Podcasts about Superhuman

What if the key to unlocking your fullest potential lies in the stories you tell yourself?In this powerful episode, Marisa Peer sits down with Shaman Durek, a 6th-generation shaman and spiritual guide to the stars, for a transformative conversation on what it truly means to live a superhuman life.Together, they explore how your inner narrative shapes your outer reality—and how you can begin rewriting that story to create a future filled with purpose, power, and possibility. Expect deep insights, spiritual wisdom, and practical guidance you can apply right away.Tune in and discover how to step beyond limits and into the extraordinary.If this inspired you, imagine helping others feel enough—just like Marisa does every day. Begin your journey here: https://link.rtt.com/6-training-250526-1

In 1994, Forrest Gump took the box-office by storm and became a staple of cable TV reruns in the following decades. Its feel good message about a simple man who lived life heart first struck a chord, but hidden inside a six minute montage was a grueling test of the human limits -- a 15,000 mile ultrarun across the US almost five times. In 2018, Rob Pope became the first to complete this superhuman run, and became fascinated with others who push their limits.   Listen to Rob talk with other superhuman folks on How To Be Superhuman Support comes from Kuat Racks  Oboz Terns Use code DIRTBAG to save 25% off your first order  Diaries+ Members-- Their support is powering the Diaries- thank you! You can join today. Our book, States of Adventure, 30 stories adapted from The Diaries, is out in the wild. See if it's available on your local shelves or order it here: geni.us/StatesofAdventure

Over the last two decades Dave Asprey, the “Father of Biohacking,” has partnered with world-renowned doctors, researchers, scientists and global mavericks to uncover the latest, most innovative methods, techniques and products for enhancing mental and physical performance. Dave has personally spent nearly $2 million taking control of his own biology--pushing the bounds of human possibility all in the name of science and evolution. He hosted the first-ever biohacking conference, which now in its seventh year draws an international audience. He's a four-time New York Times bestselling science author of Fast this Way, Super Human, Game Changers, The Bulletproof Diet and other books. He's hosted the Webby award-honoree podcast Bulletproof Radio for a decade and has been featured on the Today Show, CNN, Dr. Oz, The New York Times, Outside Magazine, Fast Company and more. Dave founded and leads a portfolio of brands: Upgrade Labs and cafes, 40 Years of Zen, TrueDark, TrueLight, Homebiotic, the Dave Asprey Box, the Human Potential Institute and the Upgrade Collective. He's also the original founder and creator of Bulletproof Coffee, the Bulletproof Diet and Bulletproof commercial wellness products. Through the Bulletproof Diet, Dave has maintained a 100-pound weight loss, improved his sleep, and upgraded his brain, ultimately transforming himself into a better entrepreneur, a better husband, and a better father. Dave has helped hundreds of thousands of people perform at levels far beyond what they'd expect, and without burning out or getting sick. Dave works to empower the entire globe with information and knowledge that unlocks the Super Human in everyone at any age. The proof of these advancements are better sleep, energy, and expanded capacity for all. 

What does it mean to be a “day one partner” for founders—and how does that change in an era of AI-driven acceleration?On this episode of The Data Minute, Peter sits down with Ed Sim, founding partner of Boldstart Ventures and the voice behind “What's Hot

Click here for more on this topic and other free resources - https://www.drjimrichards.com We all long to experience the greatness and power of God! And incredibly, God desires this for us even more deeply than we desire it for ourselves. So often, I speak with people who hunger to truly encounter the God of the Bible, yet they don't know where to look or what to expect. When we move beyond our limited religious notions about how and where divine encounters should occur, we uncover something far simpler—and far more powerful—than we ever imagined! At the very foundation of our faith, God reveals a remarkable way to begin our spiritual journey with a profoundly supernatural experience. This moment serves as the launching pad for an entire lifetime filled with extraordinary, superhuman events. And here's the wonderful truth: these experiences are meant to be normal for every believer! Join me this week as we explore the most unexpected place to start our incredible journey into experiencing the Superhuman Power of God. Let's step into the extraordinary together!

Send us a textJoin hosts Alex Sarlin and Ben Kornell as they explore the latest developments in education technology, from AI in classrooms to workforce shifts and EdTech innovation across the globe.✨ Episode Highlights:[00:03:16] Ezra Klein podcast brings AI and education to mainstream conversation[00:07:20] Alex and Ben compare and critique GPT-4, Claude, Gemini, and other AI tools[00:09:28] Utah emerges as a leading hub for EdTech startups and innovation[00:12:21] New AI bundles help educators explore tools like Superhuman and Perplexity[00:13:19] Surge in media coverage on cheating, lawsuits, and educator use of AI[00:16:17] Lawsuit filed against professor for using AI-generated content in class[00:18:00] Concerns grow about students using AI tools to bypass cognitive learning[00:23:10] Direct-to-student AI sparks debate about academic integrity and design[00:25:20] Google plans to roll out Gemini to students under 13[00:29:41] AI enables hands-on science learning like virtual frog dissections[00:33:43] AI compared to electricity as foundational infrastructure for the future[00:36:09] Rising youth unemployment signals early impact of AI-driven disruption[00:38:57] Major firms lay off workers while shifting strategy toward AI adoption[00:40:34] EdTech must define and prepare students for new AI-native job rolesPlus, special guest:[00:41:22] Sam Chaudhary, Co-founder & CEO of ClassDojo on tutoring, gamified learning, and community building

From graceful finesse to lightning-fast action! We dissect soccer's incredible transformation into a high-speed spectacle, revealing how modern training, science, and tactics have turned players into veritable superheroes on the pitch. Discover the mind-blowing speeds clocked by today's stars and explore the cutting-edge methods fueling this evolution. Get ready to have your perception of "the beautiful game" completely redefined!fast soccer, soccer speed, modern football, player fitness, soccer evolution

Loïc Houssier, Head of Engineering at Superhuman, joins us to discuss how AI and LLMs are reshaping the email experience. He highlights challenges related to the variability of user prompts and infrastructure optimization. Loïc emphasizes that a deep focus on user experience and real human workflows is key to building AI tools people actually love to use.Featuring:Loïc Houssier – LinkedInChris Benson – Website, GitHub, LinkedIn, XDaniel Whitenack – Website, GitHub, XLinks:SuperhumanReferral Code for a Free monthSponsors:Outshift by Cisco – AGNTCY is an open source collective building the Internet of Agents. It's a collaboration layer where AI agents can communicate, discover each other, and work across frameworks. For developers, this means standardized agent discovery tools, seamless protocols for inter-agent communication, and modular components to compose and scale multi-agent workflows. 

Dave Asprey's journey into biohacking began with a quest to improve his health. In his twenties, he was overweight and low on energy, but through cutting-edge science, Dave optimized his brain health, reduced his biological age, and transformed his life. As the father of biohacking, he believes he can live to 180 years and achieve what many consider impossible. In this episode, Dave discusses how entrepreneurs can leverage biohacking to boost health, wellness, and productivity. He also shares insights from his book, Smarter Not Harder, revealing efficient strategies for peak performance and longevity. In this episode, Hala and Dave will discuss:  (00:00) Introduction (01:53) How Mindset Affects Biological Aging (05:56) Benefits of Biohacking in Health and Business  (11:05) Why Biohacking Works: The Science Behind It (16:40) The Power of Laziness in Boosting Productivity (21:25) Managing Stress and Triggers in Business (31:52) The Importance of Health and Wellness Scans (34:30) ADHD as a Superpower in Entrepreneurship (39:32) Workout Tips for Busy Entrepreneurs (47:09) The Truth About Diet and Meat Consumption (01:00:03) Foods to Boost Brain Health and Performance Dave Asprey is an entrepreneur, author, biohacking pioneer, and the founder of Bulletproof 360, Inc., known for popularizing Bulletproof Coffee. A four-time New York Times bestselling author, his books include The Bulletproof Diet and Smarter Not Harder. He is also the host of The Human Upgrade podcast and has invested over $2 million in biohacking experiments, revolutionizing the fields of health, aging, and longevity. Sponsored By: Indeed - Get a $75 sponsored job credit at indeed.com/profitingIndeed  Shopify - Sign up for a one-dollar-per-month trial period at youngandprofiting.co/shopify  Microsoft Teams - Stop paying for tools. Get everything you need, for free at aka.ms/profiting  Mercury - Streamline your banking and finances in one place. Learn more at mercury.com/profiting  LinkedIn Marketing Solutions - Get a $100 credit on your next campaign at linkedin.com/profiting   Bilt - Start paying rent through Bilt and take advantage of your Neighborhood Benefits™ by going to joinbilt.com/PROFITING.  Airbnb - Find yourself a co-host at airbnb.com/host  Resources Mentioned: Dave Asprey: The Business of Biohacking | E149: youngandprofiting.co/BusinessofBiohacking Dave's Website: daveasprey.com  Dave's Book, Super Human: bit.ly/Super_Human Dave's Book, Smarter Not Harder: bit.ly/Smarter-Not-Harder Dave's Book, Bulletproof Diet: bit.ly/Bulletproof_Diet Dave's Book, Heavily Meditated: bit.ly/Heavily_Meditated  Active Deals - youngandprofiting.com/deals   Key YAP Links Reviews - ratethispodcast.com/yap  Youtube - youtube.com/c/YoungandProfiting  LinkedIn - linkedin.com/in/htaha/  Instagram - instagram.com/yapwithhala/  Social + Podcast Services: yapmedia.com  Transcripts - youngandprofiting.com/episodes-new  Entrepreneurship, Entrepreneurship Podcast, Business, Business Podcast, Self Improvement, Self-Improvement, Personal Development, Starting a Business, Strategy, Investing, Sales, Selling, Psychology, Productivity, Entrepreneurs, AI, Artificial Intelligence, Technology, Marketing, Negotiation, Money, Finance, Side Hustle, Mental Health, Career, Leadership, Mindset, Health, Growth Mindset, Mental Health, Psychology, Motivation, Manifestation, Life Balance, Self Healing, Positivity, Happiness, Sleep.

