25 GitHub servers and like 25, you know, Postgres servers and whatnot. And that's all cool. And that's good. And I think they all add in their own way. But effectively, eventually, over months or years, the ecosystem will converge to like a set of very widely used ones who basically, I don't know if you call it winning, but like that will be the most used ones. And I think that's completely fine. Because being prescriptive about this, I don't think it's any useful, any use. I do think, of course, that there will be like MCP servers, and you see them already that are driven by companies for their products. And, you know, they will inherently be probably the canonical implementation. Like if you want to work with Cloudflow workers and use an MCP server for that, you'll probably want to use the one developed by Cloudflare. Yeah. I think there's maybe a related thing here, too, just about like one big thing worth thinking about. We don't have any like solutions completely ready to go. It's this question of like trust or like, you know, vetting is maybe a better word. Like, how do you determine which MCP servers are like the kind of good and safe ones to use? Regardless of if there are any implementations of GitHub MCP servers, that could be totally fine. But you want to make sure that you're not using ones that are really like sus, right? And so trying to think about like how to kind of endow reputation or like, you know, if hypothetically. Anthropic is like, we've vetted this. It meets our criteria for secure coding or something. How can that be reflected in kind of this open model where everyone in the ecosystem can benefit? Don't really know the answer yet, but that's very much top of mind.Alessio [00:52:49]: But I think that's like a great design choice of MCPs, which is like language agnostic. Like already, and there's not, to my knowledge, an Anthropic official Ruby SDK, nor an OpenAI SDK. And Alex Roudal does a great job building those. But now with MCPs is like. You don't actually have to translate an SDK to all these languages. You just do one, one interface and kind of bless that interface as, as Anthropic. So yeah, that was, that was nice.swyx [00:53:18]: I have a quick answer to this thing. So like, obviously there's like five or six different registries already popped up. You guys announced your official registry that's gone away. And a registry is very tempting to offer download counts, likes, reviews, and some kind of trust thing. I think it's kind of brittle. Like no matter what kind of social proof or other thing you can, you can offer, the next update can compromise a trusted package. And actually that's the one that does the most damage, right? So abusing the trust system is like setting up a trust system creates the damage from the trust system. And so I actually want to encourage people to try out MCP Inspector because all you got to do is actually just look at the traffic. And like, I think that's, that goes for a lot of security issues.Justin/David [00:54:03]: Yeah, absolutely. Cool. And then I think like that's very classic, just supply chain problem that like all registries effectively have. And the, you know, there are different approaches to this problem. Like you can take the Apple approach and like vet things and like have like an army of, of both automated system and review teams to do this. And then you effectively build an app store, right? That's, that's one approach to this type of problem. It kind of works in, you know, in a very set, certain set of ways. But I don't think it works in an open source kind of ecosystem for which you always have a registry kind of approach, like similar to MPM and packages and PiPi.swyx [00:54:36]: And they all have inherently these, like these, these supply chain attack problems, right? Yeah, yeah, totally. Quick time check. I think we're going to go for another like 20, 25 minutes. Is that okay for you guys? Okay, awesome. Cool. I wanted to double click, take the time. So I'm going to sort of, we previewed a little bit on like the future coming stuff. So I want to leave the future coming stuff to the end, like registry, the, the, the stateless servers and remote servers, all the other stuff. But I wanted to double click a little bit. A little bit more on the launch, the core servers that are part of the official repo. And some of them are special ones, like the, like the ones we already talked about. So let me just pull them up already. So for example, you mentioned memory, you mentioned sequential thinking. And I think I really, really encourage people should look at these, what I call special servers. Like they're, they're not normal servers in the, in the sense that they, they wrap some API and it's just easier to interact with those than to work at the APIs. And so I'll, I'll highlight the, the memory one first, just because like, I think there are, there are a few memory startups, but actually you don't need them if you just use this one. It's also like 200 lines of code. It's super simple. And, and obviously then if you need to scale it up, you should probably do some, some more battle tested thing. But if you're interested, if you're just introducing memory, I think this is a really good implementation. I don't know if there's like special stories that you want to highlight with, with some of these.Justin/David [00:56:00]: I think, no, I don't, I don't think there's special stories. I think a lot of these, not all of them, but a lot of them originated from that hackathon that I mentioned before, where folks got excited about the idea of MCP. People internally inside Anthropik who wanted to have memory or like wanted to play around with the idea could quickly now prototype something using MCP in a way that wasn't possible before. Someone who's not like, you know, you don't have to become the, the end to end expert. You don't have access. You don't have to have access to this. Like, you know. You don't have to have this private, you know, proprietary code base. You can just now extend cloud with this memory capability. So that's how a lot of these came about. And then also just thinking about like, you know, what is the breadth of functionality that we want to demonstrate at launch?swyx [00:56:47]: Totally. And I think that is partially why it made your launch successful because you launch with a sufficiently spanning set of here's examples and then people just copy paste and expand from there. I would also highligh

If you're in SF: Join us for the Claude Plays Pokemon hackathon this Sunday!If you're not: Fill out the 2025 State of AI Eng survey for $250 in Amazon cards!We are SO excited to share our conversation with Dharmesh Shah, co-founder of HubSpot and creator of Agent.ai.A particularly compelling concept we discussed is the idea of "hybrid teams" - the next evolution in workplace organization where human workers collaborate with AI agents as team members. Just as we previously saw hybrid teams emerge in terms of full-time vs. contract workers, or in-office vs. remote workers, Dharmesh predicts that the next frontier will be teams composed of both human and AI members. This raises interesting questions about team dynamics, trust, and how to effectively delegate tasks between human and AI team members.The discussion of business models in AI reveals an important distinction between Work as a Service (WaaS) and Results as a Service (RaaS), something Dharmesh has written extensively about. While RaaS has gained popularity, particularly in customer support applications where outcomes are easily measurable, Dharmesh argues that this model may be over-indexed. Not all AI applications have clearly definable outcomes or consistent economic value per transaction, making WaaS more appropriate in many cases. This insight is particularly relevant for businesses considering how to monetize AI capabilities.The technical challenges of implementing effective agent systems are also explored, particularly around memory and authentication. Shah emphasizes the importance of cross-agent memory sharing and the need for more granular control over data access. He envisions a future where users can selectively share parts of their data with different agents, similar to how OAuth works but with much finer control. This points to significant opportunities in developing infrastructure for secure and efficient agent-to-agent communication and data sharing.Other highlights from our conversation* The Evolution of AI-Powered Agents – Exploring how AI agents have evolved from simple chatbots to sophisticated multi-agent systems, and the role of MCPs in enabling that.* Hybrid Digital Teams and the Future of Work – How AI agents are becoming teammates rather than just tools, and what this means for business operations and knowledge work.* Memory in AI Agents – The importance of persistent memory in AI systems and how shared memory across agents could enhance collaboration and efficiency.* Business Models for AI Agents – Exploring the shift from software as a service (SaaS) to work as a service (WaaS) and results as a service (RaaS), and what this means for monetization.* The Role of Standards Like MCP – Why MCP has been widely adopted and how it enables agent collaboration, tool use, and discovery.* The Future of AI Code Generation and Software Engineering – How AI-assisted coding is changing the role of software engineers and what skills will matter most in the future.* Domain Investing and Efficient Markets – Dharmesh's approach to domain investing and how inefficiencies in digital asset markets create business opportunities.* The Philosophy of Saying No – Lessons from "Sorry, You Must Pass" and how prioritization leads to greater productivity and focus.Timestamps* 00:00 Introduction and Guest Welcome* 02:29 Dharmesh Shah's Journey into AI* 05:22 Defining AI Agents* 06:45 The Evolution and Future of AI Agents* 13:53 Graph Theory and Knowledge Representation* 20:02 Engineering Practices and Overengineering* 25:57 The Role of Junior Engineers in the AI Era* 28:20 Multi-Agent Systems and MCP Standards* 35:55 LinkedIn's Legal Battles and Data Scraping* 37:32 The Future of AI and Hybrid Teams* 39:19 Building Agent AI: A Professional Network for Agents* 40:43 Challenges and Innovations in Agent AI* 45:02 The Evolution of UI in AI Systems* 01:00:25 Business Models: Work as a Service vs. Results as a Service* 01:09:17 The Future Value of Engineers* 01:09:51 Exploring the Role of Agents* 01:10:28 The Importance of Memory in AI* 01:11:02 Challenges and Opportunities in AI Memory* 01:12:41 Selective Memory and Privacy Concerns* 01:13:27 The Evolution of AI Tools and Platforms* 01:18:23 Domain Names and AI Projects* 01:32:08 Balancing Work and Personal Life* 01:35:52 Final Thoughts and ReflectionsTranscriptAlessio [00:00:04]: Hey everyone, welcome back to the Latent Space podcast. This is Alessio, partner and CTO at Decibel Partners, and I'm joined by my co-host Swyx, founder of Small AI.swyx [00:00:12]: Hello, and today we're super excited to have Dharmesh Shah to join us. I guess your relevant title here is founder of Agent AI.Dharmesh [00:00:20]: Yeah, that's true for this. Yeah, creator of Agent.ai and co-founder of HubSpot.swyx [00:00:25]: Co-founder of HubSpot, which I followed for many years, I think 18 years now, gonna be 19 soon. And you caught, you know, people can catch up on your HubSpot story elsewhere. I should also thank Sean Puri, who I've chatted with back and forth, who's been, I guess, getting me in touch with your people. But also, I think like, just giving us a lot of context, because obviously, My First Million joined you guys, and they've been chatting with you guys a lot. So for the business side, we can talk about that, but I kind of wanted to engage your CTO, agent, engineer side of things. So how did you get agent religion?Dharmesh [00:01:00]: Let's see. So I've been working, I'll take like a half step back, a decade or so ago, even though actually more than that. So even before HubSpot, the company I was contemplating that I had named for was called Ingenisoft. And the idea behind Ingenisoft was a natural language interface to business software. Now realize this is 20 years ago, so that was a hard thing to do. But the actual use case that I had in mind was, you know, we had data sitting in business systems like a CRM or something like that. And my kind of what I thought clever at the time. Oh, what if we used email as the kind of interface to get to business software? And the motivation for using email is that it automatically works when you're offline. So imagine I'm getting on a plane or I'm on a plane. There was no internet on planes back then. It's like, oh, I'm going through business cards from an event I went to. I can just type things into an email just to have them all in the backlog. When it reconnects, it sends those emails to a processor that basically kind of parses effectively the commands and updates the software, sends you the file, whatever it is. And there was a handful of commands. I was a little bit ahead of the times in terms of what was actually possible. And I reattempted this natural language thing with a product called ChatSpot that I did back 20...swyx [00:02:12]: Yeah, this is your first post-ChatGPT project.Dharmesh [00:02:14]: I saw it come out. Yeah. And so I've always been kind of fascinated by this natural language interface to software. Because, you know, as software developers, myself included, we've always said, oh, we build intuitive, easy-to-use applications. And it's not intuitive at all, right? Because what we're doing is... We're taking the mental model that's in our head of what we're trying to accomplish with said piece of software and translating that into a series of touches and swipes and clicks and things like that. And there's nothing natural or intuitive about it. And so natural language interfaces, for the first time, you know, whatever the thought is you have in your head and expressed in whatever language that you normally use to talk to yourself in your head, you can just sort of emit that and have software do something. And I thought that was kind of a breakthrough, which it has been. And it's gone. So that's where I first started getting into the journey. I started because now it actually works, right? So once we got ChatGPT and you can take, even with a few-shot example, convert something into structured, even back in the ChatGP 3.5 days, it did a decent job in a few-shot example, convert something to structured text if you knew what kinds of intents you were going to have. And so that happened. And that ultimately became a HubSpot project. But then agents intrigued me because I'm like, okay, well, that's the next step here. So chat's great. Love Chat UX. But if we want to do something even more meaningful, it felt like the next kind of advancement is not this kind of, I'm chatting with some software in a kind of a synchronous back and forth model, is that software is going to do things for me in kind of a multi-step way to try and accomplish some goals. So, yeah, that's when I first got started. It's like, okay, what would that look like? Yeah. And I've been obsessed ever since, by the way.Alessio [00:03:55]: Which goes back to your first experience with it, which is like you're offline. Yeah. And you want to do a task. You don't need to do it right now. You just want to queue it up for somebody to do it for you. Yes. As you think about agents, like, let's start at the easy question, which is like, how do you define an agent? Maybe. You mean the hardest question in the universe? Is that what you mean?Dharmesh [00:04:12]: You said you have an irritating take. I do have an irritating take. I think, well, some number of people have been irritated, including within my own team. So I have a very broad definition for agents, which is it's AI-powered software that accomplishes a goal. Period. That's it. And what irritates people about it is like, well, that's so broad as to be completely non-useful. And I understand that. I understand the criticism. But in my mind, if you kind of fast forward months, I guess, in AI years, the implementation of it, and we're already starting to see this, and we'll talk about this, different kinds of agents, right? So I think in addition to having a usable definition, and I like yours, by the way, and we should talk more about that, that you just came out with, the classification of agents actually is also useful, which is, is it autonomous or non-autonomous? Does it have a deterministic workflow? Does it have a non-deterministic workflow? Is it working synchronously? Is it working asynchronously? Then you have the different kind of interaction modes. Is it a chat agent, kind of like a customer support agent would be? You're having this kind of back and forth. Is it a workflow agent that just does a discrete number of steps? So there's all these different flavors of agents. So if I were to draw it in a Venn diagram, I would draw a big circle that says, this is agents, and then I have a bunch of circles, some overlapping, because they're not mutually exclusive. And so I think that's what's interesting, and we're seeing development along a bunch of different paths, right? So if you look at the first implementation of agent frameworks, you look at Baby AGI and AutoGBT, I think it was, not Autogen, that's the