How Revolut's Metric Obsession Accidentally Built a Founder Factory (46+ Alumni Startups)
He bought Amazon gift cards out of his own pocket to hit his KPIs. That's what metric obsession looks like at Revolut.Pierre Cahuzac is a product leader at Europe's most valuable fintech—and explains why their alumni start companies at ridiculous rates. It's not the dashboards. It's the ownership model.You'll walk away with Revolut's framework for organizing teams around metrics instead of code, the P50 vs P10 methodology for identifying human vs machine performance gaps, and why artificial deadlines create throwaway work.Six years at Revolut. Multiple product rescues. One core insight: when you own KPIs instead of features, you start thinking like a founder.Pierre breaks down the "minimum path to value" framework, how to push back on impossible targets from executives, and why their country expansion machine beats custom local builds.Plus: the real reason Revolut produces so many entrepreneur alumni, and what "onion layer thinking" means for cross-functional leadership.🤝 Connect with PierrePierre Cahuzachttps://www.youtube.com/watch?v=r1INVEjqo3M Ep. 37 Getting It Done: RB5 and the future of business finance Revolut Business 5⏱ Episode Chapters(00:00) From film director to Revolut: The unconventional path(06:14) Why film financing was too slow for innovation(10:27) How Revolut’s metric obsession works in practice(15:08) Building products with global vision, local execution(17:49) When ambitious targets almost broke the team(26:00) The Revolut Mafia: Alumni and entrepreneurship(29:07) Patterns in fintech founders(31:33) Future predictions and final thoughts#AIFirstBusiness #ProductManagement #Revolut #FinTech #StartupFounders #MetricsDriven #ProductStrategy
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From Bedroom Coding to VC Bidding War: The Small AI Models Thesis That Broke Silicon Valley
He bet against trillion-parameter models when every VC said he was insane—now NVIDIA is publishing papers proving him right.Sudarshan from Smallest.ai cracked enterprise voice AI by ignoring Silicon Valley's foundation model obsession. While competitors chased infinite compute, his autonomous vehicle background revealed the truth: compact models handling life-or-death navigation decisions outperform bloated systems requiring massive resources.The contrarian thesis almost killed fundraising until one viral launch changed everything. World's fastest text-to-speech hits millions of views, multiple term sheets arrive the same day, $8M seed closes in two weeks. But thousands of curious developers meant zero revenue.The real breakthrough wasn't technical—it was understanding enterprise buyers. Companies don't want your API documentation. They want consultants who solve problems using AI, not AI companies hunting for use cases. The transformation from model provider to solution consultant unlocked Fortune 500 deals.You'll discover the playbook for contrarian deep tech bets, why enterprise AI adoption is messier than anyone admits🤝 Connect with Sudarshanhttps://www.linkedin.com/in/sudarshankamath/ https://www.linkedin.com/company/smallest/ https://smallest.ai https://www.youtube.com/@smallest_aihttps://www.forbes.com/sites/brentgleeson/2025/04/28/how-business-leaders-are-unlocking-ais-full-potential/
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Voice AI for Insurance: The Technology Finally Ready for Prime Time
Investment banking taught him speed, but Amir Prodensky needed something bigger to build.Fresh from Revolut's hyper-growth chaos, Amir saw the massive gap in financial services customer experience. Insurance customers were stuck with phone queues and paper processes while expecting Amazon-level service.So he built Strada: AI agents that handle every customer interaction across phone, text, email, and chat while maintaining perfect context. These aren't simple chatbots—they connect to core insurance systems and take real actions like generating certificates and processing claims.Amir's framework for AI adoption moves through five stages: from co-pilot tools to fully autonomous agents. The companies moving fastest through these stages are creating unbeatable competitive advantages.His prediction: customer expectations will shift permanently once they experience resolution at AI-speed. Traditional service will feel broken in comparison.🤝 Connect with Amirhttps://www.linkedin.com/company/getstrada/ https://www.linkedin.com/in/aprodensky/ https://www.getstrada.com/ ⏱ Episode Chapters(00:00) From Bay Street to insurance AI agents(01:46) Career pivots: Banking to Revolut's US expansion(05:16) Big bets at Revolut: What worked and what didn't(14:24) Finding Strada: From horizontal automation to insurance-focused AI(21:17) AI-native product development without designers(25:06) Rapid fire: AI tools and expensive experiments that worked🔥 Enjoyed the episode?Drop a like, subscribe, and share it with someone building fast.🎙 **The AI-First Business Podcast**Sharp strategy. Fast builds. Real AI.No panel chatter. No fluff. Just the moves that scale.📺 **Want more?**Search *AI-First Business Podcast* on Spotify, Apple, or wherever you get your podcasts.📲 **Follow us:**Instagram / TikTok / LinkedIn → @aifirstbusinessAll links: [feedlink.link/aifirstbusiness](https://feedlink.link/aifirstbusiness)⚠️ **Disclaimer:** Views are personal and not reflective of any organization. For informational purposes only.#AIInsurance #InsurTech #FinTechFounders #CustomerServiceAI #AIAgents #StartupJourney #InsuranceInnovation #VoiceAI #FinTech #TechFounders
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AI is Rewriting Data Roles—Will Your Team Survive the Shift?