Send us a textIn this interview with  @peterwindsor we react to the Imola Grand Prix and discuss how Max Verstappen was able to beat Oscar Piastri after qualifying in P2. Why  @peterwindsor think that Verstappen's overtake into turn 1 might be one of the best ever in F1 and why Peter Windsor did not expect Verstappen to win the Imola Grand Prix. What does this Verstappen resurgence mean ofr the F1 2025 drivers' championship and have Red Bull finally developed their RB21 to where it is as quick  or quicker than Lando Norris' McLaren.  Did McLaren make yet another mistake by allowing Lando Norris to overtake Oscar Piastri in the closing stages of the Imola GP? What does  @peterwindsor think about Ferrari's underperformance in qualifying and does Fred Vasseur have to take all of the blame? Peter Windsor explains why Ferrari should be concerned about the performances of Lewis Hamilton and Charles Leclerc in the race and who does  @peterwindsor think will win the Monaco Grand Prix?- become a member -https://www.youtube.com/channel/UCxyxUe_jRskL8xH7n580Ecw/join- where to find me -Twitter: https://twitter.com/CxmeronCcTiktok: https://www.tiktok.com/@cxmeroncc_Facebook: https://www.facebook.com/CameronF1TVBusiness Email : cxmeronf1@gmail.com#f1 #formula1 #formulaone #maxverstappen #lewishamilton #charlesleclerc #mercedes #redbull  #ferrariThe BJ Show Sport Chat (The BJ Show) will cover all AFL games, quiz and more. Subscribe today.Listen on: Apple Podcasts Spotify

Dan Metcalfe taps in to break down what it means to be superhuman—self-generating, unplugging the brain, and tuning into the mind like it's a secret weapon. We get into character development that feels more like character detonation. It's raw, it's sharp, and it's laced with laughs. Paranoi Radio: we don't do comfort—we do evolution with attitude.// FOLLOW AND VIST DAN METCALFEhttp://www.bornsuperhuman.com/& http://www.totalbalancecompany.com/☂️☂️☂️☂️☂️☂️☂️☂️☂️☂️☂️☂️☂️☂️☂️☂️☂️☂️☂️ALERT OPERATIONS: CRYPTID WARFARE GET CLEAN: DETOX AND MAKE KIDS HEALTHY AGAIN// // GET 15% OFF AT CHECK OUT USING "PARANOI" at FLAVORS OF THE FOREST⬆️⬆️⬆️// STRUGGLING WITH MENTAL HEALTH? GET $50 OFF  YOUR NEXT LIFE CHANGING TREATMENT AT MENTAL WARIOR by Dr Atwell& VISIT ParanoiRadio.com ☂️

➡️ Join 321,000 people who read my free weekly newsletter: https://newsletter.scottdclary.com➡️ Like The Podcast? Leave A Rating: https://ratethispodcast.com/successstoryDave Asprey is an American entrepreneur, author, and biohacker best known as the founder of Bulletproof Coffee and a leading figure in the biohacking movement. A former Silicon Valley executive, Asprey has dedicated his career to optimizing human performance through science, technology, and nutrition. He popularized the concept of using butter and MCT oil in coffee to enhance energy and cognitive function, and has authored several best-selling books on health, including The Bulletproof Diet, Super Human, and Heavily Meditated. Asprey is also the host of a long-running podcast focused on wellness, longevity, and personal development.➡️ Show Linkshttps://www.instagram.com/dave.asprey/https://x.com/daveasprey/ https://www.linkedin.com/in/asprey/ ➡️ Podcast SponsorsHubspot - https://hubspot.com/ Vanta - https://www.vanta.com/scott Federated Computer - https://www.federated.computer Lingoda - https://try.lingoda.com/success_sprintCornbread Hemp - https://cornbreadhemp.com/success (Code: Success)FreshBooks - https://www.freshbooks.com/pricing-offer/ Quince - https://quince.com/success Northwest Registered Agent - https://www.northwestregisteredagent.com/success Prolon - https://prolonlife.com/clary Stash - https://get.stash.com/successstory NetSuite — https://netsuite.com/scottclary/ Indeed - https://indeed.com/clary➡️ Talking Points00:00 – Intro01:39 – Blending Ancient Wisdom with Science05:30 – Dave's Wake-Up Call12:02 – The Brain Science Breakdown19:31 – Sponsor Break23:23 – Healing Trauma at the Root37:27 – Sponsor Break41:33 – Trauma Beyond Childhood53:05 – Dave's Peak Performance Meditation56:55 – Why Sex Matters for Entrepreneurs1:04:56 – #1 Takeaway from Dave's Book1:06:30 – Psychedelics & Peak Mental StatesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Ti porto nel futuro…Un futuro non troppo lontano…!Voglio mostrarti cosa troverai nel tuo Studio Dentistico tra soli 3 anni, come renderlo il tuo Superpotere e come evitare di farti travolgere.Partiamo da un dato di fatto: il mondo è cambiato un sacco, in pochissimo tempoProbabilmente mi hai già sentito dire, che nei prossimi 3 (max 5) anni il mondo sarà completamente diverso da quello che conosciamo oggi.Sì, abbiamo già vissuto un sacco di cambiamenti……Ma il cambiamento più assurdo, quello che ribalta più di tutto le nostre vite, non è ancora finito. Anzi, è appena cominciato.All'insegna di cosa è questa trasformazione radicale?Dell'Intelligenza Artificiale.Aspetta prima di trarre conclusioni affrettate!Perché ci sono 3 falsi miti che dobbiamo scardinare……Infatti, se pensi che l'AI sia solo qualcosa che viaggia in parallelo con la tua Vita, che sia un semplice accessorio che puoi utilizzare per fare delle cose e che essendo software è solo uno strumento a tua disposizione……Ti dico che non è così. Anzi: hai perso di vista quello che conta davvero.Vuoi scoprire:cosa ci attende?in quali modi la tua Attività verrà profondamente stravolta?come e perché il tuo Team “non sarà più lo stesso”?Immergiti in questo episodio e seguimi in tutti i passaggi perché ti porto in una sorta di "visualizzazione" in cui scoprirai come sarà composto il Tuo Team e cosa sarà in grado fra pochissimi anni……E per consentirti di essere pronto a guidare con Successo quello scenario (che oggi fai fatica anche solo ad immaginare!) ti condivido una novità! ;-)Per iscriverti alla lista prioritaria di SUPERHUMAN e fruire il contenuto della puntata leggendo l'articolo di Blog dedicato, clicca qui -> https://bit.ly/il-futuro-che-ti-aspettaBuon ascolto o Buona lettura,AndreaGrazie per ascoltare il Podcast e restare in contatto con me!Scopri cosa può fare per Te il Sistema Operativo Profit Monday: https://bit.ly/SistemaOperativoProfitMonday Visita il blog per leggere gli articoli di tutte le Puntate del Podcast https://bit.ly/andreagrassi-blog Trovami sui social: FACEBOOK https://bit.ly/Andrea-Grassi-FB INSTAGRAM https://bit.ly/Andrea-Grassi-IG Segui le puntate anche su Youtube, iscriviti al canale: https://bit.ly/Andrea-Grassi-YT Scopri tutta La Verità sul Successo del tuo Studio Dentistico e sul perché fare il Dentista che ragiona solo da Professionista, potrebbe portarti alla rovina (indipendentemente da quanto lavori)......Acquista il libro "Fuori dai Denti": https://bit.ly/fuori-dai-denti

Vi snackar om att Dansmusikpodden nu har funnits i fem år, och lite om hur det hela började. Dessutom prat om allt från Kevin & Perry, Superhuman och E-types samarbete med Antiloop-David, till Deadmau5, trådlösa dj-lurar och Arturia Jup-8000 V. Och skillnaden mellan trance och trance.➢ Supporta Dansmusikpodden via Patreon ➢ Snacka loss i vår Facebook-grupp ➢ Hitta oss på övriga plattformar via vår Linktree ➢ Mejla oss: dansmusikpodden@gmail.com

Our DNA has extraordinary potential embedded within it, but many people don't utilize its full capacity. According to my guest, Dr. Carol Talbot, societal conditioning and environmental toxins have degraded our DNA and limited human evolution.  In today's interview, Dr. Carol will unveil the original, dormant blueprint within us, a potential for personal growth and transformation. Dr. Carol is the Founder and Creator of The Possibility Hub and a passionate ambassador for expanding consciousness and unlocking the superhuman abilities inherent within us all. With a PhD in Quantum Morphogenetic Science, her pioneering research on DNA bioregenesis and Source Feeding is reshaping our understanding of human potential. Her journey has led her to study with extraordinary masters and speak in over 20 countries.  As an NLP Master Trainer and Certified Master Firewalk Instructor, she uses various tools, from Quantum Morphogenetic Physics to Time-Line Therapy, Sound Healing, and Bio-Geometry, to ignite rapid transformation and help others master their reality. During our conversation, Dr. Carol guides us with practical insights and experience to help us remember our true nature. Through ancient practices and shifts in mindset, she shows us how to nourish ourselves and energize so that we can access higher ways of living and being in the world. *Disclaimer*: The health information in this episode is provided for general informational and educational purposes only and is not a substitute for professional advice. Accordingly, before taking any actions based upon such information, we encourage you to consult with the appropriate professionals.

Grab your ticket for the Man In Arena tour - https://maninthearenatour.com/?utm_source=speaker&utm_medium=organic&utm_campaign=kylecarnahan   In this raw and real conversation, Coach Frank Rich sits down with Kyle Carnahan of SuperHuman Fathers to unpack what it really means to be a man, a leader, and a father in today's world.   They dive into the lies men believe about masculinity, the damage caused by emotional suppression and blame-shifting, and how radical truth-telling can rebuild your marriage, your health, and your identity.   Kyle shares his powerful journey from physical injury to mental and spiritual strength—and why your healing as a man starts with discipline, vulnerability, and telling the f***ing truth.   This episode is for every man who feels the pressure of being a father, provider, and husband… but knows deep down he's built for more.   Key Takeaways: Why fatherhood exposes your deepest flaws—and how to grow through it   The real reason most men stay stuck in cycles of blame and avoidance   How trauma affects your ability to connect with your wife and kids   The dangers of becoming either too hard or too soft as a man   Why your body is the gateway to rebuilding your confidence and leadership   How Kyle healed his body and reignited his purpose   The power of daily discipline when life feels like it's falling apart   Why marriage isn't a burden—it's a battlefield for your personal growth   How to bring fun, lightness, and connection back into your relationship   Why you must stop hiding your struggles and start speaking the truth   How physical strength and emotional intelligence make you unstoppable   What it really takes to become a SuperHuman Father     Connect with Kyle: Instagram - https://www.instagram.com/superhumanfathers   SuperHuman Fathers -  https://superhumanfathers.com/   Power Couple Playbook podcast - https://powercoupleplaybook.com/   --- Connect with Frank and The Super Human Life on Social Media: Instagram: https://www.instagram.com/coachfrankrich/   Facebook: https://www.facebook.com/groups/584284948647477/   Website: http://www.thesuperhumanlifepodcast.com/tshlhome   YouTube: https://www.youtube.com/channel/UCjB4UrpxtNO2AFtDURMzoKQ    

Join us!

