BILLIONS

Episodes

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  From 100 sales meetings a week to $600M ARR - Carles Reina [ElevenLabs] 15.09.2026 50m

  Today on BILLIONS, I'm sitting down with Carles Reina, the first investor and fourth employee at ElevenLabs, to unpack the AI bubble, the rise of Chinese models, and Europe's fight to stay in the race.Carles helped build ElevenLabs' go-to-market engine on the road to over $600 million in annual recurring revenue. As the founder of Baobab Ventures, he also sees the other side of the boom: the funding rounds that may be getting ahead of reality.Before the scale came 80 to 100 sales meetings a week, a Google Sheets CRM, and months of testing who would actually pay. Then came a sales model most teams would question: quotas set at 20 times base salary, uncapped commissions, and average quota attainment of around 167%.But this conversation goes beyond the ElevenLabs growth story. We debate the commercial barriers Carles sees around Chinese AI models, why he believes Europe is not investing seriously enough in AI infrastructure, and what it takes to build a global company from day one.He also explains why extraordinary growth and an AI bubble can exist at the same time - and why he expects some aggressively valued startups to face a funding reality check within six to nine months of this conversation.In this masterclass, we break down:The 100-Meeting Week: How Carles tested his way from creator demand to a repeatable sales motion, then hired reps who started closing deals within weeks.The 20x Quota Rule: Why ElevenLabs set targets at 20 times base salary, rewarded overperformance with commission accelerators, and adjusted expectations when markets proved tougher.Permission to Fail: Why Carles encouraged experiments with company money - and only needed one idea out of 100 to unlock the next stage of growth.The AI Adoption Gap: Why strong Chinese models do not automatically translate into easy enterprise adoption, and why Europe needs more than technical talent to compete.The Operator-Investor Playbook: Why Carles kept Baobab small despite $23M in commitments, and why he wants to return capital to investors along the way.The Valuation Reality Check: How real AI demand can coexist with overheated funding rounds, and why a high valuation can become a liability at the next raiseGlobal from Day One: Why Carles challenges the one-market-at-a-time playbook, pushes founders to hire go-to-market talent early, and wants investors to do more than write checks.TIMELINE00:00 - Intro - from first investor to fourth employee at ElevenLabs03:25 - 80-100 sales meetings a week: finding what actually sells06:46 - Hiring "icebreakers" vs. scaling the sales team09:36 - Selling the future: from developers to enterprise12:25 - Building a sales team that experiments with AI17:05 - The 20x quota rule, uncapped commissions & 167% attainment21:46 - The incentive mistake that held back enterprise sales24:13 - Chinese AI models: great technology, harder enterprise adoption34:01 - Europe's AI infrastructure problem34:38 - Hugging Face, Nvidia & the European funding gap37:37 - Building Baobab Ventures: fundraising and early results43:37 - AI bubble or real growth? The next funding reality check47:53 - Three lessons for founders building globallySUBSCRIBE👇https://www.youtube.com/c/GuillaumeMoubeche?sub_confirmation=1 Join the lemlist family 🚀 https://community.lemlistfamily.com/join?invitation_token=9db20d2c4707b75ebb065462261c4665a3c35a59-aad63a7f-90a5-452e-a628-4ccbcbaa84caFollow mehttps://www.linkedin.com/in/-g-/https://twitter.com/GuillaumeMbhhttps://www.tiktok.com/@guillaumemoubechehttps://www.instagram.com/guillaume_moubeche/Learn how to book meetings with 30%+ of your prospects (for free): https://www.lemlistfamily.com/multichannel-masterclass?mtm_campaign=5008&mtm_source=organic&mtm_medium=youtube
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  Why the "SaaS is dead" narrative is completely wrong - Aaron Levie [box] 09.07.2026 34m

