Podcasts about Figma

Live recording of the fortnightly podcast Design Systems WTF (back for season two!), where Luke Murphy and Michelle Chin attempt to combat all the amazing wtf in design systems. In each episode, they answer a single question around design system troubles with a Q&A from the live audience.Governance seems to be one of those fancy words that gets thrown around a lot by design system people - but what level of governance is actually worthwhile, and how much of it is theater? Michelle and Luke will dive into governance, what level is good enough, and what bits they think you should scrap.Show notesBrad Frost's governance flowchart — the component approval flow Michelle borrowed and adapted: A Design System Governance Process. Also available as a Figma community file, and his lighter-touch follow-up: Master design system governance with this one weird trickNathan Curtis on governance and contribution — his writing on contribution models referenced in the episode: Contributions to Design Systems and Team Models for Scaling a Design SystemManaging Chaos: Digital Governance by Design by Lisa Welchman — Michelle's book recommendation for adding process in a way that isn't "gross", with a historical look at how web governance emerged: Rosenfeld MediaOrg Design for Design Orgs by Peter Merholz & Kristin Skinner — Luke's companion-piece recommendation on ritual and process for design teams, transferable to design systems: petermerholz.com / O'ReillyBig Vape: The Rise and Fall of Juul — the Netflix documentary on Juul and "how not to do a startup": Netflix

After an unexpected layoff, Eric Posen went from day-one outreach to three offers and a director role at Super.com in six weeks.In this episode, Eric breaks down the search in detail: how he mobilized his network, why he thinks cold applications are dead in this market, what made a referral effective, and the Claude tools he built to track roles and tailor his résumé.The biggest surprise came across seven interview processes: not one interviewer asked how he used AI. Eric, Marc, and Ben unpack why, along with take-home assignments, taste, negotiating scope and level, and choosing between three offers.This episode will be useful if you're searching for a role, preparing for interviews, or rebuilding your hiring process for the AI era.All episodes of the podcast are also available on Spotify, Apple and YouTube.New to the pod? Subscribe below to get the next episode in your inbox

Marc Ferrentino, Co-Founder and CEO of Quotient and former chief technical architect at Salesforce, joins Sam Jacobs and Asad Zaman to separate AI-marketing hype from what actually works today. Marc's core claim: the 'AI CMO' is marketing fiction, and the real near-term unlock is clearing the roughly 70% of a marketer's day lost to busywork, so smaller teams can finally operate like big ones. Topics include the collapse of specialized marketing roles into cross-functional generalists, why the apprenticeship model that trained classic marketers is most at risk, where the durable edge moves as performance marketing gets automated... and how taste separates real work from AI slop. Plus, a Quiz Pro Quo trivia round on famous tech emails, an honest look at ageism facing marketers in their 40s and 50s, and a Bulls and Bears debate on legacy martech, HubSpot, and Figma. Key Takeaways: - Marc's near-term promise to marketers is not an AI CMO but the removal of busywork. As he puts it: "companies that come out and claim to be your AI CMO… I think that is the most misleading marketing, but it's also just not true." Buckle up for a story or two about how he's seen the "AI CMO" blow up in people's faces. - The hiring bar is shifting from raw craft to AI fluency. In Marc's words: "we're all looking for the 10x developer, but the 10x developer who knows how to use AI is a 100x developer. And so it's the same thing with the marketer… the marketer who knows how to use AI is a 100x marketer… That's the person we want on the team." And he shares how his own developer interviews changed to match. - Marketing roles are not disappearing, but the specialist ladder that trained seasoned marketers is eroding. As Sam Jacobs, CEO of Pavilion, put it: "I see the collapse of specialization within a particular function. That doesn't diminish the need for the function, but does create an opportunity for those that are more fluent in all of these cross-functional tools." His deeper worry is the pipeline: "the apprenticeship model is the thing that's most at risk," raising the prospect of "a lack of classically trained marketers." - Ageism is real in marketing hiring, and it often hides inside neutral-sounding language. Asad Zaman, CEO of STA, observed, clients are saying things like: "I'm looking for somebody with high energy. High energy is like, I need somebody who is 30 to 33… high energy is like an age, basically." To what extent do the hosts agree with this perspective? Only one way to find out... Connect with the Hosts & Guests: Host: Sam Jacobs, CEO at Pavilion - https://www.linkedin.com/in/samfjacobs/ Host: Asad Zaman, CEO at STA - https://www.linkedin.com/in/azaman1/ Guest: Marc Ferrentino, Co-Founder & CEO at Quotient - https://www.linkedin.com/in/marcferrentino/ Topline is more than a YouTube Channel: Subscribe to Topline Newsletter: https://toplinemedia.substack.com/ Tune into Topline Podcast, the #1 podcast for founders, operators, and investors in B2B tech: https://www.joinpavilion.com/topline-podcast Join the free Topline Slack channel to connect with 600+ revenue leaders to keep the conversation going beyond the podcast: https://www.joinpavilion.com/topline-slack Chapters:  00:00 Introducing Marc Ferrentino 02:09 Where AI Actually Works Today 04:05 The 'AI CMO' Is a Lie 07:10 AI Multiplies, Not Replaces 12:11 The Collapse of Specialization 15:10 The Apprenticeship Model at Risk 16:11 The Real Edge Is Brand 21:18 AI Slop and the Taste Problem 23:02 Marketing for the Rest of Business 35:15 Are the Models Asymptoting? 39:01 Quiz Pro Quo 44:44 Ageism in Marketing 49:18 Curiosity over Age 58:34 The 100x Marketer 1:03:54 Bulls VS Bears

AI is making creative production faster while increasing the value of human craft, imperfection, and hands-on creative control.Drew and Rory start with Netflix's 300 AI-assisted programs and somehow end up defending Blockbuster, boxy cars, greasy roommates, and the radical act of making creative work harder on purpose. Between the usual intellectual potholes, they uncover why invisible AI succeeds, why perfect outputs are becoming exhausting, and why human-made work may become the premium signal.Covered in this episode:Netflix generative AI workflows span concept development, pre-visualization, visual effects, post-production, and release. Suno, Udio, Strudel, Foley artistry, AI music licensing, Runway visual storytelling, Claude, ChatGPT, Figma shaders, Photoshop retouching, creative consistency, nostalgic design, imperfect aesthetics, and hybrid human-AI production define the broader creative shift.---⏱️ Fast Hour00:00 Why are guests returning to Fast Hours?03:45 Why does summer trigger nostalgia?10:49 How is Netflix using generative AI?20:39 Could Blockbuster have become Netflix?24:04 What AI tools has Netflix open-sourced?28:36 What did the Suno breach reveal?32:21 Should AI be used to make music?43:31 Breaking down Runway's lamp film—hy does it work?51:43 How many movie story arcs exist?53:32 Does AI increase the value of human craft?57:53 Why are creators rejecting AI perfection?01:06:16 Why is nostalgic design returning?01:17:09 Why do simple stories feel better?01:23:09 How do AI projects maintain consistency?01:25:43 Who should Fast Hours interview next?#GenerativeAI #AIFilmmaking #AIMusic #CreativeProcess #FastHours

Jeremy catches up with friend of the show, Chris Nguyen, who's rebuilt his business twice since his last appearance. They talk about why designers can't count on job security the way they used to, what it actually takes to build something of your own, and why the perfect plan is a myth worth abandoning early.If you can't count on your job to protect you, what are you doing to protect yourself?Chris Nguyen has already rebuilt his business once since he last joined the show, and by the time this episode airs, he'll be in the middle of doing it again. He built UX Playbook into a recognized education brand, tried a community project called Backlog that fizzled out, took several months off to recover, and landed on Rectangles: a live-stream and newsletter brand built around the design conversations he wishes he'd had years ago. None of it happened on a straight line, and that's kind of the point.Jeremy and Chris talk candidly about why designers can't afford to treat a single employer as their whole safety net anymore. Jeremy's own team recently made a drastic tooling change that upended how designers on his team work day to day, and he connects that disruption directly to a bigger argument: if the ground can shift under you that fast, having something outside your job, whether it's a side project, a creative outlet, or a small business, isn't optional anymore. It's how you stay steady.The conversation keeps circling back to a simple, unglamorous truth: nobody has the plan figured out in advance. Chris talks about sitting on the Rectangles idea for the better part of a year before finally committing to a two-week sprint to get it out the door, and admits he still doesn't fully know what it'll become. Jeremy pushes on that idea with his own reflections on burnout, reinvention, and why doing something just for yourself, outside of work entirely, might be the most stabilizing thing a designer can do right now. Give this one a listen if you've been sitting on an idea and waiting for the right moment.Topics:• 03:16 – Catching up on 100 episodes and the never-ending edit grind• 05:33 – What Chris has been building since his last appearance• 06:20 – The funk, the time off, and the shift from product to media• 09:37 – Why running a media company means the content is the product• 11:36 – Chris breaks down what Rectangles actually is• 14:04 – Going beyond UX and UI into big D design• 15:26 – The early 90s aesthetic behind the Rectangles brand• 20:10 – Why Jeremy's team just walked away from their Figma license• 22:42 – Designing straight into Cursor with a component library• 29:20 – The case for building income outside a single job• 32:36 – How UX education content has changed as the industry shifts• 34:22 – The unglamorous side of building something online• 52:56 – Why a latte art post outperformed a bias breakdown on LinkedIn• 57:03 – Chris's closing advice on ideas versus execution• 58:23 – Consumption versus creation and why the balance matters• 58:43 – Where to find Chris and the Rectangles launch detailsHelpful Links:• Connect with Chris on LinkedIn• Subscribe to Rectangles• Get your UX Playbook—Thanks for listening! We hope you dug today's episode. If you liked what you heard, be sure to like and subscribe wherever you listen to podcasts! And if you really enjoyed today's episode, why don't you leave a five-star review? Or tell some friends! It will help us out a ton.If you haven't already, sign up for our email list. We won't spam you. Pinky swear.• ⁠⁠⁠⁠⁠⁠Get a FREE audiobook AND support the show⁠⁠⁠⁠⁠⁠• ⁠⁠⁠⁠⁠⁠Support the show on Patreon⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠• ⁠⁠⁠⁠⁠⁠Check out show transcripts⁠⁠⁠⁠⁠⁠• ⁠⁠⁠⁠⁠⁠Check out our website⁠⁠⁠⁠⁠⁠• ⁠⁠⁠⁠⁠⁠Subscribe on Apple Podcasts⁠⁠⁠⁠⁠⁠• ⁠⁠⁠⁠⁠⁠Subscribe on Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠• ⁠⁠⁠⁠⁠⁠Subscribe on YouTube⁠⁠⁠⁠⁠⁠• ⁠⁠⁠⁠⁠⁠Subscribe on Stitcher⁠

Tech workers can be rigorous at work and surprisingly loose with their own money. After more than 200 coaching sessions, Vaibhav Goel keeps seeing the same patterns: too much wealth tied up in one company's stock, excess cash sitting idle, missed tax-advantaged accounts, and generic advice that does not fit high earners.In this episode, Marc Baselga and Ben Erez sit down with Vaibhav Goel, a former product leader at DoorDash, Google, Lyft, LinkedIn, and Microsoft who now coaches tech professionals on their finances. They unpack what changes at different net-worth levels, how to think about 529s and concentrated equity, why traditional advisor models can miss this group, and what a more practical financial plan can look like.They explore the most common money mistakes he sees, how priorities shift at different net-worth levels, plain-English breakdowns of things like 529 accounts and long-short investing, why traditional advisor incentives leave a lot of tech workers underserved, and how to think about diversifying a portfolio that has become dangerously concentrated in one stock.If you're a tech worker who optimizes everything at work but defaults on your own finances, someone sitting on concentrated company stock and unsure what to do next, or anyone curious how the newly wealthy actually handle sudden money, this episode is for you.This conversation is for education only and is not personal financial, investment, or tax advice.All episodes of the podcast are also available on Spotify, Apple and YouTube.New to the pod? Subscribe below to get the next episode in your inbox

Noam Segal is a longtime research leader across Airbnb, Meta, Twitter, Zapier, Intercom, and Figma, a certified coach, AI builder, and my community research lead. Together, we run the annual Tech Worker Sentiment Survey, now in its second year and one of the largest of its kind: a quantitative study of how people in tech actually feel about their jobs, AI, burnout, and the future of their careers. This year's survey captured responses from thousands of workers across product, engineering, design, research, marketing, data, and sales, and the results are striking.In our in-depth conversation, we discuss:1. Why AI has split the tech workforce almost exactly in half—one half that's thriving, another that's shaken2. The four emotional archetypes defining tech workers right now (the Energized, the Conflicted, the Disoriented, and the Resentful)3. Why burnout has jumped an alarming 11 points in a single year4. Why nobody in tech would recommend their job to someone entering the industry today5. The #1 fear in tech right now (it's not job loss to AI)6. Why managers are the single biggest lever for employee well-being7. Concrete advice for what employees and leaders can do right now—Brought to you by:WorkOS—Make your app enterprise-ready, with SSO, SCIM, RBAC, and more: https://workos.com/lennyMercury—Radically different banking, now with Command: https://mercury.com/command?utm_source=lennys&utm_medium=sponsored_newsletter&utm_campaign=26q3_brand_campaign—Episode transcript: https://www.lennysnewsletter.com/p/how-tech-workers-actually-feel-about—Archive of all Lenny's Podcast transcripts: https://www.dropbox.com/scl/fo/yxi4s2w998p1gvtpu4193/AMdNPR8AOw0lMklwtnC0TrQ?rlkey=j06x0nipoti519e0xgm23zsn9&st=ahz0fj11&dl=0—Where to find Noam Segal:• X: https://x.com/noamseg• LinkedIn: https://www.linkedin.com/in/noamsegal—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 Noam Segal(02:34) About the survey: methodology and scope(06:04) The core finding: AI has split the tech workforce in half(13:03) The AI identity stance(14:40) The four archetypes: Energized, Conflicted, Disoriented, Resentful(19:35) Burnout is surging (and why shipping faster is making it worse)(22:53) A glimmer of hope(24:55) Layoff worries(29:15) The career recommendation NPS score(36:45) The ladder metaphor: rungs disappearing beneath our feet(45:14) AI is making us faster, not better(52:53) The #1 fear: being squeezed to do more for the same pay(55:55) The emotional landscape and “smiling exhaustion”(01:01:02) Designers and researchers: the most negative group two years running(01:06:27) Who's happiest(01:12:18) Managers: the single biggest lever on well-being(01:18:47) The industry is “chaotic”(01:24:53) What employees and leaders can do right now(01:31:32) AI guilt and closing thoughts—Referenced:• How tech workers are feeling in 2026: a workforce splitting in two: https://www.lennysnewsletter.com/p/how-tech-workers-are-feeling-in-2026• How tech's most resilient workers handle burnout: https://www.lennysnewsletter.com/p/how-techs-most-resilient-workers• Please stop the AI Confidence Theater: https://www.elenaverna.com/p/please-stop-the-ai-confidence-theater• Velocity over everything: How Ramp became the fastest-growing SaaS startup of all time | Geoff Charles (VP of Product): https://www.lennysnewsletter.com/p/velocity-over-everything-how-ramp• NPS Is The Worst: https://www.npsistheworst.com• The Terminator: https://www.imdb.com/title/tt0088247• Skynet: https://terminator.fandom.com/wiki/Skynet• Inside Devin: The world's first autonomous AI engineer that's set to write 50% of its company's code by end of year | Scott Wu (CEO and co-founder of Cognition): https://www.lennysnewsletter.com/p/inside-devin-scott-wu• Devin: https://devin.ai• An AI state of the union: We've passed the inflection point, dark factories are coming, and automation timelines | Simon Willison: https://www.lennysnewsletter.com/p/an-ai-state-of-the-union• Redeploying Fable 5: https://www.anthropic.com/news/redeploying-fable-5• Why half of product managers are in trouble | Nikhyl Singhal (Meta, Google): https://www.lennysnewsletter.com/p/why-half-of-product-managers-are-in-trouble• Inside Linear: Building with taste, craft, and focus | Karri Saarinen (co-founder, designer, CEO): https://www.lennysnewsletter.com/p/inside-linear-building-with-taste• Building beautiful products with Stripe's Head of Design | Katie Dill (Stripe, Airbnb, Lyft): https://www.lennysnewsletter.com/p/building-beautiful-products-with• The design process is dead. Here's what's replacing it. | Jenny Wen (head of design at Claude): https://www.lennysnewsletter.com/p/the-design-process-is-dead• OpenAI Codex lead on the new shape of product work | Andrew Ambrosino: https://www.lennysnewsletter.com/p/openai-codex-lead-on-the-new-shape• Elon Musk: ‘Chances are we're all living in a simulation': https://www.theguardian.com/technology/2016/jun/02/elon-musk-tesla-space-x-paypal-hyperloop-simulation—Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.—Lenny may be an investor in the companies discussed. To hear more, visit www.lennysnewsletter.com