Microsoft one. They were way ahead of their time because they assumed this level of reasoning and execution and planning capability that just did not exist, right? So it was an interesting thought experiment, which is what it was. Even the guy that, I'm an investor in Yohei's fund that did Baby AGI. It wasn't ready, but it was a sign of what was to come. And so the question then is, when is it ready? And so lots of people talk about the state of the art when it comes to agents. I'm a pragmatist, so I think of the state of the practical. It's like, okay, well, what can I actually build that has commercial value or solves actually some discrete problem with some baseline of repeatability or verifiability?swyx [00:06:22]: There was a lot, and very, very interesting. I'm not irritated by it at all. Okay. As you know, I take a... There's a lot of anthropological view or linguistics view. And in linguistics, you don't want to be prescriptive. You want to be descriptive. Yeah. So you're a goals guy. That's the key word in your thing. And other people have other definitions that might involve like delegated trust or non-deterministic work, LLM in the loop, all that stuff. The other thing I was thinking about, just the comment on Baby AGI, LGBT. Yeah. In that piece that you just read, I was able to go through our backlog and just kind of track the winter of agents and then the summer now. Yeah. And it's... We can tell the whole story as an oral history, just following that thread. And it's really just like, I think, I tried to explain the why now, right? Like I had, there's better models, of course. There's better tool use with like, they're just more reliable. Yep. Better tools with MCP and all that stuff. And I'm sure you have opinions on that too. Business model shift, which you like a lot. I just heard you talk about RAS with MFM guys. Yep. Cost is dropping a lot. Yep. Inference is getting faster. There's more model diversity. Yep. Yep. I think it's a subtle point. It means that like, you have different models with different perspectives. You don't get stuck in the basin of performance of a single model. Sure. You can just get out of it by just switching models. Yep. Multi-agent research and RL fine tuning. So I just wanted to let you respond to like any of that.Dharmesh [00:07:44]: Yeah. A couple of things. Connecting the dots on the kind of the definition side of it. So we'll get the irritation out of the way completely. I have one more, even more irritating leap on the agent definition thing. So here's the way I think about it. By the way, the kind of word agent, I looked it up, like the English dictionary definition. The old school agent, yeah. Is when you have someone or something that does something on your behalf, like a travel agent or a real estate agent acts on your behalf. It's like proxy, which is a nice kind of general definition. So the other direction I'm sort of headed, and it's going to tie back to tool calling and MCP and things like that, is if you, and I'm not a biologist by any stretch of the imagination, but we have these single-celled organisms, right? Like the simplest possible form of what one would call life. But it's still life. It just happens to be single-celled. And then you can combine cells and then cells become specialized over time. And you have much more sophisticated organisms, you know, kind of further down the spectrum. In my mind, at the most fundamental level, you can almost think of having atomic agents. What is the simplest possible thing that's an agent that can still be called an agent? What is the equivalent of a kind of single-celled organism? And the reason I think that's useful is right now we're headed down the road, which I think is very exciting around tool use, right? That says, okay, the LLMs now can be provided a set of tools that it calls to accomplish whatever it needs to accomplish in the kind of furtherance of whatever goal it's trying to get done. And I'm not overly bothered by it, but if you think about it, if you just squint a little bit and say, well, what if everything was an agent? And what if tools were actually just atomic agents? Because then it's turtles all the way down, right? Then it's like, oh, well, all that's really happening with tool use is that we have a network of agents that know about each other through something like an MMCP and can kind of decompose a particular problem and say, oh, I'm going to delegate this to this set of agents. And why do we need to draw this distinction between tools, which are functions most of the time? And an actual agent. And so I'm going to write this irritating LinkedIn post, you know, proposing this. It's like, okay. And I'm not suggesting we should call even functions, you know, call them agents. But there is a certain amount of elegance that happens when you say, oh, we can just reduce it down to one primitive, which is an agent that you can combine in complicated ways to kind of raise the level of abstraction and accomplish higher order goals. Anyway, that's my answer. I'd say that's a success. Thank you for coming to my TED Talk on agent definitions.Alessio [00:09:54]: How do you define the minimum viable agent? Do you already have a definition for, like, where you draw the line between a cell and an atom? Yeah.Dharmesh [00:10:02]: So in my mind, it has to, at some level, use AI in order for it to—otherwise, it's just software. It's like, you know, we don't need another word for that. And so that's probably where I draw the line. So then the question, you know, the counterargument would be, well, if that's true, then lots of tools themselves are actually not agents because they're just doing a database call or a REST API call or whatever it is they're doing. And that does not necessarily qualify them, which is a fair counterargument. And I accept that. It's like a good argument. I still like to think about—because we'll talk about multi-agent systems, because I think—so we've accepted, which I think is true, lots of people have said it, and you've hopefully combined some of those clips of really smart people saying this is the year of agents, and I completely agree, it is the year of agents. But then shortly after that, it's going to be the year of multi-agent systems or multi-agent networks. I think that's where it's going to be headed next year. Yeah.swyx [00:10:54]: Opening eyes already on that. Yeah. My quick philosophical engagement with you on this. I often think about kind of the other spectrum, the other end of the cell spectrum. So single cell is life, multi-cell is life, and you clump a bunch of cells together in a more complex organism, they become organs, like an eye and a liver or whatever. And then obviously we consider ourselves one life form. There's not like a lot of lives within me. I'm just one life. And now, obviously, I don't think people don't really like to anthropomorphize agents and AI. Yeah. But we are extending our consciousness and our brain and our functionality out into machines. I just saw you were a Bee. Yeah. Which is, you know, it's nice. I have a limitless pendant in my pocket.Dharmesh [00:11:37]: I got one of these boys. Yeah.swyx [00:11:39]: I'm testing it all out. You know, got to be early adopters. But like, we want to extend our personal memory into these things so that we can be good at the things that we're good at. And, you know, machines are good at it. Machines are there. So like, my definition of life is kind of like going outside of my own body now. I don't know if you've ever had like reflections on that. Like how yours. How our self is like actually being distributed outside of you. Yeah.Dharmesh [00:12:01]: I don't fancy myself a philosopher. But you went there. So yeah, I did go there. I'm fascinated by kind of graphs and graph theory and networks and have been for a long, long time. And to me, we're sort of all nodes in this kind of larger thing. It just so happens that we're looking at individual kind of life forms as they exist right now. But so the idea is when you put a podcast out there, there's these little kind of nodes you're putting out there of like, you know, conceptual ideas. Once again, you have varying kind of forms of those little nodes that are up there and are connected in varying and sundry ways. And so I just think of myself as being a node in a massive, massive network. And I'm producing more nodes as I put content or ideas. And, you know, you spend some portion of your life collecting dots, experiences, people, and some portion of your life then connecting dots from the ones that you've collected over time. And I found that really interesting things happen and you really can't know in advance how those dots are necessarily going to connect in the future. And that's, yeah. So that's my philosophical take. That's the, yes, exactly. Coming back.Alessio [00:13:04]: Yep. Do you like graph as an agent? Abstraction? That's been one of the hot topics with LandGraph and Pydantic and all that.Dharmesh [00:13:11]: I do. The thing I'm more interested in terms of use of graphs, and there's lots of work happening on that now, is graph data stores as an alternative in terms of knowledge stores and knowledge graphs. Yeah. Because, you know, so I've been in software now 30 plus years, right? So it's not 10,000 hours. It's like 100,000 hours that I've spent doing this stuff. And so I've grew up with, so back in the day, you know, I started on mainframes. There was a product called IMS from IBM, which is basically an index database, what we'd call like a key value store today. Then we've had relational databases, right? We have tables and columns and foreign key relationships. We all know that. We have document databases like MongoDB, which is sort of a nested structure keyed by a specific index. We have vector stores, vector embedding database. And graphs are interesting for a couple of reasons. One is, so it's not classically structured in a relational way. When you say structured database, to most people, they're thinking tables and columns and in relational database and set theory and all that. Graphs still have structure, but it's not the tables and columns structure. And you could wonder, and people have made this case, that they are a better representation of knowledge for LLMs and for AI generally than other things. So that's kind of thing number one conceptually, and that might be true, I think is possibly true. And the other thing that I really like about that in the context of, you know, I've been in the context of data stores for RAG is, you know, RAG, you say, oh, I have a million documents, I'm going to build the vector embeddings, I'm going to come back with the top X based on the semantic match, and that's fine. All that's very, very useful. But the reality is something gets lost in the chunking process and the, okay, well, those tend, you know, like, you don't really get the whole picture, so to speak, and maybe not even the right set of dimensions on the kind of broader picture. And it makes intuitive sense to me that if we did capture it properly in a graph form, that maybe that feeding into a RAG pipeline will actually yield better results for some use cases, I don't know, but yeah.Alessio [00:15:03]: And do you feel like at the core of it, there's this difference between imperative and declarative programs? Because if you think about HubSpot, it's like, you know, people and graph kind of goes hand in hand, you know, but I think maybe the software before was more like primary foreign key based relationship, versus now the models can traverse through the graph more easily.Dharmesh [00:15:22]: Yes. So I like that representation. There's something. It's just conceptually elegant about graphs and just from the representation of it, they're much more discoverable, you can kind of see it, there's observability to it, versus kind of embeddings, which you can't really do much with as a human. You know, once they're in there, you can't pull stuff back out. But yeah, I like that kind of idea of it. And the other thing that's kind of, because I love graphs, I've been long obsessed with PageRank from back in the early days. And, you know, one of the kind of simplest algorithms in terms of coming up, you know, with a phone, everyone's been exposed to PageRank. And the idea is that, and so I had this other idea for a project, not a company, and I have hundreds of these, called NodeRank, is to be able to take the idea of PageRank and apply it to an arbitrary graph that says, okay, I'm going to define what authority looks like and say, okay, well, that's interesting to me, because then if you say, I'm going to take my knowledge store, and maybe this person that contributed some number of chunks to the graph data store has more authority on this particular use case or prompt that's being submitted than this other one that may, or maybe this one was more. popular, or maybe this one has, whatever it is, there should be a way for us to kind of rank nodes in a graph and sort them in some, some useful way. Yeah.swyx [00:16:34]: So I think that's generally useful for, for anything. I think the, the problem, like, so even though at my conferences, GraphRag is super popular and people are getting knowledge, graph religion, and I will say like, it's getting space, getting traction in two areas, conversation memory, and then also just rag in general, like the, the, the document data. Yeah. It's like a source. Most ML practitioners would say that knowledge graph is kind of like a dirty word. The graph database, people get graph religion, everything's a graph, and then they, they go really hard into it and then they get a, they get a graph that is too complex to navigate. Yes. And so like the, the, the simple way to put it is like you at running HubSpot, you know, the power of graphs, the way that Google has pitched them for many years, but I don't suspect that HubSpot itself uses a knowledge graph. No. Yeah.Dharmesh [00:17:26]: So when is it over engineering? Basically? It's a great question. I don't know. So the question now, like in AI land, right, is the, do we necessarily need to understand? So right now, LLMs for, for the most part are somewhat black boxes, right? We sort of understand how the, you know, the algorithm itself works, but we really don't know what's going on in there and, and how things come out. So if a graph data store is able to produce the outcomes we want, it's like, here's a set of queries I want to be able to submit and then it comes out with useful content. Maybe the underlying data store is as opaque as a vector embeddings or something like that, but maybe it's fine. Maybe we don't necessarily need to understand it to get utility out of it. And so maybe if it's messy, that's okay. Um, that's, it's just another form of lossy compression. Uh, it's just lossy in a way that we just don't completely understand in terms of, because it's going to grow organically. Uh, and it's not structured. It's like, ah, we're just gonna throw a bunch of stuff in there. Let the, the equivalent of the embedding algorithm, whatever they called in graph land. Um, so the one with the best results wins. I think so. Yeah.swyx [00:18:26]: Or is this the practical side of me is like, yeah, it's, if it's useful, we don't necessarilyDharmesh [00:18:30]: need to understand it.swyx [00:18:30]: I have, I mean, I'm happy to push back as long as you want. Uh, it's not practical to evaluate like the 10 different options out there because it takes time. It takes people, it takes, you know, resources, right? Set. That's the first thing. Second thing is your evals are typically on small things and some things only work at scale. Yup. Like graphs. Yup.Dharmesh [00:18:46]: Yup. That's, yeah, no, that's fair. And I think this is one of the challenges in terms of implementation of graph databases is that the most common approach that I've seen developers do, I've done it myself, is that, oh, I've got a Postgres database or a MySQL or whatever. I can represent a graph with a very set of tables with a parent child thing or whatever. And that sort of gives me the ability, uh, why would I need anything more than that? And the answer is, well, if you don't need anything more than that, you don't need anything more than that. But there's a high chance that you're sort of missing out on the actual value that, uh, the graph representation gives you. Which is the ability to traverse the graph, uh, efficiently in ways that kind of going through the, uh, traversal in a relational database form, even though structurally you have the data, practically you're not gonna be able to pull it out in, in useful ways. Uh, so you wouldn't like represent a social graph, uh, in, in using that kind of relational table model. It just wouldn't scale. It wouldn't work.swyx [00:19:36]: Uh, yeah. Uh, I think we want to move on to MCP. Yeah. But I just want to, like, just engineering advice. Yeah. Uh, obviously you've, you've, you've run, uh, you've, you've had to do a lot of projects and run a lot of teams. Do you have a general rule for over-engineering or, you know, engineering ahead of time? You know, like, because people, we know premature engineering is the root of all evil. Yep. But also sometimes you just have to. Yep. When do you do it? Yes.Dharmesh [00:19:59]: It's a great question. This is, uh, a question as old as time