He walked away from aerospace engineering and built a SaaS startup cutting data transformation time by 90%.Kaustav Mitra, co-founder and CEO of Paradime.io, shares how he turned a restless career path into a weapon—building teams with autonomy, betting on AI before the noise, and rethinking how companies manage data at scale.You’ll get clear on:Why autonomy isn’t a “nice to have” but a force multiplier.How AI is reshaping the modern data stack (ETL → ELT → AI-native).The leadership habits that let small teams compete with giants.Before Paradime.io, Kaustav cut his teeth scaling analytics at Revolut and Octopus. If you’re serious about using AI to collapse development cycles and increase business velocity, this one’s non-negotiable.🤝 Connect with Kaustav Mitra & Paradime.iohttps://www.linkedin.com/in/mitrakaustav https://www.linkedin.com/company/paradimelabswww.paradime.io https://www.youtube.com/@paradimelabs⏱ Episode Chapters(00:00) Kaustav’s unconventional career path(03:32) The MBA network that changed everything(06:02) Building Paradime with high-autonomy teams(12:16) Going AI-first with DinoAI(20:18) Leveling the playing field for startups with AI(25:28) ELT evolution and the future of the modern data stack(29:51) Educating customers on AI and reframing accuracy(36:24) Bridging human and machine-readable worlds(40:39) How AI will reshape data, teams, and entrepreneurship🔥 Enjoyed the episode?Drop a like, subscribe, and share it with someone building fast.🎙 **The AI-First Business Podcast**Sharp strategy. Fast builds. Real AI.No panel chatter. No fluff. Just the moves that scale.📺 **Want more?**Search *AI-First Business Podcast* on Spotify, Apple, or wherever you get your podcasts.📲 **Follow us:**Instagram / TikTok / LinkedIn → @aifirstbusinessAll links: [feedlink.link/aifirstbusiness](https://feedlink.link/aifirstbusiness)⚠️ **Disclaimer:** Views are personal and not reflective of any organization. For informational purposes only.
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AI’s Hidden Failure Point Is in Your Data Stack (it’s costing you millions)
Barr Moses grew up running experiments in her dad’s physics lab. Today, she’s the CEO of Monte Carlo, the leading platform for data + AI observability.This episode goes beyond her founder story. It’s about why data trust is the new currency in AI—and how Barr built the playbook for companies that want to move fast without breaking everything.She’ll show you:Why clean dashboards don’t mean reliable data.The messy middle of making data dependable at scale.The real reasons intuition still matters when the numbers run out.Listen if you want to bulletproof your AI stack from the inside out.Barr Moses is CEO & Co-Founder of Monte Carlo, a data + AI observability company backed by Accel, GGV, Redpoint, and other top Silicon Valley investors. Previously, she was VP Customer Operations at Gainsight, a management consultant at Bain & Company and served in the Israeli Air Force as a commander of an intelligence data analyst unit. Barr graduated from Stanford with a B.Sc. in Mathematical and Computational Science.🤝 Connect with Barr Moseshttps://www.linkedin.com/in/barrmoses https://www.montecarlodata.com/Barr is the author of the book ""Data Quality Fundamentals: A Practitioner's Guide to Building Trustworthy Data Pipelines." More info here: https://www.oreilly.com/library/view/data-quality-fundamentals/9781098112035/ Barr has written many articles, including:https://www.montecarlodata.com/blog-the-past-present-and-future-of-data-quality-management/ https://www.montecarlodata.com/blog-top-3-ai-problems-to-solve https://www.montecarlodata.com/blog-are-we-in-an-ai-bubble/ https://www.montecarlodata.com/blog-6-things-every-cdo-needs-to-know-about-ai-readiness/ https://www.montecarlodata.com/blog-ai-fomo-is-tearing-your-company-apart/ https://www.montecarlodata.com/blog-2026-will-be-the-year-of-data-ai-observability/ https://www.montecarlodata.com/blog-will-genai-replace-data-engineers https://www.montecarlodata.com/5-hard-truths-about-generative-ai-for-technology-leaders/⏱ Episode Chapters(00:00) Barr Moses’ early path from consulting to data(03:41) Lessons from building customer success at Gainsight(06:08) The pain of unreliable data and Monte Carlo’s origin story(08:43) Why data + AI observability must be end-to-end(12:58) The growing complexity of today’s data and AI supply chain(16:03) From data observability to AI observability(20:15) The four root causes of data and AI product failures(24:51) Rebuilding trust after AI incidents go wrong(29:55) When companies realize they need observability in place(33:02) The executive questions shaping AI adoption at scale(38:52) Maturity stages in data quality and observability(43:01) The tipping point for AI in production—and what’s next(45:20) How to prepare for AI experimentation failures(47:38) What keeps Barr motivated building in this space#DataObservability #AIInfrastructure #AIDataQuality #AIObservability #MonteCarloData #BarrMoses #AIProductFailures #DataReliability #AIInsights #AIDecisions #DataInnovation #TechLeadership #AIExecution #AIStartups #AIApplications #DecisionMaking #AIRevolution #DataDriven #BusinessStrategy #AILeadership🔥 Enjoyed the episode?Drop a like, subscribe, and share it with someone building fast.🎙 The AI-First Business PodcastSharp strategy. Fast builds. Real AI.No panel chatter. No fluff. Just the moves that scale.📺 Want more?Search AI-First Business Podcast on Spotify, Apple, or wherever you get your podcasts.📲 Follow us:Instagram / TikTok / LinkedIn → @aifirstbusinessAll links: feedlink.link/aifirstbusiness⚠️ Disclaimer: Views are personal and not reflective of any organization. For informational purposes only.
AI isn’t coming—it’s already built. Hosted by Tina Yazdi, this is the podcast where you meet the ones who did it first. No panel chatter, no posturing—just sharp strategy, fast builds, and the people reshaping products, ops, and industries with AI.
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