This Week In Startups is made possible by: NetSuite https://NetSuite.ai/TWIST Squarespace https://squarespace.com/twist YSecurity https://YSecurity.io/TWIST Today's show: *America posted 400,000 farm jobs last year, and fewer than 1% got a single domestic applicant. Danny Bernstein of Reservoir believes it's time to start automating this backbreaking labor, like picking stone fruit in 110°F temperatures. So he built the world's first on-farm robotics incubator on 40 acres of California farmland. Here's why he argues that automating farms isn't just a new opportunity, it's a national security issue. PLUS Jason responded to Gal Shir's viral "AI beat me at design" tweet, got into a kerfuffle with Figma CEO Dylan Field, and wound up making a brand new J-Trade. AND we're talking about the Dept. of Education's new "do no harm" policy, the Brown University AI cheating chart that's blowing up social media, and Lon has fresh streaming recommendations in an all-new Off Duty. Guest: Danny Bernstein on X: https://x.com/bernsteind Reservoir Farms: https://reservoir.co/ Reservoir VC: https://reservoir.vc/ Relevant Links: Bonsai Robotics: https://bonsairobotics.ai/ Root AI acquired by AppHarvest: https://www.therobotreport.com/root-ai-acquired-by-appharvest-for-60m/ John Deere: https://www.deere.com/en-us/ Western Growers Association: https://www.wga.com/ Tanimura & Antle: https://www.taproduce.com/ Naturipe Berry Growers: https://www.naturipefarms.com/ Driscoll's: https://www.driscolls.com/ Taylor Farms: https://www.taylorfarms.com/ The Wonderful Company: https://www.wonderful.com/ Capital Factory: https://www.capitalfactory.com/ Gal Shir "quitting design" post: https://x.com/galshirart/status/2074854464729629060 Dylan Field response to Gal Shir: https://x.com/zoink/status/2075290218660298807 JCal response to Field and "J-Trade": https://x.com/Jason/status/2075481565115654305 Figma: https://www.figma.com/ Dept. of Education: "Do No Harm" policy announcement: https://www.ed.gov/about/news/press-release/us-department-of-education-issues-final-rule-hold-all-colleges-and-universities-accountable-low-earning-programs NPR coverage on Dept. of Education earnings test: https://www.npr.org/2026/06/30/nx-s1-5835631/turner-camhi-do-no-harm-college-loans Paul Graham "cheating chart" post: https://x.com/paulg/status/2075031014628311236 Off Duty Recommendations: "Lioness" on Paramount+: https://www.youtube.com/watch?v=jNRQ0PR4a8U "Mayor of Kingstown" on Paramount+: https://www.youtube.com/watch?v=VkQzvwxOp0s "Human Vapor" on Netflix: https://www.youtube.com/watch?v=7xe6dRKVAb8 "Sugar" on Apple TV+: https://www.youtube.com/watch?v=twvPGxuEOEA "Wind River" (now on Netflix): https://www.youtube.com/watch?v=CZgN0dpFoaE "Not Fade Away" by Peter Barton & Laurence Shames: https://www.amazon.com/Not-Fade-Away-Short-Lived/dp/1579546889 Timestamps: 0:00 Jason's ongoing World Tour 1:43 Danny Bernstein joins live from Reservoir Farms 3:38 What is "specialty crop agriculture" 5:15 Why strawberries are the "white whale" of AgTech 6:55 The labor crisis in farming 9:20 Why AgTech never scaled 9:51 NetSuite - For the first time, you can try NetSuite Next for free. If your revenues are at least in the seven figures, go to https://NetSuite.ai/TWIST 10:51 Inside Reservoir's business model 17:44 Agriculture as national security 20:09 Squarespace - Turn your idea into a beautiful website! Go to https://www.squarespace.com/twist for a free trial. When you're ready to launch, use offer code TWIST to save 10% off your first purchase of a website or domain. 22:15 Did AI beat a designer at design? 30:56 YSecurity - The on-demand security team for startups. Need enterprise-grade security without hiring a $400k CISO? YSecurity gives you 40+ expert engineers, matched to exactly what you need, by the hour, with your first six hours completely free. Go to https://YSecurity.io/TWIST 37:23 The "do no harm" college earnings test 43:27 Brown University students cheated on their midterms 52:22 Lon's streaming recommendations 59:46 Jason's new snake grabber   Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp   Follow Lon: X: https://x.com/lons   Follow Alex: X: https://x.com/alex LinkedIn: ⁠https://www.linkedin.com/in/alexwilhelm   Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis   Check out all our partner offers: https://partners.launch.co/   Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland   Check out Jason's suite of newsletters: https://substack.com/@calacanis   Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

Pour l'épisode #335 je recevais Marcel Weekes. On en débrief avec Jeremy.

Every designer you know is quietly panicking about the same thing: their Figma hours dropped from 90% of the week to 30%, and nobody told them what to do with the other 60%. Is that a crisis or a promotion?Maria Irie runs brand at Chili Piper with a team of two — and she's spent the last year rebuilding her entire job around AI without losing what makes the brand feel human. She's mid-migration from Webflow to Claude, she's turned herself into a systems-builder instead of a one-pager machine, and she's got a theory about why the scrappiest, least "scalable" parts of marketing — the Ibiza offsites, the events, the stuff that doesn't show up in a report — are exactly what AI can't touch. This isn't a "prompt better" conversation. It's what happens when a whole discipline gets rewritten mid-career.We also cover:Why Maria cut her Figma time from 90% to 30% — and what she's building insteadThe "too many windows" problem: what it actually costs your brain to run five AI tools at onceWhy a two-person brand team deliberately protects the stuff that doesn't scale — and bets the whole brand on it

Davy returns from Config with a backpack full of new Figma features. Also our annual discussion of were these releases for us?

This Week In Startups is made possible by: Digital Ocean - do.co/twist Agree.com - agree.com Every.io - every.io.   Today's show: How many startups matter in tech? Fewer than you think. That's why venture capitalists are tripping over themselves to get onto their cap tables, no matter the cost. Why? Footwork's Nikhil Basu Trivedi argues that the Valley has never been more "power-law-pilled" than it is today. Basu Trivedi joined Cendana Capital's Michael Kim and TWiST's Alex Wilhelm to go deep on secondary markets, the state of startup M&A, why the SaaSpocalypse may be temporary, and what could trigger a retrenchment of the AI trade. It's Wednesday, so it's time for our venture capital roundtable to go deep on how VCs are investing today, and where on the horizon they have their eyes fixed! Guest links: Nikhil Basu Trivedi https://x.com/nbt Footwork https://www.footwork.vc/ Michael Kim https://x.com/MKRocks Cendana Capital https://www.cendanacapital.com/ Show links: The USVC-Anduril blowup https://x.com/ankurnagpal/status/2072701195714531398 Kline Hill Cendana Partners https://www.secondariesinvestor.com/kline-hill-and-cendana-raise-400m-for-second-vc-secondaries-fund/ GPTZero's exit https://gptzero.me/news/preserving-whats-human/ Salesforce buys Fin https://www.salesforce.com/news/press-releases/2026/06/15/salesforce-signs-definitive-agreement-to-acquire-fin/ Vercel buys Better Auth https://vercel.com/blog/vercel-acquires-better-auth Figma buys Bud https://techcrunch.com/2026/07/07/figma-acquires-team-behind-a-vibe-coding-app/ Protoge https://withprotege.ai/ Windborne https://windbornesystems.com/ Etched https://www.etched.com/ Lovable's reported raise https://sifted.eu/articles/lovable-300m-13-2bn-valuation Josh Browder https://x.com/Joshuabrowder   Timestamps: 0:00 Introduction: Nikhil Basu Trivedi (Footwork) & Michael Kim (Cendana Capital) 1:59 The Anduril vs. USVC secondary market blowup 4:08 Why Silicon Valley is 'power-law-pilled' 8:23 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at https://Plaud.ai/twist and use code TWIST for 10% off! 9:37 Information asymmetry in the secondary markets 9:45 Every.io — For all of your incorporation, banking, payroll, benefits, accounting, taxes or other back-office administration needs, visit https://every.io 15:02 Is SPV fraud smoke or fire? 16:32 Superhuman acquires GPTZero 19:54 Agree.com - Stop chasing invoices and automate your entire contract-to-cash stack. Go to https://agree.com and tell them Jason sent you to get 50% off for life! 21:10 The M&A wave 27:19 The SaaSpocalypse debate 29:59 DigitalOcean - Head to https://do.co/twist to start building on DigitalOcean's AI-Native Cloud today — and cut your AI workload costs by up to 50%. 30:44 Data's moment in the energy → compute → data loop 35:01 Where will AI value accrue? 40:04 What could cause an AI correction? 42:17 Why some companies are "too big to miss" 46:23 China's possible open-weight model ban 53:28 Young founders: Etched, Thiel Fellows, Z Fellows, Neo 55:33 Portfolio spotlight: WindBorne's weather balloons and data moat 58:47 Michael's favorite fund manager: Josh Browder Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp   Follow Lon: X: https://x.com/lons   Follow Alex: X: https://x.com/alex LinkedIn: ⁠https://www.linkedin.com/in/alexwilhelm   Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis   Check out all our partner offers: https://partners.launch.co/   Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland   Check out Jason's suite of newsletters: https://substack.com/@calacanis   Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

Anthropic se está comiendo a sus propios clientes. Figma la acusa de robarse su tecnología después de meses de trabajar juntos. El gobierno de Estados Unidos ya no confía en tener sus modelos de IA en manos de terceros y contrata a Palantir para construir los suyos propios con hardware propio.Carlos Muñoz y Ricardo Moreno destapan el caso que tiene a Silicon Valley hablando: cómo una empresa de inteligencia artificial terminó compitiendo con quienes la contrataron, por qué esto es distinto a lo que hizo Meta o Google en su momento, y por qué el "Memory Trade" de Micron movió miles de millones en la bolsa el mismo día que nadie lo vio venir.━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

A client of mine just rebuilt their entire Figma design system — roughly 700 components — as code components in Claude Code. It took one day. And now their designers prototype in code, while Figma has become the tool they open "when they occasionally need to design something."In this episode, I unpack what this story reveals about where our jobs are heading. The "should designers code?" debate is over — but we didn't end it. The job market did. And the way our roles are changing isn't arriving as a memo. It's arriving as convenience.In this episode:Why prototyping in the real system (instead of a Figma simulation) is a genuine qualitative leap — and why the design-to-dev handoff gap just disappearedThe four quiet problems nobody talks about: fast isn't faithful, two sources of truth, the illusion of production-ready, and the question of where invention lives nowWhy role creep in 2026 doesn't come from your boss — it comes from your toolsThe one question that matters more than "should designers code?": are you building the mental model, or just orchestrating outputs?Your homework: pick one workflow change that happened "by itself" and choose it on purposeAI for Designers: 5-week Bootcamp

This Week In Startups is made possible by: Northwest Registered Agent https://northwestregisteredagent.com/twist Vanta https://www.vanta.com/twist Sentry https://sentry.io/twist Today's show: *There are $100 trillion in global assets sitting on top of what Hanover Park co-founder/CEO Chris Hladczuk calls "human duct tape": armies of accountants in offices patching together work from various legacy tools (QuickBooks, Excel) that are holding funds' own data hostage. Can all of this be replaced with AI? Find out how their startup went from overseeing $1B to $20B in assets in just 15 months. PLUS, we flash back to March 2020, when Jason and Figma co-founder/CEO Dylan Field broke down the design tool's initial go-to-market strategy, made some WILDLY inaccurate COVID predictions, and considered anxiety about "SaaS burnout" years before the category went full apocalyptic. Guests: Chris Hladczuk on X: https://x.com/chrishlad Hanover Park: https://www.hanoverpark.com/ Dylan Field: https://x.com/zoink Figma: https://www.figma.com/ Relevant Links: Turner Novak on X: https://x.com/TurnerNovak Banana Capital: https://www.bananacapital.vc/ Emergence Capital: https://www.emcap.com/ Lux Capital: https://www.luxcapital.com/ Susa Ventures: https://susaventures.com/ Bill.com: https://www.bill.com/ METR: https://metr.org/ Granola AI note taker: https://www.granola.ai/ Vanta: https://www.vanta.com/ Foo Camp on YouTube: https://www.youtube.com/c/foocamp TechCrunch Mahalo coverage: https://techcrunch.com/2014/01/27/inside-mobile-news-launch/ Timestamps: 0:00 Hanover Park & the fund admin problem 3:32 Why funds outsource instead of building 5:44 Why fund accounting is so complex 10:38 The "one-click migration" goal 10:48 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at https://northwestregisteredagent.com/twist 13:51 Context vs. intelligence gaps 16:11 No PMs, No Designers 20:46 Vanta - Get $1000 off your SOC 2 at https://www.vanta.com/twist 23:18 This is a $100T opportunity 25:36 Flashback w/ Dylan Field of Figma 29:15 Sentry - Your team should be focused on shipping features — not chasing down bugs. New users can get $240 in free credits when they go to https://sentry.io/twist and use the code TWIST 31:22 Pre-AI enterprise security worries 36:30 SaaS overload and SaaS burnout 37:30 The evolution of Figma pricing 42:38 The rise and fall of Mahalo dot com 51:38 The work-from-home revolution begins Subscribe to the TWiST500 newsletter: https://ticker.thisweekinstartups.com Check out the TWIST500: https://www.twist500.com Subscribe to This Week in Startups on Apple: https://rb.gy/v19fcp Follow Lon: X: https://x.com/lons Follow Alex: X: https://x.com/alex LinkedIn: ⁠https://www.linkedin.com/in/alexwilhelm Follow Jason: X: https://twitter.com/Jason LinkedIn: https://www.linkedin.com/in/jasoncalacanis Thank you to our partners: (0:00) PARTNER - AD BLURB (0:00) PARTNER - AD BLURB (0:00) PARTNER - AD BLURB Check out all our partner offers: https://partners.launch.co/ Great TWIST interviews: Will Guidara, Eoghan McCabe, Steve Huffman, Brian Chesky, Bob Moesta, Aaron Levie, Sophia Amoruso, Reid Hoffman, Frank Slootman, Billy McFarland Check out Jason's suite of newsletters: https://substack.com/@calacanis Follow TWiST: Twitter: https://twitter.com/TWiStartups YouTube: https://www.youtube.com/thisweekin Instagram: https://www.instagram.com/thisweekinstartups TikTok: https://www.tiktok.com/@thisweekinstartups Substack: https://twistartups.substack.com

Klaviyo has been rolling out something called Composer in beta - an AI agent that promises to build entire marketing campaigns from a single prompt. Audience, copy, design, segmentation, all of it. The promise is impressive. So I got access on a real client account and tested it myself. And my honest take is more nuanced than the hype - and more useful than the skeptics would have you believe. The short version: Composer is less an autonomous agent and more a really well-informed assistant. It knows your account data better than any outside AI tool could. It just still needs you. Where it genuinely surprised me was the data side - send time recommendations backed by actual account history, revenue per recipient, open rates by date, flagging which sends had enough volume to be statistically meaningful. That's marketing expert level analysis, and it's specific to your account in a way that ChatGPT or Claude simply can't replicate without a direct integration. Where it fell short was the creative side. The copy was functional but generic. The design pulled image slices from across the account that didn't really hang together. Getting it to feel on brand would have taken enough back and forth that I may as well have just written and designed it myself. In this episode I walk through exactly what happened when I tested it, what genuinely impressed me, where it still needs a human, and how to think about using it if you get access. ✨ In this episode, you'll learn: What Klaviyo Composer actually is and what it promises to do What happened when I tested it on a real client account with a real campaign prompt Why the creative output is a starting point, not a finished product The limitation that affects accounts where most emails are designed in Figma or Canva The one thing Composer did that genuinely surprised me - and why it matters Why the send time analysis is where this tool actually earns its place What to watch out for with the auto-populated segmentation suggestions How to think about the human vs. AI division of labor in your email program right now Let it handle the data. You handle the creative direction and strategy. That framing is really useful for anyone thinking about where AI fits into their email marketing going forward. Work with Joy Joya: https://joyjoya.com

What does it actually take to move an entire company from handwriting PRDs to shipping features with agents in two years?In this episode of Supra Insider, Marc Baselga and Ben Erez sit down with Alex Meyers, Principal Product Manager at Gusto, to trace how the company became AI-native from the inside. Alex shares how his own quiet tool use turned into a C-suite demo, why that demo made clear that you cannot simply mandate “be AI native,” and how PM AI hackathons became the ritual that moved the org forward.They explore why dedicated, uninterrupted build time beats an hour here and there, why the ritual has to recur as the tools keep changing, how roughly three-quarters of the PM org now merges pull requests, and where Alex thinks the work is heading as loops and goals let PMs spend more time on customers and taste.If you're a product leader trying to raise your team's AI fluency, a founder deciding how much structure to put around learning, or an operator wondering what the PM role becomes when agents handle the busywork, this episode is for you.All episodes of the podcast are also available on Spotify, Apple and YouTube.New to the pod? Subscribe below to get the next episode in your inbox

Adam and Adir discuss London’s heat wave, Victoria’s crime wave, Labor’s housing mess, the world’s most profitable companies, Nvidia and the AI bubble, remote work, Canva vs Figma, Koala, SkinKandy, The Man Shake and the latest Corporate Travel disaster. 00:00 - London's Heat Wave06:00 - Victoria's Crime Wave and the Housing Debate14:00 - The 30 Most Profitable Companies23:00 - The AI Bubble, Nvidia and the $7 Trillion Question44:00 - CGT, Capitalism and Labor's Budget Backlash54:00 - Remote Work, Gen Z and Canva's Office Crackdown1:05:01 - Koala, SkinKandy and the ASX IPO Problem1:10:00 - Man Shake1:20:00 - Corporate Travel's Latest Disaster Join us on Substack for articles, news and more: https://www.thecontrarianspod.com/See omnystudio.com/listener for privacy information.

