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
21episodes
Episodes
Newest firstAll episodes
Very few growth moats will survive AI - Sandy Diao [Descript]
4d ago00:57:15Tap to summarizeOn this episode of BILLIONS, I’m sitting down with Sandy Diao, an elite growth operator who has been remarkably right about major market trends long before the rest of the ecosystem.Sandy helped scale products to 200 million users by leading early growth efforts as employee number 30 at Pinterest. She then joined Descript as their first ghost hire, architecting an automated affiliate model that drove 25% of all new users completely self-service.Her thesis is a warning to every modern SaaS operator: the siloed channel specialist is obsolete. In a world flooded by AI-generated content, traditional acquisition paths are collapsing. The future belongs to full-stack, unified operators who realize that trust is the only channel that compounds.In this masterclass, we break down:The Pinterest Support Trench: How responding to raw customer tickets unlocked the insights to rewrite onboarding and drive massive user activation.Data-Inspired vs. Data-Driven: Why chasing exact precision can paralyze early growth, and why directional insights are the secret to building high-velocity engines.The Descript Affiliate Machine: How to structure automated, self-service loops that scale acquisition without expanding headcount.The Death of Growth Moats: Why traditional software channels are decaying and how to transition to a unified growth framework.Auditing Your Engine: Sandy's precise multi-step diagnostic process for troubleshooting an underperforming distribution strategy.TIMELINE : 00:00 – Why most growth moats won't survive the AI era01:03 – The Support Trench: How customer tickets rewrote Pinterest's onboarding10:00 – Overcoming Team Friction: How to align engineering with rapid growth experiments16:06 – From B2C to B2B: Spotting high-intent institutional signals in consumer data18:17 – Data-Inspired vs. Data-Driven: Why chasing absolute precision kills execution velocity25:09 – The Descript Affiliate Loop: Building a self-service machine that drove 25% of new users38:00 – Retention in the AI Era: Maintaining product durability when switching costs drop41:10 – The Growth Collapse: Why the siloed channel specialist is officially obsolete44:03 – The Growth Audit: Her foundational framework to diagnose an underperforming engine47:02 – Adaptive Moats & Unfair Advantages: Why the permanent distribution moat is deadREFERENCES : Ben Silbermann Evan Sharp Pinterest Descript IndiegogoThe ONE Smart Piano TeachShare Adobe Facebook/Meta Twitter (X) Coca-Cola Burt's BeesStripeGoogle AdsMeta Pixel (ex-Facebook Pixel)Claude ChatGPTGemini Power law outcomes GEO (Generative Engine Optimization)
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From Revolut employee #3 to building a £5B energy giant - Alan Chang [Fuse Energy]
1w ago00:58:10Tap to summarizeOn this episode of BILLIONS, I'm sitting down with Alan Chang, Co-Founder and CEO of Fuse Energy—a tech-driven energy company that has completely shattered the UK market.Alan was employee #3 and Chief Revenue Officer at Revolut. Instead of coasting on fintech success, he and his co-founder Charles took that hyper-growth playbook and weaponized it against traditional utility giants like British Gas and Octopus. In just three years, Fuse has exploded from £2M to £400M in annual revenue, achieving a £5 billion valuation.If you want to know how a lean tech team can buy a wind turbine, acquire a grid operator, and out-execute legacy multi-billion dollar incumbents, this is your blueprint. In this masterclass, we break down:The Revolut Exit: Why Alan walked away from fintech because the problem was "largely solved".The £1M MVP: How they bought an energy license for £50K and a single wind turbine for £750K, using a mix of their own capital and an early round.Anti-Democracy Culture: Why running a startup by committee fails, and why top performers should be paid 10x more than bottom performers.Full-Stack Infrastructure Control: Why Fuse is currently buying a grid operator to dominate supply. Internal AI Weaponization: How Fuse is building internal AI agents (PR reviews and error-tracking) to keep their team incredibly small and efficient.TIMELINE 00:00 – Leaving Revolut: Moving from a "solved" fintech industry to an unsolved energy crisis.04:20 – The £1M Full-Stack MVP: Door-knocking for a wind turbine and securing an energy license.09:33 – The Efficiency War: Why European energy costs are 3x higher than China's.13:31 – Controlling the Grid: Why Fuse is actively acquiring a grid operator.17:05 – The Execution Layer: Rejecting complex designs and demanding simplicity.22:36 – High-Performance Compensation: Why top engineers make 10x more than the bottom tier.28:50 – VC Term Sheets: Setting absolute founder-control red lines with investors.36:50 – The Main Job: Why recruiting absolute elite talent takes up the majority of a CEO's day.43:52 – Product Design: Building beautiful micro-solar and balcony battery products for consumers.46:05 – Weaponizing AI Internally: Building PR review and error-tracking agents to optimize code.REFERENCES Nik Storonsky Charles OrrRevolut (Antoine le Nel : Episode 9)British GasOctopus EnergyFuse Energy