almost, which is what's the right and wrong levels of abstraction. That's effectively what, uh, we're answering when we're trying to do engineering. I tend to be a pragmatist, right? So here's the thing. Um, lots of times doing something the right way. Yeah. It's like a marginal increased cost in those cases. Just do it the right way. And this is what makes a, uh, a great engineer or a good engineer better than, uh, a not so great one. It's like, okay, all things being equal. If it's going to take you, you know, roughly close to constant time anyway, might as well do it the right way. Like, so do things well, then the question is, okay, well, am I building a framework as the reusable library? To what degree, uh, what am I anticipating in terms of what's going to need to change in this thing? Uh, you know, along what dimension? And then I think like a business person in some ways, like what's the return on calories, right? So, uh, and you look at, um, energy, the expected value of it's like, okay, here are the five possible things that could happen, uh, try to assign probabilities like, okay, well, if there's a 50% chance that we're going to go down this particular path at some day, like, or one of these five things is going to happen and it costs you 10% more to engineer for that. It's basically, it's something that yields a kind of interest compounding value. Um, as you get closer to the time of, of needing that versus having to take on debt, which is when you under engineer it, you're taking on debt. You're going to have to pay off when you do get to that eventuality where something happens. One thing as a pragmatist, uh, so I would rather under engineer something than over engineer it. If I were going to err on the side of something, and here's the reason is that when you under engineer it, uh, yes, you take on tech debt, uh, but the interest rate is relatively known and payoff is very, very possible, right? Which is, oh, I took a shortcut here as a result of which now this thing that should have taken me a week is now going to take me four weeks. Fine. But if that particular thing that you thought might happen, never actually, you never have that use case transpire or just doesn't, it's like, well, you just save yourself time, right? And that has value because you were able to do other things instead of, uh, kind of slightly over-engineering it away, over-engineering it. But there's no perfect answers in art form in terms of, uh, and yeah, we'll, we'll bring kind of this layers of abstraction back on the code generation conversation, which we'll, uh, I think I have later on, butAlessio [00:22:05]: I was going to ask, we can just jump ahead quickly. Yeah. Like, as you think about vibe coding and all that, how does the. Yeah. Percentage of potential usefulness change when I feel like we over-engineering a lot of times it's like the investment in syntax, it's less about the investment in like arc exacting. Yep. Yeah. How does that change your calculus?Dharmesh [00:22:22]: A couple of things, right? One is, um, so, you know, going back to that kind of ROI or a return on calories, kind of calculus or heuristic you think through, it's like, okay, well, what is it going to cost me to put this layer of abstraction above the code that I'm writing now, uh, in anticipating kind of future needs. If the cost of fixing, uh, or doing under engineering right now. Uh, we'll trend towards zero that says, okay, well, I don't have to get it right right now because even if I get it wrong, I'll run the thing for six hours instead of 60 minutes or whatever. It doesn't really matter, right? Like, because that's going to trend towards zero to be able, the ability to refactor a code. Um, and because we're going to not that long from now, we're going to have, you know, large code bases be able to exist, uh, you know, as, as context, uh, for a code generation or a code refactoring, uh, model. So I think it's going to make it, uh, make the case for under engineering, uh, even stronger. Which is why I take on that cost. You just pay the interest when you get there, it's not, um, just go on with your life vibe coded and, uh, come back when you need to. Yeah.Alessio [00:23:18]: Sometimes I feel like there's no decision-making in some things like, uh, today I built a autosave for like our internal notes platform and I literally just ask them cursor. Can you add autosave? Yeah. I don't know if it's over under engineer. Yep. I just vibe coded it. Yep. And I feel like at some point we're going to get to the point where the models kindDharmesh [00:23:36]: of decide where the right line is, but this is where the, like the, in my mind, the danger is, right? So there's two sides to this. One is the cost of kind of development and coding and things like that stuff that, you know, we talk about. But then like in your example, you know, one of the risks that we have is that because adding a feature, uh, like a save or whatever the feature might be to a product as that price tends towards zero, are we going to be less discriminant about what features we add as a result of making more product products more complicated, which has a negative impact on the user and navigate negative impact on the business. Um, and so that's the thing I worry about if it starts to become too easy, are we going to be. Too promiscuous in our, uh, kind of extension, adding product extensions and things like that. It's like, ah, why not add X, Y, Z or whatever back then it was like, oh, we only have so many engineering hours or story points or however you measure things. Uh, that least kept us in check a little bit. Yeah.Alessio [00:24:22]: And then over engineering, you're like, yeah, it's kind of like you're putting that on yourself. Yeah. Like now it's like the models don't understand that if they add too much complexity, it's going to come back to bite them later. Yep. So they just do whatever they want to do. Yeah. And I'm curious where in the workflow that's going to be, where it's like, Hey, this is like the amount of complexity and over-engineering you can do before you got to ask me if we should actually do it versus like do something else.Dharmesh [00:24:45]: So you know, we've already, let's like, we're leaving this, uh, in the code generation world, this kind of compressed, um, cycle time. Right. It's like, okay, we went from auto-complete, uh, in the GitHub co-pilot to like, oh, finish this particular thing and hit tab to a, oh, I sort of know your file or whatever. I can write out a full function to you to now I can like hold a bunch of the context in my head. Uh, so we can do app generation, which we have now with lovable and bolt and repletage. Yeah. Association and other things. So then the question is, okay, well, where does it naturally go from here? So we're going to generate products. Make sense. We might be able to generate platforms as though I want a platform for ERP that does this, whatever. And that includes the API's includes the product and the UI, and all the things that make for a platform. There's no nothing that says we would stop like, okay, can you generate an entire software company someday? Right. Uh, with the platform and the monetization and the go-to-market and the whatever. And you know, that that's interesting to me in terms of, uh, you know, what, when you take it to almost ludicrous levels. of abstract.swyx [00:25:39]: It's like, okay, turn it to 11. You mentioned vibe coding, so I have to, this is a blog post I haven't written, but I'm kind of exploring it. Is the junior engineer dead?Dharmesh [00:25:49]: I don't think so. I think what will happen is that the junior engineer will be able to, if all they're bringing to the table is the fact that they are a junior engineer, then yes, they're likely dead. But hopefully if they can communicate with carbon-based life forms, they can interact with product, if they're willing to talk to customers, they can take their kind of basic understanding of engineering and how kind of software works. I think that has value. So I have a 14-year-old right now who's taking Python programming class, and some people ask me, it's like, why is he learning coding? And my answer is, is because it's not about the syntax, it's not about the coding. What he's learning is like the fundamental thing of like how things work. And there's value in that. I think there's going to be timeless value in systems thinking and abstractions and what that means. And whether functions manifested as math, which he's going to get exposed to regardless, or there are some core primitives to the universe, I think, that the more you understand them, those are what I would kind of think of as like really large dots in your life that will have a higher gravitational pull and value to them that you'll then be able to. So I want him to collect those dots, and he's not resisting. So it's like, okay, while he's still listening to me, I'm going to have him do things that I think will be useful.swyx [00:26:59]: You know, part of one of the pitches that I evaluated for AI engineer is a term. And the term is that maybe the traditional interview path or career path of software engineer goes away, which is because what's the point of lead code? Yeah. And, you know, it actually matters more that you know how to work with AI and to implement the things that you want. Yep.Dharmesh [00:27:16]: That's one of the like interesting things that's happened with generative AI. You know, you go from machine learning and the models and just that underlying form, which is like true engineering, right? Like the actual, what I call real engineering. I don't think of myself as a real engineer, actually. I'm a developer. But now with generative AI. We call it AI and it's obviously got its roots in machine learning, but it just feels like fundamentally different to me. Like you have the vibe. It's like, okay, well, this is just a whole different approach to software development to so many different things. And so I'm wondering now, it's like an AI engineer is like, if you were like to draw the Venn diagram, it's interesting because the cross between like AI things, generative AI and what the tools are capable of, what the models do, and this whole new kind of body of knowledge that we're still building out, it's still very young, intersected with kind of classic engineering, software engineering. Yeah.swyx [00:28:04]: I just described the overlap as it separates out eventually until it's its own thing, but it's starting out as a software. Yeah.Alessio [00:28:11]: That makes sense. So to close the vibe coding loop, the other big hype now is MCPs. Obviously, I would say Cloud Desktop and Cursor are like the two main drivers of MCP usage. I would say my favorite is the Sentry MCP. I can pull in errors and then you can just put the context in Cursor. How do you think about that abstraction layer? Does it feel... Does it feel almost too magical in a way? Do you think it's like you get enough? Because you don't really see how the server itself is then kind of like repackaging theDharmesh [00:28:41]: information for you? I think MCP as a standard is one of the better things that's happened in the world of AI because a standard needed to exist and absent a standard, there was a set of things that just weren't possible. Now, we can argue whether it's the best possible manifestation of a standard or not. Does it do too much? Does it do too little? I get that, but it's just simple enough to both be useful and unobtrusive. It's understandable and adoptable by mere mortals, right? It's not overly complicated. You know, a reasonable engineer can put a stand up an MCP server relatively easily. The thing that has me excited about it is like, so I'm a big believer in multi-agent systems. And so that's going back to our kind of this idea of an atomic agent. So imagine the MCP server, like obviously it calls tools, but the way I think about it, so I'm working on my current passion project is agent.ai. And we'll talk more about that in a little bit. More about the, I think we should, because I think it's interesting not to promote the project at all, but there's some interesting ideas in there. One of which is around, we're going to need a mechanism for, if agents are going to collaborate and be able to delegate, there's going to need to be some form of discovery and we're going to need some standard way. It's like, okay, well, I just need to know what this thing over here is capable of. We're going to need a registry, which Anthropic's working on. I'm sure others will and have been doing directories of, and there's going to be a standard around that too. How do you build out a directory of MCP servers? I think that's going to unlock so many things just because, and we're already starting to see it. So I think MCP or something like it is going to be the next major unlock because it allows systems that don't know about each other, don't need to, it's that kind of decoupling of like Sentry and whatever tools someone else was building. And it's not just about, you know, Cloud Desktop or things like, even on the client side, I think we're going to see very interesting consumers of MCP, MCP clients versus just the chat body kind of things. Like, you know, Cloud Desktop and Cursor and things like that. But yeah, I'm very excited about MCP in that general direction.swyx [00:30:39]: I think the typical cynical developer take, it's like, we have OpenAPI. Yeah. What's the new thing? I don't know if you have a, do you have a quick MCP versus everything else? Yeah.Dharmesh [00:30:49]: So it's, so I like OpenAPI, right? So just a descriptive thing. It's OpenAPI. OpenAPI. Yes, that's what I meant. So it's basically a self-documenting thing. We can do machine-generated, lots of things from that output. It's a structured definition of an API. I get that, love it. But MCPs sort of are kind of use case specific. They're perfect for exactly what we're trying to use them for around LLMs in terms of discovery. It's like, okay, I don't necessarily need to know kind of all this detail. And so right now we have, we'll talk more about like MCP server implementations, but We will? I think, I don't know. Maybe we won't. At least it's in my head. It's like a back processor. But I do think MCP adds value above OpenAPI. It's, yeah, just because it solves this particular thing. And if we had come to the world, which we have, like, it's like, hey, we already have OpenAPI. It's like, if that were good enough for the universe, the universe would have adopted it already. There's a reason why MCP is taking office because marginally adds something that was missing before and doesn't go too far. And so that's why the kind of rate of adoption, you folks have written about this and talked about it. Yeah, why MCP won. Yeah. And it won because the universe decided that this was useful and maybe it gets supplanted by something else. Yeah. And maybe we discover, oh, maybe OpenAPI was good enough the whole time. I doubt that.swyx [00:32:09]: The meta lesson, this is, I mean, he's an investor in DevTools companies. I work in developer experience at DevRel in DevTools companies. Yep. Everyone wants to own the standard. Yeah. I'm sure you guys have tried to launch your own standards. Actually, it's Houseplant known for a standard, you know, obviously inbound marketing. But is there a standard or protocol that you ever tried to push? No.Dharmesh [00:32:30]: And there's a reason for this. Yeah. Is that? And I don't mean, need to mean, speak for the people of HubSpot, but I personally. You kind of do. I'm not smart enough. That's not the, like, I think I have a. You're smart. Not enough for that. I'm much better off understanding the standards that are out there. And I'm more on the composability side. Let's, like, take the pieces of technology that exist out there, combine them in creative, unique ways. And I like to consume standards. I don't like to, and that's not that I don't like to create them. I just don't think I have the, both the raw wattage or the credibility. It's like, okay, well, who the heck is Dharmesh, and why should we adopt a standard he created?swyx [00:33:07]: Yeah, I mean, there are people who don't monetize standards, like OpenTelemetry is a big standard, and LightStep never capitalized on that.Dharmesh [00:33:15]: So, okay, so if I were to do a standard, there's two things that have been in my head in the past. I was one around, a very, very basic one around, I don't even have the domain, I have a domain for everything, for open marketing. Because the issue we had in HubSpot grew up in the marketing space. There we go. There was no standard around data formats and things like that. It doesn't go anywhere. But the other one, and I did not mean to go here, but I'm going to go here. It's called OpenGraph. I know the term was already taken, but it hasn't been used for like 15 years now for its original purpose. But what I think should exist in the world is right now, our information, all of us, nodes are in the social graph at Meta or the professional graph at LinkedIn. Both of which are actually relatively closed in actually very annoying ways. Like very, very closed, right? Especially LinkedIn. Especially LinkedIn. I personally believe that if it's my data, and if I would get utility out of it being open, I should be able to make my data