TestAiutaci a realizzare la nostra prima collezione di “cose” e ordina subito sul retrobottega→ https://retrobottega.caffe.design/

The boys are back with episode 72, where Rory Flynn and Drew Brucker attempt to discuss AI like serious adults. Yeah, that didn't work. They immediately detour into Figma Config, Waymo trust issues, Invisalign lisp watch, and the quiet horror of paying for AI models that may or may not be getting nerfed behind the curtain.This one gets into the big question creative teams keep circling: is taste still a moat in the AI era? Drew and Rory break down why “taste as a moat” is getting shakier, what types of taste are actually durable, and why timing, novelty, cultural awareness, editorial judgment, brand systems, and compounding context may matter more than ever.They also dig into Claude Fable, government access to stronger AI models, the widening gap between public and private model capability, Figma's new AI workflows, Weavy integration, Adobe Firefly Foundry, Disney's custom AI model deal, and Midjourney's V8.2 preview, texture upgrades, editing roadmap, and secret search tricks.---⏱️ Fast Hour00:00 The boys are back00:11 Rory recaps Figma Config03:13 Rory tries Waymo for the first time08:52 The algorithm ding09:59 Invisalign enters the chat10:41 Claude Fable returns nerfed13:32 AI regulation gets messy18:44 AI tools and IP risk22:33 Taste as a moat gets challenged25:02 Breaking down types of taste27:40 Timing, novelty, and AI trends29:53 Trend cycles hit warp speed31:12 AI slop can damage brands34:45 Vintage aesthetics and timing38:37 Taste needs systems now40:14 Evolving visual taste43:19 South Park and imperfect taste45:55 Figma updates and custom tools52:39 Shaders, motion, and Weavy56:01 Retention beats acquisition01:00:59 Adobe Firefly Foundry01:02:25 Disney enters custom AI models01:03:34 The custom model problem01:07:09 Midjourney preview mode01:08:18 Midjourney V8.2 texture and skin detail01:16:13 Midjourney V9 training and web redesign01:16:43 Midjourney editing roadmap01:21:34 Secret search tip01:23:03 Broken toes and podcast lore01:25:14 Listener shoutouts01:27:13 Subscribe, hype, tell a mechanic#FastHours #ArtificialIntelligence #AI #AICreative #GenerativeAI #AIArt #Midjourney #ClaudeAI #AdobeFirefly #Figma #Weavy #AITools #BrandStrategy #CreativeAI #AIWorkflow

In this quick one, Phil returns from San Francisco to join Barry and discuss all the latest and greatest features announced at Config 2026, Figma's annual product conference. We discuss how Figma is enabling global teams to better collaborate and enhance their work with AI, and how they are incorporating more and more of the entire design workflow in their canvas with releases like Motion, Figma Weave, and Code Layers. We also discuss how these features impact token usage and licensing costs for teams, and for clients, who have invested heavily in the platform. We wrap by discussing how Figma is investing in the community, specifically the international community, how they need to continue meeting teams where they are. Enjoy!Drinks: Devil's Purse Brewing Co. Sichuan Wit, Zero Gravity Craft Brewery Green State LagerLinks: www.figma.com

Chris Gomes set out to hire four AI product managers. Seven months later, his biggest lesson was not about AI at all.In this episode of Supra Insider, Marc Baselga and Ben Erez sit down with Chris Gomes, VP of Product at Conveyor, the Series B startup that automates responses to security questionnaires and RFPs. Chris walks through the seven months he spent hiring four AI PMs, why he spent so long defining what an “AI product manager” even means, and the realization that culture fit, not AI skill, was the thing that actually predicted success.They explore how he rebuilt a stalled interview process by pulling the most important screens to the front, the MOC framework he uses to map each interview step to specific competencies, his case for work trials and customer role-plays, how he treats references and back-channels, and why the gut-level question of whether you'd enjoy working with someone deserves more weight than most rubrics give it.If you're a hiring manager trying to run a tighter, higher-signal process, a founder thinking about your first product hires, or a PM preparing for interviews and wondering what teams are really evaluating, this episode is for you.All episodes of the podcast are also available on Spotify, Apple and YouTube.New to the pod? Subscribe below to get the next episode in your inbox

Hoy hablamos de OpenAI y Broadcom presentando Jalapeño, el chip propio de inferencia; de Google metiendo computer use dentro de Gemini 3.5 Flash; de Qualcomm buscando sitio en datacenters con Dragonfly C1000; de Figma acercando diseño, código, 3D, shaders e IA en el canvas; y de la crítica en Nature que cuestiona la narrativa de Microsoft sobre Majorana y los qubits topológicos.Puedes seguirnos en YouTube en https://youtube.com/olivernabani y puedes unirte al Discord Mashain en https://olivernabani.com/discord

What does it really take to scale a software company from $35M to $2B ARR? In this episode of Hunters & Unicorns, Simon Kouttis and Ollie Kuehne sit down with Dan Barrett, SVP International at Figma and former MongoDB leader, to unpack the lessons behind one of SaaS's most remarkable growth stories. Dan shares why he hates the word "playbook," how MongoDB evolved through multiple sales transformations, and why the best leaders focus on developing people—not following a rigid process. The conversation explores authenticity in leadership, building high-performance teams, scaling PLG and enterprise sales motions, customer success, AI's impact on software sales, and the leadership lessons that helped Dan grow from a first-time manager into one of the industry's most respected sales leaders. In this episode: • Scaling MongoDB from $35M to $2B ARR • Why Dan hates the term "playbook" • The leadership epiphany that changed his career • Building trust without fear or intimidation • PLG vs enterprise sales models • What great sales organizations do differently • How to develop future sales leaders • Why authenticity is a leadership superpower • AI, SaaS, and the future of enterprise sales Subscribe for more conversations with the leaders building the next generation of SaaS companies. #HuntersAndUnicorns #DanBarrett #Figma #MongoDB #SalesLeadership #SaaS #EnterpriseSales #PLG #CustomerSuccess #b2bsales Timestamps: 0:00 — Trailer 1:02 — Introduction & Sponsor 1:56 — Welcome Dan Barrett 2:35 — Dan's Career & the Epiphany Moment 9:00 — Pressure Before the Epiphany 10:02 — QBRs With John McMahon 11:50 — Fighting for Space to Change 13:37 — From MongoDB to Figma 17:21 — Where PLG Goes Wrong 19:00 — Rethinking the Playbook 23:55 — Learning What Works at Figma 31:46 — Playbook vs Authenticity 33:32 — Moving Into Customer Success 38:06 — Knowing When to Leave MongoDB 41:00 — Sustaining Energy for Nearly a Decade 43:31 — Hunters & Unicorns Origin Story 48:21 — Will Salespeople Survive AI 51:20 — The Future of Figma 54:03 — Closing

This week we are going behind the scenes of Config 2026 with Loredana Crisan (Figma's Chief Design Officer) https://www.linkedin.com/in/loredanacrisan/We talk about Figma's vision for AI, why design is having “an identity crisis and a renaissance at the same time,” and what it means to use AI to express what's already in your head (not outsource creativity to it).It's a clarifying conversation about taste, tools, and the future of design

This episode contains some screen sharing so it's best watched on YouTubeWhat happens when one product leader decides to stop copy-pasting between chat windows and instead build an operating layer that puts coding agents in the hands of an entire company?In this episode of Supra Insider, Marc Baselga and Ben Erez sit down with Kyler Ross, Head of Product at Cloaked, to walk through the internal “harness” he started building last Thanksgiving: an agent-friendly system of context files and scripts that lets agents read from and write to the team's real tools. Kyler explains how it gets installed on every company machine, why he treats each new agent session like onboarding an employee, and how a self-improving loop of skills and automated reviews keeps it getting better.They explore his day-to-day setup for running many agents at once, why worktrees and Claude Code hooks exist to make failure nearly impossible, a one-on-one prep skill that pulls context from every corner of the company, and the layered guardrails, including a nightly “librarian” agent, that keep confidential information from leaking.If you're a product or engineering leader trying to make your team more AI-native, someone wiring agents into real workflows, or anyone wrestling with how to run agents safely at scale, this episode is for you.All episodes of the podcast are also available on Spotify, Apple and YouTube.New to the pod? Subscribe below to get the next episode in your inbox

Season 3 is here with new co-host Lily. This episode tackles a question every designer should sit with: are you mastering your craft, or just mastering your tools?They dig into why "Figma" isn't a skill, designers vibe coding their own tools, and what a pro photographer with a Barbie camera teaches about fundamentals. Plus: why cross-platform handoffs are still broken, what AI agent demos conveniently skip, and the Ferrari Luce debate, where brand legacy meets bold new design.00:00 Intro: Welcome to Season 300:14 Craft vs. Tooling: The Core Debate01:18 Building Your Own Tools03:40 Analog vs. Hyper-Future05:22 Tooling That Incentivizes Better Design06:49 Designing for Context, Not Just Platform08:22 Cross-Platform Continuity & The AI Demo Problem18:24 Bringing It Back: What Is Craft, Really?20:09 How Tool Companies Captured Design Culture22:45 The Ferrari Luce: When Brand Meets New Craft27:00 Digital vs. Tactile in Car Interiors32:37 Wrap-Up: Own the Vertical

We're back with more from our live event at the Yerba Buena Center for the Arts in San Francisco. In this episode, we sit down with Dylan Field, a founder and the chief executive of the design company Figma, for what he describes as a “roller coaster” of a conversation. We cover everything from the company's “Design Is Dead” campaign to the sudden resignation of the Anthropic executive Mike Krieger from Figma's board. Then, we close things out with a special musical performance by eight wooden robotic dolls that make up the Teenage Engineering Choir. One quick correction to note: In our interview with Field, he makes reference to the SpaceX S-1 filing and misstates what the company says their addressable market for A.I. enterprise applications is. Field says “$22.9 trillion,” but the correct number from the SpaceX filing is $22.7 trillion. The decimal point makes it look small, but it's a difference of $200 billion. We'll be back on Friday with our final installment of “Hard Fork” Live.   Guests: Dylan Field, chief executive and co-founder of Figma. Dan Powell, robot conductor, New York Times music composer and “Hard Fork” theme-song creator. Teenage Engineering Choir   Additional Reading: This Start-Up's $20 Billion Sale Died. It Came Fighting Back.   We want to hear from you. Email us at hardfork@nytimes.com. Find “Hard Fork” on YouTube and TikTok. Subscribe today at nytimes.com/podcasts or on Apple Podcasts and Spotify. You can also subscribe via your favorite podcast app here https://www.nytimes.com/activate-access/audio?source=podcatcher. For more podcasts and narrated articles, download The New York Times app at nytimes.com/app. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Figma's Q1 2026 revenue grew 46% YoY to $333M, with net dollar retention hitting a multi-year high of 139%. But even after its post-IPO slide, the stock still trades at ~75x next-12-month free cash flow. We break down what's driving the valuation gap, why free cash flow per share is still feeling IPO dilution effects, and what Figma needs to prove on profitability as AI disruption looms over creative software.Topics covered:Why Figma's valuation is still rich despite the stock's declineFigma vs. Adobe, Microsoft, Wix, and the private design-tool fieldAI's disruption risk to creative/design softwareQ1 2026 results: $333M revenue, 139% net dollar retention, $89M free cash flow (27% margin)Free cash flow per share and the impact of IPO-related dilution$1.6B cash, no debt, and why M&A could be on the tableThe $116M RSU tax settlement behind the cash balance dipQ2 and full-year 2026 guidance (40% and 35% YoY growth)This episode is sponsored by fiscal.ai — get 15% off any paid plan at fiscal.ai/csi.Liked this breakdown? Head to chipstockinvestor.com for our full library of semiconductor and tech stock research, deep dives, and analysis — plus access to Semi Insider, our premium subscription for investors who want the data behind every call we make.

What does it look like when a designer with zero technical background commits to shipping something real?That's what this week's episode with Brett Williams is all about.He gives us a behind-the-scenes of his journey building Gather including:Brett's process for iterating on a designBrett's new prototyping.md skill workflowHow Brett maintains control while building with AIBrett's strategy for adding sound design to GatherWhen Brett relies on Figma vs. explores directly in codea lot more

What does it take to walk away from a decade in product, and a job most people would envy, to bet on yourself?In this episode of Supra Insider, Marc Baselga and Ben Erez sit down with Peter Yang, who just left his product lead role at Roblox to go full-time on his newsletter and podcast, Behind the Craft and build his own projects. Peter talks through the trade-offs of solopreneur life, why his calendar is suddenly empty, and how he uses an AI personal advisor with three principles to decide what to say no to.They explore his day-to-day AI builder stack, from running Codex as a daily driver to using Hermes for his recurring scheduled tasks, his working definition of slop and why he guards against it, and what he's actually measuring as success now that nobody is handing him a promotion.If you're a PM weighing whether to leave a stable job to build on your own, a creator trying to scale output without sliding into slop, or anyone wiring AI agents into their daily work, this episode is for you.All episodes of the podcast are also available on Spotify, Apple and YouTube.New to the pod? Subscribe below to get the next episode in your inbox

The Information's Elon Musk reporter Theo Wayt and Crypto reporter Yueqi Yang talk with TITV Host Akash Pasricha about SpaceX's historic public debut, retail investor allocations, and price discovery happening via crypto perpetual contracts. We also talk with TMF Associates President Tim Farrar about Starlink's dropping ARPU, terminal cost subsidies, and upcoming launch site expansions, and The Information's AI reporter Stephanie Palazzolo about how Anthropic is blindsiding key partners like Figma and Canva by moving directly into the software application layer.Articles discussed on this episode: https://www.theinformation.com/briefings/spacex-shares-open-150-per-sharehttps://www.theinformation.com/briefings/crypto-traders-bet-spacex-ipo-popping-20https://www.theinformation.com/articles/anthropic-blindsides-business-partnersSubscribe: YouTube: https://www.youtube.com/@theinformation The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agendaTITV airs weekdays on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Follow us:X: https://x.com/theinformationIG: https://www.instagram.com/theinformation/TikTok: https://www.tiktok.com/@titv.theinformationLinkedIn: https://www.linkedin.com/company/theinformation/Chapters:00:00 - Introduction01:13 - SpaceX Goes Public in Historic $2T IPO 10:06 - Starlink Margin Squeeze & Telco Threats 19:57 - Inside the SpaceX Retail Trading Playbook 33:54 - Anthropic Blindsides Software App Partners

Hoy hablamos de Anthropic metiéndose en terreno de Figma y Canva con Claude Design, Xiaomi liberando MiMo Code como agente coder con memoria persistente, Google negociando con Samsung para parte de sus próximas TPUs Icefish, la nueva fábrica europea de Infineon en Dresde y la tripulación de Artemis III.Puedes seguirnos en YouTube en https://youtube.com/olivernabani y puedes unirte al Discord Mashain en https://olivernabani.com/discord

From the comical wizard prompts of 2024 to the heavy-lifting reality of Figma MCP, Davy and PJ chart the compressed timeline of design system and canvas automation.

What does it take to bring AI into businesses that run on physical work, human judgment, and processes nobody has ever written down?In this episode of Supra Insider, Marc Baselga and Ben Erez sit down with Noah Levin, founder of Serious People, to unpack what he calls being a “free-range AI consultant.” Noah explains why most of his work is business consulting from first principles rather than AI consulting, why agents still need humans to deliver real value, and how he groups AI for any company into three buckets: a coworker, an operator, and a product or engineering capability.They explore how AI is collapsing the distance between a conversation and a working prototype, why the new IP is business judgment instead of code, why he believes everything is becoming product management, and the humility it takes to solve problems on a client's terms inside companies that aren't, and shouldn't be, run like tech startups.If you're a product leader figuring out where AI actually creates leverage, an operator weighing whether to go independent, or a builder realizing that distribution now matters more than the thing you build, this episode is for you.All episodes of the podcast are also available on Spotify, Apple and YouTube.New to the pod? Subscribe below to get the next episode in your inbox

Daniel Mahncke and Shawn O'Malley take a deep dive into Wix.com — the Israeli website-building platform whose investment case now turns on two of the most debated questions in the stock today: whether the generative-AI wave that lets anyone spin up a site from a text prompt is the end of Wix or whether Wix is too sticky, and whether the Base 44 acquisition — Wix's bet on AI-powered app generation — is the next leg of the story or a distraction from the SMB infrastructure business the company already dominates. IN THIS EPISODE YOU'LL LEARN: (00:00:00) Intro (00:00:48) How Wix Was Founded (00:23:46) Why Clients Keep Using Wix (00:26:19) How Much of Wix Is Actually Vulnerable to AI (00:35:32) Why Wix Is More Sticky Than It Seems (00:37:01) Whether Vibecoding Is Likely to Disrupt Drag-and-Drop Website Building (00:45:34) Why Base44 Could Change the Entire Investment Case (01:01:25) How Wix Could Survive and Turn Into a Multibagger (01:04:29) Valuation Discussion of Wix (01:09:21) Whether Shawn and Daniel Add Wix to the Intrinsic Value Portfolio Disclaimer: Slight discrepancies in the timestamps may occur due to podcast platform differences. BOOKS AND RESOURCES Join the exclusive ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Mastermind Community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Track ⁠⁠⁠⁠⁠⁠The Intrinsic Value Portfolio⁠⁠⁠⁠⁠⁠. Portfolio Review ⁠Submit Tool⁠. Value Investor Club ⁠Article⁠. Chit Chat Stocks w/ ⁠Manuel Cunha⁠. Future Investing ⁠Interview w/ Manuel Cunha⁠. Rene Sellman ⁠Substack Article⁠. Manuel Cunha ⁠Substack Article⁠. Previous Intrinsic Value breakdowns: ⁠Figma⁠, ⁠Microsoft⁠, ⁠Salesforce⁠, ⁠Adobe⁠. Follow Shawn on ⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠. Follow Daniel on ⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠⁠. Related ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠books⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ mentioned in the podcast. Ad-free episodes on our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Premium Feed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. NEW TO THE SHOW? Get smarter about valuing businesses through ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Check out ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Investor's Podcast Starter Packs⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Follow our official social media accounts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Try our tool for picking stock winners and managing our portfolios: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Finance⁠⁠⁠⁠⁠⁠⁠⁠. Enjoy exclusive perks from our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠favorite Apps and Services⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn how to better start, manage, and grow your business with the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠best business podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. SPONSORS Support our free podcast by supporting our ⁠⁠⁠⁠sponsors⁠⁠⁠⁠: ⁠Fiscal.AI⁠ References to any third-party products, services, or advertisers do not constitute endorsements, and The Investor's Podcast Network is not responsible for any claims made by them. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm

