Podcast
BILLIONS
Hosted by Guillaume Moubeche · EN
After building my company to a $150M valuation in 4 years, I had one question left: How do you build a billion-dollar company? I’m Guillaume Moubeche, and on the BILLIONS Podcast, I’m taking you inside the room with the world’s most iconic builders, founders, and investors to find the answer. This is more than just another startup podcast; it’s a masterclass in high-growth SaaS, AI implementation, and wealth creation.
From SaaS growth strategies and AI Agent pivots to the raw truth behind venture capital and exit strategies, we go where others don't.
What you’ll learn on BILLIONS:
SaaS Scal
27episodes
Episodes
Newest firstAll episodes
Creating a $140B market: The secondary market masterclass - Larry Aschebrook [G Squared]
Apr 3000:56:12Tap to summarizeToday on BILLIONS, I'm sitting down with Larry Aschebrook, the guy who invented a market that Wall Street didn't think existed.Larry started personally buying shares in Twitter and Uber on the side and he realized: there are thousands of employees sitting on life-changing paper gains, with zero liquidity, waiting for companies that might never IPO.So in 2011, he quit his safe university job and launched G Squared, a fund to solve that problem. Nobody took him seriously. The secondary market was "taboo." Companies thought selling shares meant you were failing.Today, he manages $5 billion. He turned a $150M Spotify bet into $1 billion. He made $800M on Coursera. And the market he built is now worth $140 billion a year.Larry, welcome to BILLIONS.TIMELINE : 00:00 : The psychology of the secondary market pioneer. 01:13 : Quitting a decade-long career for a "ghost" market. 03:23 : The Hustle: Cold-calling alumni for early Twitter and Uber shares. 05:41 : The $150 million Spotify bet and the $9M personal risk with zero collateral. 11:19 : Data Arbitrage: How Larry knew record labels were secretly buying Spotify. 15:43 : Scaling G Squared: From a $35 million pool to $7 billion AUM. 20:05 : Why DPI (Cash Back) is the only metric that matters, and why paper gains are a lie. 25:09 : The Scars: Learning from the "quick commerce" collapse and other losses. 37:09 : The Future: OpenAI, SpaceX, and the evolution of private liquidity. 53:12 : Advice for Founders: Why you must hire "grinders," not just pedigree.REFERENCES : Daniel Ek Spencer McLeodMitchell GreenJim SimonsElon Musk Spotify Twitter Uber Palantir Coursera Anthropic OpenAI SpaceX Stripe Wiz Toast NetflixApple Music Instacart Postmates Meituan Alibaba Turo GetaroundKlarna Revolut Databricks 23andMe Gorillas Pagaya
Transcribe →
McKinsey's AI leader moved to head a $2B AI workforce - Matthew Fitzpatrick [Invisible]
Apr 2800:48:39Tap to summarizeIs the traditional SaaS model officially dead ? On this episode of BILLIONS, I’m sitting down with Matthew Fitzpatrick, the man Fortune 500 CEOs called when they didn’t know what to do with AI.Matthew walked away from one of the most prestigious roles in tech, leading 1 000 engineers at McKinsey’s QuantumBlack Labs to lead Invisible Technologies.Invisible is the "invisible" engine behind the AI revolution. They don't just build software; they provide the RLHF (Reinforcement Learning from Human Feedback) and the data that trains the models the entire world is building on. With $100M raised at a $2B+ valuation, Matthew is proving that the future isn't in selling tools, but in selling outcomes.In this masterclass, we break down:The McKinsey Exit: Why a top AI leader "jumped ship" for a $2B startup.The Death of SaaS: Why "Outcome-based pricing" is replacing the subscription model.The Enterprise Gap: Why 90% of companies are failing to get AI