open or publish it in whatever forms that I choose, as long as I have control over it as opt-in. So the idea is around OpenGraph that says, here's a standard, here's a way to publish it. I should be able to go to OpenGraph.org slash Dharmesh dot JSON and get it back. And it's like, here's your stuff, right? And I can choose along the way and people can write to it and I can prove. And there can be an entire system. And if I were to do that, I would do it as a... Like a public benefit, non-profit-y kind of thing, as this is a contribution to society. I wouldn't try to commercialize that. Have you looked at AdProto? What's that? AdProto.swyx [00:34:43]: It's the protocol behind Blue Sky. Okay. My good friend, Dan Abramov, who was the face of React for many, many years, now works there. And he actually did a talk that I can send you, which basically kind of tries to articulate what you just said. But he does, he loves doing these like really great analogies, which I think you'll like. Like, you know, a lot of our data is behind a handle, behind a domain. Yep. So he's like, all right, what if we flip that? What if it was like our handle and then the domain? Yep. So, and that's really like your data should belong to you. Yep. And I should not have to wait 30 days for my Twitter data to export. Yep.Dharmesh [00:35:19]: you should be able to at least be able to automate it or do like, yes, I should be able to plug it into an agentic thing. Yeah. Yes. I think we're... Because so much of our data is... Locked up. I think the trick here isn't that standard. It is getting the normies to care.swyx [00:35:37]: Yeah. Because normies don't care.Dharmesh [00:35:38]: That's true. But building on that, normies don't care. So, you know, privacy is a really hot topic and an easy word to use, but it's not a binary thing. Like there are use cases where, and we make these choices all the time, that I will trade, not all privacy, but I will trade some privacy for some productivity gain or some benefit to me that says, oh, I don't care about that particular data being online if it gives me this in return, or I don't mind sharing this information with this company.Alessio [00:36:02]: If I'm getting, you know, this in return, but that sort of should be my option. I think now with computer use, you can actually automate some of the exports. Yes. Like something we've been doing internally is like everybody exports their LinkedIn connections. Yep. And then internally, we kind of merge them together to see how we can connect our companies to customers or things like that.Dharmesh [00:36:21]: And not to pick on LinkedIn, but since we're talking about it, but they feel strongly enough on the, you know, do not take LinkedIn data that they will block even browser use kind of things or whatever. They go to great, great lengths, even to see patterns of usage. And it says, oh, there's no way you could have, you know, gotten that particular thing or whatever without, and it's, so it's, there's...swyx [00:36:42]: Wasn't there a Supreme Court case that they lost? Yeah.Dharmesh [00:36:45]: So the one they lost was around someone that was scraping public data that was on the public internet. And that particular company had not signed any terms of service or whatever. It's like, oh, I'm just taking data that's on, there was no, and so that's why they won. But now, you know, the question is around, can LinkedIn... I think they can. Like, when you use, as a user, you use LinkedIn, you are signing up for their terms of service. And if they say, well, this kind of use of your LinkedIn account that violates our terms of service, they can shut your account down, right? They can. And they, yeah, so, you know, we don't need to make this a discussion. By the way, I love the company, don't get me wrong. I'm an avid user of the product. You know, I've got... Yeah, I mean, you've got over a million followers on LinkedIn, I think. Yeah, I do. And I've known people there for a long, long time, right? And I have lots of respect. And I understand even where the mindset originally came from of this kind of members-first approach to, you know, a privacy-first. I sort of get that. But sometimes you sort of have to wonder, it's like, okay, well, that was 15, 20 years ago. There's likely some controlled ways to expose some data on some member's behalf and not just completely be a binary. It's like, no, thou shalt not have the data.swyx [00:37:54]: Well, just pay for sales navigator.Alessio [00:37:57]: Before we move to the next layer of instruction, anything else on MCP you mentioned? Let's move back and then I'll tie it back to MCPs.Dharmesh [00:38:05]: So I think the... Open this with agent. Okay, so I'll start with... Here's my kind of running thesis, is that as AI and agents evolve, which they're doing very, very quickly, we're going to look at them more and more. I don't like to anthropomorphize. We'll talk about why this is not that. Less as just like raw tools and more like teammates. They'll still be software. They should self-disclose as being software. I'm totally cool with that. But I think what's going to happen is that in the same way you might collaborate with a team member on Slack or Teams or whatever you use, you can imagine a series of agents that do specific things just like a team member might do, that you can delegate things to. You can collaborate. You can say, hey, can you take a look at this? Can you proofread that? Can you try this? You can... Whatever it happens to be. So I think it is... I will go so far as to say it's inevitable that we're going to have hybrid teams someday. And what I mean by hybrid teams... So back in the day, hybrid teams were, oh, well, you have some full-time employees and some contractors. Then it was like hybrid teams are some people that are in the office and some that are remote. That's the kind of form of hybrid. The next form of hybrid is like the carbon-based life forms and agents and AI and some form of software. So let's say we temporarily stipulate that I'm right about that over some time horizon that eventually we're going to have these kind of digitally hybrid teams. So if that's true, then the question you sort of ask yourself is that then what needs to exist in order for us to get the full value of that new model? It's like, okay, well... You sort of need to... It's like, okay, well, how do I... If I'm building a digital team, like, how do I... Just in the same way, if I'm interviewing for an engineer or a designer or a PM, whatever, it's like, well, that's why we have professional networks, right? It's like, oh, they have a presence on likely LinkedIn. I can go through that semi-structured, structured form, and I can see the experience of whatever, you know, self-disclosed. But, okay, well, agents are going to need that someday. And so I'm like, okay, well, this seems like a thread that's worth pulling on. That says, okay. So I... So agent.ai is out there. And it's LinkedIn for agents. It's LinkedIn for agents. It's a professional network for agents. And the more I pull on that thread, it's like, okay, well, if that's true, like, what happens, right? It's like, oh, well, they have a profile just like anyone else, just like a human would. It's going to be a graph underneath, just like a professional network would be. It's just that... And you can have its, you know, connections and follows, and agents should be able to post. That's maybe how they do release notes. Like, oh, I have this new version. Whatever they decide to post, it should just be able to... Behave as a node on the network of a professional network. As it turns out, the more I think about that and pull on that thread, the more and more things, like, start to make sense to me. So it may be more than just a pure professional network. So my original thought was, okay, well, it's a professional network and agents as they exist out there, which I think there's going to be more and more of, will kind of exist on this network and have the profile. But then, and this is always dangerous, I'm like, okay, I want to see a world where thousands of agents are out there in order for the... Because those digital employees, the digital workers don't exist yet in any meaningful way. And so then I'm like, oh, can I make that easier for, like... And so I have, as one does, it's like, oh, I'll build a low-code platform for building agents. How hard could that be, right? Like, very hard, as it turns out. But it's been fun. So now, agent.ai has 1.3 million users. 3,000 people have actually, you know, built some variation of an agent, sometimes just for their own personal productivity. About 1,000 of which have been published. And the reason this comes back to MCP for me, so imagine that and other networks, since I know agent.ai. So right now, we have an MCP server for agent.ai that exposes all the internally built agents that we have that do, like, super useful things. Like, you know, I have access to a Twitter API that I can subsidize the cost. And I can say, you know, if you're looking to build something for social media, these kinds of things, with a single API key, and it's all completely free right now, I'm funding it. That's a useful way for it to work. And then we have a developer to say, oh, I have this idea. I don't have to worry about open AI. I don't have to worry about, now, you know, this particular model is better. It has access to all the models with one key. And we proxy it kind of behind the scenes. And then expose it. So then we get this kind of community effect, right? That says, oh, well, someone else may have built an agent to do X. Like, I have an agent right now that I built for myself to do domain valuation for website domains because I'm obsessed with domains, right? And, like, there's no efficient market for domains. There's no Zillow for domains right now that tells you, oh, here are what houses in your neighborhood sold for. It's like, well, why doesn't that exist? We should be able to solve that problem. And, yes, you're still guessing. Fine. There should be some simple heuristic. So I built that. It's like, okay, well, let me go look for past transactions. You say, okay, I'm going to type in agent.ai, agent.com, whatever domain. What's it actually worth? I'm looking at buying it. It can go and say, oh, which is what it does. It's like, I'm going to go look at are there any published domain transactions recently that are similar, either use the same word, same top-level domain, whatever it is. And it comes back with an approximate value, and it comes back with its kind of rationale for why it picked the value and comparable transactions. Oh, by the way, this domain sold for published. Okay. So that agent now, let's say, existed on the web, on agent.ai. Then imagine someone else says, oh, you know, I want to build a brand-building agent for startups and entrepreneurs to come up with names for their startup. Like a common problem, every startup is like, ah, I don't know what to call it. And so they type in five random words that kind of define whatever their startup is. And you can do all manner of things, one of which is like, oh, well, I need to find the domain for it. What are possible choices? Now it's like, okay, well, it would be nice to know if there's an aftermarket price for it, if it's listed for sale. Awesome. Then imagine calling this valuation agent. It's like, okay, well, I want to find where the arbitrage is, where the agent valuation tool says this thing is worth $25,000. It's listed on GoDaddy for $5,000. It's close enough. Let's go do that. Right? And that's a kind of composition use case that in my future state. Thousands of agents on the network, all discoverable through something like MCP. And then you as a developer of agents have access to all these kind of Lego building blocks based on what you're trying to solve. Then you blend in orchestration, which is getting better and better with the reasoning models now. Just describe the problem that you have. Now, the next layer that we're all contending with is that how many tools can you actually give an LLM before the LLM breaks? That number used to be like 15 or 20 before you kind of started to vary dramatically. And so that's the thing I'm thinking about now. It's like, okay, if I want to... If I want to expose 1,000 of these agents to a given LLM, obviously I can't give it all 1,000. Is there some intermediate layer that says, based on your prompt, I'm going to make a best guess at which agents might be able to be helpful for this particular thing? Yeah.Alessio [00:44:37]: Yeah, like RAG for tools. Yep. I did build the Latent Space Researcher on agent.ai. Okay. Nice. Yeah, that seems like, you know, then there's going to be a Latent Space Scheduler. And then once I schedule a research, you know, and you build all of these things. By the way, my apologies for the user experience. You realize I'm an engineer. It's pretty good.swyx [00:44:56]: I think it's a normie-friendly thing. Yeah. That's your magic. HubSpot does the same thing.Alessio [00:45:01]: Yeah, just to like quickly run through it. You can basically create all these different steps. And these steps are like, you know, static versus like variable-driven things. How did you decide between this kind of like low-code-ish versus doing, you know, low-code with code backend versus like not exposing that at all? Any fun design decisions? Yeah. And this is, I think...Dharmesh [00:45:22]: I think lots of people are likely sitting in exactly my position right now, coming through the choosing between deterministic. Like if you're like in a business or building, you know, some sort of agentic thing, do you decide to do a deterministic thing? Or do you go non-deterministic and just let the alum handle it, right, with the reasoning models? The original idea and the reason I took the low-code stepwise, a very deterministic approach. A, the reasoning models did not exist at that time. That's thing number one. Thing number two is if you can get... If you know in your head... If you know in your head what the actual steps are to accomplish whatever goal, why would you leave that to chance? There's no upside. There's literally no upside. Just tell me, like, what steps do you need executed? So right now what I'm playing with... So one thing we haven't talked about yet, and people don't talk about UI and agents. Right now, the primary interaction model... Or they don't talk enough about it. I know some people have. But it's like, okay, so we're used to the chatbot back and forth. Fine. I get that. But I think we're going to move to a blend of... Some of those things are going to be synchronous as they are now. But some are going to be... Some are going to be async. It's just going to put it in a queue, just like... And this goes back to my... Man, I talk fast. But I have this... I only have one other speed. It's even faster. So imagine it's like if you're working... So back to my, oh, we're going to have these hybrid digital teams. Like, you would not go to a co-worker and say, I'm going to ask you to do this thing, and then sit there and wait for them to go do it. Like, that's not how the world works. So it's nice to be able to just, like, hand something off to someone. It's like, okay, well, maybe I expect a response in an hour or a day or something like that.Dharmesh [00:46:52]: In terms of when things need to happen. So the UI around agents. So if you look at the output of agent.ai agents right now, they are the simplest possible manifestation of a UI, right? That says, oh, we have inputs of, like, four different types. Like, we've got a dropdown, we've got multi-select, all the things. It's like back in HTML, the original HTML 1.0 days, right? Like, you're the smallest possible set of primitives for a UI. And it just says, okay, because we need to collect some information from the user, and then we go do steps and do things. And generate some output in HTML or markup are the two primary examples. So the thing I've been asking myself, if I keep going down that path. So people ask me, I get requests all the time. It's like, oh, can you make the UI sort of boring? I need to be able to do this, right? And if I keep pulling on that, it's like, okay, well, now I've built an entire UI builder thing. Where does this end? And so I think the right answer, and this is what I'm going to be backcoding once I get done here, is around injecting a code generation UI generation into, the agent.ai flow, right? As a builder, you're like, okay, I'm going to describe the thing that I want, much like you would do in a vibe coding world. But instead of generating the entire app, it's going to generate the UI that exists at some point in either that deterministic flow or something like that. It says, oh, here's the thing I'm trying to do. Go generate the UI for me. And I can go through some iterations. And what I think of it as a, so it's like, I'm going to generate the code, generate the code, tweak it, go through this kind of prompt style, like we do with vibe coding now. And at some point, I'm going to be happy with it. And I'm going to hit save. And that's going to become the action in that particular step. It's like a caching of the generated code that I can then, like incur any inference time costs. It's just the actual code at that point.Alessio [00:48:29]: Yeah, I invested in a company called E2B, which does code sandbox. And they powered the LM arena web arena. So it's basically the, just like you do LMS, like text to text, they do the same for like UI generation. So if you're asking a model, how do you do it? But yeah, I think that's kind of where.Dharmesh [00:48:45]: That's the thing I'm really fascinated by. So the early LLM, you know, we're understandably, but laughably bad at simple arithmetic, right? That's the thing like my wife, Normies would ask us, like, you call this AI, like it can't, my son would be like, it's just stupid. It can't even do like simple arithmetic. And then like we've discovered over time that, and there's a reason for this, right? It's like, it's a large, there's, you know, the word language is in there for a reason in terms of what it's been trained on. It's not meant to do math, but now it's like, okay, well, the fact that it has access to a Python interpreter that I can actually call at runtime, that solves an entire body of problems that it wasn't trained to do. And it's basically a form of delegation. And so the thought that's kind of rattling around in my head is that that's great. So it's, it's like took the arithmetic problem and took it first. Now, like anything that's solvable through a relatively concrete Python program, it's able to do a bunch of things that I couldn't do before. Can we get to the same place with UI? I don't know what the future of UI looks like in a agentic AI world, but maybe let the LLM handle it, but not in the classic sense. Maybe it generates it on the fly, or maybe we go through some iterations and hit cache or something like that. So it's a little bit more predictable. Uh, I don't know, but yeah.Alessio [00:49:48]: And especially when is the human supposed to intervene? So, especially if you're composing them, most of them should not have a UI because then they're just web hooking to somewhere else. I just want to touch back. I don't know if you have more comments on this.swyx [00:50:01]: I was just going to ask when you, you said you got, you're going to go back to code. What