In this "quick one", Barry and Phil crack some beers and explore the impact of AI on design leadership, change management, and the future of work. They discuss recent developments in AI tools like Figma agent and Gemini, the cultural and emotional implications of AI adoption that come with this change, and practical strategies for integrating AI into creative and organizational processes, including the importance of focusing on value and experimentation in AI adoption. It is a timely and much-needed conversation for design leaders, and creatives in general, in the throes of AI transformation. Enjoy!Drinks: Sprindrift Blood Orange Tangerine Sparkling Water, Tree House Brewing Company Waffleberry Double IPALinks: www.figma.com

Daniel Mahncke and Shawn O'Malley take a deep dive into Wix.com — the Israeli website-building platform whose investment case now turns on two of the most debated questions in the stock today: whether the generative-AI wave that lets anyone spin up a site from a text prompt is the end of Wix or whether Wix is too sticky, and whether the Base 44 acquisition — Wix's bet on AI-powered app generation — is the next leg of the story or a distraction from the SMB infrastructure business the company already dominates. IN THIS EPISODE YOU'LL LEARN: (00:00:00) Intro (00:01:32) How Wix was founded (00:21:35) Why clients keep using Wix (00:28:05) How much of WIX is actually vulnerable to AI (00:37:07) Why Wix is more sticky than it seems (00:38:24) Whether vibecoding is likely to disrupt drag-and-drop website building (00:46:54) Why Base44 could change the entire investment case (01:06:24) How Wix could survive and turn into a multibagger (01:09:21) Valuation discussion of Wix (01:13:26) Whether Shawn and Daniel add Wix to the Intrinsic Value Portfolio BOOKS AND RESOURCES Join the exclusive ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Mastermind Community⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Track ⁠⁠⁠⁠The Intrinsic Value Portfolio⁠⁠⁠⁠. Portfolio Review Submit Tool. Value Investor Club Article. Chit Chat Stocks w/ Manuel Cunha. Future Investing Interview w/ Manuel Cunha. Rene Sellman Substack Article. Manuel Cunha Substack Article. Previous Intrinsic Value breakdowns: Figma, Microsoft, Salesforce, Adobe. Follow Shawn on ⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠. Follow Daniel on ⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠. Related ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠books⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ mentioned in the podcast. Ad-free episodes on our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Premium Feed⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. NEW TO THE SHOW? Get smarter about valuing businesses through ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The Intrinsic Value Newsletter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Check out ⁠⁠⁠⁠⁠⁠⁠⁠The Investor's Podcast Starter Packs⁠⁠⁠⁠⁠⁠⁠⁠. Follow our official social media accounts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Facebook⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Try our tool for picking stock winners and managing our portfolios: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TIP Finance⁠⁠⁠⁠⁠⁠. Enjoy exclusive perks from our ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠favorite Apps and Services⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. Learn how to better start, manage, and grow your business with the ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠best business podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠. SPONSORS Support our free podcast by supporting our ⁠sponsors⁠: Plus500 Netsuite Shopify Vanta References to any third-party products, services, or advertisers do not constitute endorsements, and The Investor's Podcast Network is not responsible for any claims made by them. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://theinvestorspodcastnetwork.supportingcast.fm

In today's conversation, Brett sits down with CMO of Figma, Sheila Joglekar Vashee. Previously the second marketing hire at Dropbox, where she helped scale the company past $1 billion in revenue, she now leads marketing at Figma fresh off its IPO. In an industry that has spent a decade trying to turn marketing into something closer to hedge fund trading, Sheila argues the art was always the point — we just stopped talking about it. She unpacks how to run marketing as a portfolio of moonshots, why giving teams different goals breeds dysfunction, how to scale taste across an organization, and why old playbooks are obsolete, even as the fundamentals hold. In today's episode, we discuss: How to run marketing like a portfolio of moonshots The value of disruptive energy for senior marketers Why "Ubiquity is the opposite of cool" How to actually scale taste across an organization What great marketing looks like in the AI era Referenced: Apple: https://www.apple.com/ Dennis Woodside: https://www.linkedin.com/in/dennis-woodside-341302/ Dropbox: https://www.dropbox.com/ Dylan Field: https://www.linkedin.com/in/dylanfield/ Figma: https://www.figma.com Francoise Brougher: https://www.linkedin.com/in/francoise-brougher-341a72/ Gap: https://www.gap.com/ Google Chrome: https://www.google.com/chrome/ Harley-Davidson: https://www.harley-davidson.com/ HubSpot: https://www.hubspot.com/ Notion: https://www.notion.com/ Opendoor: https://www.opendoor.com/ Pinterest: https://www.pinterest.com/ Square: https://squareup.com/ The Web Is What You Make of It (Dear Sophie): https://www.youtube.com/watch?v=pzOBOuyr-EU Urban Outfitters: https://www.urbanoutfitters.com/ Yamini Rangan: https://www.linkedin.com/in/yaminirangan/ Where to find Sheila: LinkedIn: https://www.linkedin.com/in/sheilavashee/ X: https://x.com/sheilavashee Where to find Brett: LinkedIn: https://www.linkedin.com/in/brett-berson-9986644/ X: https://x.com/brettberson Where to find First Round Capital: Website: https://firstround.com/ First Round Review: https://review.firstround.com/ Twitter/X: https://twitter.com/firstround YouTube: https://www.youtube.com/@FirstRoundCapital This podcast on all platforms: https://review.firstround.com/podcast Timestamps: 00:00 Introduction 00:07 What excellent marketing actually is in 2026 01:36 Why giving teams different goals creates dysfunction 02:36 The most important decision Sheila made as CMO last year 04:26 The real difference between an SVP and a CMO 06:05 Marketing is one engine - not separate pieces 07:15 The tension between brand and growth 09:25 The decisions a CMO should never be making 09:55 Running marketing like a portfolio of moonshots 12:46 "Ubiquity is the opposite of cool" 15:11 Why a few companies get a flywheel of momentum 16:44 The Silicon Valley clock and irrational perception cycles 19:25 How to actually scale taste across an org 21:09 What changes for a CMO in a post-LLM world 23:15 Why the artistic side of marketing never really left 26:05 Whether taste can ever be encoded in software 27:15 Telling an optimistic, yet realistic story about AI 30:50 You need to make people care 32:11 What surprised Sheila about being a public-company CMO 33:46 Why Figma won enterprise where Dropbox couldn't 35:25 Sheila's favorite campaign ever 37:10 Why announcement videos full of humans, lack humanity 38:55 Playbooks are obselete, but the fundamentals are not 40:25 Why marketing in 2026 demands disruptive energy 41:54 How Sheila architects her week 48:55 Where corporate politics actually come from 53:55 "Sheila, are you going to change the world in this job?" 58:09 What's unique about the CMO and CEO relationship

The "SaaSpocalypse"—the panic that AI will make software-as-a-service obsolete—hasn't rattled Figma's Matt Colyer. As the company's director of product management for developers, he's been building his own agents for two years and is buying more software services than ever.In addition to making the case that AI is a “goldmine” for SaaS companies, Colyer talked with Dan Shipper for AI & I about why great design requires a diamond-shaped process: First you diverge, generating as many ideas as possible, then you converge around the best ones. Chat is linear, which makes it good for iterating on one design but bad at generating lots of options. Figma's new on-canvas agent is a first attempt at fixing that.They also get into why AI design tools need to break free of the text box, how Figma's MCP server is closing the loop between code and design, and why "review" has become the biggest bottleneck in AI-assisted product work.If you found this episode interesting, please like, subscribe, comment, and share!To hear more from Dan Shipper:Subscribe to Every: https://every.to/subscribeFollow him on X: https://twitter.com/danshipperTimestamps:1:03 - Introduction2:15 - Why the SaaSpocalypse narrative has it backwards5:27 - Matt's email agent origin story13:21 - Divergent vs. convergent design thinking17:39 - Figma's MCP server19:45 - Why design agents need personalization22:09 - Every problem is a context problem25:12 - Apple and Google as the reigning kings of context28:18 - Why review is the new bottleneckLinks to resources mentioned in the episode:Matt Colyer on X: https://x.com/mcolyerFigma: https://figma.comFigma MCP server: https://www.figma.com/blog/introducing-figma-mcp-server/

DAMIONCarnival Corporation's data breach exposed personal data of nearly 6 million customers: An April social engineering attack on an employee account compromised names, dates of birth, and government-issued ID numbers. WHO DO YOU BLAMESkills: Technology & Cybersecurity: Experience with information technology and cybersecurity matters is increasingly important to mitigate the risks our business faces, promote innovation and maintain a competitive edge in a rapidly evolving technological ageLeast represented 5/11CEO Josh WeinsteinNO: at Carnival since 2002, started as General CounselSir Johathon BandNO: First Sea Lord and Chief of Naval Staff, the most senior officer position in the British Navy (2006 to 2009, when he retired); Admiral and Commander-in-Chief Fleet (2002 to 2006); Served as a naval officer in increasing positions of authority (1967 to 2002)Jason CahillyNO: CEO Dragon Group LLC, provides capital and business management consulting and advisory services worldwide; The NBA: CFO & Chief Strategic Officer; Goldman Sachs: Partner; Global Co-Head of Media and Telecommunications; Head of Principal Investing for Technology, Media & TelecommunicationsNelda ConnorsNO: CEO/Chair Pine Grove Holdings, a privately held investment company; CEO Atkore International, manufacturer of electrical, safety and infrastructure solutions; VP Eaton Corporation, electrical and automotive supplierLaura WeilNO: Founder Village Lane Advisory LLC, specializes in providing executive and strategic consulting services to retailers COO New York & Company, women's apparel and accessories retailer; CEO Ashley Stewart, women's apparel retailer; CEO Urban Brands, apparel retailer; COO AnnTaylor Stores, women's apparel retailer; CFO American Eagle Outfitters, apparel retailerAudit Committee: Oversee management's risk assessment processes to identify principal and emerging risks, including financial, IT, cybersecurity and non-HESS operational risksLaura Weil*: NOJason Cahilly: NOJeffrey Gearhart: NOWalmart Corporate Secretary and lawyerStuart Subotnick: NOCEO at Metromedia Company, wireless/communications, until 2010; Carnival director since 1987 Health, Environmental, Safety and Security Committee: Oversee management's processes to identify principal and emerging health, environmental, safety, security and sustainability-related risks, including those related to ship operations and cybersecurity, RAAS health, environmental, safety, security audits, IAG and external investigations into significant ship incidents, and health, environmental, safety, security-related hotline complaints, and assess the steps management has taken to minimize such risks.Sir Johathon Band*: NONelda Connors: NOHelen Deeble: NOFormer CEO P&O Ferries Division Holdings, shipping and logistics businessKatie Lahey: NOExecutive Chair Korn Ferry Australasia, leadership and talent firmMicky Arison (75%): Exec Chair and former CEO and 7% stockholderThe CEO Pay Ratio1,063:124 retail CEOs made as much in a day as their typical employee earned in a year — and a big one didn't. WHO DO YOU BLAMEThe separation of CEO and Chair: Hamilton E. James Chair/Ron Vachris MMNot uniqueOnly 50% of the board is men. WTF?uniqueOne share = one voteNot uniqueState of HQ = WashingtonAlso StarbucksState of Inc = WashingtonAlso StarbucksPledge of allegiance to stakeholdersCostco generally has: Higher wages; Better benefits; Lower turnover; Higher sales per employee.Industry-leading employee compensation AND Self-imposed low-margin pricing philosophyWalmart only low-margin pricingOther comps:Todd Vasos of Dollar General, Shane O'Kelly of AutoZone, Gerald Morgan of Texas Roadhouse, Jack Sinclair of Sprouts Farmers Market, William Stengel of Genuine Parts Company, Michael Creedon of Dollar Tree, Ronald Sargent of Kroger, Lauren Hobart of Dick's Sporting Goods, Joshua Kobza of Restaurant Brands Inc., Kecia Steelman of Ulta Beauty, Scott Boatwright of Chipotle, Ted Decker of Home Depot, Bob Eddy of BJ's Wholesale Club, Corie Barry of Best Buy, James Conroy of Ross Stores, Chris Turner and David Gibbs of Yum Brands, Chris Kempczinski of McDonald's, Marvin Ellison of Lowe's, Brian Cornell of Target, Ernie Herrman of TJX Companies, Doug McMillon of Walmart, Brian Niccol of Starbucks, Hal Lawton of Tractor Supply Co, Laura Alber of Williams-SonomaFigma Gets an Activist Investor. Exhibit A on Why Companies Don't Want to Go Public. Figma's first year as a public company hasn't gone well. Findell Capital Management said it needs to take steps to shed its unwarranted reputation as an artificial-intelligence “loser.” WHO DO YOU BLAME?Figma founder and CEO Dylan Field: Owns 10% of shares but 72% of voting power: Class B shares worth 15 votes per shareDylan owns 158 Class A Shares (or 0.00003556% of 444,278,887)And Chair$5B net worth$865M total summary compensation in 2025; $91M in 2024Nominating Agreement:Figma must nominate Dylan Field to be a director and include him in the proxy statementThe company must use its resources to back him up and actively convince other shareholders to vote for him In response to a question about how he was going to change the world, Dylan said he was going to build better software for drones.Bro fest sausage party2 of 9 directors are womenTop 5 NEOs all dudesPeter ThielForced Dylan to drop out of Brown for a dumb fellowshipVC Blowhardiness on the BoardVC dude John Lilly (Greylock): Lead Independent Director2nd longest tenure (2014)Member of the Audit Committee; Member of the Nominating Committee (only Lilly and Rimer)VC dude Andrew Reed (Sequoia)Director at debt-maker Klarna Group (also way down since IPO): down roughly 54% from its initial $40.00 IPO price, and down nearly 68% from its all-time highMember of the Compensation Committee (which modeled Dylan's pay package after Elon Musk)VC dude Danny Rimer (Index Ventures)Director since 2014B.A. in History and Literature from HarvardMember of the Compensation Committee (which modeled Dylan's pay package after Elon Musk)Member of the Nominating Committee (only Lilly and Rimer)Luis von AhnDuolingo co-founder and CEO2025: shared an internal email outlining Duolingo's new "AI-first" strategy where Duolingo would “gradually stop using contractors to do work that AI can handle”Stated that "AI is a better teacher than humans" and that the future role of teachers would be reduced to providing "childcare."Blamed the controversy on a "lack of context" in his original statements"AI-First" memo goes viral: $389; today $118MATTDanone, Starbucks shine in methane-reduction rankingDanone is the only company in the group aligned with the Global Methane Pledge, an initiative backed by 150 countries that targets a 30 percent reduction in global levels of the gas by 2030. The French multinational also leads the pack in progress toward its target, having come close to hitting it five years ahead of schedule.WHO DO YOU CREDIT?Chair of the CSR committee Lise Kingo (9% influence), one of three directors tagged as merit directorsmaster's degree in Responsibility & Business from the University of Bathbachelor degrees in Religions and Ancient Greek Artbachelor's degree in Marketing and Economicscertificate as International Director from INSEADEx Novo Nordisk environmental affairs, internal audit, compliance, human resources, communication, branding and sustainabilityHelped create the UN SDGs and the UN Global CompactSomehow only bats 559 on carbon intensity (career) and 415 for scope 1/2 (career)Also, using deference metrics, the ONLY DIRECTOR tagged as fully independentEmployee rep member of the CSR committee Bettina Theissig (5% influence) and the employees of DanoneThe committee charter mandates employees get a say: At least two thirds of the CSR Committee must be independent, as defined by the AFEP-MEDEF Code. At least one Director representing employees must be a member of the Committee.In France (Danone's domicile), the European Investment Bank found that French employees were the most aware of environmental issues - 82% of French employees said they were highly concerned about environmental issues, highest in EuropeLead Independent Director and chair of the Nom/comp committee who put together the comp plan, Valerie Chapoulaud-Floquet15% influence, second to the 18% influence CEO (democracy!!), got 99.16% shareholder approval in April (even as CEO got 89.73% approval and pay got 93.19% approval)20% of short-term pay and 30% of long-term pay is based on hitting sustainability targetsWhen you pay a CEO to do a thing, they are more likely to do a thingEx-CEO Emmanuel FaberOusted in 2021 by the board of directors and activist investors, he transformed Danone into an “enterprise a mission” (a French version of a B corp)Investors voted 99% in favor of the move and a year later ousted Faber, the board resigned, and the new board and CEO are basically moving back towards being environmental leaders because it paid offShort term share price laggedHe said in 2024 that nature is “at the core” of Danone, It took the stock 3 years from Faber's ousting to return to Faber levels - and in the meantime, they were sued for plastics and emissionsIsn't this HIS win?Current CEO Antoine de Saint-AffriqueBecause CEOGM Board Director Jonathan McNeill Stepping DownCEO of DVx Ventures. Ex COO at Lyft Inc. and ex president, Global Sales, Delivery and Service at Tesla, current director at Lululemon, GM director since 2022, on the Governance and Corporate Responsibility committee and Risk and Cybersecurity committee.We know that half of boards on average think someone on the board should be replaced - did the GM board not like McNeill?WHO/WHAT WOULD WE BLAME FOR PUSHING MCNEILL OUT?Outsider dude bro DRLet's be honest, McNeill worked at much more… modern?... companies than GMThe board is OLD SCHOOL - ex Northrop Grumman, ex Visa, ex Lazard, ex HP, ex eBay, ex Novartis, ex Walmart, other directorships at Goldman, Huntsman, P&G… these are professional, insular boardsMeanwhile, he's investing as a VC in AI, other auto/mobility startups, comes from boards that are bro founder lead (Tesla, Lyft) He's invested in AI, crypto, heavy tech, intertwined with VCs all overNot deferential enoughBarra is connected to 94% - THE ENTIRE - boardMcNeill has the highest network power on the board at $9tn, higher than even Mary Barra (who is super connected), but is NOT a power player in the board community of GM - the dominant board communities for GM are massive blue chip US companies, where McNeill has deeper connections in smaller IT/tech focused companiesHe doesn't need the pay, he gets nothing for the connections really, he has connection to Barra but his network is different - was he too independent?Pissed he doesn't have enough influence McNeill has the LOWEST influence on the GM board at 4%He's relatively new, younger, working as a VC where you have a lot of power of capital allocation“I don't need this shit” effect?Too many womenMcNeill's dvX ventures portfolio team is 6 dudes and 1 womendvX entire operations staff is two woman - guess what they do“Chief of Staff” (ie, HR)Executive Assistant (yes, listed on the team)Board is 2 women, 3 men (McNeill not on board)This one seems unlikely I guess?Too busy, meh, move onOne of dvX portfolio companies is curbee, with GM Ventures' Kurt Baumgarten on the board (and the dvX co-founder is founder of Curbee)McNeill on at least 3 of his portfolio boards or advisory committees, plus LULU and GM…