In this episode I brought on Taylor Learmont IFBB fitness pro. She's also known as LittleTfitness. Taylor Learmont is a Canadian-born fitness professional, content creator, and two-time IFBB Fitness Pro Champion. With a background in gymnastics, dance, and cheerleading, Taylor transitioned into the fitness industry, gaining significant recognition for her engaging and authentic content on platforms like Instagram, TikTok, and YouTube. She emphasizes strength training, mobility, and body positivity, aiming to inspire her audience to embrace their fitness journeys without succumbing to industry pressures. Through her app, online coaching, and social media presence, Taylor continues to empower individuals worldwide to lead healthier, more confident lives.In this episode we discuss Taylors journey to the stage and she has learned from her mistakes to become a top level competitor. Taylor keeps it raw and real in this conversation. Even if you're not a competitor, this can be a great episode to learn how to become more resilient. Today's guestIG: @littletfitnesMy website & for more information on my coaching serviceswww.nicoleferrierfitness.comMy go to supplementsShop Legion supplementscode NFFYour host Nicole Ferrier @nicoleferrierfitness on Instagram and tiktok

Episode Summary In this episode of the ChatGPT Experiment Podcast, host Cary Weston sits down with George B. Thomas—HubSpot expert, content strategist, and passionate advocate for human-centered technology. They dive deep into how AI, especially tools like ChatGPT, can help simplify complex tasks, reclaim time, and amplify impact. George shares his journey of curiosity, how he built the “superhuman framework,” and how he used it to create a digital clone of himself that can help others 24/7 with authenticity and purpose. The episode is filled with warmth, insight, and a strong message about using AI to be more human, not less.   Top 3 Takeaways Curiosity + Simplicity = Power: George emphasizes the importance of staying curious and simplifying the complex to unlock new possibilities with AI. The Superhuman Framework: Built around purpose, passion, persistence, and love—plus ten “H-pillars”—this framework drives George's approach to personal and professional growth. AI as a Force Multiplier: George's “clone” project demonstrates how AI can extend your values, knowledge, and personality to help more people, even when you're not physically present.   About George B. Thomas George B. Thomas is a content strategist, speaker, and AI enthusiast with over a decade of experience helping businesses grow using HubSpot and inbound marketing. Known for his empathetic, practical approach, George has 42 HubSpot certifications and a passion for empowering teams and individuals through frameworks like his “superhuman” method. He also created a digital clone of himself to scale access to his knowledge and personality, blending technology with deeply human values. You can find George at georgebthomas.com, helper.georgebthomas.com, or on LinkedIn.   Cary offers customized one-on-one ChatGPT training in 60 minute sessions. Find out more information on the sessions, answers to frequent questions, and how to register at www.ChatGPTExperiment.com +++++++++ CONNECT WITH CARY ChatGPT Podcast Website: www.ChatGPTExperiment.com Marketing Podcast: www.PracticalMarketingShow.com Cary's Agency Website: www.CMWeston.com LinkedIn: https://www.linkedin.com/in/caryweston   LINKEDIN NEWSLETTER The Chat GPT Experiment is also a LinkedIn Newsletter and you can find it here: https://www.linkedin.com/newsletters/the-chat-gpt-experiment-7110348839919702016/   MUSIC CREDITS The instrumental music used in this podcast is called “Curious” by Podington Bear.

Mike Mulligan and David Haugh welcomed in Leila Rahimi and Mark Grote for transition.