Susan Cain, author of the groundbreaking bestseller Quiet: The Power of Introverts in a World That Can't Stop Talking, shares a guide for how introverts can thrive in the workplace without sacrificing their authentic selves. Drawing from her extensive research and personal experience, Cain offers a powerful reframing: success doesn't require becoming more extroverted—it demands becoming more fully yourself.—What you'll learn:1. A simple definition of introversion and how it differs from shyness—plus a simple two-question test to determine where you fall on the spectrum2. Five practical tactics introverts can use to be more successful in business while staying true to their natural temperament3. How to handle challenging workplace scenarios like meetings dominated by loud voices and networking events that drain your energy4. Specific strategies for managers and founders to create environments where introverted team members can contribute their best work5. Practical techniques for saying no to energy-draining commitments6. Strategies for managers to better support and leverage introverted team members7. Practical advice for raising introverted children to help them develop confidence while honoring their natural temperament8. Why seeking to become “more extroverted” is the wrong goal—and what to focus on instead to achieve professional success—Brought to you by:• Enterpret—Transform customer feedback into product growth• Vanta—Automate compliance. Simplify security• Fundrise Flagship Fund—Invest in $1.1 billion of real estate—Find the transcript at: https://www.lennysnewsletter.com/p/the-hidden-power-of-introverts-susan-cain—Where to find Susan Cain:• X: https://x.com/susancain• LinkedIn: https://www.linkedin.com/in/susancain/• Website: https://susancain.net/• Instagram: https://www.instagram.com/susancainauthor/#• Facebook: https://www.facebook.com/authorsusancain• Substack: https://substack.com/@susancain—In this episode, we cover:(00:00) Introduction to Susan Cain(05:07) Understanding introversion(08:55) The spectrum of introversion and extroversion(13:27) Overcoming public speaking anxiety(17:13) Learning to embrace your introverted self(23:16) The power of leaning into your strengths(24:36) Strategies for introverts to thrive in their career(34:06) The importance of saying no(38:35) What to do instead of networking(41:59) Effective meeting participation for introverts(47:31) Creating a productive work environment(51:14) Raising an introverted child(57:58) Finding the right career fit(01:08:09) Lightning round and final thoughts—Referenced:• The power of introverts: https://www.ted.com/talks/susan_cain_the_power_of_introverts• The hidden power of sad songs and rainy days: https://www.ted.com/talks/susan_cain_and_min_kym_the_hidden_power_of_sad_songs_and_rainy_days• Why bittersweet emotions underscore life's beauty: https://www.ted.com/talks/susan_cain_why_bittersweet_emotions_underscore_life_s_beauty• Desensitization: https://en.wikipedia.org/wiki/Desensitization_(psychology)• Malcolm Gladwell's website: https://www.gladwellbooks.com/• Warren Buffett on X: https://x.com/warrenbuffett• Dale Carnegie speaking courses: https://www.dalecarnegie.com/en/presentation-skills-public-speaking-training• Bill Gates on X: https://x.com/billgates• Kathy Fish on LinkedIn: https://www.linkedin.com/in/kathy-fish-23b5777/• Why most public speaking advice is wrong—and how to finally overcome your speaking anxiety | Tristan de Montebello (CEO & co-founder of Ultraspeaking): https://www.lennysnewsletter.com/p/master-public-speaking-tristan-de-montebello• Ultraspeaking: https://ultraspeaking.com/lenny/• Rethinking the Extraverted Sales Ideal: The Ambivert Advantage: https://faculty.wharton.upenn.edu/wp-content/uploads/2013/06/Grant_PsychScience2013.pdf• Cutco: https://www.cutco.com/• Tim Ferriss's post about his new book: https://x.com/tferriss/status/1878936085033791817•  Mihaly Csikszentmihalyi: https://en.wikipedia.org/wiki/Mihaly_Csikszentmihalyi• Naval on X: https://x.com/naval• On saying no: https://www.lennysnewsletter.com/p/how-to-say-no• Susan Cain—How to Overcome Fear and Embrace Creativity: https://tim.blog/2019/01/24/susan-cain/• Zigging vs. zagging: How HubSpot built a $30B company | Dharmesh Shah (co-founder/CTO): https://www.lennysnewsletter.com/p/lessons-from-30-years-of-building• Renee Wood on LinkedIn: https://www.linkedin.com/in/recoale/• The Sopranos on Max: https://play.max.com/show/818c3d9d-1831-48a6-9583-0364a7f98453• The Talented Mr. Ripley on Prime Video: https://www.primevideo.com/detail/The-Talented-Mr-Ripley/0HA0GNFQ4ZXYPDNJHQEENK2Q6Q• Tugboat Institute: https://www.tugboatinstitute.com/• Leonard Cohen quote: https://www.goodreads.com/quotes/4484-there-is-a-crack-in-everything-that-s-how-the-light—Recommended books:• Quiet: The Power of Introverts in a World That Can't Stop Talking: https://www.amazon.com/Quiet-Power-Introverts-World-Talking/dp/0307352153• Creativity: Flow and the Psychology of Discovery and Invention: https://www.amazon.com/Creativity-Flow-Psychology-Discovery-Invention/dp/0062283251• Quiet Power: The Secret Strengths of Introverted Kids: https://www.amazon.com/Quiet-Power-Secret-Strengths-Introverted/dp/0147509920• Gandhi: An Autobiography—The Story of My Experiments with Truth: https://www.amazon.com/Gandhi-Autobiography-Story-Experiments-Truth/dp/0807059099• Flow: The Psychology of Optimal Experience: https://www.amazon.com/Flow-Psychology-Experience-Perennial-Classics/dp/0061339202• The Power of Myth: https://www.amazon.com/Power-Myth-Joseph-Campbell/dp/0385418868/• Bittersweet: How Sorrow and Longing Make Us Whole: https://www.amazon.com/Bittersweet-Oprahs-Book-Club-Longing/dp/0451499794• Good Energy: The Surprising Connection Between Metabolism and Limitless Health: https://www.amazon.com/Good-Energy-Surprising-Connection-Metabolism/dp/0593712641• The 5 Types of Wealth: A Transformative Guide to Design Your Dream Life: https://www.amazon.com/Types-Wealth-Transformative-Guide-Design/dp/059372318X—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. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Ep. 292 Can you really do 10 hours of research in just 20 minutes? Kipp dives into how to leverage Google's AI tools to quickly gather and synthesize information. Learn more about the deep research capabilities of Google Gemini, the seamless integration with NotebookLM for organizing and querying your data, and the innovative new interactive audio feature for real-time, engaging learning.  Mentions Gemini https://gemini.google.com/ NotebookLM https://notebooklm.google/ Dharmesh Shah https://www.hubspot.com/company/management/dharmesh-shah Get our guide to build your own Custom GPT: https://clickhubspot.com/customgpt We're creating our next round of content and want to ensure it tackles the challenges you're facing at work or in your business. To understand your biggest challenges we've put together a survey and we'd love to hear from you! https://bit.ly/matg-research Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Join our community https://landing.connect.com/matg Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat  ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Produced by Darren Clarke.

NVIDIA Mini AI Supercomputer, Microsoft's Small AI Model Breakthrough, and HubSpot's New AI Platform | Hashtag Trending In today's episode of Hashtag Trending, hosted by Jim Love, we delve into groundbreaking developments in AI technology. NVIDIA introduces Project Digits, a mini AI supercomputer with 1,000 teraflops of performance at an unprecedentedly low cost of $3,000. Microsoft reveals a new technique called R Star Math, proving that smaller AI models can outperform larger ones in math reasoning tasks. Lastly, HubSpot's co-founder, Dharmesh Shah, launches Agent AI, a platform for building and sharing AI task agents. Tune in to hear how these innovations are pushing the boundaries of AI computing. 00:00 Introduction and Today's Headlines 00:24 NVIDIA's Project Digits: A Mini AI Supercomputer 02:51 Microsoft's Breakthrough with Smaller AI Models 05:34 HubSpot Co-Founder's New AI Platform: Agent AI 07:03 Conclusion and Contact Information

Get our Business Monetization Playbook: https://clickhubspot.com/monetization Episode 655: Sam Parr ( https://x.com/theSamParr ) and Shaan Puri ( https://x.com/ShaanVP ) talk to Dharmesh Shah ( https://x.com/dharmesh ) about how to increase the odds of hitting your first million and your next million.  — Show Notes:  (0:00) Intro (3:33) Lesson 1: Get leverage (9:26) Lesson 2: Be an asset, not a liability (13:40) Lesson 3: Get even closer to the value creation (19:42) Mini Masterclass on Power Negotiating (24:35) Dharmesh's little-known $2M failure (29:35) Lesson: Insight compression (34:08) Dharmesh sells Chat.com (41:06) Agents are the new apps (44:51) The future is hybrid teams (49:23) Agents Dharmesh uses today (53:20) Dharmesh's next big thing (1:02:58) Uncomfortable company values (1:05:33) Local maximum vs global maximum (1:06:57) RaaS: Results-as-a-Service (1:09:59) Being a first time billionaire — Links: • Agent AI - https://agent.ai/  • Harvey MacKay books - https://harveymackay.com/books/  • Getting To Yes - https://tinyurl.com/43ne6v97  • Connecting Dots - https://connectingdots.com/  • MFM Vault - https://frontend-production-f8b7.up.railway.app/  — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth • Sam's List - http://samslist.co/ My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano

Episode 359 of The VentureFizz Podcast features Matt Douglas, Founder & CEO of Sincere. Boston has this legacy reputation that you can't build consumer companies in the area, yet there are so many great companies that have scaled like Wayfair, DraftKings, iRobot, SimpliSafe, and so… so… many more. Plus, don't get me started on how many brands, especially footwear, are located here. Anyway, Sincere is another example of a great consumer company at scale. It is highly likely that you've used one of their products like Punchbowl to plan a party, Timehop to relive past memories, or Memento, where you can collect and preserve memories together for a group video or photo album. Sincere's latest brand is Lovebird, a new platform for the wedding industry which is taking on The Knot and other outdated incumbents and as highlighted in this interview with Matt, there will be more coming from Sincere. In this podcast, we cover: * A discussion around the legacy of an entrepreneur and what led Matt down the path of starting a corporate foundation at Sincere for charitable initiatives. * Matt's background story, growing up with 5 brothers and how he started his entrepreneurial roots early on. * Getting his career started and how he became the youngest Product Manager at Adobe. * His brushes with tech luminaries like Steve Jobs, Bill Gates, Mark Zuckerberg, Alexis Ohanian, Justin Kan, and Dharmesh Shah. * The background story of Punchbowl and the three key characteristics he used for building a business. * Why the expansion into the wedding market with Lovebird made sense for the company and how they are differentiating themselves from the competitors. * Matt's philosophy around buying premium domains and a hint about his best 5 letter domain that is not even live yet. * And so much more.

Welcome back to another episode of the Niche Pursuits News Podcast! This week Spencer and Jared break down the latest news affecting SEOs and small publishers, they share their side hustle progress, and they talk about some weird niche sites for inspiration. They discuss Sam Altman's tweet - https://x.com/sama/status/1854238332534108188 They go over Dharmesh Shah's tweet - https://x.com/dharmesh/status/1854307883304792294 They talk about how AI Overviews is rolling out to more countries - https://searchengineland.com/google-expands-ai-overviews-to-over-100-countries-447832 They discuss how AI Overviews impacts publishers' traffic -  https://community.mariehaynes.com/posts/traffic-down-as-aios-launch-globally-forbes-seeing-declines-chatgpt-search-is-live They reveal that traffic is up for HCU-hit sites - https://www.google.com/url?q=https://www.seroundtable.com/google-helpful-content-update-recovery-data-38358.html&sa=D&source=docs&ust=1731069165137684&usg=AOvVaw1-h6THpgh8jvp1VR5d5YjX Spencer shares a weird political map - https://electoralvotemap.com/ Jared shares a calculator tool - https://charactercalculator.com/   Ready to join a niche publishing mastermind, and hear from industry experts each week?  Join the Niche Pursuits Community here: https://community.nichepursuits.com Be sure to get more content like this in the Niche Pursuits Newsletter Right Here: https://www.nichepursuits.com/newsletter Want a Faster and Easier Way to Build Internal Links?  Get $15 off Link Whisper with Discount Code "Podcast" on the Checkout Screen: https://www.nichepursuits.com/linkwhisper Get SEO Consulting from the Niche Pursuits Podcast Host, Jared Bauman: https://www.nichepursuits.com/201creative  

A tech regulation shakeup is on the way with President-elect Donald Trump set to take office in January. Trump has made it clear that he plans to dismantle Biden's AI policies on "day one," aligning himself with those who've pushed back against regulation. Today on TechCrunch's Equity podcast, hosts Kirsten Korosec, Devin Coldewey and Margaux MacColl  dove into what Trump's win could mean for AI policy and innovation moving forward.While AI is always on the mind these days, there was so much more startup and venture news for the Equity crew to get into this week. Listen to the full episode to hear about:OpenAI's acquisition of Chat.com, the domain previously acquired by HubSpot co-founder and CTO Dharmesh Shah for a whopping $15.5 million. We're not sure if this signals a brand change for the AI startup, but users' trips to ChatGPT just got three letters shorter.DeepRoute's $100 million raise and the startup's race to get its automated systems out before Tesla FSD is available in China.Biotech startup Archon's $20 million effort to power up drug development with its ‘antibody cages'. Of course, we couldn't talk about the news without a biochemistry lesson from Devin where we learned a new scientific term: thingies.Google's new AI-focused data center and collaboration with the Saudi Public Investment fund. The move had the team thinking more about tech's climate commitments at large, and who is walking back their pledges in favor of AI.The election bidding boom - from Polymarket to Kalshi and a potential $450 million payout.Equity will be back next week with a special interview between TechCrunch senior editor Julie Bort and Salesforce CEO Marc Benioff, so stay tuned.Equity is TechCrunch's flagship podcast, produced by Theresa Loconsolo, and posts every Wednesday and Friday. Subscribe to us on Apple Podcasts, Overcast, Spotify and all the casts. You also can follow Equity on X and Threads, at @EquityPod. For the full episode transcript, for those who prefer reading over listening, check out our full archive of episodes over at Simplecast. Credits: Equity is produced by Theresa Loconsolo with editing by Kell. Bryce Durbin is our Illustrator. We'd also like to thank the audience development team and Henry Pickavet, who manages TechCrunch audio products.