Is per-seat pricing dying a slow death, and is your SaaS expense structure ready for its replacement? In episode #373, Ben Murray breaks down the shift from per-seat subscriptions to usage and outcome-based pricing, and what it means for your finance org. Bloomberg projects subscription pricing falling from 60% to 30% of SaaS models over the next decade, while outcome-based pricing climbs from 10% to 60%. This is no longer a thesis on a slide. GitHub, Salesforce, Zendesk, Intercom, Figma, HubSpot, and others are already repricing, and public companies are reporting AI ARR in the hundreds of millions. If you cannot answer what your AI margins are when the board asks, you are already behind. See exactly how legacy SaaS leaders are repricing, from Zendesk charging per automated resolution to Salesforce billing per AI conversation plus flex credits, and what GitHub's June 1 move to token-based billing signals for the rest of the market. Understand why a single bucket of cloud hosting that blends traditional infrastructure with inference spend leaves you blind, and what instrumentation to put in place before budget season. Learn the questions your board will ask about AI margins, and how to answer whether low-usage customers are quietly subsidizing your heaviest users. Get the case for reconvening your pricing committee now to align product roadmap, AI features, and the expense framework that tracks them. Know which AI unit economics to track by revenue stream and by usage bucket so you can defend margin as your pricing model changes in real time. Listen now and put the tracking framework in place before the AI margin questions land on your desk. Resources Mentioned Ben's blog post: https://www.thesaascfo.com/saas-per-seat-pricing/ New course on AI unit economics and metrics: https://www.thesaasacademy.com/ai-finance-metrics-saas

n this special segment of The Full Ratchet, the following Investors are featured: David Ulevitch of Andreessen Horowitz Jake Saper of Emergence Capital Sandesh Patnam of Premji Invest Each investor highlights a situation where they decided not to invest, why they passed, and how it played out. The host of The Full Ratchet is Nick Moran of New Stack Ventures, a venture capital firm committed to investing in founders outside of the Bay Area. We're proud to partner with Ramp, the modern finance automation platform. Book a demo and get $150—no strings attached.   Want to keep up to date with The Full Ratchet? Follow us on social. You can learn more about New Stack Ventures by visiting our LinkedIn and Twitter.

In this episode, we debrief Telehash #4 and dig into the open-source future of Bitcoin mining. We share behind-the-scenes metrics from HydraPool's six-and-a-half–hour live stress test, including 30.8 zettahashes processed, an average of 1.32 EH/s, a peak of 2.495 EH/s, 2,231 workers, 59 unique users, and an impressively low ~1% server CPU under >2,000 connections. We explain why rejection rates under ~2% matter, how stale and “difficulty too low” shares differ in solo vs pooled mining, and how Stratum “suggest difficulty,” plus our d= and h= password parameters, help right-size starting difficulty—making Telehash inclusive for both exahash renters and single-chip Bitaxe miners. We also touch on leaderboards, loyalty uptime rules, and shout out supporters like Elektron Energy, Compass, Saaz Mining, and Abundant Minds. From hardware to policy, we discuss Bitaxe UX updates (LVGL, Figma-driven UI, external display/knob), DOOMAXE fun, and industry standardization—from firmware and pools to racks, cooling, and power—arguing that open reference designs cut costs and risk for everyone. We cover GridPool's “winners list” approach to decentralized variance smoothing, the Patoshi/extra nonce story, vardiff dynamics, and privacy-conscious VPN mining. We reflect on immersion's decline versus hydro, ASIC roadmap realities and slowing efficiency gains, the supply-chain and security stakes (FCC Wi‑Fi moves, vendor backdoors), and why nonprofit coordination via the 256 Foundation matters for open firmware, dev kits, and reference designs. We close with community invites, next steps for Telehash #5, and a call for ASIC makers and big miners to collaborate on open standards that benefit small and large operators alike.

Episode web page: https://bit.ly/42TFjM4 Episode summary: In this episode of Insights Unlocked, Manú Bartlett speaks with Pedro Hernandez, advocacy manager for EMEA and Latin America at Figma, about how AI is reshaping design, leadership, and the future of creative work. Drawing from more than 15 years of experience across UX, product design, and design operations, Pedro shares why the industry is moving beyond a narrow focus on speed and toward a deeper balance between experimentation, craft, and human-centered thinking. Pedro explores how design communities across Europe and Latin America are adapting to AI in different ways, why leaders must rethink how they evaluate design work in the age of rapid prototyping, and how “craft” now means being intentional, critical, and thoughtful when collaborating with AI tools. He also discusses the growing importance of soft skills, curiosity, and research as teams become more multidisciplinary again. The conversation also dives into how leaders can stay connected to customer needs while navigating AI-driven workflows, why experimentation matters at every level of an organization, and how Figma is researching what design leaders truly need from modern collaboration tools. You'll learn: How AI is changing the relationship between speed, experimentation, and design craft Why the best design leaders are learning to balance rapid production with intentional decision-making What “craft” means in the era of AI-powered design workflows How Latin American and European design communities are approaching AI differently Why curiosity, research, and soft skills are becoming more important in modern product teams How leaders can stay closer to customers while adopting new AI tools and workflows Why the future of design may look more multidisciplinary and collaborative again Resources & links Pedro Hernandez on LinkedIn (https://www.linkedin.com/in/pedrohernandez/) Figma's Config (https://config.figma.com/) Figma's State of Design report (https://www.figma.com/state-of-design/) Manú Bartlett on LinkedIn (https://www.linkedin.com/in/manubartlett/) Nathan Isaacs on LinkedIn (https://www.linkedin.com/in/nathanisaacs/) Learn more about Insights Unlocked: https://www.usertesting.com/podcast

Web funnels are like teenage hex.Everyone claims they are crushing it. Almost nobody really has a clue.Elise Zareie spent last year actually building them.She has been in UA since 2019. Last year she became a part-time product manager just to ship funnels herself. That meant learning Figma, coordinating designers, front-end developers, back-end developers, and analytics teams. Running QA. Shipping it. Then using AI to test faster than she ever could before.In this episode she talks through what the process actually involves, the three levers that move the needle in any funnel, the one benchmark she watches obsessively on landing pages, how she uses Claude to generate full funnel copy from screenshots of top-performing creatives, and why AI visuals are making consumers more suspicious, not less.Key topicsWhy web funnels are harder to build than most people think and what the process actually looks likeHow to identify the dominant funnel in a vertical before building anythingThe 40% page-one to page-two benchmark and what to do when you fall below itHow to match landing page copy to ad creative using UTM tagsHow Elise uses Claude to generate funnel copy and assessment questions from top-performing creativesHow AI helped her launch a male-specific funnel in two weeks for an app with 80% female usersWhy AI-generated visuals are creating consumer suspicion and what to do about it