The CEO's Strategic Growth Edge: A Go-To-Market System That Scales“You don't need more leads—you need clarity. Clarity on where your business can grow the most, the fastest, and at the highest margin. That's what a real go-to-market system delivers. It's not about volume anymore—it's about alignment, focus, and making sure every team—marketing, sales, and customer success—is executing toward the same outcome. That's how CEOs scale with confidence.” That's a quote from Sangram Vajre, and a sneak peek at today's episode.Welcome to Revenue Boost: A Marketing Podcast. I'm your host, Kerry Curran—revenue growth expert, industry analyst, and relentless advocate for turning marketing into a revenue engine. Each episode, we bring you the strategies, insights, and conversations that help drive your revenue growth. So search for Revenue Boost in your favorite podcast directory and hit subscribe to stay ahead of the game.In The CEO's Strategic Growth Edge: A Go-to-Market System That Scales, I'm joined by bestselling author and GTM expert Sangram Vajre to discuss why go-to-market isn't a marketing tactic—it's a CEO-level growth system. In this episode, you'll learn the three phases every business must navigate to scale, why alignment beats activity in every growth stage, how CEOs can drive clarity, trust, and margin-focused decisions across teams, and why AI is only a threat if you're still riding the demand-gen horse.If you're a growth-minded CEO or exec, this episode gives you the roadmap and the mindset to scale faster, smarter, and stronger. Be sure to listen through to the end, where Sangram shares three key tips—his ultimate advice for any leader ready to level up their go-to-market strategy. Let's go!Kerry Curran, RBMA (00:00.77)So welcome, Sangram. Please introduce yourself and share a bit about your background and expertise.Sangram Vajre (00:06.992)Well, at the highest level, I feel like I've had the opportunity to be in the B2B space for the last two decades and have had a front-row seat to categories that have shaped how we think about go-to-market. I ran marketing at Pardot. We were acquired by ExactTarget and then Salesforce—that was a $2.7 billion acquisition. It was a huge shift in mindset, going from a $10 million company to a $10 billion one, and I learned a lot.I became a student of go-to-market, if you will. That was in the marketing automation space. Then I launched a company called Terminus, which has been acquired twice now. Along the way, I've written three books. The one we're going to talk a lot about is MOVE, which became a Wall Street Journal bestseller. That book has created a lot of opportunities and work for us.I walked into writing this book, Kerry, thinking I knew go-to-market because I had two $100M+ exits. But I walked out of the process a student of go-to-market because I learned so much. Writing it forced me to talk to folks like Brian Halligan, the CEO of HubSpot, and partners at VC firms who have seen 200 exits—not just the three I've experienced.It really expanded my vision. Now I lead a company called Go-To-Market Partners. We're a research and advisory firm focused on helping companies understand who owns go-to-market and how to run it at a transformational level. Our clients are primarily CEOs and executive teams. That's our focus.Kerry Curran, RBMA (01:46.094)Excellent. Well, I'm very excited to dive in. I first saw you speak at Inbound last fall, and what really resonated with me was the shift from just an ABM program to a company-wide GTM program—one that includes everything from problem-market fit all the way to customer success, loyalty, and retention. Really making GTM the core of revenue growth.So I'd love for you to dive in and share that framework and background.Sangram Vajre (02:23.224)Yeah. And by the way, for people who've never attended Inbound—you should. I've spoken there for eight years straight and always try to bring new ideas. Each year, they keep giving me more opportunities—from main stage to workshops. I think you attended the 90-minute workshop, right? Hopefully it wasn't boring!Kerry Curran, RBMA (02:48.61)Yeah, it was excellent. I love this stuff, so I was taking lots of notes.Sangram Vajre (02:52.814)That was fun. The whole idea was: how can you build your entire go-to-market strategy on a single slide? Now, people might think, “There's no way—you need way more detail.” But it's not about making it complete; it's about making it clear.So everyone can be aligned. For example, in the operating system we've developed, we write research about it every Monday in a newsletter called GTM Monday, read by 175,000 people. The eight pillars are based on the most important questions. And Kerry, I don't know if you'll agree, but I think I've done a disservice for two decades by asking the wrong question.Like, I used to ask, “Where can we grow?”—which sounds smart but is actually foolish. The better question is, “Where can we grow the most, the fastest, the best, at the highest margin?” That's the true business perspective. So the operating system is built around these eight essential questions.If every executive team can align on these—not with certainty, but with clarity—then they can gain a clear understanding of what they're doing, where they're going, who their ICP is, what bets they're making, and which motions to pursue. I've done this over a thousand times with executive teams, helping them build their entire go-to-market strategy on a single slide. And it's like a lightbulb moment for them: “Okay, now I know what bets we're making and how my team is aligned.” It's a beautiful thing.Kerry Curran, RBMA (04:50.988)Yeah, because that's one of the hardest challenges across business strategy and growth: where to invest, where to lean in. So bring us through the questions and framework.Sangram Vajre (05:01.688)Yeah. So the first one is “Where can you grow the most?” The second one is really about what we call the Market Investment Map. I'll give you maybe three or four so people can get an idea. The Market Investment Map is especially useful for companies with more than one product or more than one segment. This is the least used but most valuable framework companies should be using.You might remember from the Inbound talk—I used HubSpot as an example since I was speaking at Inbound. It's interesting because at my last company, Terminus, we acquired five companies in eight years. So we had to learn this process. The Market Investment Map is about matching your best segments to the best products to create the highest-margin offering.If your entire business focuses only on pipeline and revenue—which sounds right—you're actually focused on the wrong things. You may have seen people post on LinkedIn saying, “I generated $10 million in pipeline,” and then a month later, they're laid off. Why? Because that pipeline didn't matter. It might have been general pipeline, but if you looked at pipeline within your ICP—the customers your company really needs to close, retain, and expand—it might have only been half a million. That's not enough to sustain growth or justify your role.So, understanding the business is critical. It's not just about understanding marketing skills like demand gen, content, or design. Those are table stakes. You need to understand the business of marketing—how the financials work, how to drive revenue, and how to say, “Yeah, we generated $10 million in pipeline, but only half a million was within ICP, so it won't convert or drive the margin we need.” That level of EQ and IQ is what leaders need today.Our go-to-market operating system goes deep into areas like this.Kerry Curran, RBMA (07:31.022)And I love the alignment with the ICP. I'm sure you'll get deeper into that. I also know you talk about getting rid of MQLs because the real focus should be on getting closer to the ICP—on who's actually going to drive revenue.Sangram Vajre (07:45.892)Yeah. John Miller, a good friend who co-founded Marketo, has been writing about this too. I was the CMO of Pardot. Then we both built ABM companies—I built Terminus; he built Engagio, which is now part of Demandbase. We've been evangelizing the idea of efficient marketing machines for the last two decades.We're coming full circle now. That approach made sense in the “growth at all costs” era. But in this “efficient growth” era, everything can be measured. The dark funnel is real. AI can now accelerate your team's output and throughput. So we have to go back to first principles—what do your customers really want?I was in a discussion yesterday with executives and middle managers, and the topic of AI came up. Some were worried it would take their jobs. And I said, “Yes, it absolutely will—and it should.” I gave the example I wrote about recently: imagine you were the best horseman, with saddles, barns, and a generational business built around horses. Then Henry Ford comes along with four wheels. You just lost your job—not because you were bad, but because you got infatuated with the horse, not with your customer's need to get from point A to point B.Horses did that—it was better than walking. But then came cars, trains, airplanes. Business evolves. If you focus on your customers' needs—better, faster, cheaper—you'll always be excited about innovation rather than afraid of it. So yes, AI will replace anyone who stays on their horse. If you're riding the demand gen horse or relying only on content creation, a lot is going to change. Get off the horse, refocus on customer needs, and figure out how to move your business forward.Kerry Curran, RBMA (10:21.708)Yeah. So talk a bit about honing in on the ICP. I know in one of the sessions you asked, “Who's your target audience?” And of course, there was one guy in the front row who said, “Everyone,” and we all laughed. But I still hear that all the time. Talk about how important it is, to your point, to know your customer and get obsessed with what they need.Sangram Vajre (10:45.56)Yeah. So the first pillar of the go-to-market operating system is called TRM, or Total Relevant Market. We introduced that in the book MOVE for the first time. It's a departure from TAM—Total Addressable Market—which is what that guy in the front row was referring to during that session. It was epic, and I think he was a sales leader, so it was even funnier in a room full of marketers.But it's true—and real. He was being honest, and I appreciated that. The reality is, we've all been conditioned to focus on more and more—bigger and bigger markets. That makes sense if you have unlimited funds and can raise money. It makes sense if the market is huge and you're just trying to get in and have more people doing outbound.As a matter of fact, a few weeks ago, we did a session where someone said something profound that I'll never forget. He said, “The whole SDR function is a feature bug in the VC model.” That was fascinating—because the whole SDR model was built to get as many leads as possible, assign 22-year-olds to make cold calls, and push them to AEs.We built this because it worked on a spreadsheet. If we generate 1,000 leads, we need 50 callers to convert them. It's math. But nobody really tried to improve it because we had the money. Now we're in a different world. We have clients doing $10–15 million in revenue with five-person teams automating so much.People don't read as many automated emails. My phone filters out robocalls, so I never pick up unless it's someone I know. Non-personalized emails go into a folder I never open. Yet people keep sending thousands of them, thinking it works.For example, I send our GTM Monday newsletter via Substack. It's free for readers, and it's free for me to send—even to 175,000 people. Meanwhile, marketers spend thousands every time they email their list using legacy tools. Why? Because these people haven't opted in to be part of the journey the way Substack subscribers have.The market has changed. Buying big marketing automation tools for $100,000 is going to change drastically. Fractional leaders and agencies will thrive because what CEOs really need is people like you—and frameworks like a go-to-market operating system—to guide them. You and I have the gray hair and battle scars to prove it. What matters now is using a modern framework, implementing it, and measuring outcomes differently.Kerry Curran, RBMA (14:08.11)Yeah, you bring up such a valid point. In so many of my conversations, I see the same thing. It's been a sales-led growth strategy for years. Investments went to sales—more BDRs, more cold emails, more tech stack partners.Even as I was starting my consultancy, I'd talk to partners or prospects who'd say, “Well, we just hired more salespeople. We want to see how that goes.” But to your point, without the foundational framework—without targeting the right audience—you're just spinning your wheels on volume.Sangram Vajre (15:06.318)Exactly. One area we emphasize in our go-to-market operating system is differentiation. Everyone's doing the same thing. Let me give you an example. Last week, I looked at a startup's email tool that reads your emails and drafts responses automatically. Super interesting. I use Superhuman for email.Two days later, Superhuman sent an email saying they'd launched the exact same feature. So this startup spent time and money building a feature, and Superhuman—already with a huge user base—replicated and launched it instantly. That startup is out of business.With AI, product development is lightning fast. So product is no longer your differentiator. Your differentiation now is how you tell your story, how quickly you grab attention, how well you build and maintain a community. That becomes your moat. Those first principles matter more than ever. Product is just table stakes now.Kerry Curran, RBMA (16:33.878)Right. And connecting that to your marketing strategy, your communication, your messaging—it also sets up your sales team to close faster. By the time a prospect talks to a rep, your marketing has already educated them on your differentiation. So talk more about the stages and what companies need to keep in mind when applying your go-to-market framework.Sangram Vajre (17:07.482)One of the things we mention in the book—and go really deep into in our operating system—is this 3P format: Problem-Market Fit, Product-Market Fit, and Platform-Market Fit. We believe these are the three core stages of a business. I experienced them firsthand at Pardot, Salesforce, and Terminus through multiple acquisitions.If you remember, I always talk about the “squiggly line,” because no company grows up and to the right in a straight line. If you look at daily, weekly, or monthly insights, there are dips—just like a stock market chart. So the squiggly line shows you can go from Problem to Product, but you'll experience a dip. That's normal and natural. Same thing when you go from Product to Platform—you hit a dip. Those dips are what we call the “valleys of death.”Some companies overcome those valleys and cross the chasm, and others don't. Why? Because at those points, they discover they can market and sell, but they can't deliver. Or maybe they can deliver, but they can't renew. Or maybe they can renew but not expand. Each gap becomes a value to fix in the system.And it's hard. I've gone from $5 million to $10 million to $15 million, all the way to $100 million in revenue—and every 5 to 10 million increment brings a new set of challenges. You think you've got it figured out, and then you don't—because everything else has to change with scale.I'll never forget one company I was on the board of—unfortunately, it didn't make it. The CEO was upset because they were doing $20 million in revenue but didn't get the valuation they wanted. Meanwhile, a competitor doing only $5 million in revenue in the same space got a $500 million valuation. Why? Because the $20M company was doing tons of customization—still stuck in Problem-Market Fit. The $5M company had reached Product-Market Fit and was far more efficient. Their operational costs were lower, and their NRR was over 120%.If you've read some of my research, you know I'm all in on NRR—Net Revenue Retention—as the #1 metric. If you get NRR above 120%, you'll double your revenue in 3.8 years without adding a single new customer. That's what executives should focus on.That's why we say the CEO owns go-to-market. All our research shows that if the CEO doesn't own it, you'll have a really hard time scaling.Kerry Curran, RBMA (20:23.992)That makes so much sense, because everything you're talking about—while it includes marketing functions—is really business strategy. It needs to be driven top-down. It has to be the North Star the whole company is paddling toward.I've been in organizations where that's not the case. And as you said, leadership has to have the knowledge and strategic awareness to navigate those pivots—those valleys of death. So talk about how hard it is to bring new frameworks into an organization and the change management that comes with that. As you evangelize the idea that the CEO owns GTM, what's resonating most with them?Sangram Vajre (21:26.456)Great question. First of all, CEOs who get it—they love it. The people who struggle most are actually CMOs and CROs because they feel like they should be the ones owning go-to-market. And while their input is critical, they can't own it entirely.In all our advisory work, Kerry, we mandate two things:The CEO must be in the room. We won't do an engagement without that. The executive team must be involved. We don't do one-on-one coaching—because transformation happens in teams.People often get it wrong. They think, “We need better ICP targeting, so that's marketing's job.” Or, “We need pipeline acceleration—let sales figure that out.” Or, “We have a retention issue—fire the CS team.” No. The problem isn't a department issue—it's a process and team issue.The CEO is the most incentivized person to bring clarity, alignment, and trust—the three pillars of our GTM operating system. They're the ones sitting in all the one-on-one meetings, burning out from the lack of alignment. The challenge is most CEOs don't know what it means to own GTM. It feels overwhelming.So we help them reframe that. Owning doesn't mean running GTM. It means orchestrating clarity, alignment, and trust. Every meeting they lead should advance one of those. That's the job. When the ICP is agreed upon, marketing should be excited to generate leads for it. Sales should be eager to follow up. CS should be relieved they're not getting misaligned customers. That's leadership. And there's no one more suited—or incentivized—to lead that than the CEO.Kerry Curran, RBMA (24:08.11)Absolutely. And the CFO plays a key role too—holding the purse strings, understanding where the investments should go.Sangram Vajre (24:20.622)Yes. In fact, in the book and in our research, we emphasize the importance of RevOps—especially once a company reaches Product-Market Fit and moves toward Platform-Market Fit.If you're operating across multiple products, segments, geographies, or using multiple GTM motions, the RevOps leader—who often reports to the CFO or CEO—becomes critical. I'd say they're the second most important person in the company from a strategy standpoint.Why? Because they're the only ones who can look at the whole picture and say, “We don't need to spend more on marketing; we need to fix the sales process.” A marketing leader won't say that. A sales leader won't say that. You need someone who can objectively assess where the real bottleneck is.Kerry Curran, RBMA (25:17.836)Yeah, that definitely makes so much sense. Are there other areas—maybe below the executive team—that help educate the company from a change management perspective to gain buy-in? Or is it really a company-wide change?Sangram Vajre (25:33.742)Yeah, you mentioned ABM earlier. Having written a few books on ABM and building Terminus, we've seen thousands of companies go through transformation. We now have over 70,000 students who've gone through our courses. I love getting feedback.What's interesting is that ABM has been great for aligning sales and marketing—but it hasn't transformed the company. Go-to-market is not a marketing or sales strategy. It's a business strategy. It has to bring in CS, product, finance—everyone.Where companies often fail is by looking at go-to-market too narrowly—like it's just a product launch or a sales campaign. That's way too myopic. Those companies burn a lot of cash.At the layer below the executive team, it gets harder because GTM is fundamentally a leadership-driven initiative. An SDR, AE, or director of marketing typically doesn't have the incentive—or business context—to drive GTM change. But they should get familiar with it.That's why we created the GTM Operating System certification. Hundreds of professionals have gone through it—including you! And now people are bringing those frameworks into leadership meetings.They'll say, “Hey, let's pull up the 15 GTM problems and see where we're stuck.” Or, “Let's revisit the 3 Ps—where are we today?” Or use one of the assessments. It's pretty cool to see it in action.Kerry Curran, RBMA (27:35.758)Yeah, and it's extremely valuable. I love that it's a tool that helps drive company-wide buy-in and educates the people responsible for the actions. So you've shared so many great frameworks and recommendations. For those listening, what's the first step to get started? What would you recommend to someone who's thinking, “Okay, I love all of this—I need to start shifting my organization”?Sangram Vajre (28:09.082)First, you have to really understand the definition of go-to-market. It's a transformational process—not a one-and-done. It's not something you define at an offsite and then forget. It's not owned by pirates. It's iterative. It happens every day.Second, the CEO has to be fully bought in. If they don't own it, GTM will run them. If you're a CEO and you feel overwhelmed, that's usually why—you're running go-to-market, not owning it.Third, business transformation happens in teams. If you try to build a GTM strategy in a silo—as a marketer, for example—it will fail. The best strategies never see the light of day because the team isn't behind them. In GTM, alignment matters more than being right.Kerry Curran, RBMA (29:27.982)Excellent. I love this so much. Thank you! How can people find you and learn more about the GTM Partners certification and your book?Sangram Vajre (29:37.476)You can go to gtmpartners.com to get the certification. Thousands of people are going through it, and we're constantly adding new content. We're about to launch Go-To-Market University to add even more courses.We also created the MOVE Book Companion, because we're actually selling more books now than when it first came out three years ago—which is crazy!Then there's GTM Monday, our research newsletter that 175,000 people read every week. Our goal is to keep building new frameworks and sharing what's possible. Things are changing so fast—AI, GTM tech, everything. But first principles still apply. That's why frameworks matter more than ever.You can't just ask ChatGPT to “give me a go-to-market strategy” and expect it to work. It might give you something beautifully written, but it won't help you make money. You need frameworks, team alignment, and process discipline.And I post about this every day on LinkedIn—so follow me there too!Kerry Curran, RBMA (30:54.988)Excellent. Well, thank you so much. This has been a great conversation, and I highly recommend the book and the certification to everyone. We'll include all the links in the show notes.Thank you, Sangram, for joining us today!Sangram Vajre (31:09.284)Kerry, you're a fantastic host. Thank you for having me.Kerry Curran, RBMA (31:11.854)Thank you very much.Thanks for tuning in to Revenue Boost: A Marketing Podcast. I hope today's conversation sparked some new ideas and challenged the way you think about how your organization approaches go-to-market and revenue growth strategy. If you're serious about turning marketing into a true revenue driver, this is just the beginning. We've got more insightful conversations, expert guests, and actionable strategies coming your way—so search for us in your favorite podcast directory and hit subscribe.And hey, if this episode brought you value, please share it with a colleague or leave a quick review. It helps more revenue-minded leaders like you find our show. Until next time, I'm Kerry Curran—helping you connect marketing to growth, one episode at a time. See you soon.

Today on the show we have Ziv Peled, the Chief Customer Officer of AppsFlyer.In this episode, Ziv shares his experience using AI to radically improve customer success performance.We then discussed the shift from product expertise to growth partnership and wrapped up by exploring how AI is changing internal team dynamics and go-to-market strategies.Mentioned ResourcesAppsFlyerMatik.ioChurn FM is sponsored by Vitally, the all-in-one Customer Success Platform.

Could AI take over in the next few years? Daniel Kokotajlo thinks so. Here's why.