into production.The Scaling Laws: The truth about data bottlenecks and the future of AI training.Process as Code: How Invisible integrates human intelligence with AI to solve "impossible" problems.TIMELINE : 00:00 The data bottleneck: Why Enterprise AI is currently "stuck"01:01 Why McKinsey’s AI chief left to lead a $2B unicorn02:33 The "Four Platforms": How Invisible actually works05:58 SaaS vs. Outcomes: The pricing model of the future09:19 Why the "AI Bubble" reality check is coming15:12 The "Capability Gap" holding back the Fortune 50022:15 RLHF & Data: Building the workforce behind the major models31:42 "Process is Code": The new architecture for billion-dollar companies41:10 Matthew’s advice for founders: Don't just build a "wrapper"48:20 The future of the "Invisible" empireREFERENCES :Mary MeekerElon Musk Étude MIT SloanÉtude NBER (National Bureau of Economic Research)Article BloombergMcKinsey & Company Quantum Black Invisible Technologies SwissGear Y CombinatorWeCP (We Create Problems)Databricks SnowflakeJevons paradox Reinforcement learning from human feedback (RLHF)Chain-of-thought reasoning Revolut
Transcribe →
$0 to $100M ARR in 3 months: The AI plan to run every company - Ben Cera [CloudKitchens & Polsia]
Apr 1600:58:19Tap to summarizeOn this episode of BILLIONS, I’m sitting down with Ben Cera, the man who helped Travis Kalanick (Uber Founder) build CloudKitchens, and who is now building the "God Mode" for startups: Polsia.Polsia is an AI that builds and runs companies autonomously. No employees, no meetings, just 24/7 execution. Ben is currently at a $6M annual run rate with a 30% week-on-week growth and he plans to hit $100M ARR in just 3 months. If you want to understand how AI agents are replacing the traditional SaaS model and how "Product-Market Fit" has become a search problem, this is your masterclass.In this episode, we break down:The CloudKitchens Era: Lessons learned from building a global giant with Travis Kalanick.The Autonomous Blueprint: How Pulsia builds companies from scratch without human intervention.$100M ARR in 90 Days: The aggressive growth strategy behind the AI revolution.The "SaaS-pocalypse": Why the software you use today is about to be replaced by agents.The "Taste" Economy: Why humans are moving from "builders" to "orchestrators."TIMELINE : 00:00 "Click a button, get a company": The vision for Polsia01:12 Building with Travis Kalanick: The CloudKitchens masterclass04:45 The $100M ARR Plan: How to scale an AI company in 90 days09:30 Why Product-Market Fit is just a "Search Problem"15:10 The SaaS-pocalypse: Replacing legacy software with AI agents22:40 How Polsia finds demand and builds products autonomously31:15 The Meta Ads Strategy: Scaling from $10/day to millions38:50 Why "Taste" is the only human skill left in the AI era45:10 Influencer-led distribution: The new "Billion-dollar" funnel53:05 Ben’s advice for founders: Stop building for others, build for yourselfREFERENCESTravis Kalanick (X/Twitter) Rick Rubin CloudKitchensFuture FoodsPolsiaChatGPT ClaudeSora 2 Uber Meta Ads ShopifyStripeUniversal PaperclipsWikipedia / Craigslist / Amazon HubSpot DoorDash
Transcribe →
$0 to 2 Unicorns: bootstrap vs $250M VC - Jason Cohen [WP Engine]