  Today on BILLIONS, I'm sitting down with Aaron Levie, the co-founder and CEO of Box, who has rapidly transitioned his enterprise platform from a pure SaaS model into a cutting-edge playground for autonomous AI agents.Aaron has a masterclass view of the data infrastructure that legacy tech giants wish they controlled. In this conversation, we pull back the curtain on the high-stakes battle for sovereign AI. We unpack the real fallout of the U.S. government's unprecedented export controls on Anthropic's frontier models, why data platforms like Snowflake are posting blockbuster quarters amidst the AI boom, and how specialized tools like Cursor show that the future of intelligence is multifaceted, not winner-take-all.If you want to understand where the real economic value of applied AI resides over the next decade, this is the blueprint.In this masterclass, we break down:The Export-Control Precedent: Inside the unprecedented restriction of Anthropic's frontier model from non-US users and why Aaron calls it a brand-new moment in AI regulation.The Safety-Rhetoric Boomerang: How AI safety messaging scared the government into a model-approval pipeline — and why some safety advocates may quietly prefer that outcome.China's $50B Scenario: Why Aaron believes China can simply throw $50B at compute to stay in the race and why France, Japan, the UK, and Germany may be forced to build their own sovereign models.The Multifaceted Intelligence Future: Why the AI market won't be "winner-take-all," and how Cursor's applied-layer harness (routing tasks across cheap and premium models) became the template.Building for Machine Users: How Box adapted its file system MCP server, CLI, Markdown editing, HTML compatibility so agents and people work off the same data.Why More Agents Make SaaS More Valuable: Why deploying 100x more agents than employees increases the value of the underlying CRM, ERP, and content systems instead of killing them.The CS-Grad Dislocation: A grounded look at the shifting job market away from Big Tech layoffs and into AI startups and industries like life sciences and manufacturing.TIMELINE : 00:00 – Turning Box from SaaS into an AI agent platform03:00 – Sovereign AI: why countries will build their own models05:51 – Can open and Chinese models catch up to the frontier?08:51 – The chip embargo debate and Jensen Huang's argument14:09 – AI safety, regulation, and government model approval18:29 – Why AI won't be winner-take-all (the Cursor case study)21:33 – How Box built a file system for AI agents27:17 – Is SaaS dead? Why agents make software more valuable30:48 – Will AI replace jobs? The truth about CS grads
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  Why focus on only ONE product built a $1B super-brand (on just $6,000) - Pete Maldonado [Chomps] 02.07.2026 52m

  Today on BILLIONS, I'm sitting down with Pete Maldonado, the visionary who took $6,000, one failed food venture behind him, and zero institutional backing and built a dominant food empire that's approaching $1 billion in revenue this year.Pete and his co-founder Rashid bet everything on a category the entire industry assumed was dead: the gas-station meat stick. For nearly ten years they bootstrapped taking less than $1M in primary capital prioritizing extreme operational focus and deleting complexity at every corner. They stayed so maniacally disciplined that they only ever scaled one product format : meat sticksusing just 12 core recipes to capture market share from corporate giants.But extreme efficiency comes with massive friction. Pete opens up about the devastating reality of underestimating their explosive demand curve, which cost them 9 figures in lost revenue last year alone, the inside story of surviving an overnight COVID collapse with Trader Joe's, and why he chose to step down as CEO to hand over the keys to his co-founder.In this masterclass, we break down:The $6,000 Side Hustle Genesis: How a personal trainer used early Shopify tools and a $99 Photoshop Elements subscription to design a world-class brand from his desk.The Rule of Deleting Complexity: Why going deep on a single SKU beats going wide, and how relentless simplicity early on became the reason they could scale at all.The 9-Figure Forecasting Nightmare: The brutal operational pain of undershooting cultural shifts and cutting massive amounts of purchase orders when demand outpaces supply.The Over-the-Register Museum Trap: How an unexpected plexiglass policy at Trader Joe's wiped out retail sales overnight during COVID—and the pivot that saved the team from layoffs.The Hidden Weight of Personal Guarantees: Moving past bank-debt structures that put family homes on the line to engineer a 100% secondary private equity deal with Stride Consumer Partners.Stepping Down at the Peak: Pete's candid psychological transition from active day-to-day CEO to hands-off Chairman to protect his family time and scale the company further.TIMELINE : 00:00 – Building Chomps on $6,000: a $6,000 food brand from nothing09:46 – Brand awareness vs. distribution: never hit a shelf before the customer knows you11:53 – Riding the diet tribes: CrossFit, Paleo, Whole30, Keto, and now GLP-119:13 – The 2016 Trader Joe's inbound: staying methodical and rejecting advisor pressure to over-expand28:05 – Forecasting demand and surviving COVID33:31 – The plexiglass "museum": surviving canceled COVID orders with zero layoffs37:17 – Personal guarantees & the 100% secondary raise: de-risking the families40:46 – Casting a wider net: breaking the bottom-of-funnel ROAS trap to unlock top-of-funnel scale46:15 – Stepping down: from CEO to ChairmanREFERENCESRashid Ali Noah Kagan Tim Ferriss Liz Carter The Million Dollar Weekend Nutrisystem Jenny CraigTrader Joe'sWhole FoodsSproutsThrive MarketJack Link'sSlim JimStride Consumer PartnersShopifyWordPressAmazon Whole30 Approved CrossFit Paleo Keto GLP-1
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  The man who built a bank for people banks don't want - Jason Wilk [Dave] 25.06.2026 47m

