The AI-First Business Podcast

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

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/

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

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.

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.

She spent a decade in public health—and built the product she wished existed.Ludovica’s journey spans biotech, epigenetics, and behavior change. But after years designing obesity interventions, one insight stuck: people don’t need more advice—they need fewer barriers.She founded Reveal My Food to make healthy eating frictionless. It’s the first AI-powered nutrition and food-ordering platform designed for employee health—merging science, behavioral design, and real-time environments.In this episode:Why education doesn’t change eating habits—but context doesHow to build for default choices, not willpowerThe hidden architecture of obesogenic environmentsWhat nutrition tech gets wrong about human behaviorHer goal? Return 100 million years of good health to humanity. And it starts with what’s on your plate—by design.📖 Chapters(00:00:00) Why culture and diet are inseparable(00:03:08) From biotech to public health: Her path to food systems(00:06:33) How society makes healthy eating nearly impossible(00:10:20) The rise of the obesogenic food environment(00:13:18) Why public health interventions fail(00:19:38) From physical to digital food environments(00:22:47) The pitch: What Reveal My Food actually does(00:24:50) How AI personalizes workplace meals(00:29:10) Why staff canteens are the perfect entry point(00:33:10) Building the largest real-world nutrition dataset(00:36:12) What AI unlocks that wasn’t possible beforeConnect with Ludovica de Pieri www.linkedin.com/in/ludovicadepieriConnect with Reveal My Foodhttps://www.revealmyfood.com/https://www.youtube.com/@Revealmyfoodhttps://www.instagram.com/revealmyfood/

"Culturalization isn’t just better marketing—it’s survival."What’s the right way to scale globally with AI? Is localization enough—or do you need cultural depth to win trust and customers?This episode is part of our **Revolut Mafia Series**, spotlighting the 100+ alumni now building some of the sharpest AI startups in tech.Ashish and Ahmed, co-founders of Native (ex-Revolut), debate what it takes to break into new markets when AI drops the cost of experimentation to near zero. Ashish argues for deep culturalization—reshaping content for meaning, not just translation. Ahmed says simplicity scales better—and over-culturizing adds bloat and risk.This episode covers:-How AI is redefining global marketingWhen localization fails (and why)What Revolut taught them about fast shipping and market trustThe rise of technical founders as AI-native operatorsIf you're building a startup, launching in multiple markets, or rethinking your GTM strategy—this is required viewing.📖 Chapters(00:00:00) From Revolut to Nativ: Founders’ origin story(00:02:17) Why global marketing is broken—and what Nativ fixes(00:06:39) AI-native founding: How building companies just changed(00:10:26) Why VCs want technical founders now(00:16:14) The Revolut culture: Extreme ownership + execution(00:20:12) Scaling signals: When to go all in(00:24:17) Localization ≠ translation: The real nuance(00:34:38) What most teams get wrong about global content🤝 Connect with AshishLinkedin and X YoutubeDataShines GithubAshish Ranjan Jha on Floating QuestionsPublished work on AI/MLFight Fraud with Machine Learning  [author]🤝 Connect with AhmedLinkedin and XInstagram and TikTokwww.ahmedahres.com⁠ Machine learning engineer: the job of a problem-solverAhmed Ares on Platform Rules Podcast➡️ Nativhttps://www.usenativ.com/ https://speedrun.a16z.com/companies/nativ 

AI Agents Are Quietly Turning Your Back Office Into a Growth EngineMost companies still treat finance and operations as cost centers. Sumant Shringari thinks that’s outdated — and dangerous.In this episode, Sumant explains how his company Pontus uses AI agents, automation, and machine learning to turn back-office chaos into serious business value. Finance isn’t just about reporting anymore — it’s becoming a core growth engine. By eliminating inefficiencies and unlocking operational leverage, companies are converting bloat into scalable revenue. Forget “support functions” — this is where your next margin expansion lives. If you're not deploying AI to turn operational chaos into value, you’re already falling behind.Sumant Shringari is the founder of PONTUS, where he helps the world’s largest enterprises eliminate inefficiency through outcome based automation. Before launching PONTUS, he led product at Gordian Software, powering revenue gains for travel giants like Booking.com and Priceline. A former AI researcher, Sumant has published several papers at the intersection of artificial intelligence and biology. He holds five degrees from the University of Pennsylvania—which, in hindsight, may have been excessive.#AI #AIagents #Automation #Finance #OperationalEfficiency #CostCenters #ValueDrivers #BusinessTransformation #TechnologyAdoption #MachineLearningConnect with Sumant ShringariPublished Academic Work from Sumant ShringariConnect with PONTUS🔗 LinksPontus Business Case FrameworkLenny’s Podcast + NewsletterWes Kao's NewsletterPattern Recognition and Machine Learning (Information Science and Statistics) by Christopher BishopAndrej KarpathySelling With: The art of selling with champions to shape internal buying conversations & close enterprise deals by Nate Nasralla Enjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