Apr 901:02:17Tap to summarizeOn this episode of BILLIONS, I’m sitting down with a legendary architect of the SaaS world: Jason Cohen, founder of WP Engine and Smart Bear.Jason has "cracked the code" twice, using two diametrically opposite strategies:The Pure Bootstrap: He built Smart Bear to millions in profit with zero outside funding, eventually leading to a unicorn valuation.The VC War Machine: He raised $250 million from Silver Lake for WP Engine, scaling it to $400M in revenue and 200,000 customers by 2024.This is a masterclass in capital efficiency. Whether you are a solo-founder or a venture-backed CEO, Jason’s framework for building "enduring companies" is the raw truth you won't hear in most boardrooms.TIMELINE : 00:00 - Why AI products almost never work01:20 - Switching from Bootstrapping to $250M VC rounds04:51 - The SaaS-pocalypse: The truth behind HubSpot & legacy decline09:30 - Solving legacy problems with AI-powered search16:17 - Experts vs. Muggles: The three categories of AI products21:55 - Why evergreen insights beat AI hype26:06 - The Power Move: Firing yourself as CEO to save the company34:01 - The "301 Redirect" strategy for management transitions40:48 - Hidden multipliers and the labor of love44:02 - The Raw Truth: Post-exit depression and infinite optionality58:25 - Redefining identity: Leveraging accumulated wisdomREFERENCES :
Transcribe →
Never wrote a line of code, now a $6.6B unicorn : the vibe coder - Lazar Jovanovic [Lovable]
Apr 201:01:01Tap to summarizeLazar Jovanovic is the world's first official "Vibe Coding Engineer." Working at Lovable (the AI startup that hit $100M ARR in just 8 months) Lazar is proving that the future of software engineering isn't about syntax; it's about taste and intent.In this episode, we dive into how Lazar ships production-grade apps for a $6.6B unicorn without writing a single line of manual code. We discuss the "SaaS-pocalypse," why ignorance is a superpower in the AI era, and how you can transition from a traditional role to a Vibe Coder.TIMELINE : 00:00 - Meet the world's first "vibe coding" engineer01:06 - Why "not knowing how to code" is your new superpower04:43 - Is software maintenance dead in the age of AI?09:15 - The Lovable story: hitting $100M ARR in 8 months15:42 - The end of bootstrapping? Vibe coding vs. the old way24:16 - SaaS-pocalypse: the future of software interfaces29:47 - Beyond code: the only metrics that matter for AI products37:01 - Will enterprises ever adopt AI-generated code?44:35 - The "Aladdin & Genie" trick for mastering AI prompts56:05 - How to become a vibe coder (no permission required)REFERENCES : Warren MasonKurt Cobain Pieter Levels.Marc LouVictor Wembanyama Elena VernaJony IveLovable Claude OpenAIShopify Stripe TechCrunch Salesforce HubSpot 28 Days of LovableShe BuildsAladdin and the Genie
Transcribe →
The 15-day pivot that saved a $1.3B company - Des Traynor [INTERCOM]
Mar 2800:55:56Tap to summarizeToday on BILLIONS, I'm sitting down with Des Traynor, co-founder of Intercom.In 2023, his company was stuck at 10% growth. Customer service teams were shrinking. The old model was dying. So he did something radical: he launched an AI agent priced at $0.99 per resolved conversation. Not per seat. Per outcome.The result? Growth doubled to 25%. $343M in revenue. And a complete reinvention of a $1.3B company in 18 months.TIMELINE : 00:00:00 - 00:01:02 : Des Traynor - Intercom00:01:02 - 00:05:22 : The $1.3 billion bet on AI : moving 15 days after ChatGPT launched00:05:22 - 00:09:08 : Why building AI is not building SaaS00:09:08 - 00:12:51 : The "torture test" for engineering reliability00:12:51 - 00:20:14 : Developing the "white smoke" moment for product00:20:14 - 00:25:16 : Defining what "good" looks like in AI00:25:16 - 00:34:53 : The Blockbuster warning: Adapt or die00:34:53 - 00:40:27 : Killing hallucinations with actor-critic logic00:40:27 - 00:48:55 : Outcome-based pricing and the future of CRM00:48:55 - 00:55:56 : The end of frontline customer service jobsREFERENCES : Fergal Reid Ciarán Lee Eoghan McCabeMarc Andreessen If Anyone Builds It, Everyone DiesOpenAI / ChatGPTZendeskSalesforce Fin.AIGong ClickUpDALL-ECursor WindsurfDevinClaude CodeAttioClarifyNetflixThe Cheeky Pint