Shoot us a Text.We're live from Austin this morning where we'll be speaking to the ATAE Comms Directors, but before that, we're talking about how car dealer Bernie Moreno is headed to the Senate, the second annual list of CBT 40 Under 40 honorees and how Open AI spent a whopping $15M on the Chat.com domain.Show Notes with links:Bernie Moreno, former auto dealer and Trump-backed Republican, flipped a longstanding Democratic Senate seat in Ohio, securing a narrow victory over Sherrod Brown.Moreno won 50.2% of the vote, defeating Brown's 46.4%, marking a GOP gain in the Senate.The race was one of the most expensive Senate contests in history, crucial for Republican control.His opponent, incumbent Sherrod Brown, targeted Moreno's dealership past, implying he “would say anything to sell a car.” This line of attack backfired, galvanizing support from auto industry insiders who saw it as a slight against the profession.A critic of federal EV mandates, Moreno argued for consumer choice, advocating that Ohioans—and the auto market—should not be subjected to standards set by California.Moreno credited auto industry colleagues for their unwavering support, stating, “I appreciate the hundreds of phenomenal entrepreneurs in the car business.”CBT News has announced its second annual 40 Under 40 awards, spotlighting rising stars in the automotive retail industry. These honorees demonstrate exceptional talent in areas like sales, marketing, management, and innovation, shaping the future of automotive retail.The award recognizes contributions in sales, customer experience, and community service and aims to inspire future leaders in automotive retail.Co-founders Bridget and Jim Fitzpatrick commend honorees' resilience: "The resilience and dedication demonstrated by every member of the retail automotive community is truly inspiring."Friends of ASOTU: Nathanael Greklek, Chief Digital Brand Leader at Mohawk Auto Group,  and Michael Lucki, GM/Operating Partner at Riverhead MazdaOpenAI has made waves by purchasing the chat.com domain from HubSpot's Dharmesh Shah, a move signaling their evolving approach to user interaction.Sam Altman, OpenAI's CEO, shared the new domain, which directly redirects to ChatGPT.Originally bought by Shah for $15.5M, he later sold it to OpenAI, reportedly at a profit.Shah cited "Chat-based UX" as the next big trend in software for natural, intuitive interactions.Shah hinted that OpenAI paid with shares rather than cash, a unique twist on the transaction.This move aligns with OpenAI's recent rebranding efforts, including new model series like “o1” aimed at simplifying and enhancing user perception.Hosts: Paul J Daly and Kyle MountsierGet the Daily Push Back email at https://www.asotu.com/ JOIN the conversation on LinkedIn at: https://www.linkedin.com/company/asotu/ Read our most recent email at: https://www.asotu.com/media/push-back-email

Brian Tolkin is the Head of Product at Opendoor. Previously, he was one of the early employees at Uber, where he was instrumental in launching and growing UberPool, UberHop, and UberExpress and started one of the first product operations teams in tech. In our conversation, we dive into:• How to enable product and ops to work well together• How to run great product reviews• How to make good decisions with limited data• How he uses the jobs-to-be-done framework at Opendoor• How to stay calm under pressure as a leader• Wild stories from his time at Uber• Challenges faced at Opendoor during the pandemic• Much more—Brought to you by:• Pendo—The only all-in-one product experience platform for any type of application• Explo—Embed customer-facing analytics in your product• Attio—The powerful, flexible CRM for fast-growing startups—Find the transcript and references at: https://www.lennysnewsletter.com/p/scaling-uber-and-opendoor-brian-tolkin—Where to find Brian Tolkin:• X: https://x.com/briantolkin• LinkedIn: https://www.linkedin.com/in/briantolkin/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Brian's background(02:14) Career beginnings at Uber(02:49) Transitioning from product operations to product management(06:47) Product and operations synergy(10:00) Surge pricing at Uber(12:18) Scaling challenges, and stories(15:47) Opendoor and Covid adaptations(25:38) Product reviews and Jobs to Be Done(40:30) The challenges of A/B testing(42:23) Increasing conviction in solutions(44:33) Leveraging intuition in product decisions(47:07) Partnering with Zillow(52:55) Staying calm under pressure(56:25) Finding the “kernel of truth” in product management(01:00:21) Failure corner: Early days of Uber Pool(01:06:11) Lightning round and final thoughts—Referenced:• Twitter's former Head of Product opens up: being fired, meeting Elon, changing stagnant culture, building consumer product, more | Kayvon Beykpour: https://www.lennysnewsletter.com/p/twitters-former-head-of-product-kayvon-beykpour• Opendoor: https://sell.opendoor.com/• How to sell your ideas and rise within your company | Casey Winters, Eventbrite: https://www.lennysnewsletter.com/p/how-to-sell-your-ideas-and-rise-within• Thinking beyond frameworks | Casey Winters (Pinterest, Eventbrite, Airbnb, Tinder, Canva, Reddit, Grubhub): https://www.lennysnewsletter.com/p/thinking-beyond-frameworks-casey• Zigging vs. zagging: How HubSpot built a $30B company | Dharmesh Shah (co-founder/CTO): https://www.lennysnewsletter.com/p/lessons-from-30-years-of-building• FlashTags: A Simple Hack for Conveying Context Without Confusion: https://www.onstartups.com/flashtags-a-simple-hack-for-conveying-context-without-confusion• Jobs to Be Done Theory: https://www.christenseninstitute.org/theory/jobs-to-be-done• The ultimate guide to JTBD | Bob Moesta (co-creator of the framework): https://www.lennyspodcast.com/the-ultimate-guide-to-jtbd-bob-moesta-co-creator-of-the-framework/• Zillow: https://www.zillow.com/• Zillow, Opendoor announce multi-year partnership: https://investor.opendoor.com/news-releases/news-release-details/zillow-opendoor-announce-multi-year-partnership• Building product at Stripe: craft, metrics, and customer obsession | Jeff Weinstein (Product lead): https://www.lennysnewsletter.com/p/building-product-at-stripe-jeff-weinstein• Stripe Atlas: https://stripe.com/atlas• Founders podcast: https://www.founderspodcast.com/• Uber will deliver ice cream to you today: https://www.dispatch.com/story/lifestyle/food/2016/07/13/uber-will-deliver-ice-cream/24201840007/• UberKittens: https://www.uber.com/newsroom/uberkittens/• UberPuppies: https://www.uber.com/blog/uberpuppies-want-to-play/• Shoe Dog: A Memoir by the Creator of Nike: https://www.amazon.com/Shoe-Dog-Memoir-Creator-NIKE/dp/1471146723• The Black Swan: The Impact of the Highly Improbable: https://www.amazon.com/Black-Swan-Impact-Improbable-Incerto/dp/1400063515• The Design of Everyday Things: https://www.amazon.com/dp/0465050654• Shantaram: https://www.amazon.com/Shantaram-SHANTARAM-Paperback-GregoryDavidRoberts/dp/B00QPVJESC• Full Swing on Netflix: https://www.netflix.com/title/81483353• Formula 1: Drive to Survive on Netflix: https://www.netflix.com/title/80204890• Break Point on Netflix: https://www.netflix.com/title/81569920• Air on Prime Video: https://www.amazon.com/AIR-Matt-Damon/dp/B0B8Q3JMCG• Fi smart dog collar: https://tryfi.com/• Particle: https://particlenews.ai/• Sara Beykpour on LinkedIn: https://www.linkedin.com/in/sarabeykpour/• A new-parent gift guide for product managers: https://www.lennysnewsletter.com/p/a-new-parent-gift-guide-for-product• Jeff Holden on LinkedIn: https://www.linkedin.com/in/jeffholden/• Travis Kalanick on X: https://x.com/travisk—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. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Ep. 245 Why should you be a Claude super fan? Kipp and Kieran dive into the game-changing world of Claude apps and how anyone can build web apps in no time. Learn more on how Claude's new features empower you to create and publish lightweight apps effortlessly, real-life examples of innovative use cases, and the mind-blowing potential for profitability and customization with Claude's intuitive tools. Mentions Claude 3.5 Sonnet https://www.anthropic.com/news/claude-3-5-sonnet Gary Vaynerchuk https://garyvaynerchuk.com/ Dharmesh Shah https://www.hubspot.com/company/management/dharmesh-shah Replit https://replit.com/ Resource [Free] Steal our favorite AI Prompts featured on the show! Grab them here: https://clickhubspot.com/aip We're on Social Media! Follow us for everyday marketing wisdom straight to your feed YouTube: ​​https://www.youtube.com/channel/UCGtXqPiNV8YC0GMUzY-EUFg  Twitter: https://twitter.com/matgpod  TikTok: https://www.tiktok.com/@matgpod  Join our community https://landing.connect.com/matg Thank you for tuning into Marketing Against The Grain! Don't forget to hit subscribe and follow us on Apple Podcasts (so you never miss an episode)! https://podcasts.apple.com/us/podcast/marketing-against-the-grain/id1616700934   If you love this show, please leave us a 5-Star Review https://link.chtbl.com/h9_sjBKH and share your favorite episodes with friends. We really appreciate your support. Host Links: Kipp Bodnar, https://twitter.com/kippbodnar   Kieran Flanagan, https://twitter.com/searchbrat  ‘Marketing Against The Grain' is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Produced by Darren Clarke.