What do venture capital, layer cakes, and early-stage startups have in common? Tyler from Menlo Ventures breaks it all down. With 15 years in the VC game, Tyler’s focus on FinTech and vertical SaaS has led him to develop the “layer cake” approach—building businesses with stacked, sustainable revenue models. He dives into the importance of long-term customer retention, adding products post-acquisition, and spotting early product-market fit.But is the layer cake model the best strategy? While Tyler champions sustainable, customer-focused growth, not everyone’s convinced. Are traditional growth models better at managing risks like customer dependency and market volatility? Tune in to hear Tyler’s take on startups, Menlo’s hands-on support for founders, and why he thinks "flat revenue cohorts" are the key to long-term success.If you’ve ever wondered how venture capitalists spot the next big thing—or how "beautiful layer cakes" fit into all of this—this episode has you covered.Topics Covered:The "layer cake" business model for scaling startups.FinTech and vertical SaaS investment strategies.Menlo Ventures' hands-on approach to building great teams.For: Founders, aspiring VCs, and anyone curious about how startups grow—or fail.Connect with Tyler Sosin hereTyler Sosin LinkedinMenlo VenturesConnect with Ash Akhan hereAsh Akhan LinkedinEpisode References:GoCardless Y CombinatorEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

AI wasn’t always a welcome guest in cybersecurity—but that changed with Darktrace.🎙️ In this episode, CISO Michael Beck shares how he left the UK  government to tackle a new kind of threat landscape: one where traditional defenses  were no longer enough, and AI had to prove its worth in the face of deep industry skepticism .📌We break down:🔍 The early resistance: Why AI in cybersecurity was dismissed—and what it took to gain trust 📈 Darktrace’s blueprint: How anomaly detection and continuous learning  redefined cyber defense ⚙️ Adoption lessons: What teams need to know when integrating AI into legacy systems 🧍‍♂️ The human factor: Why perception, communication, and credibility are as important as the tech itself  This episode is for:👩‍💼 Leaders navigating AI integration🛠️ Builders scaling in critical industries🧠 Anyone curious how trust, timing, and innovation collide in high-stakes environments Connect with Michael Beck:LinkedinPodcase Episode: Gen AI in Cybersecurity: Innovations, Threats, and Defence Strategies with DarktraceDarktrace:WebsiteThe AI Arsenal: Understanding the Tools Shaping CybersecuritReferences:National Cyber Security Center (NCSC)Verizon Data Breach Investigations Report (2025)Red Team / Blue TeamBook Reco: Financial IntelligenceMovie Reco: WarGamesMITRE ATT&CK🎯 Did we hit the mark for you? Help us win favor with the algorithm gods, drop a 5 ⭐️ rating and like!📺 Watch the full episode now on Youtube🔥 Want early-access and exclusive content? Subscribe on Substack or follow our channelsEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

What happens when a life shaped by East London streets, children’s homes, and prison pivots to building tech startups? Meet Duane—who found his way to becoming tech founder from a different angle. In this episode, Duane breaks down his wild transformation from running with the wrong crowd to running his own B2B tech ventures in accounting, HR, and payroll. Spoiler: coding saved the day.Key Highlights:From children’s homes to prison, Duane’s early environment shaped his path—until it didn’t.Prison reflections sparked a shift: what’s your plan, or are you just part of someone else’s?Tech became the escape route, with coding opening doors to building successful businesses.Duane doesn’t hold back, sharing raw insights into how resilience, reflection, and intentional living redefined his future. This one’s for the hustlers and tinkerers navigating life’s curveballs. Tune in for a story of grit, growth, and second chances in the tech game.Connect with Duane Jackson hereConnect with Ash Akhan here#Entrepreneurship #TechFounder #ResilienceEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

The hustle is born from finding solutions no one else has thought of.What’s the secret sauce behind startup success? Steve dives into the chaotic early days of GoCardless—think empty offices, language barriers, and an emerging Shoreditch tech scene. From gritty beginnings to creating Duffel, a travel tech innovator, this episode unpacks the lessons, laughs, and challenges that shaped some of the UK’s most notable entrepreneurs.Discover how the GoCardless alumni network sparked industry-changing ventures and why APIs are revolutionizing the future of travel. Plus, hear Steve’s take on navigating cultural shifts, balancing creativity with business, and why the startup grind might just be worth it.Whether you're an entrepreneur, a tech enthusiast, or just here for the stories, this one’s for you.Connect with Steve Domin hereSteve Domin LinkedinDuffelDuffel LinkedinConnect with Ash Akhan hereAsh Akhan LinkedinEpisode References:| GoCardless | GoCardless || Y Combinator | Y Combinator |#VentureCapital #FinTechInnovation #StartupFunding #LayerCakeStrategy #BusinessGrowth #InvestmentTrends #TechEntrepreneurship #SaaSInvestment #TheFutureofFinance #Startups #AI #ArtificialIntelligence #BusinessTransformation #AIInnovation #Leadership #AIFuture #TechStartups #DigitalTransformation #InnovationPlaybook #AIadoptionEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