Allison Schaaf is the creator and owner of PrepDish (longtime BLP sponsor!) and her business is based on planning, specifically around meals! But she also has plenty of wisdom to share around planning the rest of life, from long term goals to handling emails and managing a team. She is also highly interested in streamlining tasks as she is a mother of 4 (including a baby!). Shared by Allison: - Clever Fox planner - Superhuman email - Traction - Die with Zero PrepDish trial mentioned: prepdish.com/plans (two weeks free - and now with Instacart shopping links!) Episode Sponsors: PrepDish: Convenient meal plans, recipes, and shopping lists to reduce your weekly mental load! Visit prepdish.com/plans for your first 2 weeks, FREE Mint Mobile: Low-cost wireless phone service – a great way to save every single month! Learn more at mintmobile.com/BLP IXL: Tailored and effective online learning (my kids have used this for years as part of their school curriculum)! Best Laid Plans listeners can get an exclusive 20% off IXL membership when they sign up today at IXL.com/PLANS. Green Chef: The best meal kit for eating well. Visit greenchef.com/bestlaidfree and use code bestlaidfree to get started with FREE salads for 2 months plus 50% off your first box. Learn more about your ad choices. Visit megaphone.fm/adchoices

This month, The Writers' Den dives into the space-time continuum with Hugo, Nebula, and Locus award-winning science fiction author James Patrick Kelly, a master storyteller whose work explores the boundaries of imagination and reality. In this mind-expanding conversation, Kelly shares how time travel can be used as a narrative device to illuminate character, deepen plot, and challenge perceptions of truth. Joining the discussion is John Herman, NHWP's featured author and a multidisciplinary artist and educator known for creative storytelling across mediums.This episode is co-hosted by Masheri Chappelle, NHWP Trustee Chair, and Dan Pouliot, young adult fantasy author and finalist for the 2023 NH Literary Awards for his YA novel Super Human. Together, they guide a genre-defying conversation on one of fiction's most fascinating literary tools. Don't miss this powerful exploration of time travel in fiction—where the past, present, and future collide.

((ระดับความ disturb : 1 กะโหลก))  คนเราร้อยพ่อพันแม่ จะมีคนที่พิเศษในบางเรื่องกว่าชาวบ้านร้านตลาดก็คงไม่ผิดอะไร อีพีนี้ของ Untitled Case ยชธัญหยิบเอาเรื่องแปลกของคนเหนือมนุษย์มาเล่าสู่กันฟัง  เคสแรก ธัญนำเรื่องของคุณ Natasha Demkina สาวชาวรัสเซียมาเล่า เธอมีประวัติที่ค่อนข้างพิเศษ ทั้งพัฒนาการที่เกินช่วงวัยตั้งแต่สมัยเด็ก แต่เมื่อโตขึ้นกลับกลายเป็นว่าเธอเหมือนจะมีพลังในการมองทะลุ เอ็กซ์เรย์เข้าไปในร่างกายของคนอื่นได้ จนสามารถวินิจฉัยโรคตามอวัยวะภายในได้เสียอย่างนั้น นำมาซึ่งการพิสูจน์ในที่สุด เคสสอง ยชพาไปรู้จักมนุษย์กลุ่มหนึ่งที่เรียกว่า Indigo Children หรือเด็กสีคราม ที่นำเสนอแนวคิดว่ามีเด็กที่มีพลังเหนือธรรมชาติค่อยๆ วิวัฒนาการขึ้นมาในกลุ่มมนุษยชาติของเรา เด็กเหล่านี้ไม่ได้มีผิวสีน้ำเงิน แต่ผู้เสนอแนวคิดอย่าง Nancy Ann Teppe นักพลังจิต บอกว่าเธอเห็นออร่าสีครามของคนจำนวนหนึ่งขึ้นมา จนกลายเป็นทฤษฎีสมคบคิดแปลกๆ เช่นนี้ https://linktr.ee/untitledcase #SalmonPodcast #UntitledCase #ยชธัญ  —--- ติดต่อโฆษณาได้ที่ podcast.salmon@gmail.com Follow Untitled Case on Instagram Salmon Podcast https://www.instagram.com/salmon_podcast/ ยช https://www.instagram.com/yodddddddd/ ธัญ https://www.instagram.com/thann401/ มาร่วมจอยคอมมูนิตี้ลึกลับของชาว UC ได้ที่กลุ่ม Untitled Club by Untitled Case https://www.facebook.com/groups/289112405610043 Learn more about your ad choices. Visit megaphone.fm/adchoices

((ระดับความ disturb : 1 กะโหลก))  คนเราร้อยพ่อพันแม่ จะมีคนที่พิเศษในบางเรื่องกว่าชาวบ้านร้านตลาดก็คงไม่ผิดอะไร อีพีนี้ของ Untitled Case ยชธัญหยิบเอาเรื่องแปลกของคนเหนือมนุษย์มาเล่าสู่กันฟัง  เคสแรก ธัญนำเรื่องของคุณ Natasha Demkina สาวชาวรัสเซียมาเล่า เธอมีประวัติที่ค่อนข้างพิเศษ ทั้งพัฒนาการที่เกินช่วงวัยตั้งแต่สมัยเด็ก แต่เมื่อโตขึ้นกลับกลายเป็นว่าเธอเหมือนจะมีพลังในการมองทะลุ เอ็กซ์เรย์เข้าไปในร่างกายของคนอื่นได้ จนสามารถวินิจฉัยโรคตามอวัยวะภายในได้เสียอย่างนั้น นำมาซึ่งการพิสูจน์ในที่สุด เคสสอง ยชพาไปรู้จักมนุษย์กลุ่มหนึ่งที่เรียกว่า Indigo Children หรือเด็กสีคราม ที่นำเสนอแนวคิดว่ามีเด็กที่มีพลังเหนือธรรมชาติค่อยๆ วิวัฒนาการขึ้นมาในกลุ่มมนุษยชาติของเรา เด็กเหล่านี้ไม่ได้มีผิวสีน้ำเงิน แต่ผู้เสนอแนวคิดอย่าง Nancy Ann Teppe นักพลังจิต บอกว่าเธอเห็นออร่าสีครามของคนจำนวนหนึ่งขึ้นมา จนกลายเป็นทฤษฎีสมคบคิดแปลกๆ เช่นนี้ https://linktr.ee/untitledcase #SalmonPodcast #UntitledCase #ยชธัญ  —--- ติดต่อโฆษณาได้ที่ podcast.salmon@gmail.com Follow Untitled Case on Instagram Salmon Podcast https://www.instagram.com/salmon_podcast/ ยช https://www.instagram.com/yodddddddd/ ธัญ https://www.instagram.com/thann401/ มาร่วมจอยคอมมูนิตี้ลึกลับของชาว UC ได้ที่กลุ่ม Untitled Club by Untitled Case https://www.facebook.com/groups/289112405610043 Learn more about your ad choices. Visit megaphone.fm/adchoices

Rahul Vohra (Founder and CEO at Superhuman) joins SaaStock's Alex Theuma to discuss how Superhuman stayed ahead of the generative AI wave, how they're shaping the future of productivity with autonomous email agents, and why great products that delights users — not flashy marketing — are the key to viral growth. Rahul also opens up about the loneliness of being a CEO, his meditation practices, and the game design principles behind Superhuman's success. Check out the other ways SaaStock is helping SaaS founders move their business forward: 

In Episode 1 of Season 2 of The Thrive Factor podcast, I interview Cobus Visser, author, public speaker, and firewalking instructor. Cobus suffers from a life-threatening disease called hemophilia. In this episode we talk about overcoming severe odds, climbing Kilimanjaro without crutches, and building a marketing business. You cannot connect with Cobus Visser here: https://cobusvisser.com/You can connect with Rouan Kruger here: https://www.instagram.com/kmirouan                                                                          https://www.tiktok.com/@rouan.high.perfor?_t=ZM-8vlpmhC3Cnm&_r=1Support the show

“The 80/20 curve also applies to time: 1% of your time produces 50% of all your productivity.”   This is a special episode only available to our podcast subscribers, which we call The Mini Chief. These are short, sharp highlights from our fabulous CEO guests, where you get a 5 to 10 minute snapshot from their full episode. This Mini Chief episode features Perry Marshall, Author and Sales & Marketing Guru. His full episode is titled Redefining the 80/20 Rule, buying time for superhuman productivity, and solving tough problems. You can find the full audio and show notes here:

In this episode of Hey Julia Woods, Laura Perry shares how confronting hidden shame transformed her life, marriage, and business. What she once thought was ADHD turned out to be paralyzing self-judgment rooted in unmet expectations and perfectionism. Her story reveals how healing internal narratives can unlock clarity, connection, and a 10x boost in productivity._______

Welcome back to Talent Talk podcast on this episode. We give a huge shout out to the birthday boy AJ & We talk new music from Karri, Destin, Conrad, and more. Around the culture jumps into Leksi Harris new album and Chris Brown's Eras tour. Don't forget to like comment and subscribe. Thank you! Timestamps00:00 - Happy Birthday AJ08:14 - NEW MUSIC  22:05 - Rez's Vows???28:19 - Miley Cyrus New Music30:06 - Leksi Harris DEBUT Album HIATUS37:00 Breezy Bowl46:52 Superhuman or NO AIR?54:23 - Bad Bunny Tiny Desk58:27 - Dreamvillefest1:08:19 - Last thoughts/technical difficulties 

Biohacking is a multi-billion dollar industry because people are using it to feel superhuman. Biohacking helps you to look and feel younger, prevent and reverse disease, live longer, have more energy, better sex, moods, sleep and anything else you can imagine. So we've brought in the father of Biohacking to tell you all about how it works, what supplements and modern technology you can use, and to give you some simple steps you can start biohacking your body right now.   TOPICS DISCUSSED IN THIS EPISODE: What is biohackling? Biohacking your internal and external environment How to enhance your mitochondrial function and have more energy Biohacking your sleep, gut, oral health and everything else Anti aging and health span vs. life span Biohacking safely and making results last   More from Dave Asprey: Danger Coffee: Get your mold free Danger Cofee Discount with code REVERSABLE and REVERSABLEDARK for the True Dark coffee here: dangercoffee.com Get your blue light blocking glasses here: truedark.com Instagram: @dave.asprey Twitter: @daveasprey Website: daveasprey.com     Leave us a Review: https://www.reversablepod.com/review   Need help with your gut? Visit my website gutsolution.ca to join a program: Get help now   Contact us: reversablepod.com/tips    FIND ME ON SOCIAL MEDIA: Instagram  Facebook  YouTube        

Amanda Kahlow shares her story of stepping away from her company, navigating IVF and adoption, and launching her new venture, 1mind. A candid look at reinvention, leadership, and what really matters. About Guest Amanda Kahlow is a confident, brave, positive, passionate, and spiritual individual with an abundance of energy, love, empathy, and enthusiasm for life. Amanda is a serial entrepreneur. She is the founder and former CEO of 6sense. She started her first company at 21 and is now working on her next AI venture.  Amanda is an eternal optimist with a healthy dose of skepticism and curiosity, always seeking purpose and new ideas. She is dedicated to creating a different kind of Silicon Valley startup, emphasizing passion, discipline, integrity, and accountability while leading with compassion.  Amanda is focused on giving back both personally and professionally. Years ago she got clear her personal mission statement "I am a passionate positive spiritual warrior to EMPOWER women and girls." She uses her aptitude for humanistic motivational speaking to share her story every chance she can to inspire others. She is an advisor to the organization, Girl Rising. Amanda is committed to their mission to educate girls in developing countries as a way to build thriving, prosperous, healthy communities and effect positive social change. About Guest Company1mind is a platform that deploys AI-powered Superhumans for revenue teams. These Superhumans have a face, voice, and deep technical and product knowledge. They lead unlimited, simultaneous conversations, 24/7—to qualify and pitch leads on websites, join conference calls as active participants, run custom demos, provide real-time support, and work alongside your team in deal rooms. 1mind Superhumans integrate with your existing workflows, scale instantly, and help you grow revenue, reduce headcount, and drive pipeline all the way to closed won.Social Links https://www.linkedin.com/in/amandakahlow/ https://www.linkedin.com/company/1mindai/Book recommended by Amanda: The greatest salesman in the world by Og Mandino Amazon.com : the greatest salesman in the worldPodcast recommended by Amanda: Pattern Breakers with host Mike Maples Jr. https://greatness.floodgate.com/ Connect with Alice HeimanLinkedIn Profile: https://www.linkedin.com/in/aliceheiman/Alice's Website: https://aliceheiman.com/

In today's founder spotlight, we're joined by a rare breed, Adam Schwartz, who has lived the full startup cycle, not once but multiple times, and has done so on his own terms. He is a founder who went from building scrappy marketplaces to scaling a profitable, venture-free company. Adam's latest venture, Parable, has secured investment from founder-operators: the minds behind HubSpot, Ramp, Vimeo, Superhuman, Squarespace, and more.