  On this episode of BILLIONS, I'm sitting down with Jason Wilk, four-time founder and CEO of Dave, the neobank built to take on the predatory overdraft fees that quietly bleed billions a year from the Americans who can least afford them.Jason's story is one of the wildest comebacks in fintech. After going public via SPAC in January 2022, Dave hit a $5 billion valuation, then the macro turned.Rates spiked, growth capital dried up, and within nine months the stock had collapsed 98%, dragging the company's market cap down to roughly $50 million, less than the cash sitting on its own balance sheet.Most teams would have panicked, slashed headcount, or sold cheap. Jason did the opposite: he froze hiring, refused layoffs, killed every non-core product, and put the entire company behind one number, unit economics. Today Dave is back to a nearly $4 billion market cap, with 2026 guidance of over $700M in revenue and over $300M in EBITDA, a ~$400M earnings swing in just a few years.In this masterclass, we break down:The $75 microloan bet : how Dave used cash-flow data instead of FICO to underwrite the smallest loan in the country, importing a model that worked in India and Africa but no one had cracked in the US.120 meetings for a Series A : why traditional VCs had never even heard of overdraft fees, and what it took to finally get the check.Surviving a 98% wipeout : the operational playbook Jason ran when growth capital ground to a halt and raising more was off the table.Making millionaires at the bottom : how a Performance Stock Unit structure turned the crash into the biggest wealth-creation event in the company's history."VC money is just very high-APR debt" : why Jason wishes he'd taken his $10M Series A as venture debt and kept the equity.Eating other people's margin : Dave's new credit card and multi-product roadmap, aimed at the $100B+ a year Americans pay in credit card APRs and late fees.TIMELINE :00:00 – Why he declared war on the $34 overdraft fee01:55 – The $75 microloan that ignores your credit score04:26 – 120 investor meetings to close the Series A09:48 – Going public via SPAC at a $5B valuation11:15 – How the stock crashed 98% in 9 months16:19 – Making employees millionaires at rock bottom19:38 – From burning $100M to $300M in EBITDA23:17 – Why VC money is worse than a loan shark27:00 – The new credit card attacking a $100B market43:29 – Running a $4B company with 300 peopleREFERENCES :Jason WilkSV Angel Ron ConwayPaul GrahamGoBuyside / « Gocleff » Dave PlaidAcorns BankSimple Norwest Venture Partners Tiger Global Y Combinator
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  Why the world’s biggest tech companies may never IPO again - Peter Singlehurst [Baillie Gifford] 18.06.2026 58m

  On this episode of BILLIONS, I'm sitting down with Peter Singlehurst, who built the private companies team from scratch at legendary investment firm Baillie Gifford, deploying billions into more than 100 of the most important private companies on the planet.Peter operates on a timeline that makes typical venture capitalists look shortsighted. From backing Tesla in 2013 at a $3B market cap to entering SpaceX at a $30B valuation, his strategy completely bypasses the short-term noise of quarterly earnings.In this masterclass, he breaks down why optimizing for the highest possible price at an IPO is a lethal mistake, the massive arbitrage hidden within the world's most misunderstood tech giant (ByteDance), and the raw post-mortem of their highest-profile mistake: Northvolt.We break down:The Philosophy Swerve: How a philosophy graduate skipped a PhD to build a multi-billion dollar growth engine and why Baillie Gifford deliberately hires people with no finance background.The Death of the IPO Monopoly: Why the world's most valuable hyper-growth companies no longer need public exchanges to unlock liquidity.Debt Kills, Dilution Doesn't: Peter's contrarian warning to scaling founders on why leverage is a ticking time bomb for pre-profitable businesses.The ByteDance Arbitrage: The inside story of buying shares at ~4x free cash flow while Western investors ran away.The Northvolt Post-Mortem: A transparent breakdown of their highest-profile mistake and how to spot a venture-stage asset masquerading as a growth-stage giant.Disrupting the 2-and-20 Norm: How Baillie Gifford structures an ultra-LP-friendly 1-and-10 fee model charged on invested capital, not committed capital.TIMELINE : 00:00 – "You get the shareholders you deserve": the long-term underwriting mindset00:53 – From philosophy to growth equity: why Baillie Gifford avoids finance backgrounds05:44 – Entry mechanics: Tesla's $3B public entry vs SpaceX's $30B private scale08:23 – The leverage trap: why a little dilution never killed a business, but debt does13:50 – Democratizing elite assets: how the Schiehallion Fund opens up Stripe, SpaceX & Databricks to everyday savers23:15 – Designing the ideal IPO: why chasing the highest possible price destroys public-market trust30:07 – The founder risk matrix: Bezos' 1997 shareholder letter & Musk's "bet the house" blueprint35:30 – The ByteDance arbitrage: buying shares at ~4x free cash flow52:47 – Flipping the venture fee model: the LP-friendly 1-and-10 on invested capital56:09 – The Northvolt post-mortem: growth equity risk vs venture equity riskREFERENCESElon Musk Jeff Bezos Jeff Bezos’s letter to his shareholders in 1997Warren Buffett Larry AshbrookHendrick Borginon Baillie Gifford Tesla SpaceX ByteDance Amazon Alibaba Anduril Bending SpoonsAirbnbSpotify StripeDatabricksAffirmWiseTempusKlarna FigmaNorthvoltUberLyftMeta (Facebook)
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  Why high valuations are secretly killing tech unicorns — Martino Cadoni [Deepl] 12.06.2026 58m