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The fastest revenue engine in SaaS history: $5.4B run rate in 10 Years - Ron Gabrisko [Databricks]
2w ago00:51:34Tap to summarizeIs the traditional "per-seat" SaaS model officially obsolete? In 2016, Ron Gabrisko joined a startup with less than $1M in ARR. It was a company of 50 engineers and a product beloved by developers who had never even spoken to a sales rep. Ten years later, Databricks is a $134B giant doing $5.4B in ARR and they are still growing at a staggering 65% year-over-year.No CRO in history has built a revenue engine this fast, from this early a starting point. Ron didn't do it by following the standard Silicon Valley playbook; he did it by pioneering Consumption-Based Pricing and leveraging Open Source as the ultimate top-of-funnel engine. In this masterclass, we break down: Consumption vs. Seats: Why Databricks tied its pricing to the "most basic unit of value" and how it fueled a $100B+ valuation.The Open Source Funnel: How to monetize a community without "locking them in".Building Trust with Engineers: Why Ron hires "really technical sales folks" to add value rather than just pitching.Scaling through Innovation: Why Databricks didn't stop at one product, but built a sticky ecosystem (Spark, Delta, MLflow).The GenAI Future: Why owning and protecting your data is the "secret sauce" for the next decade of AI.Timeline : 00:00 – The $5.4B Machine: Intro01:20 – Joining Databricks at sub-$1M ARR with 7 PhD founders04:12 – Selling to engineers: hiring "really technical sales folks"06:29 – Killing the SaaS Seat: consumption and the "most basic unit of value"09:22 – Net retention 130%: the multi-product open source strategy14:53 – Planning 65% YoY: the science of forecasting19:03 – Structuring 5,000+ sellers: verticalization and outcome-based selling29:11 – "Don't give your data to us": the data ownership philosophy33:54 – Usage-based vs value-based: why pricing is public on the website
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$100M ARR in 7 quarters: inside the $10B AI machine - Reggie Marable [Sierra]
4w ago00:48:09Tap to summarizeOn this episode of BILLIONS, I’m sitting down with Reggie Marable, the Chief Revenue Officer at Sierra. Reggie’s path wasn't a straight line. He went from being a professional linebacker in the CFL to working in a Sprint call center, and eventually rose to become the Head of Sales for Slack North America. After years at Salesforce, he walked away to join Sierra as employee #23.Founded by Bret Taylor (former Salesforce Co-CEO) and Clay Bavor, Sierra has reached a $10B valuation and is on a path to $100M ARR in just seven quarters. Their secret? A business model that should terrify every legacy SaaS founder: Outcome-Based Pricing. In this masterclass, we break down:The Sierra Sprint: How to scale to a $10B valuation in record time.Service as Software: Why Sierra only charges customers when a problem is actually resolved.The Sales Shift: Why Reggie left a massive leadership role at Slack for an early-stage startup.Hiring for the AI Era: Why Reggie looks for "humble, hardworking, and low-ego" talent over pedigree.The Recovery: How getting fired earlier in his career became the foundation for his $10B mindset.TIMELINE :00:00 – "If your dreams don't scare you...": The Muhammad Ali mindset.01:17 – From the CFL to a Sprint call center: Reggie’s raw beginnings.04:07 – The "fired" moment: How losing his job led to a total reinvention.05:33 – The Salesforce & Slack era: Mentoring 200+ people and scaling Slack North America.10:00 – Why Reggie left Slack to become employee #23 at Sierra.12:23 – Outcome-based pricing: Why the "per seat" model is dying.16:20 – AI agents in the wild: Real-world results for Cigna, Singtel, and Sonos.19:00 – The resolution model: Charging for solved problems, not software access.31:15 – Operational cadence: How a $10B startup manages its weekly rhythm.35:50 – Hiring strategy: Why "humble and hardworking" beats high-ego sellers.44:10 – The "diversity" advantage: Building high-performance teams through inclusion.47:16 – Reggie’s final advice: "Success is a winding road."REFERENCES :
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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
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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
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$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
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$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 :
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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
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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
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