Take the 2026 AI Engineering Survey and get >$2k in credits and AIE WF tickets!This was recorded before Railway suffered a major GCP outage on May 19, despite being a multi-AZ, multi-zone mesh ring, with HA fiber interconnects between their Metal GCP AWS, because workload discoverability was unintentionally still tied to GCP. All has been resolved with a post-mortem.Railway did not start as an AI infrastructure company.It was founded in 2020 years before agents became the default way people thought about deploying software. Jake Cooper, formerly at Bloomberg and Uber, started Railway with a simple obsession: the activation energy to ship something to production should be near zero. Push code, get a URL, iterate. No Docker files, no Kubernetes manifests, no Ansible scripts stacked on Ansible scripts.For years, this was a slow grind. Railway spent its first 18 months hand-acquiring its first 100 users with Jake personally greeting every Discord signup on a second monitor.Today, Railway has raised $124m and is growing very fast. A 35-person team supports 3 million users, adding roughly 100,000 signups a week. Their bare metal data centers have a 3-month payback period vs. renting in the cloud, with 70% margins funding aggressive cloud bursting when needed. The servers they own have actually appreciated in value as RAM prices have climbed basically meaning the value of their hardware now exceeds the capital they've raised.From rebuilding Railway's network overlay over a weekend to moving the vast majority of workloads onto its own bare metal data centers, Jake Cooper is trying to build a new cloud for an agent-native world. In this episode, Railway's founder and “conductor” joins swyx and Alessio to unpack why the next era of software infrastructure is not just “Heroku but newer,” what agents need that humans did not, and why the old deployment loop of Git, PRs, CI/CD, and static cloud resources may be heading for a rewrite.We go deep on Railway's infrastructure stack: own-metal data centers, three-month cloud payback periods, cloud bursting, data center debt, Railpack, Nixpacks, Temporal, feature flags, Central Station, content-addressable filesystems, agent-safe production forks, and why the CLI may become more important than the canvas in an agent world. Jake also shares the founder journey behind Railway, how the company survived losing $500K/month, why it now serves millions of users with only 35 people, and why he believes the pull request is dying.We discuss:* How Railway went from a slow six-year grind to adding 100,000 users a week* How Railway thinks about agents as the next dominant software species* Why agents need version control, observability, compute, storage, and orchestration at 1000x scale* The economics of Railway's own-metal data centers and three-month payback* How Railway uses cloud bursting while scaling its own infrastructure* Why data center debt can be a better tool than venture debt for infra startups* Central Station, Railway's internal system for clustering customer feedback and incidents* Why responsible disclosure and over-communication matter for platforms* Why feature flags, progressive rollouts, and shadow traffic are essential for agents* Temporal's strengths, pain points, and why workflows matter for agents* Railpack, Nixpacks, Nix, and lazy-loaded content-addressable filesystems* Why “cattle, not pets” may change if you can clone the pets* Why Railway is building a new cloud from scratch instead of copying hyperscalers* The solo founder path, focus, writing, and how Jake thinks about company buildingRailway:* Website: https://railway.com/* X: https://x.com/RailwayJake Cooper:* LinkedIn: https://www.linkedin.com/in/thejakecooper/* X: https://x.com/JustJakeTimestamps00:00:00 Introduction: What Is Railway?00:02:07 Jake's Path to Railway00:06:13 Railway's Six-Year Growth Story00:08:52 Rebuilding the Business After the Free Tier00:11:17 Agents as the Next Software Platform00:13:29 Railway's Infrastructure Philosophy00:15:42 Bare Metal, Cloud Economics, and the Compute Crunch00:17:22 Cloud Bursting and Five-Cloud Networking00:20:20 Data Center Debt and Infra Financing00:23:31 Data Centers in Space00:25:24 What Agents Need From Infrastructure00:28:24 CLIs, Canvas, and Agent-Native UX00:35:15 Central Station, Incidents, and Responsible Disclosure00:40:30 Safe Rollouts, SRE Agents, and Production Forks00:45:00 AI SRE, Specs, Code, and Tests00:48:24 Self-Replicating Infrastructure and the New Serverless00:53:18 Heroku, Temporal, and Workflow Engines01:04:07 Railpack, Nixpacks, and Lazy-Loaded Filesystems01:06:01 Coding Agents, Token Spend, and Roadmap Acceleration01:10:56 The Pull Request Is Dying01:12:28 Feature Flags and the Agent-Era SDLC01:16:15 Cattle, Pets, and Cloning Machines01:19:29 Solo Founder Lessons01:24:12 Focus, GPUs, and Building a New Cloud01:28:20 Closing ThoughtsTranscriptAlessio [00:00:00]: Hey, everyone. Welcome to the Latent Space Podcast. This is Alessio, founder of Kernel Labs, and I'm joined by Swyx, editor of Latent Space.Swyx [00:00:10]: Hey, hey, hey. Today we're in the studio with Jake Cooper of Railway.Alessio [00:00:14]: Conductor of Railway.Swyx [00:00:15]: Conductor at Railway. Yeah.Alessio [00:00:16]: Choo-choo.Swyx [00:00:17]: Do you actually have that anywhere, like on your business card?Jake [00:00:20]: We call some of our volunteer moderators conductors. I don't have a business card. We're not that big yet. At some point I will. I got handed a nice business card from the Supermicro folks, and I was like, “Damn, this is pretty official.”Swyx [00:00:30]: Business cards are coming back.Jake [00:00:32]: They're cool. They're hip. The conductor thing is good. We're trying to figure out what we want to call each other internally. Some people think it's super cringe and say, “You don't need a name for people internally.” Some people want to call each other something. We still don't have a really good one.Jake [00:00:55]: We've got New Railcrews, Trainiacs. Nothing has stuck yet.Swyx [00:01:00]: I like Trainiac. Trainiac sounds good. Railwayians. For those who don't know, what is Railway? Let's give people a crisp definition up front.Jake [00:01:09]: Railway is the easiest way to ship anything. You go to the canvas, or you talk with Claude, and you say, “Deploy a Postgres instance, deploy my GitHub repository, run this code,” and you're off to the races.Swyx [00:01:22]: You've got a nice animation on the landing page.Jake [00:01:24]: Thank you. None of my work, by the way. They don't let me touch the design stuff anymore.Jake [00:01:25]: We want to make it trivially easy not just to deploy things, but to evolve applications over time. Most tooling right now stacks entropy on top of entropy: Docker, Kubernetes, Ansible scripts, and all these other things. If we can version all of your software and keep track of all the changes, then we can make it trivial to clone environments, fork into a parallel universe, get copies of production data, get copies of any services, make changes, validate them, and collapse them back in without reproducing everything across a staging environment.The Railway Origin Story: From Uber Systems to a New CloudSwyx [00:02:07]: I was looking at your background: Bloomberg, Uber. Nothing immediately stands out as, “This guy is going to found the next great platform as a service.” What prepared you for Railway?Jake [00:02:21]: It was curiosity to keep going deeper. I started out on front-end stuff, working on Wolfram Mathematica and porting it over. Then I briefly moved to Bloomberg, then toward Uber and distributed systems, taking the Jump Bikes systems and moving them to a distributed system built on top of Cadence, the pre-Temporal Temporal.Swyx [00:02:44]: Which, by the way, I'm happy to talk about, pros and cons.Jake [00:02:48]: Totally.Swyx [00:02:51]: But let's do the Railway story.Jake [00:02:52]: It has been a continual step of wanting an experience. Whether it's walking up to a bike, unlocking it, and having it work frictionlessly, or something else, the depth required to make that happen follows from the experience. A lot of the work I do, and a lot of the team does, is in service of that experience. We fundamentally don't care how deep we have to go. We will swim to the bottom of the swimming pool to get the experience.Jake [00:03:17]: I don't have a physics PhD. I did an EECS degree. It has always been about figuring out the next step: how do we get there? That's what led to starting Railway for that experience and then moving all the way to bare metal data centers. I was adding patches to the kernel this week to get the experience there because I can see how much better it can be.Swyx [00:03:49]: Other patches to the Linux kernel this week?Jake [00:03:51]: Yeah. Not upstream. Our fork.Swyx [00:03:52]: That's a flex. Railpack? No, this is different. This is the OS on top of Railpack?Jake [00:03:57]: No, this is an actual kernel patch. It's always literally: what do we have to do to get that experience? Then figure it out. Anything is figureoutable.Swyx [00:04:10]: Would you send the patch upstream, or does it not fit other use cases?Jake [00:04:13]: Maybe. We have to work out the experience internally. It has to do with the storage layer we're building for some of the agentic stuff. Maybe it'll be useful upstream, but it's deeply useful for us internally.Open Source, Forks, and Non-Deterministic VersioningSwyx [00:04:29]: You mentioned open source before. How do you think about starting from open source, and then coding agents letting you do a lot more from forks of it?Jake [00:04:38]: GitHub's original sin is that it's almost a series of broken pointers. You have this thing, then you clone it, and now you've lost the whole upstream. How do we make it trivial for people to modify really small pieces of it?Jake [00:04:51]: We think of Git in a discrete sense: I've either made a change and merged upstream, or I haven't. What would it look like if it were percentage-based, a little more non-deterministic, or a stream of changes that users traverse as a percentage rolled out in general and then rolled all the way up?Jake [00:05:13]: We have the open-source kickback program and let you deploy templates because we want to make it trivial for people to version these shards over time. It solves a large problem around authentication, authorization, and security. NPM has a way to define, “Don't take any new packages.” The ideal end state is that you roll out progressively to users with the minimum impact zone and continue rolling up. JPMorgan should probably be the last one on the patch line, for all our sakes, because our money and livelihoods are there.Jake [00:05:53]: It's okay if Johnny Vibe Coder gets a broken patch because there's so much entropy in the system that the rubber has to meet the road at some point. You have to test at varying levels.The Long Grind: First Users, Free Tier, and Making the Business WorkSwyx [00:06:13]: I wanted to pull up this glorious chart, which is your usage or number of daily signups?Jake [00:06:22]: Daily signups, I think.Swyx [00:06:24]: You started six years ago. It was a slow grind, and now you're on a rocket ship. You say, “Don't doubt your fight and don't quit.” Maybe pick out certain points that were key inflections for the company.Jake [00:06:40]: At the start, it's about getting your first 100 users, hell or high water. We had a website and a support link. The support link was the Discord channel. I had notifications on with two monitors: the monitor I was working on and the other monitor with Discord. If anybody came in, I was immediately like, “Hey, how's it going?” It was rare, so getting those first 100 users to come back was the start.Jake [00:07:14]: Then you build a consultancy factory because users want all these things. You have to go back to the board and ask, “What is the actual product offering I want to build on top of this?”Jake [00:07:28]: VCs want charts that always go up and to the right, but in reality you don't necessarily want charts that look like that. For us, there have been periods of expansion where we add features to test use cases, and periods of compaction where we ask, “If the experience we have is good, how do we make it significantly better?” Maybe we strip out features that don't fit our ICP anymore.Jake [00:07:57]: The boom from 2022 to 2023 came from the free tier. Everybody under the sun was using it.Swyx [00:08:09]: A lot of Reddit bots and Discord bots.Jake [00:08:12]: And crypto miners. When you build an open product on the internet where anybody can sign up, the internet is a horrible place with so many things. You go through periods of asking, “How do I reach as many people as possible?” Then, “How do I fit the exact use case for the people who really matter and are really excited about this specific thing?”Jake [00:08:39]: Then there was a two-year period of making the actual business work. During the free-tier era, we were losing about half a million dollars a month.Swyx [00:08:59]: On a $20 million bank account.Jake [00:09:02]: On a $20 million bank account with maybe $50,000 a month in revenue. That's a horrible business. I don't know how anybody invested. But you have to go through it and say, “We have an experience people love, but the business has to work.”Jake [00:09:17]: There are two schools of thought. You can run the horrible business all the way up with bad margins, or you can go back and make it work. We've always wanted a super lean team. We're 35 people right now. It's very small.Swyx [00:09:36]: Supporting three million already?Jake [00:09:38]: Yeah. We're adding 100,000 users a week right now, so it's growing fast. We don't want to add headcount for the sake of headcount or throw bodies at problems. We want to build systems. It's hard to build systems during expansion because you're adding things to the system because people are asking for them or things are breaking.Jake [00:10:00]: We had to cut off the free users for a little while, rebuild the business, and make sure it worked. We want to reach as many people as possible because software is important. It's become difficult to create things in the physical world, so it's important to make it easy for people to build in the virtual world and have access to creation. But there are legs to that journey.Jake [00:10:30]: You can see divots in the charts. If you follow between 2025 and 2026, it's either summer or winter. People go on holiday with family.Swyx [00:10:50]: It affects that much?Jake [00:10:51]: Yeah. It's kind of B2C and kind of B2B. People are shipping constantly, then they stop. Our activation curve now shows more people activating on weekdays because we have more business users, so it smooths out over time.Agents as the New Interface to DeploymentSwyx [00:11:17]: Was there a point where you started prioritizing AI development or agent development?Jake [00:11:24]: We've prioritized agentic as a top-of-funnel thing. Over the last six months, we've deeply prioritized agentic as a mechanism to build and deploy things because we believe the curve is so steep and that is how people will build and deploy software.Jake [00:11:42]: It almost fundamentally doesn't matter whether this is dot-com or not because we're all on the internet anyway. If agents are going to deploy a bunch of things and we hit an inference wall at some point, we'll fix those problems. The dominant species over the next 10 years is that we've moved from assembly to C to C++ to JavaScript to words. You're going to need to close that loop.Swyx [00:12:13]: When you say this is dot-com, did you mean buying the domain, or the general case?Jake [00:12:17]: I mean the dot-com era, when companies had a huge run-up because people understood the internet was important. Then they hit bottlenecks, fundamental laws of physics, math didn't work, and everybody came back down to earth. But it didn't matter because the internet became so impactful. If you operate on a long enough time horizon, you should build these things anyway because you can see where it's going.Jake [00:12:45]: That's where I think a lot of agent stuff is. You get to a point where you're running thousands of agents in parallel. What is the inference cost? What is the compute cost? How do you make that efficient? How do you coordinate all this? We have issues coordinating humans; we don't even have good tooling for that. Now we have to figure out how to get agents to coordinate, safely version changes, and know when to raise their hand for someone to intervene. Otherwise it becomes an interrupt factory.Railway's Infrastructure Thesis: Network, Compute, Storage, and MetalSwyx [00:13:19]: Let's go right into the technical side. What are the core infrastructure or architectural beliefs of Railway that allow you to do what you do?Jake [00:13:29]: The primitives matter a lot for us. We need network, compute, storage, and orchestration around it. You need control over a lot of those things. We've talked a lot about how we don't really use Kubernetes because we want higher-order control to place workloads in very specific places.Jake [00:13:48]: The reason is that you have to be very efficient with agents: memory reuse and all these other things, or you're going to massively blow up your cost structure. Being able to rack and stack your own servers and build your own metal unlocks performance and cost. Experiences where you're running 1,000 agents in parallel are not massively cost prohibitive.Jake [00:14:13]: Token use and compute use are blowing up. Over time, those things have to get a lot more efficient. You can get a lot of margin to make those experiences solid by building your own metal. That's all in service of offering a differentiated experience to as many people as humanly possible.Swyx [00:14:51]: You have a data center in Singapore.Jake [00:14:53]: Yeah. We have two in every other region now. In Singapore, we're adding a second one in Q3.Swyx [00:14:58]: What's it like? I've never built a data center. Do you go to Equinix and say, “I want some slots?”Jake [00:15:05]: Yeah. Equinix. You basically go and say, “I want power and I want a cage.” They say, “Great, here's what it's going to be.” You rent the cage for a period of time, fill it with racks and servers, and hook up internet to it. That's all the pieces.Swyx [00:15:36]: Then you handle everything else.Jake [00:15:37]: You handle everything else.Swyx [00:15:39]: What's the math versus clouds doing it for you?Jake [00:15:43]: If we rented in the cloud, our payback period when we go to metal is about three months.Swyx [00:15:50]: Which is crazy.Jake [00:15:51]: It's nuts. That's four years of depreciated hardware. You're going to see a lot of this compute crunch because hyperscalers are buying up a lot of stuff. We're working directly with OEMs, resellers, and people building these machines: Supermicro, Dell, and others.Jake [00:16:11]: Upstream, there's a bunch of supply pressure. When we raised our last round, between deploying capital for servers and now, the amount of money we've raised is less than the amount of money we have in the bank plus the value of the servers because the servers have appreciated as RAM has gone up. It's nuts how valuable hardware has become.Jake [00:16:50]: If you look at hyperscalers, they deployed around $80 billion of capital expenditures this year, and next year will be more. That's a massive infrastructure build-out. You look at that and think it's crazy that they're spending way more than the Manhattan Project. But if every person is going to run dozens or hundreds of agents in parallel, you have no conceptual idea how much compute is required to make that experience happen, even if you're deeply efficient and sharing resources. And that doesn't even count inference.Swyx [00:17:22]: How do you plan the build-out? The growth chart is so vertical. Are you usually at 100% utilization as soon as racks are live? How far ahead are you planning?Jake [00:17:33]: We still maintain cloud presence for bursting. We work with AWS, GCP, and a few other clouds. We can rent, and then the moment we get space or power, we compact those workloads off the cloud. We started on the clouds, then built a system to migrate to our own metal. There's nothing that says you can't continually do that again, and that's exactly what we do. We never want to be compute constrained.Jake [00:18:09]: At the start of the year, we actually became compute constrained because one upstream provider wasn't able to give us quota at the rate we needed, and the hardware was slower. I spent a weekend rebuilding our entire network overlay so we could straddle five clouds: Oracle, AWS, ourselves, GCP, and one other one. We can do more than that now.Jake [00:18:38]: We got into a spot where we were trying to pack instances tight because we couldn't get enough compute. That led to a few reliability issues, which are now past us. I made a tweet pointing out that it's becoming harder and harder to acquire compute at the rate these models need to acquire compute. We got bit by it.Swyx [00:19:15]: How do you think about pricing knowing you might not have your own metal available at all times? Are you pricing assuming you need extra margin if you end up going into the cloud?Jake [00:19:26]: Because we've built out our metal data centers, our margins on metal are around 70%. We can deeply subsidize the cloud business if we want to scale at a reasonable rate. We have a few levers: metal, which makes the margins; cloud burst; debt to buy servers; and venture capital. It's an interesting operational problem: how much cash do we have, how much should we raise, how quickly can we deploy it, and can we scale revenue as quickly as we scale compute?Jake [00:20:05]: If we continue making it trivially easy for people to build and deploy, then the faster we close that loop and the more operationally excellent we are with capital, the faster the business can scale. It's almost a straight linear deployment rate.Financing Infrastructure: Hardware Debt, VC, and Operational LeverageSwyx [00:20:20]: I think infra startups raising debt is a tool people don't utilize enough or know enough about. What can you tell us about that? Is it secured against your CPUs?Jake [00:20:32]: It's secured against our hardware.Swyx [00:20:37]: What rates do you get? Who are the lenders?Jake [00:20:39]: We pay prime plus a spread, and we can refinance any of the debt as rates go down. The terms are pretty good. The unfortunate thing is that Twitter has no nuance, so people say, “Venture debt bad.” But as with all things, there are specific tools and areas where you can be deliberate instead of using one tool as a hammer. Venture capital is not the hammer for everything. You have to explore and figure out what works.Swyx [00:21:12]: VC is usually the most expensive financing you can get.Jake [00:21:15]: Yeah. I also think people think about VC incorrectly from a capital-raising perspective. Most people think, “How do I raise as much money as possible from whoever is probably the best I can get at that time?” That's close to right, but what we've tried to do is figure out what unfair advantage we can buy with that equity.Jake [00:21:34]: It's the most expensive equity you're going to give away at that point in time, assuming the company keeps getting better. How do you use it to work with someone stellar who complements you? In the seed stage, I had never started a company. Ray Tonsing had good advice, and I could text him all the time. He was really fast. Awesome.Jake [00:22:01]: Then with John and Erica at Unusual, they said, “You roughly know what you're doing building a product. We'll mostly leave you alone and be available for advice.” Amazing. Then we got to Series A and the business was an operational tire fire because we didn't know how to scale a business. Work with Erica, and Jordan is over at Redpoint, so bonus.Jake [00:22:28]: Now we've raised from TQ and FPV as we're moving into enterprises. Every step of the way, we've asked: who can we partner with at this specific time to unlock the next section of the journey? I don't know enterprise sales. As an engineer, I can eyeball what features we might need, and we have wonderful people internally who can help. But you want boardroom dynamics where everyone is aligned and asking, “How do we win this?” instead of bickering about strategy.Data Centers in Space and the Physics of ComputeSwyx [00:23:31]: You had a tweet about data centers in space. Why no data centers in space?Jake [00:23:37]: It's not “no data centers in space.” My hot take is that I think it is solvable. I've just never seen anybody solve it.Swyx [00:23:49]: You said, “How are you going to dissipate that much heat in a vacuum?” You're making a physics claim.Jake [00:23:55]: I haven't seen anybody prove how you're going to dissipate that much heat in a vacuum. It doesn't mean it's not possible. It just means nobody has brought it up yet.Swyx [00:24:05]: Astrophage.Jake [00:24:06]: I don't know what that is.Swyx [00:24:07]: The Martian thing. Okay, you're very logical.Jake [00:24:09]: It could work. A lot of people are putting the cart before the horse. They say, “We're going to put data centers in space.” Okay, but how? “We have time to figure it out.” It's like in The Martian where they ask how they're going to intercept something and say, “We'll figure it out.”Swyx [00:24:36]: Making a bet on human invention is weird because you blind trust that it can be solved. But with physics, there are first-principles bounds you can put on it. Maybe not. Maybe you're asking to travel time or break a fundamental thermodynamic law.Jake [00:24:57]: I don't know how VCs do this either. How do you know what's not possible and a grift versus what's possible but sounds completely insane? “We're going to put data centers in space.” Coin flip as to which it is, and I guess you'll know in 10 years. That's one cycle.What Agents Need: Versioning, Observability, and 1,000x ScaleSwyx [00:25:23]: Moving back to agents. The branching, fast spin-up, and orchestration you do feels like pre-work that happened to be exactly what agents want. What do agents want differently than humans?Jake [00:25:37]: They want the ability to version things. It's not that different; it materializes slightly differently. Agents want a way to test changes incrementally. Engineers have feature flags. Is there a reason agents can't use feature flags? I don't think so.Jake [00:25:54]: They want version control. Can we use Git or not Git? That one is up in the air. I think something outside Git will emerge for how we version these things over time. They need observability. You need to query what happened, when it happened, which steps failed, traces, logs, metrics, and all the rest. They need network, compute, and storage. They need to write files, save files, iterate on files, and snapshot file systems.Jake [00:26:25]: A lot of what humans needed is in line with what agents need. Branching and forking are not different; we're just moving 1,000 times quicker. It can look like you need something massively different, but what you need is something massively better than what existed. You need orchestration massively better than Kubernetes. You need networking probably better than Envoy. It goes all the way down the stack.Jake [00:26:55]: If the workload profile doesn't change so much as it gets massively compressed because you need thousands of these things, what assumptions change? etcd is going to melt. You need to replace it with something. You can go all the way down the stack and say, “That part has to change, that part has to change, and that part has to change.”Jake [00:27:19]: The interesting thing about the super-exponential curve is that you have to build systems where you can rip out those parts at any time because a new bottleneck might emerge. You get good at parallel agents, and a different part of the system breaks. So it's similar to what humans needed, but at 1,000x scale.Jake [00:27:55]: How do you do code review in the age of agents?Swyx [00:28:00]: You throw more agents at it.Jake [00:28:01]: You don't. But then who reviews for CVEs and all these other things?Swyx [00:28:07]: More agents.Jake [00:28:08]: And that's how we hit the inference wall. You can continually throw agents at the problem, but I think there's a limit to the number of agents you can throw at a problem.CLI, Agent Handles, and Closing the LoopSwyx [00:28:24]: You already had a CLI before it was cool. How is the shape of what you're exposing changing, if at all?Jake [00:28:28]: CLIs have always been cool. The CLI changes because we think about how to give Claude, Codex, ChatGPT, or any model a handhold.Jake [00:28:50]: A CLI is a single command: deploy, get logs, and so on. Things that were prohibitively annoying to humans are not annoying to agents. They're nice. If I handed you a CLI with 40 arguments and 600 flags, you'd think, “I'm never going to use all of this.” But if you hand it to an agent, it says, “This is excellent. I have so many handles to work with.”Jake [00:29:24]: If you're going to expose things to agents that way, you want as many handles as possible where they can get information, query dynamic information, and close the loop quickly. Most problems right now are about how to close the loop as quickly as possible. Where does the agent get stuck, and how can you remove that?Jake [00:29:49]: Telemetry is important. If you can tell where the agent gets stuck from the CLI and say, “12% of people deviate from the happy path because of this, and now I add this argument and drive it down to 2%,” you massively increase the rate of loop closure.Jake [00:30:03]: That's how we think about not just the CLI, but every point in the dashboard. It's a user journey: I hear about Railway. I get something deployed. I get my first green build or aha moment. I see an endpoint, logs, whatever. Then I iterate. The iteration loop is indefinite. The user wants to deploy a new thing, a Postgres instance, change code, and keep iterating.Jake [00:30:36]: If you focus on the iteration loops and what's blocking them from closing quickly, one thing we say internally is: you never want to be waiting on compute anymore. You always want to be waiting on intelligence. If you're waiting on compute, there's a bottleneck that needs to be destroyed because eventually that bottleneck becomes so large that another workflow emerges to change it.Jake [00:31:04]: We've built a product where you push code, build it, and so on. But I fundamentally believe the push-pull loop is going away. We'll get to a point where you make a small change in production, that change is versioned across your infrastructure, you're working alongside copy-on-write versions of your database and infrastructure, and then you merge it in and it's instantaneously live. That's the holy grail of loops. The push-pull-rebuild thing is a point of friction that we're removing entirely.Canvas as Output: Dashboards, Context Anchors, and HyperstructuresSwyx [00:31:43]: It's incredibly fast. If anyone hasn't tried it, that fast feedback is great. My hot take is that Railway was famous for its canvas, which visualizes your infrastructure and lets you manipulate it visually. But that was for humans. For the next phase of growth, Railway CLI is more important than canvas.Jake [00:32:05]: The canvas is funny because it's a mechanism to show changes over time. You're right that previously we used it a lot as an input. Moving forward, its goal is more like an output. You would go to the canvas, make changes, see them, and watch your infrastructure evolve. Now agents have access to the CLI and can make those changes. So the canvas becomes an output: what information does the human need at this moment to make suitable decisions about control requests? Do I approve this or not?Jake [00:32:57]: It also has to be an anchor for your context, a port in the storm. Think of it like layers in a file system. You start with a project, then drill down into services, then into a function or code, because you want to represent the entire thing not just in your head, but in the canvas. Other people can share that representation, think on the same wavelength, and move quickly.Jake [00:33:33]: A lot of organizations get in trouble as they scale because all the context lives in someone's head. “How does this microservice work?” “I have no idea; go ask this person.” Then you have whole categories of products built around context discovery. A lot of that melts away if you have a solid hierarchy and can infinitely nest services, code, context, and everything else all the way down. That's what lets you build these structures over time.Jake [00:34:18]: It's also what lets us build what I've called hyperstructures: things that are way bigger. You look at the Golden Gate Bridge and ask, “How did we build that?” There's a meme that we lost the technology. To some extent, yes, because the coordination that built those things evolved and changed. We lost some of the art of building structure as we jammed everything into Slack.Swyx [00:34:52]: But you jam everything in Discord.Jake [00:34:53]: Same point. It doesn't matter. It's message passing and interrupts, message passing and interrupts.Swyx [00:35:00]: So you're arguing there should be something better and more structured than Slack?Jake [00:35:04]: Yeah. For sure. I think Slack is awful, and Discord is awful too.Central Station: Context Routing, Support, and Incident ClustersSwyx [00:35:09]: This is the equivalent of my mom test. What have you done that has your solution to this?Jake [00:35:15]: Internally, we've built a tool called Central Station that aggregates all the context from our users. Every piece of feedback, every customer support item, everything gets aggregated into clusters. If an incident is brewing, we can determine how many users are affected and break off a discussion based on that.Jake [00:35:40]: That is more helpful than long-running channels where you're trying to decide which channel to put something in. If you can dynamically aggregate information and dynamically route it to the right person based on context, it works better. We know internally that these four people are close to networking. If we see a networking thing, we can drill it down to those four people. If it's with this part, we can look at the commits. This is no longer a manual process internally.Jake [00:36:13]: If you go to station or help.railway.com, that's why we built it. We wanted to scale with a massive amount of leverage by aggregating feedback.Swyx [00:36:27]: This is built in-house?Jake [00:36:28]: Yep.Swyx [00:36:29]: I remember helping out on this one with Angelo in 2023. You scale a lot with a very small team.Jake [00:36:38]: Yeah. We're about 10 times bigger now.Swyx [00:36:40]: You have your full developer code here? Very cool.Jake [00:36:44]: If you go to railway.com/stats, we expose this as a pub-sub-able thing. It's all real-time metrics. There's a way to get it as JSON somewhere if you care.Jake [00:37:01]: We're big on trying to build everything in public and talk about what we're working on. We've had issues in the past, and we'll say, “Here's how we're fixing these things.” We've gotten compliments and flak for incident reports. We're always trying to make them better and talk with people.Incidents, Disclosure, and Progressive RolloutsSwyx [00:37:20]: You had a big one recently. I liked that it was scoped to 3,000. You presumably used Central Station. Talk through what happened and how you address it internally as a team.Jake [00:37:38]: Internally, this one really sucked. It had to do with an upstream provider that didn't do the behavior it said it documented, which is unfortunate given they wrote the RFC for how the behavior should work. We rolled those things out, and Central Station caught it initially when a couple users said caches weren't invalidating. We turned it off immediately.Jake [00:38:03]: When you roll out to a large user base of three million people, you get a lot of disparate behaviors. We tested in staging and had tests, but we hit an edge case. We've hardened those systems, and now we can make that better. But it was a tough one.Swyx [00:38:39]: I always wonder how private disclosure is supposed to work if people find an issue. Are they supposed to contact you first? When you run a platform, these things will happen. What channels should people pursue to quietly resolve it before it becomes a bigger incident?Jake [00:38:59]: There's responsible disclosure. We err on the side of over-disclosing and letting you know something is wrong versus having your provider gaslight you. We've erred on sharing those things more publicly, even if they impact a small subset of users. That's a decision we've made internally. We have four values. One is honor. The honorable thing is to notify people to the widest degree at which they may have been affected or there was an issue, and then confront it head-on: why did it happen, what can we do better?Swyx [00:39:45]: Not the whole user base. That's because of incremental rollouts and other things?Jake [00:39:50]: Yeah. Progressive rollouts.Swyx [00:39:54]: That should be the norm at all large platforms.Jake [00:39:58]: It should. A variety of companies do this. There's the quote that Meta runs 10,000 different versions of Meta. To our earlier point about agents, they need the same thing. They need shadow traffic and all these other things. We've built so much ceremony around production being sacred that we need to make it trivially easy to test different behaviors in a safe environment. Then you can make mistakes in a safe environment.Safe AI SRE: Customer Agents, Forked Environments, and Production ParityAlessio [00:40:30]: Do you see a world where these things get automatically caught, not necessarily by your agent, but by your customer's agent? The cache invalidation issue seems easy to check if you know to look for it.Jake [00:40:44]: It's hard because to determine it, we almost need to hook into your observability infrastructure. That's why we have the template loop on the platform: so you can roll things out progressively. You can roll out to Johnny Vibe Coder initially, or push a shard that someone consumes at their own leisure. Or you can roll it out over weeks: 0.1% of people, 1% of people, early adopters, then all the way up. That's the non-deterministic version control we talked about earlier.Jake [00:41:30]: I believe that's where most things should go, because most companies end up building staged rollout systems in-house. It's the same thing built again and again at every company. There's a massive opportunity to consolidate developer debt.Alessio [00:41:45]: You should have a free tier. Model providers give free tokens if you let them use the data. You could give free compute if someone is the number-one shard that goes out and lets you plug into their observability.Jake [00:41:55]: We do that. That's why we talked about the impact on 3,000 people. We start with lower-impact people. Larger companies on the platform are last to receive those rollouts so they have a version of the platform that's deeply stable.Alessio [00:42:16]: I have three services, so I'm sure I get the first rollout. You can nuke my thing at any time. There are all these SRE agent companies. Observability people also want agents that fix upstream problems. You have your own agent in the canvas now. How do you see that playing out?Jake [00:42:39]: It's the stacking entropy problem. If you don't have primitives to make iteration in production safe, it becomes difficult. If you're an observability provider saying, “Here's the fix to this error,” assume 80% are good and make sense. But in the last 20% long tail of complex issues, if you let somebody stamp it, you create an opportunity for an incident.Jake [00:43:08]: That's why forked environments are important. People have staging, but it always drifts from production. You need primitives, workflows, and experience built first-party on the platform so you can fork any service at any point in time.Jake [00:43:33]: I think of the canvas as a sheet of transparency paper. The agent is a little guy you push up into the canvas. It should say, “I need to copy that service and that service so I can test these two things.” It gets a read-only copy of production. Anything that's PII gets marked as a transform when we clone the database, create a copy-on-write version, or read from it. Then the agent makes changes and asks, “Does this actually work?” as close to production as possible.Jake [00:44:22]: That's how close you have to be, or you get massive drift. The system becomes unstable. You see this with massive systems built on Docker for local, Kubernetes for production, and a specific thing for something else. That complexity slows developers and becomes unstable at scale, making it hard to iterate. We want to compress that way down and say, “As close to prod as possible is where we want to be.”From AISRE Skeptic to Agent BelieverSwyx [00:45:00]: I was texting Erica for questions, and she says you were originally not a believer in AISRE. Have you come around on it?Jake [00:45:10]: I flipped, but I'm still not a believer in AISRE if you don't have the primitives to make it safe. If you unleash AISRE on production infrastructure without safe primitives for copying volumes and making sure things are fine, it's going to nuke your production database. It's not a matter of if, but when. I'm a big believer in making those loops safe.Jake [00:45:33]: I was a deep AI skeptic until 2023. In 2024, I thought, “Maybe I can roughly make this thing do it.” In 2025, I thought, “Now I can hold this.” Over winter break, everybody came back saying, “It's almost impossible to hold this.”Swyx [00:46:01]: Did you see this on the Claude docs? CloudBot? OpenCloud?Jake [00:46:06]: It's gotten to a point where it's harder to hold it wrong than to hold it right. There's a scene in Avengers where Vision picks up Thor's hammer and says it's terribly well-balanced. It self-balances and works well. I'm a deep believer at this point that this will be the dominant species: assembly, C, C++, JavaScript, words.Swyx [00:46:35]: It feels like a big jump.Jake [00:46:37]: It is. But it's not like you abandon CPU-based discrete logic and move straight to fuzzy logic. You need both. Your skills should call code or applications or some static structure. You can use skills to distill what the procedure should be or how the code should act.Jake [00:47:02]: I'm coming to a thesis: you need three points. You need a clear spec defining the system, the code, and the tests. When you say it out loud, if you've been in engineering long enough, you're like, “Of course. That's an RFC, tests, and code.” But they all matter. Having them together lets them reinforce each other: the spec and tests match, but the code doesn't, so reconcile it. Or the tests and code match but the spec doesn't, so reconcile that. That's the iteration loop.Jake [00:47:41]: That's why you're seeing people talk about software factories, docs, and reconciliation. Some of that is architectural astronomy if you don't implement it, but that loop is where most things will end up.Swyx [00:48:07]: For listeners, we've been talking about this on the pod for three years: the holy trinity of specs and tests. Itamar Friedman from Qodo is the reference if people want to look it up.Self-Modifying Infrastructure and the End of Push-Pull-RebuildSwyx [00:48:18]: One thing I want to mention on the OpenCloud idea is self-modification. I don't know how Railway would support it, but I have my OpenClaw, and I just tell it it has the Railway CLI and can do whatever. In theory, whatever capabilities or new infra it needs, it can call the Railway CLI, provision it, and add it to itself. The agent can modify its own infra.Jake [00:48:45]: It's nuts. I have a loop set up where you put the Railway CLI on top of something that runs on Railway. You're authenticated as whatever the current box is, and you can make any changes to it. Then you call Railway deploy, and it deploys itself.Jake [00:49:04]: It's like: “I need to spin up this instance of this environment. I already exist in this environment. Excellent, I have access to a Postgres instance now.” That's where we want to go with agentic, self-replicating infrastructure. That's your loop: iterate in production. You continue making changes. If it works, merge it upstream. If it doesn't, throw it away.Jake [00:49:37]: How do you make throwaway copies trivial to spin up and super cheap? The era of “I have an AWS instance with four vCPU and 16 gigs of RAM” is going to get destroyed. If you do that for agents, you need a thousand of those machines. It's prohibitively expensive compared with what we've spent a ton of time figuring out: the atomic unit of deploy, whether you call it isolates, sandboxes, or something else. Only pay for what you use, spin up instantaneously, and close the loop as quickly as possible.Jake [00:50:15]: If the system can self-replicate safely and say, “This is my environment, I'm making these changes,” it can come back with, “Does this look good? This is a new state of infrastructure given this prompt. I think I've solved it.” Then you go back and say, “Actually, it looks different.” It does the loop again. Then you say, “Cool. Apply.”Swyx [00:50:38]: That's retroactively obvious, which is the most useful kind. Any other comments on agent deployment on Railway?Jake [00:50:51]: It's getting better every day. I'm on X or Twitter. You can always yell at me about the parts not working as well as they should, because plenty of things should work way better.The New Serverless: Stateful, Long-Running, Pay-for-What-You-Use LinuxSwyx [00:51:04]: At this stage, when people want massively or embarrassingly parallel compute, they usually talk serverless. I feel like there's a new serverless compared to the previous five years of serverless. You're in that new bucket. Do you have comparisons or philosophical differences you want to call out?Jake [00:51:31]: It's somewhere in between. It's the ability to run stateful, long-running workflows or executions.Swyx [00:51:42]: Vercel has Fluid Compute, Cloudflare has some container thing, Google has App Runner and others.Jake [00:51:55]: That's where everything is roughly going, and it's why we've been working on this for six years. We believe users need access to a computer: a box that speaks Linux. They need to deploy what they want. Other systems change the surface area of what you can build. For us, users need a computer and need to deploy anything they truly want. That's why we've focused on the primitives: network, compute, storage. If we give you those and expose them so you can run things indefinitely, that's where we believe it's going.Jake [00:52:43]: Twitter has no nuance, so everyone says “servers” or “serverless.” It's always somewhere in the middle: I want to run it for a long time, but I don't want to provision the resource statically or pay for things I'm not using. That's been our thesis from day one: pay only for what you use, run it indefinitely, and it is full Linux.Swyx [00:53:12]: That's why I like the naming of Fluid. It's fluid. Flexible.Heroku, Focus, and Carrying the Torch Without Becoming the PastSwyx [00:53:18]: Another milestone is the Heroku official deprecation. You're one of the presumptive new Herokus. “New Heroku” has been a category for as long as I've been in developer tooling. It's finally happening. What was that like? Any behind-the-scenes of, “This is the moment”?Jake [00:53:42]: You have people where you're like, “You were running stuff on here? You, as this company?” It's crazy that names you would know are running on it and now coming to us saying, “We want to move a lot of this off.”Swyx [00:54:00]: Any behind-the-scenes on why Salesforce let Heroku stagnate?Jake [00:54:05]: I can only guess. It's hard when it's not your business. Salesforce's business is to build a great CRM. That's their focus. Then you acquire a compute business as an offshoot. A lot of early Meta people talk about focus. Boz has a write-up about how in the early days of Meta they had no money, so they were forced to focus. Then they turned on the money tree and had no reason not to split their focus.Jake [00:54:52]: But that dilutes your product. You get offshoots where you ask, “Is this the focus of the business?” If it's not core, it languishes. A lot of companies get in trouble when they split focus because they're fighting a multi-front war, not just externally but internally for alignment. Where are we going? What are we doing? What is our purpose?Jake [00:55:24]: If you're Salesforce-built and mission-driven, you want to work on Salesforce. Heroku is off to the side. It's not core to the business. Getting resources, budget, focus, and alignment internally becomes hard. It was a matter of time.Swyx [00:56:06]: Kudos for them to call it out instead of leaving it unknown.Jake [00:56:12]: Their release was a little odd. They called it out, but they didn't say they were shutting it down. Behind the scenes, I think they issued messages to people saying they should close accounts and that they were going to deprecate and remove things over time.Jake [00:56:30]: It's crazy because some of my first deployment experiences were on Heroku. You start with dragging things into an FTP server, then you try to get a deploy working, and then it's Heroku. It was the on-ramp for us. But the wheel turns. New things emerge. We're happy to carry the torch for a lot of that. But we don't want to be the new Heroku. We want to be the way people build and deploy software, and ultimately the way people monetize software over time.Swyx [00:57:19]: It's still a big crown to be the new Heroku. There are 50 companies that fought for that.Jake [00:57:23]: Everybody is holding some portion of it. We're happy to support people and companies. The platform works differently. The game loop is similar, but we've been dogmatic about where these things are going: primitives, agents, fan-out. Some things fit; some workflows need to change. We have an approximation of Heroku pipelines with the environment system. It's exciting. We've got a ton of people we can support, and it's growing a lot.Temporal, Workflow Engines, and State MachinesSwyx [00:58:12]: I have one more technical question about Temporal. I've sold my shares. You're a power user and one of our earliest customers. I met you through Temporal. You built on Temporal. You have complaints. This may be the most neutral and informed conversation anyone will hear about Temporal without someone working at the company.Jake [00:58:39]: That's fair. I've used Temporal for almost 10 years because of Cadence at Uber.Swyx [00:58:52]: Give people a sense of what Cadence was at Uber.Jake [00:58:57]: Cadence was the precursor to Temporal. It powers trip actions, rides, when you rent a Jump bike or scooter or car. You're running workflows for a period of time and saying, “This ride will run indefinitely until it finishes.” You attach information: you paused in this zone, so add this charge to the bill. When you end the trip, the workflow is done. That experience was powered by Cadence at the time.Swyx [00:59:34]: I used to say it's like programming the entire user journey top-down as one function.Jake [00:59:39]: It's a powerful idea and important. It's also important for the next phase of the agentic journey. You want an agent to do a specific task, be complete or incomplete on that task, and move on to the next thing. You need a way to manage workflows dynamically.Jake [00:59:59]: Temporal was always great in theory, and great when you got it working the way you wanted in production. But it required you to model the entire journey in your head. If you didn't, you could cause issues where replaying the state of the workflow causes non-determinism.Swyx [01:00:25]: Because it works on deterministic workflow history.Jake [01:00:28]: Exactly. I describe it as a jet engine. If you know how to operate it and run it, it's great. But you can't hand it to people trying to build complicated things if they don't have the whole state in their head.Jake [01:00:48]: We run our whole deployment pipeline on top of it. That's a reasonably complicated workflow: pre-commit hooks, signaling, queuing, and all the rest. We ran into the same thing at Uber. As you express a large workflow, it gets more complicated, with more states in the state machine that you have to map back to the workflow.Swyx [01:01:15]: It's a lot of ifs.Jake [01:01:16]: Exactly. At Uber, we built a system for doing the state machine and testing it. We've started to build some of those things here because it's grown heavily. It's not quite love-hate. When it works well, it works super well. But if someone who doesn't have full context puts something into the system that invalidates state or causes non-determinism, or spins off a ton of activities, you have to keep track of underlying SRE knobs like activity slots. Those should scale with memory, vCPU, and so on. It becomes a bear to scale.Swyx [01:02:10]: You need a capable sysadmin running things behind the scenes. If you moved off, what would you do?Jake [01:02:19]: We'd build our own workflow engine. We have a few internally that we've worked on.Swyx [01:02:27]: This is one of those classes of things you typically wouldn't vibe code, but I'm wondering if you can.Jake [01:02:33]: I still don't think you should vibe code it. You still want to run decent tests to make sure it works.Swyx [01:02:39]: Timo didn't invent that from scratch either. There are libraries you can run. On top of that, it's just a state machine that you have to map out. Ultimately, you define the instructions you want and run them through a state machine.Jake [01:03:00]: It's very doable. Workflow stuff is interesting. Restate is doing neat stuff here.Swyx [01:03:10]: You're tied into JavaScript. Are you a JavaScript maxi?Jake [01:03:13]: Internally, we have TypeScript, Rust, and Go. We don't add more languages. Actually, we have a little C because we write BPF code and hooks. But those are the languages.Swyx [01:03:28]: Is this for sidecars?Jake [01:03:32]: No. It's for the networking stack, volumes, and things like that. We use TypeScript a lot because it powers the dashboard, but we're moving a lot of workflow stuff off the dashboard stack and into the infrastructure stack.Railpack, Nixpacks, and Content-Addressable FilesystemsSwyx [01:04:00]: Cool. Any other technical infrastructure stuff? Railpacks?Jake [01:04:07]: We built an engine for determining dependencies based on source code. It's called Railpack. We built the first version, Nixpacks, on top of Nix, and then we moved.Swyx [01:04:17]: People have been trying to get me to adopt Nix and NixOS for four years. Is it ever going to be a thing?Jake [01:04:23]: I don't know. We're excited about it, but it has pain points. Think of it as a stack of versioned binaries at specific slices in time. If you want version X and version Y, you bloat the package space, which blows up image size and makes real-world workloads difficult.Swyx [01:04:53]: But you content-address it and cache it. In theory, there are optimizations.Jake [01:05:00]: In theory, yes. But with a large enough user base and disparate enough machines, you run into a problem Meta described in the XFAAS paper, their internal serverless system. It becomes difficult at scale unless you break out specific runtimes.Jake [01:05:24]: We didn't want to do that because we wanted to truly allow you to deploy anything. That was our initial thing with Nix. But we've moved toward interesting work around content-addressable file systems that can lazy-load anything from any point and page it into memory.Swyx [01:05:48]: Amazing.Jake [01:05:49]: The future is very bright. It's crazy, and it's going to be nuts.Coding Agent Spend, Roadmaps, and Token ROISwyx [01:05:54]: Founder journey stuff?Alessio [01:05:56]: Your cloud usage: you tweeted you're going to spend $300K this month?Jake [01:06:01]: I think we got to $200K.Alessio [01:06:02]: Coding agents?Jake [01:06:03]: Yeah.Swyx [01:06:04]: Across the company?Alessio [01:06:05]: You only have 35 people, so I'm sure they're not all spending $10K a month. What's the distribution?Jake [01:06:10]: I think I'm at about $25K. We have power users all the way down. We came back from winter break, and I basically said, “If you're writing code by hand, you're doing this wrong.” The tools are good enough now that you can move extremely quickly. There are issues and pain points, but you should be reviewing the code you are writing instead of writing it by hand.Jake [01:06:40]: Architectural patterns matter more now than ever, but you shouldn't spend your time generating code you would write. If you know how to write it, ask the agent to write it and reconcile it until it looks like you would have written it yourself.Jake [01:06:58]: People misconstrue my propensity to push people toward agents as connected to our growth and some reliability bumps. They're not necessarily related. The tools are good enough to move extremely quickly and build things way larger than you could before.Jake [01:07:19]: To the earlier point about cooling data centers in space: I don't know. But with software, you can ask, “How would I build block storage from scratch? How would I do these things?” I have ideas because I have history and have read papers. Let me work them out and build massive test benches with thousands of tests, because those are now free to author. If you're not using AI systems to speed-run your roadmap and reconcile your existing system onto the future, you're missing a large point of what's happening.Alessio [01:08:12]: What's the path to spending $3 million a month? Is it bound by ideas and things customers can absorb?Jake [01:08:19]: For most companies, it's bound by deployment at this point. That's why we've seen a massive boom in users and companies, from Fortune 50s down, asking how to get developers to move faster. You'll probably hit your CFO before any technical limits because they'll look at the eye-watering amount of money spent on tokens. Inference costs have to come down, but we're inference constrained now. There will be price discovery around what makes sense for an org to adopt.Jake [01:09:06]: I think you'll end up with the F1 driver concept. If someone is really adept at these things, it makes sense to put them in a $3 million car. If they're not, it probably doesn't make sense. You'll take a few people and say, “You can drive the F1 car. We need to go in this direction. Figure out if it works and prototype it.”Jake [01:09:33]: We've done some of that and vastly accelerated our roadmap. We thought we'd ship something in a few years; now we can probably ship it in a few months because we validated it and don't have to build it incrementally. We can skip steps and move toward our vision.Alessio [01:09:58]: A lot of people are realizing the roadmap doesn't always have a business impact, so they say tokens are too expensive. But if your roadmap were built to make more money by the time you built it, you'd have token pricing for it, the same way you do with sales. You'd spend a billion dollars on sales if you knew you would get $2 billion of revenue.Jake [01:10:19]: Exactly. A naive way to measure this is the percentage of tokens that end up in production. If you can measure impact because those tokens end up in production, that's awesome. But the burden of proof will rise. Internally, we have a growing number of pull requests that haven't merged. The question becomes: how do you get this into production? It's about how quickly you can build and deploy software, which is exciting because that's our whole thing.The SDLC Shift: Prompt Requests, Feature Flags, and Safe RolloutsSwyx [01:10:56]: The SDLC is changing. One thesis is that the pull request is dying. It's going to be the prompt request. Beyond that, code review is also kind of dying if you have all the other systems in place. What else is changing about the SDLC?Jake [01:11:19]: The AISRE and the tools to make it happen. AISRE is pie-in-the-sky aspirational. What does it take to get an AISRE? What tools do you need to build?Swyx [01:11:32]: You should expose your tooling to customers at some point. The Central Station command center.Jake [01:11:39]: We have it for template maintainers. Template maintainers can deploy and maintain templates, and they get feedback. We're going to expose those things incrementally.Swyx [01:11:51]: Clustering around incidents. Everyone has a version of that, but I don't think anyone has solved it.Jake [01:11:56]: I won't say we've solved it internally, but it's gotten so good that we can see incidents forming pretty quickly. At some point, those will be things either someone else builds or we build. We've always built things purpose-built for us. If it makes sense to make it useful for users, monetize it, or turn that loop into a profit center instead of a cost center, we want to do that.Jake [01:12:28]: Pull request is definitely dying.Swyx [01:12:29]: Do you do first-party feature flagging and incremental rollout stuff?Jake [01:12:34]: We have a feature-flagging engine we built internally and will eventually roll out.Swyx [01:12:38]: I don't see it as a user. How come you didn't give us what you have?Jake [01:12:43]: We have to beta test it. We care a lot about the quality of the things. There's plenty we've used internally that doesn't make it all the way through the journey because it fails. It works for one service but not multiple services. We'd have to build it for multiple services and know that if we released it, we'd rebuild it again and again. Some things are worth that, but many inform the roadmap.Jake [01:13:18]: We don't want to dilute the experience by saying, “This works, but only for this service,” unless it's a core initiative. Over the next few months, we'll roll out things that work for a single service, then multiple services, then multiple services across the environment. You have to be deliberate. Otherwise you create broken disparate experiences and support load because people ask how to use the feature.Jake [01:13:52]: It's the earlier expansion and compaction pattern. You expand the company to get features, then compact and smooth them out so the experience is stellar. You told me in the hallway, “It's gotten so much better.” Internally we're saying, “This part really sucks. We need to make it significantly better.”Swyx [01:14:11]: I can attest to that over the last three years watching you build Railway. For listeners, feature flagging is a huge part of Uber culture. So much so that they have too many feature flags and another thing to remove feature flags. Facebook has Gatekeeper. Agents are going to need this. It's fundamental to incremental rollouts. OpenAI acquired Statsig. GPT-5 is routing and flagging through different models.Jake [01:14:56]: It's super important. If the software development lifecycle is going to change because we're doing things 1,000 times faster and 1,000 times more concurrently, what becomes important at scale?Jake [01:15:16]: Before I started Railway, I built a feature-flagging product and tried to sell it. It was an easier version of LaunchDarkly. I ran into a problem: anyone small enough to adopt your technology doesn't care about feature flags, and anyone large enough to need feature flags needs so much scale that you have to build out all the infrastructure. I scrapped it.Jake [01:15:42]: But what is old is new again. Companies are trying to move quickly, but you can't YOLO a vibe-coded thing straight into production. You need to say, “Here's my blast radius, my impact, and I want to shadow it for these users.” Feature flags. You're going to need the tools larger companies built to maintain their structures. Everything gets compressed by 1,000x so everybody can build those structures quickly.Jake [01:16:07]: That's exactly where we are: compressing the software development lifecycle, then expanding it and adding more new things.Cattle, Pets, and Clonable InfrastructureSwyx [01:16:15]: Another term that comes to mind for newer developers is “cattle, not pets.” People treat production like a pet. It has a name. You baby it and keep it alive. With cattle, you can mass farm, roll out, portion parts out, and kill them.Jake [01:16:37]: I think that might change. You can move toward having pets as long as you have a cloning machine for your pets.Swyx [01:16:52]: Yeah.Jake [01:16:52]: If you can snapshot every single thing at every frame, it doesn't matter if something gets obliterated because you have a snapshot of it. The things we've built right now are designed to block changes from the hermetically sealed DevOps line. You have to write a Dockerfile because you nee