  On this episode of BILLIONS, I'm sitting down with elite finance operator Martino Cadoni, current CFO of DeepL (one of Europe's leading AI companies) and the veteran strategist behind one of Central Europe's biggest banking IPOs.Martino cut his teeth in corporate America's legendary "CFO factory" the grueling General Electric leadership program, working relentless 996 schedules to solve high-stakes financial fires across the globe. From being flown to Budapest on a day's notice to re-evaluate multi-million dollar reserves in two weeks during a currency crisis, to managing capital and balance-sheet strategy as deputy CFO at HSBC, Martino knows exactly what it takes to build institutional readiness.In this masterclass, he pulls back the curtain on private vs. public markets, exposing the lethal structural mistakes tech unicorns make during down rounds and explaining exactly how legacy banking giants accidentally funded their own demise.In this masterclass, we break down:The GE CFO Factory: Inside the intense 996 operational rotation program that builds high-agency, first-principles problem solvers.The "Zombie Corn" Trap: Why raising capital at massive valuations with high preferred share thresholds completely paralyzes tech startups when the market turns.The Balance Sheet Obsession: Why optimizing accounts payable, invoice due dates, and basic payment timing yields instant cash flow wins that most tech companies completely step over.The AI Billing Paradigm Shift: Navigating the massive industry uncertainty around revenue models—from traditional per-seat subscriptions to usage and outcome-based billing.How Traditional Banking Lost: Why legacy financial institutions wasted billions on stock buybacks and short-term dividends instead of innovating, allowing Revolut and Nubank to ruthlessly strip away their market share.TIMELINE : 00:00 – Finance as an Accelerator: The core value-creation thesis + who Martino is (from a $749M banking IPO to DeepL).01:26 – The GE "CFO Factory": Rotations, the 996 schedule, the Budapest currency emergency, and the Toyota/agile principles behind high-agency finance.10:34 – The Balance Sheet Obsession: Why tech over-indexes on the P&L, and the easy cash wins in accounts payable, invoice timing, and FX.17:48 – Public Markets, SOX & the Cost of Capital: Building precise guidance, how interest-rate cycles dictate fintech lending, and Revolut's revenue diversification.27:49 – The "Zombie Corn" Trap: How high preferred-share thresholds freeze startups when the market turns and the common-share advantage.35:12 – Down Rounds & Cap Table Management: Pitching fresh investors a path to upside, and why a concentrated cap table lets you manage LPs one-on-one.41:26 – Why DeepL & the AI Billing Shift: Joining Europe's AI race, and the industry struggle to move from per-seat to usage and outcome-based pricing.50:13 – Defensibility & the Short-Term Trap: Avoiding FOMO, building embedded moats, and how legacy banks burned billions on buybacks while Revolut and Nubank ate their lunch.REFERENCESThierry PietonKazuma ShipchandlerJohn Elkann Jarek KutylowskiMatt Cohler Danny RimerGeneral Electric (GE) Converteam Moneta Money BankKlarna DeepL Revolut BenchmarkIndex VenturesIVPIconicB2VentureGICATomicoOntario Teachers' Pension Plan
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  How a $75 sneaker bot became a $300M/Month financial engine - Steven Schwartz [Whop] 04.06.2026 53m