Ryan Dilks and Justin Peach go through the weekend's action across the Championship.Sheffield United are shocked by Oxford!The falling apart continues for Leeds!Burnley go top!Troubling times at Sheffield Wednesday!It's the Second Tier.Sign up to our Patreon here!Watch this episode on YouTube here!Follow us on X, Instagram and email us secondtierpod@gmail.com.Win a FREE bottle of Jameson! To enter, nominate your Jameson Weekend Hero by sending a voicenote on WhatsApp to +44 75371 44387. We'll play our next winner on the show next week!**Please rate and review us on Apple, Spotify or wherever you get your pods. It means a lot and makes it easy for other people to find us. Thank you!** Hosted on Acast. See acast.com/privacy for more information.

If you want to fast forward to the UFO start at about 42 Minutes. The beginning of this video is about Michael Grubb's near death experience and he went to the black void during his NDE. He was also trained by Aliens to have superhuman abilities. Michael's YouTube Channelhttps://www.youtube.com/@MichaelGrubbEvolvedMinistryMichael's Websitehttps://evolved-ministry.teachable.com/CONTACT:Email: jeff@jeffmarapodcast.comTo donate crypto:Bitcoin -  bc1qk30j4n8xuusfcchyut5nef4wj3c263j4nw5wydDigibyte -  DMsrBPRJqMaVG8CdKWZtSnqRzCU7t92khEShiba -  0x0ffE1bdA5B6E3e6e5DA6490eaafB7a6E97DF7dEeDoge  -  D8ZgwmXgCBs9MX9DAxshzNDXPzkUmxEfAVEth. -   0x0ffE1bdA5B6E3e6e5DA6490eaafB7a6E97DF7dEeXRP -  rM6dp31r9HuCBDtjR4xB79U5KgnavCuwenWEBSITEwww.jeffmarapodcast.comSOCIALS:Instagram: https://www.instagram.com/jeffmarapodcast/Facebook: https://www.facebook.com/jeffmarapodcast/Twitter: https://www.twitter.com/jeffmaraP/JeffMara does not endorse any of his guests' products or services. The opinions of the guests may or may not reflect the opinions of the host.

Tracy McGrady Questions LeBron James Superhuman Health, Nick Wright Tears Russell Westbrook Down, Rob Parker Blasts Ja Morant Gun Investigation, Lakers vs Clippers Playoff Preview Download the Gametime app, create an account, and use code CLNS for $20 off your first purchase. Learn more about your ad choices. Visit megaphone.fm/adchoices

Are you optimizing your health, or just coasting on what's considered “normal”? In this episode of the Fully Alive podcast, host Zach Gurick sits down with Dr. Castel Santana—better known as Dr. Cas—to uncover the groundbreaking science behind 10X Health System. Backed by industry leaders like Grant Cardone and Dr. Gary Brecka, 10X Health is revolutionizing longevity with genetic testing, blood biomarker analysis, hormone optimization, and the Superhuman Protocol. Learn how precision functional medicine can help you combat chronic inflammation, optimize your body at the cellular level, and take control of your long-term wellness. Ready to transform your health? Let's dive in!The information presented in Fully Alive is for educational and informational purposes only and is not intended as a substitute for professional medical advice, diagnosis, or treatment. Always seek the advice of your physician or other qualified healthcare provider with any questions you may have regarding a medical condition or treatment and before making changes to your health regimen. Guests' opinions are their own and do not necessarily reflect those of the podcast host, production team, or sponsors.

Eiso Kant, CTO of poolside AI, discusses the company's approach to building frontier AI foundation models, particularly focused on software development. Their unique strategy is reinforcement learning from code execution feedback which is an important axis for scaling AI capabilities beyond just increasing model size or data volume. Kant predicts human-level AI in knowledge work could be achieved within 18-36 months, outlining poolside's vision to dramatically increase software development productivity and accessibility. SPONSOR MESSAGES:***Tufa AI Labs is a brand new research lab in Zurich started by Benjamin Crouzier focussed on o-series style reasoning and AGI. They are hiring a Chief Engineer and ML engineers. Events in Zurich. Goto https://tufalabs.ai/***Eiso Kant:https://x.com/eisokanthttps://poolside.ai/TRANSCRIPT:https://www.dropbox.com/scl/fi/szepl6taqziyqie9wgmk9/poolside.pdf?rlkey=iqar7dcwshyrpeoz0xa76k422&dl=0TOC:1. Foundation Models and AI Strategy [00:00:00] 1.1 Foundation Models and Timeline Predictions for AI Development [00:02:55] 1.2 Poolside AI's Corporate History and Strategic Vision [00:06:48] 1.3 Foundation Models vs Enterprise Customization Trade-offs2. Reinforcement Learning and Model Economics [00:15:42] 2.1 Reinforcement Learning and Code Execution Feedback Approaches [00:22:06] 2.2 Model Economics and Experimental Optimization3. Enterprise AI Implementation [00:25:20] 3.1 Poolside's Enterprise Deployment Strategy and Infrastructure [00:26:00] 3.2 Enterprise-First Business Model and Market Focus [00:27:05] 3.3 Foundation Models and AGI Development Approach [00:29:24] 3.4 DeepSeek Case Study and Infrastructure Requirements4. LLM Architecture and Performance [00:30:15] 4.1 Distributed Training and Hardware Architecture Optimization [00:33:01] 4.2 Model Scaling Strategies and Chinchilla Optimality Trade-offs [00:36:04] 4.3 Emergent Reasoning and Model Architecture Comparisons [00:43:26] 4.4 Balancing Creativity and Determinism in AI Models [00:50:01] 4.5 AI-Assisted Software Development Evolution5. AI Systems Engineering and Scalability [00:58:31] 5.1 Enterprise AI Productivity and Implementation Challenges [00:58:40] 5.2 Low-Code Solutions and Enterprise Hiring Trends [01:01:25] 5.3 Distributed Systems and Engineering Complexity [01:01:50] 5.4 GenAI Architecture and Scalability Patterns [01:01:55] 5.5 Scaling Limitations and Architectural Patterns in AI Code Generation6. AI Safety and Future Capabilities [01:06:23] 6.1 Semantic Understanding and Language Model Reasoning Approaches [01:12:42] 6.2 Model Interpretability and Safety Considerations in AI Systems [01:16:27] 6.3 AI vs Human Capabilities in Software Development [01:33:45] 6.4 Enterprise Deployment and Security ArchitectureCORE REFS (see shownotes for URLs/more refs):[00:15:45] Research demonstrating how training on model-generated content leads to distribution collapse in AI models, Ilia Shumailov et al. (Key finding on synthetic data risk)[00:20:05] Foundational paper introducing Word2Vec for computing word vector representations, Tomas Mikolov et al. (Seminal NLP technique)[00:22:15] OpenAI O3 model's breakthrough performance on ARC Prize Challenge, OpenAI (Significant AI reasoning benchmark achievement)[00:22:40] Seminal paper proposing a formal definition of intelligence as skill-acquisition efficiency, François Chollet (Influential AI definition/philosophy)[00:30:30] Technical documentation of DeepSeek's V3 model architecture and capabilities, DeepSeek AI (Details on a major new model)[00:34:30] Foundational paper establishing optimal scaling laws for LLM training, Jordan Hoffmann et al. (Key paper on LLM scaling)[00:45:45] Seminal essay arguing that scaling computation consistently trumps human-engineered solutions in AI, Richard S. Sutton (Influential "Bitter Lesson" perspective)

“Step one, write down 25 things that you really, really want to do in your life. Step two, order the list in importance to you. Step three, put a circle around the top five and cross off the bottom 20. That's how you succeed.”   In this Best of Series episode, we replay a chat we had in 2019 with Perry Marshall, Author and Sales & Marketing Guru, on Redefining the 80/20 Rule, buying time for superhuman productivity, and solving tough problems.  

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

Gaurav Misra is the co-founder and CEO of Captions, an AI-powered video creation company and one of the most successful consumer AI products in the world today. Previously he was a product leader at Snap, where he created the design engineering function and spent years helping develop features used by hundreds of millions of users worldwide. With a background in both engineering and design, Gaurav brings a unique cross-functional perspective to product development.What you'll learn:1. Why the “ship a marketable feature every week” approach helps his team stay focused and the product stay top of mind for users amid constant AI breakthroughs2. How to balance rapid shipping with maintaining quality by cutting scope rather than compromising on timelines3. The “secret roadmap” strategy that helps Captions develop breakthrough features competitors never see coming4. Why taking on strategic technical debt is essential for startups to outpace larger companies5. How Captions accidentally ignored their most successful product for 1.5 years (and why it still grew to 500K users with no updates or support)6. How Snap's unique product development approach—with designers functioning as PMs—enabled their success as the last major social network to break through7. Why AI video will transform marketing before other industries—Brought to you by:• Brex — The banking solution for startups• Paragon—Ship every SaaS integration your customers want• Coda—The all-in-one collaborative workspace—Find the transcript at: https://www.lennysnewsletter.com/p/how-to-win-in-the-ai-era-gaurav-misra—Where to find Gaurav Misra:• X: https://x.com/gmharhar• LinkedIn: https://www.linkedin.com/in/gamisra1/—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) Gaurav's background(04:47) The exciting era of AI and startups(09:30) Staying top of mind(11:26) Tips for staying focused(13:14) Shipping marketable features weekly(19:03) Managing technical debt in startups(25:31) Snap's unique product development approach(32:09) Brainstorming with AI(35:09) What Snap got right(41:06) Scaling with a small, agile team(49:33) The shift toward prototyping in product management(51:47) The product manager role(55:40) Snap's mission and product decisions(01:02:13) The future of AI-generated video(01:10:20) Leveraging AI for marketing(01:14:37) Failure corner(01:20:21) Lightning round and closing thoughts—Referenced:• Snap: https://www.snap.com/• Captions: https://www.captions.ai/• Iron Man on Disney+: https://www.disneyplus.com/movies/iron-man/6aM2a8mZATiu• J.A.R.V.I.S.: https://en.wikipedia.org/wiki/J.A.R.V.I.S.• Cursor: https://www.cursor.com/• Devin: https://devin.ai/• Eye contact: https://www.captions.ai/eye-contact• Nvidia: https://www.nvidia.com• Descript: https://www.descript.com• Evan Spiegel on LinkedIn: https://www.linkedin.com/in/evan-spiegel-8ab74034a/• TikTok: https://www.tiktok.com/• Spotlight: https://www.snapchat.com/spotlight/• Building product at Stripe: craft, metrics, and customer obsession | Jeff Weinstein (Product lead): https://www.lennysnewsletter.com/p/building-product-at-stripe-jeff-weinstein• Patrick Collison on X: https://x.com/patrickc• DeepSeek: https://www.deepseek.com/• ByteDance Goku: New video generation AI model, better than OpenAI Sora: https://medium.com/data-science-in-your-pocket/bytedance-goku-new-video-generation-ai-model-better-than-openai-sora-56c017a320a5• Will Smith eating spaghetti and other weird AI benchmarks that took off in 2024: https://techcrunch.com/2024/12/31/will-smith-eating-spaghetti-and-other-weird-ai-benchmarks-that-took-off-in-2024/• Silo on AppleTV+: https://tv.apple.com/us/show/silo/umc.cmc.3yksgc857px0k0rqe5zd4jice• Severance on AppleTV+: https://tv.apple.com/us/show/severance/umc.cmc.1srk2goyh2q2zdxcx605w8vtx• Linear: https://linear.app/• Superhuman: https://superhuman.com/• Notion: https://www.notion.com• Perplexity: https://www.perplexity.ai/• OmniHuman-1 AI Video Generation Looks Too Real: https://www.youtube.com/watch?v=fY0KB516m-E—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