Dylan Field is the co-founder and CEO of Figma, the collaborative design platform that has revolutionized how product teams work. In my first-ever live podcast, recorded at Figma Config, Dylan and I dig into:• How intuition and product taste drive Dylan's decision-making• The challenge of keeping things simple• Dylan's thoughts on the future of product management• Lessons from Figma's early days• How Figma built their initial user base• Dylan's journey from intern to CEO of a 1,000+-person company• The future of design tools and AI—Brought to you by:• WorkOS—Modern identity platform for B2B SaaS, free up to 1 million MAUs• Anvil—The fastest way to build software for documents• User Testing—Human understanding. Human experiences.—Find the transcript at: https://www.lennysnewsletter.com/p/dylan-field-live-at-config—Where to find Dylan Field:• X: https://x.com/zoink?lang=en• LinkedIn: https://www.linkedin.com/in/dylanfield/—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) Introduction(01:11) Welcoming Dylan Field(02:36) Highlights and surprises from Config(06:58) The philosophy of design(08:01) Raccoon feet and muffin hands(09:57) Building and refining intuition and product taste(12:50) How to influence leadership(16:14) The role of product managers(21:12) The future of product management(22:20) The importance of simplicity in design(26:10) The long road to Figma's launch(27:44) Advice for aspiring entrepreneurs(29:07) Knowing when it's time to ship(30:39) Early user acquisition strategies(35:50) Spotting trends and future innovations(39:20) Reflections on leadership and growth(43:16) Lightning round—Referenced:• Mihika Kapoor on LinkedIn: https://www.linkedin.com/in/mihikakapoor/• Rick Rubin on the Creative Act—60 Minutes: https://www.youtube.com/watch?v=sE1teB5bN-w• Figma pages: https://help.figma.com/hc/en-us/articles/360038511293-Create-and-manage-pages• Leading through uncertainty: A design-led company—Brian Chesky (Config 2023): https://www.youtube.com/watch?v=Dkfijg7s76o• An inside look at how Figma builds product | Yuhki Yamashita (CPO of Figma): https://www.lennysnewsletter.com/p/an-inside-look-at-how-figma-builds• Vision, conviction, and hype: How to build 0 to 1 inside a company | Mihika Kapoor (Product at Figma): https://www.lennysnewsletter.com/p/vision-conviction-hype-mihika-kapoor• An inside look at Figma's unique GTM motion | Claire Butler (first GTM hire): https://www.lennysnewsletter.com/p/an-inside-look-at-figmas-unique-bottom• Zigging vs. zagging: How HubSpot built a $30B company | Dharmesh Shah (co-founder/CTO): https://www.lennysnewsletter.com/p/lessons-from-30-years-of-building• Nadia Singer on LinkedIn: https://www.linkedin.com/in/nadiasinger/ • Sho Kuwamoto on LinkedIn: https://www.linkedin.com/in/shokuwamoto/• FigJam: https://www.figma.com/figjam/• Tim Van Damme on LinkedIn: https://www.linkedin.com/in/tim-van-damme-maxvoltar/• Coda: https://coda.io/• Shishir Mehrotra on LinkedIn: https://www.linkedin.com/in/shishirmehrotra/• Websim: https://websim.ai/• eToys.com commercial (from Dylan's childhood acting career): https://www.youtube.com/watch?v=k3Y92aCmmbU—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. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Episode 579: Sam Parr ( https://twitter.com/theSamParr ) and Shaan Puri ( https://twitter.com/ShaanVP ) talk about 3 niche trends they've found that are guaranteed to make $1M+. Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Shaan gets his hotness score (2:30) Reddit trend leads to $6M ARR beauty app for men (10:12) Male nail care influencers (12:42) Sam upstages Shaan's beauty score (14:00) Spin-off businesses: Med Spas (16:00) Aging influencers and modern male grooming products (20:27) The story of Teflon and Dupont's billion dollar problem (22:49) Forever chemicals are in our water (26:14) Pfas free products (29:12) A regulatory inflection point is here (33:16) Trend: Assassins with water guns (34:32) $0 - $250K MRR app (35:22) Playground virality (38:00) Trading expertise for social vouching (49:10) Exporting a profitable internal tool — Links: • Umax - https://tinyurl.com/mezh49ac • Acqua Pana - https://www.acquapanna.com • MAMAVATION - https://www.mamavation.com • Splashin - https://www.splashin.app • Splashin TikTok - https://www.tiktok.com/discover/splashin-app — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 578: Shaan Puri ( https://twitter.com/ShaanVP ) sits down with Joe Lonsdale ( https://twitter.com/JTLonsdale ) to talk about how he leveraged one internship at PayPal into one billion dollar success after another. Today Joe is Managing Partner of 8VC and an early investor in Anduril. Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) The One Reason strategy (3:18) Learning Global Macro Finance from Peter Thiel (5:35) Taking multi-million dollar bets at 4:30am (8:43) Hire for raw IQ over expertise (10:33) Nurturing employees into unicorn founders (12:24) Solving hard problems with Addepar (13:53) Always “Being on” (15:32) How to spot opportunities for new businesses (21:10) How Epirus landed a military defense contract (27:09) Getting hits in hard domains (28:24) Business Idea: AI-powered Estate Planning (29:19) Business Idea: Business Process Outsourcing for local government (30:58) Big swings vs. base hits (31:49) Idea vs. execution (32:38) Focus vs. diversity of thought/attention (33:33) Insights from Elon's inner circle (35:36) Joe Lonsdale's unfair advantages (38:48) How to invest your time to make your first $1M (40:40) Working on an A+ problem as an intern at PayPal (43:15) Be within 2 standard deviations of top talent (44:14) Early days at Palantir (46:56) Building a top engineering culture (48:31) Borrowing trust as 21-year old defense contractor (52:22) Peter Thiel's biggest contrarian bet — Links: • Joe's Twitter - https://twitter.com/JTLonsdale • Joe's blog - https://blog.joelonsdale.com/ • Joe's podcast - https://www.americanoptimist.com/ • 8VC - https://www.8vc.com/ • Addepar - https://addepar.com/  • Palantir - https://www.palantir.com/ • Epirus- https://www.epirusinc.com/ • OpenGov - https://opengov.com/ • Prologis - https://www.prologis.com/ • Lessons from Peter Thiel - https://joelonsdale.com/lessons-peter-thiel/ — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 577: Sam Parr ( https://twitter.com/theSamParr ) and Shaan Puri ( https://twitter.com/ShaanVP ) talk about mysterious billionaire Thomas Tull.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Blue Collar Billy of The Week: Thomas Tull (2:29) Moneyball strategy for movies (5:20) Formula for box office hits: Bigger is better (7:25) International appeal (specifically China) (8:22) Data analytics for movie marketing (13:15) Flywheels at the highest level (24:31) Moneyball for X (26:42) Business lessons from the UFC (31:03) We give Zuck PR advice (33:02) What Dana White taught me about marketing (34:06) Level 1: Sell a product (34:46) Level 2: Sell a solution not a product (35:20) Level 3: Sell a Lifestyle (36:55) Level 4: Sell a feeling (39:18) Level 5: Identity in a box (46:49) Why Sam's new project will fail (52:38) Shaan workshops Sam's idea — Links: • The Information article - https://tinyurl.com/4csvs9ab • Legendary - https://www.legendary.com/ • “We Don't Sell Saddles Here” - https://tinyurl.com/2s39sjzf • SmartAsset - https://smartasset.com/ • Sam's List - https://samslist.co/ — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 576: Shaan Puri ( https://twitter.com/ShaanVP ) sits down with Tim Ferriss ( https://twitter.com/tferriss ) to talk about his latest lifestyle experiments and how to spend a perfect 24-hours. Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Tim's "What's next?" framework (7:22) Creativity gyms + why money doesn't buy happiness (12:11) Book Recommendation: The New Toughness Training for Sports (15:51) Tim Ferriss's perfectly optimized day (23:06) The art of podcasting  (32:03) From selling supplements to published author (38:42) Law of Category (42:23) Barbell strategy for Youtube (54:12) What would it look like if it was easy? (56:14) What is Tim's unfair advantage? (59:47) What silly story are we telling ourselves? (1:02:23) Stories about Naval — Links: • Tim's blog - https://tim.blog/ • Tim's books - https://tim.blog/tim-ferriss-books/ • “The New Toughness Training for Sports” - https://tinyurl.com/nhh6m4px • “The 22 Immutable Laws of Marketing” - https://tinyurl.com/2bmz43ve • 1,000 True Fans - https://kk.org/thetechnium/1000-true-fans/ • Blue Ocean Strategy - https://tinyurl.com/5739vvry — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 575: Sam Parr ( https://twitter.com/theSamParr ) and Shaan Puri ( https://twitter.com/ShaanVP ) talk about the weirdest things they've seen this week in business.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Kid Rock, our honorary Billy of the Week (8:13) Shaan's *new* rules for content  (Partial list) (9:05) Rule 1: Older is better (13:07) Rule 5: Early. Arbitrage. Exploit (17:58) Rule 4: Pay for learning (19:45) Sam's cheat code for better alpha (23:57) How Kirk Kerkorian Became the Greatest Deal Maker in Capitalist History (29:48) Three rules of wealth. Compounding rate, length of runway, and… (34:11) Must Listen: Business Untitled (36:28) LeBron James is now a podcaster? — Links: • Kid Rock on Theo Von - https://www.youtube.com/watch?v=nReTPXtTDDc  • Kid Rock's Rodeo - https://kidrock.com/blogs/news/kid-rocks-rock-roll-rodeo • Kid Rock's Honky Tonk - https://www.kidrockshonkytonkandsteakhouse.com/ • Nick Sleep Letters - https://tinyurl.com/2thhv6cy • AirChat - https://www.air.chat/ • GLG Insights - https://glginsights.com/ • The Gambler - https://tinyurl.com/4d4e62m2 • Business Untitled - https://tinyurl.com/26zkw9pr • LeBron's new podcast - https://tinyurl.com/2kuvsv5v — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 574: Sam Parr ( https://twitter.com/theSamParr ) and Shaan Puri ( https://twitter.com/ShaanVP ) talk to Jeremy Giffon about what businesses he would buy if he was starting Tiny TODAY and a bunch of opportunities that he sees people sleeping on.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Intro (1:23) Idea: Build businesses for people with audiences (5:48) Idea: Wirecutter for products that won't kill you (10:30) One chart business category: Regulation (14:55) Opportunity: Become a protege (19:19) Philosophy students > Business students (22:00) The myth the holdco (26:14) The pre- and post- fall (28:17) Idea: “Special situations" I.e. Distressed Venture (32:15) Working hard vs working winning while lazy (40:19) Hanging around the hoop (42:30) The most successful people respond immediately (43:55) Be Dennis the Menace (45:15) MrBeast shouldn't be selling chocolate (47:53) Billionaire is a state of mind (51:05) Silicon Valley guys envy hedge fund guys — Links: • Jeremy Giffon's Twitter - https://twitter.com/jeremygiffon • Live Oasis - https://www.live-oasis.com/ • Afina - http://afina.com/ — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 573: Sam Parr ( https://twitter.com/theSamParr ) and Shaan Puri ( https://twitter.com/ShaanVP ) talk to Jeremy Giffon about how Tiny Capital turned $5M in equity into 30 profitable companies.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Humble beginnings at Tiny Capital (4:40) Tiny's first acquisition (8:17) 50X return on Dribbble (10:14) Skip the cash flow statements (11:57) How to spot the opportunity (14:00) Chris's superpower (16:20) Stomaching aggressively low offers (17:46) Make an offer and stop talking (19:36) It's not you vs. them (22:06) "What would need to be true to make this deal?" (23:03) How to crush the cold email (25:15) Worst deal -- ignored red flags, lost everything (27:00) Best deal: Mealime (25X return) (29:16) Weirdest deal ($36.00 acquisition) — Links: • Tiny Capital - https://www.tiny.com/ • Dribbble - https://dribbble.com/ • Metalab - https://www.metalab.com/ • Mealime - https://www.mealime.com/ — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

David DeSanto is the chief product officer of GitLab, which is the largest remote-only company in the world. They share many of their team meetings on YouTube, and they've grown from being an open-source code management product competing with GitHub to a multi-product platform that covers security, compliance, continuous integration, project management, and deployment tools, many of which are infused with AI magic. In our conversation, we discuss:• How GitLab operationalizes transparency• The philosophy behind recording and sharing team meetings on YouTube• Their extensive public employee handbook• GitLab's core value of having “short toes”• Challenges and advice for doing remote work well• Strategies for ensuring effective communication in a remote work environment• GitLab's breadth-over-depth strategy• The company's unique approach to AI• The value of using humor in high-stakes conversations—Brought to you by:• Orb—The flexible billing engine for modern pricing• Eppo—Run reliable, impactful experiments• Paragon—Ship every SaaS integration your customers want—Find the transcript at: https://www.lennysnewsletter.com/p/the-gitlab-way—Where to find David DeSanto:• X: https://twitter.com/david_desanto• LinkedIn: https://www.linkedin.com/in/ddesanto/• Threads: https://www.threads.net/@david.the.beard—Where to find Lenny:• Newsletter: https://www.lennysnewsletter.com• X: https://twitter.com/lennysan• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/—In this episode, we cover:(00:00) David's background(04:20) Maintaining an epic beard(05:29) Why GitLab publicly shares team meetings(09:49) The GitLab Handbook(11:30) GitLab's issue tracker(14:29) How to successfully build a culture of transparency(18:11) Benefits of operating with transparency(19:55) The value of building in public(21:53) How GitLab implements their core value of kindness(25:16) What it means to have “short toes”(27:41) Other core values(32:16) Common reasons for not fitting in at GitLab(34:42) Advice for remote teams(42:04) Advice for getting into product(43:52) Advice for PMs who are struggling in a remote world(48:25) Specific tools that help with remote work(53:13) Time zones and remote work(57:18) Breadth-over-depth strategy(01:04:14) AI at GitLab(01:13:11) GitLab's products and solutions(01:14:54) Lightning round—Referenced:• GitLab: https://about.gitlab.com/• UX Showcase—David DeSanto introduction to UX team and AMA: https://www.youtube.com/watch?v=fEdsmnVKNj4• The GitLab Handbook: https://handbook.gitlab.com/• Sid Sijbrandij on LinkedIn: https://www.linkedin.com/in/sijbrandij/• Y Combinator: https://www.ycombinator.com/• GitLab issues: https://docs.gitlab.com/ee/user/project/issues/• Salesforce: https://www.salesforce.com/• GitLab values: https://handbook.gitlab.com/handbook/values• GitLab organizational structure: https://handbook.gitlab.com/handbook/company/structure• GitLab direction: https://about.gitlab.com/direction/• Dogfooding: A simple practice to help you build better products: https://medium.com/agileinsider/dogfooding-a-simple-practice-to-help-you-build-better-products-b5954af4d5f7• The ultimate guide to adding a PLG motion | Hila Qu (Reforge, GitLab): https://www.lennysnewsletter.com/p/the-ultimate-guide-to-adding-a-plg• Zigging vs. zagging: How HubSpot built a $30B company | Dharmesh Shah (co-founder/CTO): https://www.lennysnewsletter.com/p/lessons-from-30-years-of-building• HubSpot: https://www.hubspot.com/• Crossing the Chasm: Marketing and Selling Disruptive Products to Mainstream Customers: https://www.amazon.com/Crossing-Chasm-3rd-Disruptive-Mainstream/dp/0062292986• Geoffrey Moore on finding your beachhead, crossing the chasm, and dominating a market: https://www.lennyspodcast.com/geoffrey-moore-on-finding-your-beachhead-crossing-the-chasm-and-dominating-a-market/• Open-core model: https://en.wikipedia.org/wiki/Open-core_model• GitLab Duo: https://about.gitlab.com/gitlab-duo/• GitLab Docs: https://docs.gitlab.com/• Anthropic: https://www.anthropic.com/• GitLab Acquires UnReview to Expand Its DevOps Platform with Machine Learning Capabilities: https://about.gitlab.com/press/releases/2021-06-02-gitlab-acquires-unreview-machine-learning-capabilities/• Essentialism: The Disciplined Pursuit of Less: https://www.amazon.com/Essentialism-Disciplined-Pursuit-Greg-McKeown/dp/0804137382• The Mission Critical Core/Context Model for Product Managers: https://secretpmhandbook.com/the-mission-critical-corecontext-model-for-product-managers/• The Devil's Hour on AppleTV+: https://tv.apple.com/us/show/the-devils-hour/umc.cmc.3zw4tyzd4lvor5mwhujms63x3• Glass Onion: A Knives Out Mystery on Netflix: https://www.netflix.com/title/81458416• Taylor Swift's The Eras Tour on Prime Video: https://www.amazon.com/TAYLOR-SWIFT-ERAS-EXTENDED-VERSION/dp/B0CP99SN2B• The STAR method: https://capd.mit.edu/resources/the-star-method-for-behavioral-interviews/• Artifact News: https://artifact.news/• Superhuman: https://superhuman.com/• Arc browser: https://arc.net/• An inside look at how The Browser Company builds product: https://www.lennysnewsletter.com/p/competing-with-giants-an-inside-look—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. Get full access to Lenny's Newsletter at www.lennysnewsletter.com/subscribe