  Is traditional international banking officially obsolete?On this episode of BILLIONS, I'm sitting down with Steven Schwartz, co-founder of Whop, the internet marketplace that is quietly constructing a brand-new financial infrastructure for global creators.What started as a simple $75 sneaker bot sold in Facebook groups has exploded into a massive global network. Today, Whop is a powerhouse where nearly 40,000 people earn over $300 million every single month, and the platform processes nearly $1 million daily in physical product sales alone.Steven breaks down how they partnered with stablecoin giant Tether to unlock open financial networks for unbanked regions across the globe, why they are deliberately driving traditional credit card processing fees to zero, and why 70% of his entire corporate team consists of former founders.In this masterclass, we break down:The Facebook Group Bootstrapping: How Steven and his co-founder Cameron built an iOS app to flip Yeezys and turned a micro-win into an addiction.The Core Pivot: Moving from niche downloadable software keys to hosting full community ecosystems with integrated chat rooms and video courses.The Midtown Micro-Payments Project: The wild story of building laminated QR code profiles to route Apple Pay and Venmo donations directly to the homeless.Commoditizing the Gatekeepers: Why Whop refuses to profit off standard credit card processing and is actively racing payment margins to zero.The On-Chain Future: How stablecoin rails let an entrepreneur in Nigeria, Thailand, or anywhere without reliable banking infrastructure send and receive money across borders, building a real business without ever needing a legacy bank account.Hiring High Agency: Why Whop acquires companies first and foremost for talent, bringing in former founders who are high-agency, obsessive, and have already built zero-to-one products, rather than chasing headcount.TIMELINE 00:00 – The $75 Sneaker Bot: monitoring Nike's Twitter to auto-buy rare drops03:09 – The Pivot: from niche software keys to courses & private communities05:34 – Payments Philosophy: the homeless QR-code project & racing fees to zero08:34 – The Tether Bet: stablecoins & bypassing legacy banks for the unbanked19:32 – "Powered by Whop": the viral loop & the zero-fee ecosystem23:48 – Acquiring for Talent: why 70% of the team are former founders40:04 – From Alabama Construction to $180K/Month: real-world impact42:38 – "Eating Glass": the perseverance to deliver a global mission
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  Very few growth moats will survive AI - Sandy Diao [Descript] 28.05.2026 57m

  On 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] 22.05.2026 58m

  On 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] 15.05.2026 51m

  Is 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 Machine01:20 – 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 websiteREFERENCESBen HorowitzAli GhodsiElon Muska16zBerkeley, MIT, Stanford RegeneronAnthropicOpenAI Gemini / GCPSalesforcePalantirAdobeNeonApache SparkDelta LakeMLflow Apache IcebergHadoop GenieLake Watch Lakehouse Databricks One
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  $100M ARR in 7 quarters: inside the $10B AI machine - Reggie Marable [Sierra] 07.05.2026 48m

  On 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 :Muhammad Ali Jay-Z Dr. Martin Luther King Jr. Brian TracyAlbert EinsteinNelson MandelaBrett TaylorClay BavorRyan RaddingElliot GreenwaldLily WangStephanie EvansGreg MarshMandy St. Leger Morehouse College Canadian Football League SprintSalesforceSlackSierraCigna Next SingtelAfrotech & Sistas in Sales
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  Creating a $140B market: The secondary market masterclass - Larry Aschebrook [G Squared] 30.04.2026 56m

  Today 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] 28.04.2026 48m

  Is 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] 16.04.2026 58m

  On 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] 09.04.2026 1h 2m

  On 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 : Heather BrunerAnnie Duke Daniel Pink Lazar JovanovicElon Musk SmartBear WP Engine HubSpot BasecampShopify Waymo Notion Google SheetsElasticsearch Algolia Lovable Claude Code
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  Never wrote a line of code, now a $6.6B unicorn : the vibe coder - Lazar Jovanovic [Lovable] 02.04.2026 1h 1m

  Lazar 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] 28.03.2026 55m

  Today 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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  Building Odoo's American war machine - Wilfried Juncker [Odoo] 19.03.2026 54m

  Today 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
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  From selling startups to Google to backing multibillion‑dollar AI winners - Anish Acharya [a16Z] 12.03.2026 55m

  Today 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
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  The man who helped OpenAI to go from millions to billions in revenue - Zack Kass [Open AI] 06.03.2026 53m

  Today 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