In this episode, Savannah talks to Julie about the intersectionality of a crossdresser's understanding of their feminine Identity against a cosplayer's feminine presentation of a known character meant as a homage to that character. This dynamic duo gear up, set batteries to power, turbines to speed, and discuss the similarities and differences between embodying one's own inherent femininity and embodying the femininity of a beloved and admired character.-----SAVANNAH HAUK is the author of “Living with Crossdressing: Defining a New Normal” and “Living with Crossdressing: Discovering your True Identity“. While both focus on the male-to-female (mtf) crossdresser, “Defining a New Normal” delves into crossdressing and relationships and “Discovering Your True Identity” looks at the individual crossdressing journey. Her latest achievements are two TEDx Talks, one entitled "Demystifying the Crossdressing Experience" and the other "13 Milliseconds: First Impressions of Gender Expression". Savannah is a male-to-female dual-gender crossdresser who is visible in the Upstate of South Carolina, active in local groups and advocating as a public speaker at LGBTQ+ conferences and workshops across the United States. At the moment, Savannah is working on more books, blogs, and projects focused on letting every crossdresser–young and mature–find their own confidence, expression, identity and voice.IG @savannahhauk | FB @savannahhauk | FB @livingwithcrossdressing | web @livingwithcrossdressing.com------JULIE RUBENSTEIN is a dedicated ally to transgender community and the certified image consultant and co-owner of Fox and Hanger. F&H is a unique service for transgender women and male-to-female crossdressers that creates customized virtual fashion and style “lookbooks”. Julie intuitively connects with each client to find them appropriate clothes, makeup, hair, and shape wear all in alignment with their budget, body type, authentic style and unique personality. Julie also provides enfemme coaching and wardrobe support. Julie has made it her life's work to help MTF individuals feel safe and confident when it comes to their female persona, expression and identity.IG @Juliemtfstyle | FB @foxandhanger | web @FoxandHanger.com

Rahul Vohra is the founder and CEO of Superhuman. Prior to Superhuman, Rahul founded Rapportive, the first Gmail plug-in to scale to millions of users, which he sold to LinkedIn in 2012. He is also a prominent angel investor, and his fund has invested $50 million in over 120 companies, including Placer, Supabase, Mercury, Zip, ClassDojo, and Writer.What you'll learn:• The unexpected insight about virality Rahul gained from LinkedIn's head of growth.• Why Rahul restructured his entire executive team to spend 60% to 70% of his time on product, design, and marketing instead of the typical CEO responsibilities.• The counterintuitive approach to finding product-market fit using a methodical system inspired by Sean Ellis, and how this algorithmically determines your roadmap.• How manually onboarding every user (Superhuman had 20 full-time people doing this at peak) created superfans and allowed engineers to focus on product rather than onboarding flows.• The “Single Decisive Reason” framework for making better decisions by avoiding collections of weak justifications.• How Superhuman's AI features have evolved to create a truly intelligent email experience that works while you sleep.—Brought to you by:• Eppo—Run reliable, impactful experiments• Fundrise Flagship Fund—Invest in $1.1 billion of real estate• OneSchema—Import CSV data 10x faster—Find the transcript at: https://www.lennysnewsletter.com/p/superhumans-secret-to-success-rahul-vohra—Where to find Rahul Vohra:• X: https://x.com/rahulvohra• LinkedIn: https://www.linkedin.com/in/rahulvohra/• Email: Rahul@superhuman.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 Rahul and Superhuman(05:00) The most pivotal moment in Rahul's career(07:01) The secret to virality(11:02) Superhuman's product evolution and core values(13:32) Overcoming slowdowns at scale(18:06) Time management and meditation(27:35) The role of a president(30:56) Attention to detail(43:00) Finding your unique position(47:32) The power of manual onboarding(52:37) Mastering product-market fit(59:33) Game design in business software(01:05:35) Contrarian pricing strategies(01:09:29) Leveraging AI(01:15:40) Transitioning to enterprise solutions(01:19:08) The Single Decisive Reason framework(01:22:32) Conclusion and final thoughts—Referenced:• Superhuman: https://superhuman.com/• Rapportive: https://techcrunch.com/2012/02/22/rapportive-linkedin-acquisition/• Elliot Shmukler on LinkedIn: https://www.linkedin.com/in/eshmu/• What Are ‘Whales' in Video Games: https://gamerant.com/video-games-whales-concept-term-explained/• Figma: https://www.figma.com/• Notion: https://www.notion.com/• Loom: https://www.loom.com/• How to use Team Comments to reimagine email collaboration: https://blog.superhuman.com/how-to-use-team-comments-to-reimagine-email-collaboration/• Rajiv Ayyangar's post on X about Superhuman: https://x.com/rajivayyangar/status/1816176308130570385• Transcendental Meditation: https://www.tm.org/• Laurent Valosek on LinkedIn: https://www.linkedin.com/in/laurent-valosek-18708b5a/• Peak Leadership Institute: https://www.peakleadershipinstitute.com/• Ed Sim's website: https://edsim.net/• Adelle Sans: https://fonts.adobe.com/fonts/adelle-sans• Comic Sans: https://en.wikipedia.org/wiki/Comic_Sans• Greenfield project: https://en.wikipedia.org/wiki/Greenfield_project• Why Mailbox died: https://www.theverge.com/2015/12/8/9873268/why-dropbox-mailbox-shutdown• Bill Trenchard on X: https://x.com/btrenchard• How Superhuman Built an Engine to Find Product-Market Fit: https://review.firstround.com/how-superhuman-built-an-engine-to-find-product-market-fit/• Using the Sean Ellis Test for Measuring Your Product-Market Fit: https://medium.productcoalition.com/using-sean-ellis-test-for-measuring-your-product-market-fit-c8ac98053c2c• Sean Ellis on LinkedIn: https://www.linkedin.com/in/seanellis/• The original growth hacker reveals his secrets | Sean Ellis (author of “Hacking Growth”): https://www.lennysnewsletter.com/p/the-original-growth-hacker-sean-ellis• The Trouble with Rewards: https://www.kornferry.com/insights/briefings-magazine/issue-13/519-the-trouble-with-rewards• The art and science of pricing | Madhavan Ramanujam (Monetizing Innovation, Simon-Kucher): https://www.lennysnewsletter.com/p/the-art-and-science-of-pricing-madhavan•  Van Westendorp Price Sensitivity Meter: https://en.wikipedia.org/wiki/Van_Westendorp%27s_Price_Sensitivity_Meter• AI-powered email for high-performing teams: https://superhuman.com/ai• Linear's secret to building beloved B2B products | Nan Yu (Head of Product): https://www.lennysnewsletter.com/p/linears-secret-to-building-beloved-b2b-products-nan-yu• Single Decisive Reason: decision-making for fast-scaling startups: https://blog.superhuman.com/single-decisive-reason-decision-making-for-fast-scaling-startups/• Reid Hoffman on LinkedIn: https://www.linkedin.com/in/reidhoffman/—Recommended books:• Positioning: The Battle for Your Mind: https://www.amazon.com/Positioning-Battle-Your-Al-Ries/dp/0071373586• Monetizing Innovation: How Smart Companies Design the Product Around the Price: https://www.amazon.com/Monetizing-Innovation-Companies-Design-Product/dp/1119240867—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

At the start of every month, host Aaron Millar and producer Jason Paton preview what's coming up on Armchair Explorer, play their favorite clips, and reveal the stories they're most excited to share. A cross between a highlight reel, an interview, and two people telling travel tales down the pub, our Pathways episodes are your guide to choosing your adventures with us. MARCH EPISODES ADVENTURE: No Guidebook, No Google, No Clue: Togo, Wallis and Kyrgyzstan with Best-Selling Travel Author Brian Thacker We follow best-selling travel author Brian Thacker on a unique, mad-cap adventure to three of the remotest countries on Earth: Togo, East Africa; Wallis & Futuna, in the South Pacific; and the Central Asian mountains of Kyrgyzstan. Inspired by the intrepid spirit of explorers of old, Brian decided to tear up the guidebook, throw away the phone and turn up to a country knowing absolutely nothing about it in advance.  IMMERSION: Homecoming: Chief Joseph's Promise and the Flight of the Nez Perce We go on location to the traditional lands of the Nez Perce, in eastern Oregon, to uncover a piece of history unknown to most outsiders. In the late 19th century, the Wallowa Band of the Nez Perce tribe were driven from their homeland. 200 warriors, protecting hundreds more women and children, fought for five days against 520 US soldiers. Their leader, before surrendering, promised his people that one day they would come home. After nearly 200 years, his promise may just be starting to come true. BUCKET LIST: Whale Watching in Victoria, B.C. We go to the southern tip of Vancouver Island, in British Columbia, Canada for a bucket list adventure spotting humpback and orca whales. Victoria is one of the best places in North America for whale watching and Nik Coutino, a local guide and expert, shares his best experiences, all set to immersive music and sound design. ADVENTURE: Becoming Forrest with Ultra Runner Rob Pope 15,600 miles, 422 days, and 2 boxes of chocolates, Rob Pope tells the story of his epic journey retracing the exact run that Forrest Gump did in the movie. It's a really fun story, Rob is a hilarious guy, but it's also incredibly inspiring. Before she passed away Rob's mum told him to do one thing in his life that truly makes a difference, and boy did he do it.  Rob is also the host of the Red Bull podcast How to be Superhuman – we shared the first episode of their 3rd series last month. If you missed it, check it out. It's awesome. *** If you enjoy the show, please subscribe on whatever podcast player you're reading this on right now. Go on, do it. It means you get to choose what episodes you listen to, rather than the algorithm guess (wrongly) and kick us off your feed.  Following the show on socials will definitely maybe bring you good travel karma! Facebook: @armchairexplorerpodcast Instagram: @armchairexplorerpodcast  Armchair Explorer is produced by Armchair Productions. Aaron Millar and Jason Paton presented the show, Charles Tyrie did the audio editing and sound design. Our theme music is by the artist Sweet Chap. Learn more about your ad choices. Visit megaphone.fm/adchoices