NLW previews Google I/O and the bigger question hanging over it: whether Google can turn its massive AI advantages into products people actually want to use. The episode connects Codex coming to ChatGPT mobile, the rise of always-on agents, rumors around Gemini Spark, and Google's potential opening as a cheaper high-performance model provider for builders and enterprises. In the headlines: Cerebras' explosive IPO debut, Figma's AI recovery, OpenAI and Apple tensions, Anthropic's massive new valuation, and more.Apply for our Growth Engineering role: ⁠⁠⁠https://jobs.aidailybrief.ai/⁠⁠⁠Enterprise Claw Cohort 3 Registration: ⁠https://enterpriseclaw.ai/⁠Brought to you by:KPMG – Agentic AI is powering a potential $3 trillion productivity shift, and KPMG's new paper, Agentic AI Untangled, gives leaders a clear framework to decide whether to build, buy, or borrow—download it at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.kpmg.us/Navigate⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Granola - The AI notepad for people in back-to-back meetings. 100% off your first 3 months with code AIDAILY at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠http://granola.ai/aidaily⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Scrunch - The AI customer experience platform - ⁠⁠⁠https://scrunch.com/⁠⁠⁠Mercury - Modern banking for business and now personal accounts. Learn more at ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://mercury.com/personal-banking⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Zenflow Work - Agents for knowledge work - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://zenflow.free/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Drata - The agentic trust management platform - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://drata.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Blitzy - Want to accelerate enterprise software development velocity by 5x? ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://blitzy.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠AssemblyAI - The best way to build Voice AI apps - ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.assemblyai.com/brief⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Robots & Pencils - Cloud-native AI solutions that power results ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://robotsandpencils.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://pod.link/1680633614⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Our Newsletter is BACK: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://aidailybrief.beehiiv.com/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Interested in sponsoring the show? sponsors@aidailybrief.ai