Transcribe →
Building Odoo's American war machine - Wilfried Juncker [Odoo]
Mar 1900:54:29Tap to summarizeToday on BILLIONS, I'm sitting down with Wilfried Juncker.He's the Managing Director for Odoo's Americas a Belgian software unicorn that just hit a €8 billion valuation.Under Wilfried's watch, Odoo's Americas operation exploded from 35 people in 2016 to over 950 in America only.In this episode, we're digging into how Wilfried built Odoo's American war machine, what it takes to conquer a new market from scratch, and how he's fighting high SMB churn while scaling at breakneck speed.While SAP and Oracle charge millions for ERP, Odoo's open-source model is democratizing enterprise software and Wilfried built the Americas war machine that's making it happen.Wilfried, thanks a lot for being here!TIMELINE : 00:00:00 - 00:01:05 : Odoo's explosive growth from 70 to 2,000 employees00:01:05 - 00:02:30 : The early days and Wilfried's journey at Odoo00:02:30 - 00:05:25 : Entering the US market with channel partners strategy00:05:25 - 00:09:25 : Open source model and freemium conversion tactics00:09:25 - 00:14:20 : Building the partner ecosystem and revenue sharing00:14:20 - 00:18:07 : Scaling partner relationships and management approach00:18:07 - 00:24:12 : Hiring and retention philosophy - promote from within only00:24:12 - 00:27:14 : Industry specialization vs size-based team structure00:27:14 - 00:34:32 : Managing SMB churn while maintaining growth00:34:32 - 00:42:17 : Demo-first culture and bottom-up sales approach00:42:17 - 00:48:20 : Resource allocation and offline marketing strategy00:48:20 - 00:52:27 : Unconventional customer acquisition tactics00:52:27 - 00:54:29 : Building local ecosystems and final thoughtsREFERENCES :- Oracle NetSuite- Microsoft Dynamics- SAP- Acumatica- Sage- Epicor- Infor- QuickBooks- HubSpot- GitHub- Lemlist- Clay- Lucia- NPR- NASA
Transcribe →
From selling startups to Google to backing multibillion‑dollar AI winners - Anish Acharya [a16Z]
Mar 1200:55:21Tap to summarizeToday on BILLIONS, I'm sitting down with Anish Acharya.He sold his first company to Google. His second to Credit Karma — then stayed and helped scale their U.S. Card business to nearly a billion dollars in annual revenue.In 2019, Andreessen Horowitz made him a General Partner. Since then, he's led the Series A in Deel, which just hit a $17.3 billion valuation in October 2025.Most VCs have never operated anything. Anish built, scaled, sold, and then learned how to pick.Anish, thanks a lot for being here !TIMELINE : 00:00:00 - 00:02:30 : Anish Acharya’s entrepreneurial journey00:02:30 - 00:06:28 : Why 2008 and today are the most exciting times for founders00:06:28 - 00:11:38 : The AI model competition and Google's comeback00:11:38 - 00:14:50 : Why the "LLM wrapper" fear is no longer relevant00:14:50 - 00:20:07 : Multi-model approach and the future of AI applications00:20:07 - 00:24:01 : Learning from Credit Karma and the importance of winning00:24:01 - 00:29:14 : Why paternalism kills products and going with human nature00:29:14 - 00:35:28 : AI's human impact and why it's different from social media00:35:28 - 00:42:45 : The future of coding, jobs, and why SaaS isn't dead00:42:45 - 00:55:21 : Investing in Deel, AI companionship, and what it costs to winREFERENCESMark Zuckerberg Sam Altman Sergey Brin Nicolas Dessaigne - Billions EP2Andrej Karpathy Alex Bouaziz Shuo Wang Harry Stebbings - Billions EP4Eugenia Kuyda Credit KarmaDeel ChatGPT Gemini Claude GrokCursor Lovable HarveyReplikaWabiLife360 PapayaQwen
Transcribe →