For decades, we've been told that our DNA is a fixed blueprint—an unchangeable code that dictates our health and lifespan. But what if that's only half the story? Sharon Hausman-Cohen, a physician, researcher, and genomics expert at IntellxxDNA, joins Dave to reveal the cutting-edge science of genetic optimization—how understanding your DNA can unlock longer life, better brain function, and even protection from chronic disease. Forget the old-school genetic reports that left you with useless percentages. The new frontier of precision genomics goes beyond risk factors to actionable insights, showing you exactly how to turn on your body's most powerful longevity genes and turn off the pathways driving inflammation, cognitive decline, and disease. What You'll Learn in This Episode: • Why genetics alone don't determine your future—and how to use epigenetics to control your health • The truth about MTHFR, APOE4, and other “bad” genes—are they actually harming you? • How genetic reports can predict and eliminate brain fog, fatigue, and pain • The hidden genetic reasons behind ADHD, depression, and anxiety—and how to fix them • Why some people age faster—and the one longevity gene that determines your biological age • Cutting-edge breakthroughs in DNA-based biohacking—is it possible to edit your genes for peak performance? This is the future of personalized medicine. By understanding your own genetic blueprint, you can stop guessing and start making the precise changes that will optimize your energy, brainpower, and lifespan! ** Visit IntellxxDNA at https://intellxxdna.com/asprey/ When you go to the website to find a clinician please select “human upgrade/longevity” as the type of consult to get specialized biohacking clinicians! ** SPONSORS -Timeline | Head to https://www.timeline.com/dave to get 10% off your first order. -Leela Quantum Tech | Head to https://leelaq.com/DAVE for 10% off. Resources: • Dave Asprey's New Book - Heavily Meditated: https://daveasprey.com/heavily-meditated/ • IntellxxDNA Website: https://intellxxdna.com/asprey/ • 2025 Biohacking Conference: https://biohackingconference.com/2025 • Danger Coffee: https://dangercoffee.com • Dave Asprey's Website: https://daveasprey.com • Dave Asprey's Linktree: https://linktr.ee/daveasprey • Upgrade Collective – Join The Human Upgrade Podcast Live: https://www.ourupgradecollective.com • Own an Upgrade Labs: https://ownanupgradelabs.com • Upgrade Labs: https://upgradelabs.com • 40 Years of Zen – Neurofeedback Training for Advanced Cognitive Enhancement: https://40yearsofzen.com Timestamps: • 00:00 – Intro • 02:00 – The Role of Genetics in Longevity • 03:37 – Gene Variants & Cognitive Health • 05:58 – Epigenetics vs. Genetics • 08:21 – Genomics & Pain Management • 09:26 – Breakthroughs in Genetic Research • 12:33 – The Future of Genomic Medicine • 14:27 – How to Use Genomic Reports • 38:25 – Mitochondria & Longevity • 42:40 – BH4 & Mental Health • 43:42 – Folinic Acid & Brain Function • 44:37 – Genomics & Autism • 46:06 – Personalized Medicine • 56:00 – APOE4 & Alzheimer's Risk • 59:44 – Genetics & Heart Health • 01:04:54 – The Future of Precision Medicine • 01:20:23 – Conclusion & Next Steps See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

This Week in Startups is brought to you by…Lemon.io. Get 15% off your first 4 weeks of developer time at https://Lemon.io/twistNorthwest Registered Agent. Get more privacy, more options, and more done—visit northwestregisteredagent.com/twist today!Vapi. Go to Vapi.ai and use code Twist200 to get $200 in creditsToday's show: Jason interviews Rahul Vohra, CEO and founder of Superhuman, and Vlad Tenev, CEO and co-founder of Robinhood. This is a packed episode featuring founder tips, fun stories about how Superhuman and Robinhood got their start and much more!Timestamps:(0:00) Episode teaser(2:13) Product market fit and founder journeys(3:25) Jason's investment in Superhuman and market positioning(5:14) AI's role and features in Superhuman(10:25) Lemon.io. Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist(14:37) Targeting users and competitive advantages(22:23) Evolution and new features of Superhuman(20:52) Northwest Registered Agent. Get more privacy, more options, and more done—visit northwestregisteredagent.com/twist today!(24:37) Tackling spam with Superhuman's AI(27:05) Custom auto labels and email classification(29:47) Vapi. Go to Vapi.ai and use code Twist200 to get $200 in credits(32:03) Superhuman's auto reminders and drafts(34:14) Vlad Tenev and the origins of Robinhood(39:31) Product design philosophies of Robinhood and Superhuman(49:29) Scaling design principles and investment decisions(52:31) Subjectivity in product design(55:14) Customer feedback in product development(1:00:00) Superhuman's subscription model and customer acquisition(1:05:11) PR strategies and news hijacking(1:08:33) Robinhood's waitlist and viral moments(1:12:06) Investment experiences with Robinhood(1:13:35) Navigating company valuation fluctuations(1:15:03) Influences on Vlad Tenev and new Robinhood desktop product(1:20:11) Diversification of Robinhood's business(1:22:02) Company resilience and employee reorganization(1:25:52) Crypto regulation and startup mentality(1:30:05) Investment trends among Robinhood users(1:31:12) Retail benefits for startups and capital raising challenges(1:34:04) Accreditation for private investing and solutionsSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpLinks from this episode:Check out Superhuman: https://superhuman.com/Check out Robinhood Legends: https://robinhood.com/us/en/legend/Article “How Superhuman Built an Engine to Find Product Market Fit**”:** https://review.firstround.com/how-superhuman-built-an-engine-to-find-product-market-fit/Check out Rick Rubin's book: https://www.amazon.ca/Creative-Act-Way-Being/dp/0593652886Article on Bezos and Washington Post: https://www.newsweek.com/bezos-makes-big-change-washington-post-opinion-focus-endorsed-musk-2036618Media Bias Chart: https://www.allsides.com/media-bias/media-bias-chartCheck out “Working Backwards” book about Amazon insights: https://www.amazon.ca/Working-Backwards-Insights-Stories-Secrets/dp/1250267595Check out Rahul's article on acquisition: https://www.linkedin.com/pulse/rip-mailbox-founders-how-stop-worrying-love-being-acquired-vohra/Follow Rahul:X: https://x.com/rahulvohraLinkedIn: https://www.linkedin.com/in/rahulvohra/Follow Vlad:X: https://x.com/vladtenevLinkedIn: https://www.linkedin.com/in/vlad-tenev-7037591b/Follow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:(10:25) Lemon.io. Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist(20:52) Northwest Registered Agent. Get more privacy, more options, and more done—visit northwestregisteredagent.com/twist today!(29:47) Vapi. Go to Vapi.ai and use code Twist200 to get $200 in credits

This Week in Startups is brought to you by…Gusto. Get three months free when you run your first payroll at http://gusto.com/twistLemon.io. Get 15% off your first 4 weeks of developer time at https://Lemon.io/twistAtlassian. Head to https://www.atlassian.com/software/startups to see if you qualify for 50 free seats for 12 months.Today's show: Jason and Lon Harris cover Nikola's Chapter 11 and how founders can avoid the same mistake, Superhuman AI's new features, Mira Murati's Thinking Machines and where Sam Altman went wrong holding onto top talent, plus much more!Timestamps:(0:00) Episode teaser(1:26) Introduction to startup news and trends(2:47) Bill Ackman's J trade and Herbalife controversy(5:24) Comparing trading strategies: Jason vs. Pelosi(9:49) Gusto. Get three months free when you run your first payroll at http://gusto.com/twist(11:29) HP's acquisition of Humane and its significance(13:52) Challenges facing the AI industry(20:30) Lemon.io. Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist(21:47) OpenAI veterans launch a new venture(28:09) Chamath's venture into high stakes poker(29:35) Atlassian. Head to https://www.atlassian.com/software/startups to see if you qualify for 50 free seats for 12 months.(36:37) Nikola's Chapter 11 filing and securities fraud(48:10) The upside of failing as a founder in the U.S.(50:24) Superhuman introduces AI-powered email features(51:58) Preview of upcoming guests on the podcast(53:03) Key characteristics of successful founders(56:21) Play-along: Guess the fake startup(1:04:12) Movie trilogy rankings: Superman, Star Wars, TerminatorSubscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.comCheck out the TWIST500: https://www.twist500.comSubscribe to This Week in Startups on Apple: https://rb.gy/v19fcpCheck out these past Guess The Fake Startups segments:https://www.youtube.com/watch?v=iKP2iiF1oYIhttps://www.youtube.com/watch?v=rhnOXuGnh14https://www.youtube.com/watch?v=ueazpyGOgccFollow Lon:X: https://x.com/alexFollow Jason:X: https://twitter.com/JasonLinkedIn: https://www.linkedin.com/in/jasoncalacanisThank you to our partners:(9:49) Gusto. Get three months free when you run your first payroll at http://gusto.com/twist(20:30) Lemon.io. Get 15% off your first 4 weeks of developer time at https://Lemon.io/twist(29:35) Atlassian. Head to https://www.atlassian.com/software/startups to see if you qualify for 50 free seats for 12 months.Great TWIST interviews: Will Guidara,Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta,Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarlandCheck out Jason's suite of newsletters: https://substack.com/@calacanisFollow TWiST:Twitter: https://twitter.com/TWiStartupsYouTube: https://www.youtube.com/thisweekinInstagram: https://www.instagram.com/thisweekinstartupsTikTok: https://www.tiktok.com/@thisweekinstartupsSubstack: https://twistartups.substack.comSubscribe to the Founder University Podcast: https://www.youtube.com/@founderuniversity1916

Palmer Luckey is an entrepreneur and innovator best known for founding Oculus VR and Anduril Industries. In 2012, he launched Oculus VR and developed the Oculus Rift, a groundbreaking virtual reality headset that redefined a wide array of industries. The company was acquired by Facebook in 2014 for $2 billion, where Luckey subsequently worked until 2017. Following his departure, he founded Anduril Industries - a defense technology company specializing in autonomous systems including drones, surveillance towers, and aircraft. Anduril has secured major contracts with the U.S. Department of Defense and international allies. The company has raised significant funding, including $1.5 billion in 2022, valuing it at $8.5 billion. Shawn Ryan Show Sponsors: http://armra.com/srs http://helixsleep.com/srs http://patriotmobile.com/srs http://hexclad.com/srs http://ziprecruiter.com/srs https://ROKA.com | Use Code SRS Palmer Luckey Links: Anduril Industries - https://www.anduril.com/ ModRetro - http://modretro.com/ X - https://x.com/PalmerLuckey/ Please leave us a review on Apple & Spotify Podcasts. Vigilance Elite/Shawn Ryan Links: Website | Patreon | TikTok | Instagram | Download Learn more about your ad choices. Visit podcastchoices.com/adchoices