In this latest episode of Executive Function, Brett sits down with Praveer Melwani, CFO at Figma. Praveer joined Figma in 2017 as the company's first business operations and finance hire—when the team was around 30 people and not yet charging for the product—and stepped into the CFO seat in 2022, helping to lead the company's IPO in 2025. In today's conversation, Praveer breaks down the step functions that took him from IC to CFO, why Figma started acting like a public company three years before IPO, and how AI is rewriting capital allocation and the CFO job itself. In today's episode, we discuss: What separates a world-class finance leader from a traffic-cop CFO How Praveer went from Figma's first biz ops hire to CFO of a public company in nine years Why Figma started acting like a public company three years before its IPO What Praveer has learned working alongside Dylan Field for nine years Why Figma intentionally cut its 90% gross margin to invest in AI References: Adobe: https://www.adobe.com Brendan Mulligan: https://www.linkedin.com/in/brendanmulligan Cloudflare: https://www.cloudflare.com Dropbox: https://www.dropbox.com Dylan Field: https://www.linkedin.com/in/dylanfield/ Fidelity: https://www.fidelity.com Figma: https://www.figma.com GIC: https://www.gic.com.sg NerdWallet: https://www.nerdwallet.com Shaunt Voskanian: https://www.linkedin.com/in/shauntvoskanian/ Where to find Praveer: LinkedIn: https://www.linkedin.com/in/praveer-melwani Where to find Brett: LinkedIn: https://www.linkedin.com/in/brett-berson-9986094/ Twitter/X: https://twitter.com/brettberson Where to find First Round Capital: Website: https://firstround.com/ First Round Review: https://review.firstround.com/ Twitter/X: https://twitter.com/firstround YouTube: https://www.youtube.com/@FirstRoundCapital This podcast on all platforms: https://review.firstround.com/podcast Timestamps: 00:00 Introduction 02:13 From banking to Dropbox to Figma 04:14 The phase shift when Figma's COO left 05:36 Hiring leaders in functions you don't understand 07:18 Selling the exec team on AI consumption pricing 09:48 Using Claude Code to learn new things as CFO 11:36 Building an internal board of peer CFOs 13:52 Inside Figma's CFO job description 16:38 What separates good CFOs from world-class CFOs 18:42 Capital allocation and risk in a post-ChatGPT world 21:45 Why Praveer wants to take more bets 24:32 How AI is materially changing the CFO role 25:36 The nine-year working relationship with Dylan Field 29:12 How deeply in the details should a CFO be? 31:47 What Dropbox taught Praveer about building strong teams 33:24 Praveer's first-principles test for hiring VPs 38:47 Why Figma acted like a public company in 2022

Elad Gil (@eladgil) is CEO of Gil & Co, a multi-stage investment firm, holding company, and operating company working on the world's most advanced technologies. Elad is a serial entrepreneur, operating executive, and investor or advisor to private companies, including AirBnB, Anduril, Coinbase, Figma, Instacart, OpenAI, SpaceX, and Stripe. He was previously VP of Corporate Strategy at Twitter and started mobile at Google. He was the founder and CEO of Mixerlabs and Color. Elad is the author of the bestseller High Growth Handbook: Scaling Startups from 10 to 10,000 People.This episode is brought to you by:Matic the intelligent robot vacuum and mop that navigates obstacles and needs no babysitting: MaticRobots.com/TimAG1 all-in-one nutritional supplement: DrinkAG1.com/TimEight Sleep Pod Cover 5 sleeping solution for dynamic cooling and heating: EightSleep.com/Tim Helix Sleep premium mattresses: HelixSleep.com/TimTimestamps[00:00:00] Start.[00:02:21] What's the “AI personal IPO” that just quietly happened across Silicon Valley?[00:05:28] Tens to hundreds of millions per researcher: What top AI pay packages actually look like.[00:06:44] The compute ceiling: Why Korean memory fabs are the unlikely bottleneck throttling every AI lab on earth.[00:11:11] From zero to $30B run rate: The fastest revenue ramps in the history of capitalism.[00:17:24] The dot-com survival rate was one in 100. Buckle up, AI founders.[00:20:35] Your value-maximizing window: Why the next 12–18 months may be as good as it gets.[00:21:32] Durable advantage — and why the AI market is an oligopoly (for now).[00:24:12] Exit options for AI founders: labs, hyperscalers, vertical players, and the underrated merger of equals.[00:28:11] Math, biology, and intuitive leaps: Elad's pre-investing background.[00:29:42] Elad's revisionist genesis story.[00:30:50] Go where the cluster is: 91% of global AI private market cap lives in a 10×10 mile square.[00:33:20] The accidental investor: Patrick Collison walks, Airbnb intros, and deals that just happened.[00:34:37] Want money? Ask for advice. Want advice? Ask for money.[00:35:00] The High Growth Handbook: Tactical guide, not bedtime reading.[00:35:41] Market first, team second — with a Perplexity-and-Anduril asterisk.[00:37:43] Smoke in the distance: AlexNet and the transformative GPT-3 moment.[00:45:15] AI cold-reading: Feeding photos to the model and getting eerily accurate personality reads.[00:48:56] Has Elad ever done a retrospective on his own investing?[00:52:13] Power laws are terrifying: 10 companies, 80% of returns, two decades.[00:55:53] Avoiding science projects, and how SPACs accidentally saved hard tech investing.[00:59:20] The one-belief framework: Coinbase = crypto index. Stripe = e-commerce index. That's the whole memo.[01:00:54] Due diligence theater vs. the one question that actually matters.[01:02:13] The four-year vest is a relic: How venture capital ate growth investing.[01:07:16] Boards as in-laws: You can't fire them, so choose wisely.[01:09:47] “Valuation is temporary. Control is forever.” — Naval Ravikant, as quoted by Elad, as relayed to you.[01:11:30] How great companies actually grew: toolbars, name-targeted ads, and billions in distribution spend.[01:15:36] Selling software vs. selling labor hours: The real shift generative AI made.[01:18:40] Spotting a great market: regulatory shifts, technology shifts, and Hashi getting bought by IBM.[01:21:28] Fake TAM, real TAM, and the Coke CEO who realized he wasn't in the soda business.[01:22:47] Right now, consensus is just correct. Save the contrarianism for later.[01:25:15] Market entry vs. market disruption: SpaceX launched rockets, then disrupted the internet.[01:26:16] How Elad learns: X, papers, 20-minute calls with the right people — and four AI models running in parallel.[01:27:15] Deep dive: ADHD, autism, and why diagnostic rates soared without more people actually having it.[01:33:40] Longevity for realists: sleep, creatine, and maybe rapamycin when the real drugs arrive.[01:40:30] Ibogaine, anesthesia, and the next frontier of bioelectric medicine.[01:45:15] Elad's first-ever 10-year plan — and why making one changes everything.[01:46:53] Parting thoughts.*For show notes and past guests on The Tim Ferriss Show, please visit tim.blog/podcast.For deals from sponsors of The Tim Ferriss Show, please visit tim.blog/podcast-sponsorsSign up for Tim's email newsletter (5-Bullet Friday) at tim.blog/friday.For transcripts of episodes, go to tim.blog/transcripts.Discover Tim's books: tim.blog/books.Follow Tim:Twitter: twitter.com/tferriss Instagram: instagram.com/timferrissYouTube: youtube.com/timferrissFacebook: facebook.com/timferriss LinkedIn: linkedin.com/in/timferrissSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.