The man who helped OpenAI to go from millions to billions in revenue - Zack Kass [Open AI]
Mar 600:53:29Tap to summarizeToday on BILLIONS, I'm sitting down with the man who had the hardest sales job in Silicon Valley history: Zack Kass.Before ChatGPT was a household name, it was just a research lab. Zack was Head of Go-To-Market. He joined when OpenAI was around a hundred people doing two million in revenue. His job? Sell human-level intelligence to Fortune 500 executives who didn't even know what a token was.He built the playbook for Microsoft. For Coca-Cola. He turned a nonprofit lab into an eighty billion dollar superpower. Then he walked away.Zack, thanks a lot for being here!TIMELINE00:00:00 - 00:06:34 : Joining OpenAI as the first sales person00:06:34 - 00:09:47 : The early GPT-3 wrapper ecosystem00:09:47 - 00:11:03 : Strategy behind ChatGPT's development00:11:03 - 00:16:45 : The chat interface decision and market response00:16:45 - 00:21:04 : ChatGPT's explosive growth and company atmosphere00:21:04 - 00:26:45 : Lessons from viral growth and Microsoft partnership00:26:45 - 00:30:21 : Scaling challenges and the "bigger boat" moment00:30:21 - 00:33:44 : Personal burnout and health crisis00:33:44 - 00:37:29 : AI as humanity's last invention00:37:29 - 00:45:21 : Technology, inequality, and policy failures00:45:21 - 00:48:35 : Global AI competition and geopolitics00:48:35 - 00:50:18 : AI's potential to solve major problems00:50:18 - 00:54:33 : The next renaissance and education transformationREFERENCES- Sam Altman- Brad Lightcap- Lukas Biewald- Chris Van Pelt - John Maynard Keynes- Elon Musk- Jeff Bezos- Koch brothers- "The Next Renaissance: AI and the Expansion of Human Potential" by Zach Cass- "Attention Is All You Need" - Figure Eight- Lilt- Weights & Biases - Scale AI - Jasper - Harvey - Bain & Company- Waymo- Prenuvo- DeepSeek- OpenAI- RLHF- CRISPR - Jevons paradox - Jaws
Transcribe →
The growth playbook behind Revolut's $100B+ growth engine - Antoine Le Nel [Revolut]
Feb 2700:56:55Tap to summarizeToday on BILLIONS, I'm sitting down with Antoine Le Nel the guy who spent 7 years scaling Candy Crush into one of the most addictive products ever created... then walked away to go kill traditional banking.At King, he helped turn a mobile game into a machine that prints billions. When Activision bought them for $5.9 billion, he could've stayed forever.Instead, he joined Revolut in 2021 — right as most fintech were collapsing. Three years later? $75 billion valuation. $4 billion in revenue. 65 million customers.His secret? Ignoring everything Silicon Valley preaches about growth.Antoine, thanks for being here!TIMELINE :00:00:00 - 00:01:07 : Scaling Candy Crush to a $5.9 billion exit00:01:07 - 00:03:38 : How to avoid the "one-hit wonder" trap in gaming00:03:38 - 00:06:54 : The Facebook hack that reached 70% of global users for free00:06:54 - 00:10:35 : Activision's acquisition and the reality of pre-ipo stock options00:10:35 - 00:16:59 : Why Revolut prioritizes unit economics over venture capital hype00:16:59 - 00:21:00 : Decoding the exponential LTV curve that defies banking logic00:21:00 - 00:30:13 : Charging for the card: A masterclass in buying user engagement00:30:13 - 00:46:01 : Killing the middleman: Revolut's secret to autonomous, lean teams00:46:01 - 00:54:08 : From ROI to F1: Building a generational brand with Audi00:54:08 - 01:00:53 : The uncomfortable truth about brand value and engineering mindsetsREFERENCES:- Mark Zuckerberg - Nik Storonsky- Patrick Collison- King Digital Entertainment - Activision Blizzard - Stripe - Booking.com - Primavera Sound - Como football team- Audi F1- Drive to Survive- Revolut Business
Transcribe →