Episode 572: Sam Parr ( https://twitter.com/theSamParr ) and Shaan Puri ( https://twitter.com/ShaanVP ) talk about the 10 revelations learned from spending a week with Texas billionaires.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Tim Ferriss asks Shaan a hard question (panic ensues) (2:46) The Indian Warren Buffett (7:25) "Investing is not a team sport" (8:31) Mohnish Pabrai's Nap Room (10:28) Required reading list of a billionaire (11:47) He built 5 billion-dollar companies by 41 (15:39) 5 Revelations from a day with Joe Lonsdale (19:50) The final level of the money game: private chefs, full size basketball court, etc (20:52) Nick Gray, cocktail party legend (23:45) Hanging out with smarter people (27:17) Nerd sports that make the best entrepreneurs (31:17) Pay attention to what other people pay attention to (33:47) Ben Levy's superpower as a superconnector — Links: • The Dhando Investor - https://tinyurl.com/53p9bhfv • PeachyBbies - https://peachybbies.com/ — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 571: Shaan Puri (https://twitter.com/ShaanVP) talks to creator Jenny Hoyos who's mastered the virality recipe, about her step by step process for creating viral content that's pulled in over a BILLION views.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (00:00) Intro - Jenny's back story. From single digit views to hundreds of millions of views per episode. (1:15) Jenny is the anti-Mr. Beast. “They call me Mr. Least.” (2:10) Breaking down the perfect short. “Returning viewership is incredibly important.” (3:10) Examples of brands/channels that are doing the viral thing well.  (4:00) The 4 criteria for a viral video. (8:20) Weaving your personal life into your content. (12:30) Shaan and Jenny build a viral video concept in real time.  (16:50) The hook dictates the idea. (18:00) Power words - What are they and how to use them. (20:10) The metrics to pay attention to. (21:40) What your visuals should be. (24:10) Foreshadowing and how to use it. (25:25) The best storytelling. (26:50) Getting people to rewatch. (33:30) Nailing the ending. (35:00) Steal like an artist (36:40) Building tools to understand viewer psychology. (40:25) Guiding principle to winning audiences. (42:15) Predictions for the future of content demand. (43:30) Mindset for being creative. (48:25) Jenny's ultimate goal. (51:00) Where to find Jenny. — Links: Jenny's YouTube channel: https://www.youtube.com/@JennyHoyosLOL — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 570: Shaan Puri (https://twitter.com/ShaanVP) and Sam Parr (https://twitter.com/theSamParr) go through Sam's journey of launching his company Hampton. It's a step by step walkthrough of what went right and what went wrong.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (00:00) Intro - A radically transparent look inside Hampton launch. (2:22) The beginning of the idea just after Sam sells The Hustle, starts tinkering with buying AirBnBs. (3:00) Fail #1: Short-term rental crew. Fail #2: Community of truckers. (4:30) The Hampton idea and what the business is.  (5:45) Fail #3: V1, V2, V3 of Hampton - no one wanted it (8:00) Accepted where the demand was and found the hook for Hampton. Research begins. (10:08) Where the name came from. (12:05) Hired a branding agency (This was a hack that helped build the brand) (14:12) Things Sam said no to  (17:00) Leverage the founder story (20:18) Shaan's branding agency experience (21:40) Shaan's $25K Mistake: Hiring a naming agency (26:00) Takeaways — Links: https://www.joinhampton.com/ Hampton Brand Inspiration doc: https://tinyurl.com/4uw5a9sv — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 569: Shaan Puri (https://twitter.com/ShaanVP) and Sam Parr (https://twitter.com/theSamParr) get into being productive without being a slave to your calendar. How to disable distractions, being effective vs being efficient, and living the unscheduled life. Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) The joy of an unscheduled life (01:56) Maker vs manager schedule (02:32) Working in intentional spaces (04:59) Living without a to-do list (05:27) Reverse engineer your ideal day (8:26) "Show me your calendar and I'll show you your priorities" (09:19) Name your top 3 (quarterly) (12:56) Disable distractions (13:33) Be effective, not efficient (14:55) Do the big thing first (16:30) No loser works out at 7:00 am (17:47) The barbell strategy for building relationships (20:17) No as a default mode (21:04) Accepting the trade-offs — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 568: Shaan Puri (https://twitter.com/ShaanVP) and Sam Parr (https://twitter.com/theSamParr) challenge each other to the Japanese practice of misogi, plus they're breaking down the new economy of suffering.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Intro (2:20) Sam challenges Shaan to a Misogi (5:13) The rules of Misogi (11:42) Shaan challenges Sam to not be bothered (14:04) The Speed Project (15:08) The Monkey Run (16:00) Barkley Marathon (18:38) Iconic branding (20:02) "The definition of luxury is dominating your customer" (21:48) Shaan's favorite luxury brand: Harvard (27:16) How to put a 10% remix on an idea (29:09) Remixing corporate merch (30:50) Greg Isenberg gets a free jacket, starts a movement (32:58) Marissa Mayer's hilarious launch (37:01) Management Time: Who's Got the Monkey? (47:55) $14K Specialty beds — Links: • Jesse Itzler's Big A## Calendar - https://jesseitzler.com/products/calendar-2024 • The Comfort Crisis - https://eastermichael.com/book/ • Monkey Run - https://www.theadventurists.com/monkey-run/ • The Speed Project - https://www.instagram.com/thespeedproject • Exporting American prestige - https://tinyurl.com/2k76ssdz • Marissa Mayer's hard launch - https://twitter.com/marissamayer/status/1772664475331473680 • “Management Time: Who's Got The Monkey” - https://hbr.org/1999/11/management-time-whos-got-the-monkey • Cubby Beds - https://cubbybeds.com/ — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 567: Shaan Puri (https://twitter.com/ShaanVP) and Sam Parr (https://twitter.com/theSamParr) talk to Anthony Pompliano ( https://twitter.com/apompliano ) about Michael Saylor's $900M bet on Bitcoin, invisible blue-collar businesses he's buying, plus 10 tech startups that could 10x your income and your reputation.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 Listen to the first episode of MoneyWise here - https://tinyurl.com/7m5ff3rt — Show Notes: (0:00) Intro (00:25) Bitcoin going up? (5:26) Michael Saylor's bet-the-company, burn-the-boats strategy (14:18) Pomp's take: genius or insane? (16:42)Product manager to people manager to money manager (20:35) Pomp's weird side businesses (28:51) The truth about buying blue-collar businesses (30:01) You can't put rocket fuel in a car (35:06) The prolific ownership of Philip Anschutz (36:35) Pomp's List: Startups You Should Work For (38:58) 10X reputation: Anduril or OpenAI (43:37) Shaan interviews at Facebook (50:35) 10X Potential: Eight Sleep, Varda, Figure.ai, Traba, Placer.ai, Rainmaker, Galvanick (1:04:45) How Pomp thinks about trade positions (1:10:28) A simple thesis on Solana (1:11:22) Being early on Andrew Tate — Links: • MicroStrategy - https://www.microstrategy.com/ • Out Where The West Begins - https://tinyurl.com/4v5mc8y5 • Figure - http://figure.ai/ • Eight Sleep - https://www.eightsleep.com • Varda - https://www.varda.com/ • Traba - https://traba.work/ • Placer - https://www.placer.ai/ • Rainmaker - https://www.makerain.com/ • Galvanick - https://www.galvanick.com/ — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 566: Shaan Puri (https://twitter.com/ShaanVP) and Sam Parr (https://twitter.com/theSamParr) bring you the most taboo business model they've ever seen–plus the content funnel making this momfluencer $10M/yr.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 Access Hampton's “2023 Ecommerce Analysis: People, Profits, and Projections” here - http://joinhampton.com/ecom — Show Notes: (0:00) Sam and Shaan have "the talk" (2:50) Free egg freezing. Really? (8:37) Assessing the regret score of your life decisions (10:20) Economics of revenue per employee for ecomm (13:38) The content funnel of Dr. Becky (21:34) How momfluencers build trust (25:00) Strategic relatability, beautifully done (29:45) Genius marketing antics of Mini Katana (33:55) $1b dollar business plan: Freeze-dried candy (35:17) Hormozi's best advice - Find the 10/10 opportunity (38:10) The function of quitting — Links: • Cofertility - https://www.cofertility.com/ • Good Inside - https://www.goodinside.com/ • Dr. Becky on Instagram - https://www.instagram.com/drbeckyatgoodinside • Big Little Feelings - https://biglittlefeelings.com/ • V Shred - https://vshred.com/ • Miss Excel - https://www.miss-excel.com/ • Kinobody - https://www.facebook.com/kinobodyfitness — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 565: Shaan Puri (https://twitter.com/ShaanVP) and Sam Parr (https://twitter.com/theSamParr) are dropping an emergency pod to break down Paul Graham's essay about Reddit's IPO yesterday.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Intro (1:59) If you want to learn, teach.  (3:45) Show up – the ultimate high agency move (5:54) Trust your gut (7:47) How to get the best ideas (12:30) Don't be precious about the name (13:33) How Reddit faked early traction (16:45) Talent filters (19:37) “The best products are you pushed out” (23:42) We read Chris Saccsa's early emails (26:32) Reddit's exits to Conde Nast, then buys it back (29:20) 19 years later and still not profitable  — Links: • Y Combinator - https://www.ycombinator.com/ • Reddit - https://www.reddit.com/ • Paul Graham Essays - https://paulgraham.com/articles.html • Product Hunt - https://www.producthunt.com/ — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth My First Million is a HubSpot Original Podcast // Brought to you by The HubSpot Podcast Network // Production by Arie Desormeaux // Editing by Ezra Bakker Trupiano Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 564: Shaan Puri (https://twitter.com/ShaanVP) and Sam Parr (https://twitter.com/theSamParr) talk to Jason Fried about his 6-Week Sprint playbook, how he's planning for the end of subscription revenue, and what it's like to have Jeff Bezos as an investor.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Intro (2:30) Long term planning is a fantasy (8:30) The 6-Week Sprint Playbook (14:00) Does Jason regret selling We Work Remotely? (16:00) Cash flow king (21:00) Taking money from Jeff Bezos (29:30) Who does Jason admire? (33:00) Non-recurring revenue is back (37:00) The Founder Letter Launch strategy (45:30) Campfire v. Slack (50:40) Pile on the wackier stuff early (in life and business) (53:30) Taking financial risks that don't put you at risk (57:00) Where does Jason spend his profits? — Links: • Jason on Twitter - https://twitter.com/jasonfried • Rework - https://tinyurl.com/38mfc66n • 37Signals - https://37signals.com/ • Basecamp - https://basecamp.com/ • We Work Remotely - https://weworkremotely.com/ • Once - http://once.com/ — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 563: Shaan Puri (https://twitter.com/ShaanVP) teaches his framework for ruthless focus. Follow these 5 steps to crush your goals in 2024.  Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Intro (2:00) Define your Yes Threshold (4:00) Manager schedule vs. Maker schedule (6:30) The Pyramid of Clarity (8:30) Floor goals and F*ck Yeah Goals (10:00) Write it out. Be specific (12:00) Input vs. Output (16:00) Putting it all together — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More

Episode 562: Shaan Puri (https://twitter.com/ShaanVP) and Sam Parr (https://twitter.com/theSamParr) get into the economics of personality tests–including the most famous one which is used by 89% of Fortune 100 companies. Want to talk to Shaan? Text “hi” to 650-334-0790 Want to see Sam and Shaan's smiling faces? Head to the MFM YouTube Channel and subscribe - http://tinyurl.com/5n7ftsy5 — Show Notes: (0:00) Intro (1:00) Data mining the basketball court (7:00) Origin of Myers-Briggs Test (14:30) Formula for Grit (16:00) Sam takes the Grit Scale Test (23:00) Cognition Labs, a math nerd's wet dream (34:00) Be willing to walk backwards (39:50) Speedrunning: 3 Founders Who Repeated the Playbook (42:00) Don't explore, exploit (49:00) $600M protein bar in 4 years — Links: • Grit - https://angeladuckworth.com/grit-book/ • Gallup - https://www.gallup.com/ • Lunchclub - https://lunchclub.com • Cognition - https://www.cognition-labs.com/ • Gold-Medalist Coders article - https://tinyurl.com/tc65a2vc • David Protein - http://davidprotein.com/ — Check Out Sam's Stuff: • Hampton - https://www.joinhampton.com/ • Ideation Bootcamp - https://www.ideationbootcamp.co/ • Copy That - https://copythat.com • Hampton Wealth Survey - https://joinhampton.com/wealth — Check Out Shaan's Stuff: Need to hire? You should use the same service Shaan uses to hire developers, designers, & Virtual Assistants → it's called Shepherd (tell ‘em Shaan sent you): https://bit.ly/SupportShepherd Past guests on My First Million include Rob Dyrdek, Hasan Minhaj, Balaji Srinivasan, Jake Paul, Dr. Andrew Huberman, Gary Vee, Lance Armstrong, Sophia Amoruso, Ariel Helwani, Ramit Sethi, Stanley Druckenmiller, Peter Diamandis, Dharmesh Shah, Brian Halligan, Marc Lore, Jason Calacanis, Andrew Wilkinson, Julian Shapiro, Kat Cole, Codie Sanchez, Nader Al-Naji, Steph Smith, Trung Phan, Nick Huber, Anthony Pompliano, Ben Askren, Ramon Van Meer, Brianne Kimmel, Andrew Gazdecki, Scott Belsky, Moiz Ali, Dan Held, Elaine Zelby, Michael Saylor, Ryan Begelman, Jack Butcher, Reed Duchscher, Tai Lopez, Harley Finkelstein, Alexa von Tobel, Noah Kagan, Nick Bare, Greg Isenberg, James Altucher, Randy Hetrick and more. — Other episodes you might enjoy: • #224 Rob Dyrdek - How Tracking Every Second of His Life Took Rob Drydek from 0 to $405M in Exits • #209 Gary Vaynerchuk - Why NFTS Are the Future • #178 Balaji Srinivasan - Balaji on How to Fix the Media, Cloud Cities & Crypto • #169 - How One Man Started 5, Billion Dollar Companies, Dan Gilbert's Empire, & Talking With Warren Buffett • ​​​​#218 - Why You Should Take a Think Week Like Bill Gates • Dave Portnoy vs The World, Extreme Body Monitoring, The Future of Apparel Retail, "How Much is Anthony Pompliano Worth?", and More • How Mr Beast Got 100M Views in Less Than 4 Days, The $25M Chrome Extension, and More