"In the rush to engineer cutting-edge AI, don't forget the user; it's not just about creating technology for the sake of it, but about how it genuinely improves our work experience."Michael Machado, who led the development of Salesforce Anywhere, Salesforce AI research, and  Einstein Voice at Salesforce, now leads DevRev with a modern approach to product management that fuses design, engineering, and AI to shape the future of work. We discuss Agent OS (AI-powered operating systems designed for autonomous agents) and how to bring customers and product developers closer.This episode is perfect for startup founders, product managers, AI enthusiasts, and anyone looking to modernize business workflows. It’s especially useful for teams aiming to integrate AI into their products, streamline customer support, and adopt a design-first approach for a competitive edge. If you’re curious about the future of work and how cutting-edge platforms like DevRev are shaping it, this one’s for you.Connect with Michael Machado:LinkedIn2022 San Francisco CTO Summit: Michael Machado on Legacy Support Tools vs AIMichael's Journey from CRM > Dev CRMEffortless 2023 Conference DevRev:Linkedin and WebsiteInstagramYoutubeReferences:Unreasonable HospitalityEinstein VoiceEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Is the future of healthcare being shaped without doctors? Dr. Sven Jungmann dives into the growing role of AI in medicine, the ethical dilemmas, and why many physicians feel left behind in this tech revolution.We explore the reality of physician shortages, an aging population, and how AI could ease the pressure—but only if doctors get involved. With many eager to adopt AI, the barriers are glaring: no access to resources, poor collaboration with developers, and a widening knowledge gap.Who’s driving this change—tech or medicine? And what happens when ethical considerations fall through the cracks? Dr. Jungmann and Tina Yazdi dig into the messy intersection of healthcare and AI, exposing both the promise and pitfalls.Key points:How AI is reshaping healthcare workflows and redefining the roles of doctors and nurses.The disconnect between physicians and developers that’s slowing innovation.Why ethical AI development demands healthcare professional involvement.The opportunities AI presents for reducing burnout, boosting efficiency, and improving care.Will AI be the saving grace of healthcare—or just another tech-driven misstep? Tune in to rethink the future of medicine.Connect with Dr. Sven JungmannWebsiteLinkedinInstagramPublished WorkBooks by Dr JungmannSiftedMedical LiteratureEpisode References:Design ThinkingBiomedical InformaticsAlgorithmic Bias (Clinical)Fosbury FlopBreath Analysis TechnologyPhysician Availability CrisisEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Are traditional healthcare models ready for the disruptive innovations of entrepreneurs like Dr. Sven Jungmann?With extensive medical expertise and entrepreneurial vision, Dr. Jungmann co-founded Halitus to develop state-of-the-art breath analysis devices. Using AI/ML and digital health, Dr. Jungmann is bridging healthcare and tech.We cover:Dr. Sven Jungmann's shift from traditional medicine to entrepreneurshipHow Halitus is building scalable breath analysis by combining AI/ML with medical hardwareThe need for multidisciplinary healthcare innovation to reduce riskHow data and technology help healthcare become more patient-centric and efficientUnexpected fundraising challenges for hardware-based innovation"Gold standards" for AI-driven diagnosticsWho will and won't benefit from AIRegulatory and market challenges facing healthcare innovatorsConnect with Dr. Sven JungmannWebsiteLinkedinInstagramHalitus and moreHalitusSpeedinvestcapitalmind investecWellster HealthtechCASCPublished WorkFightBack NOWBeyond the Bedside: A doctor’s guide for careers outside the hospitalWie gesund wollen wir sein?SiftedMedical LiteratureEpisode References:Forward + Adrian AounDr. Wiktor SzczudlinskiGalen on olfactionCT Scans for Lung DiseaseEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

'AI-First' has replaced 'Data-Driven'. AI technology must be integrated into systems, teams, tools, and products to survive. But what about the legal and compliance?Ramakrishnan has been at the forefront of AI adoption for enterprises, having held executive and advisory roles at Element AI and Perpetua Labs. Currently, he's co-founder and CEO at Armilla AI, which is pioneering insurance for organizations that train, develop and deploy AI systems:The real decision makers behind AI initiativesTop-down regulations vs. bottom-up ethical AIBlack box AI systems + best practices for model testing"Ground truths" for compliant and ethical systemsExisting frameworks for complianceContingencies and repairing trustMore:Karthik RamakrishnanAI Maturity FrameworkLeadership in Insurance PodcastNavigating Code Quirks & Corporate Quandaries2024 Predictions: Regulation, Risk, and InnovationReferences:Lawsuits - Air Canada, Cigna, State FarmAI is changing cybersecurityRed teaming: Guide to testing AI modelsKathy Baxter + Salesforce: AI Ethics Maturity ModelEU AI ActAutomation In HistoryChief AI OfficerExisting StandardsNISTISO/IEC 42001Responsible AI (RAI)McKinseyEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Join us to dive into the world of AI infrastructure  with Wes Cummins, CEO and Chairman of Applied Digital. Prior to founding the company he also founded and led 272 Capital LP and led B. Riley Asset Management as President. Applied Digital (Nasdaq: APLD) designs, develops and operates next-generation datacenters across North America to provide digital infrastructure solutions to the rapidly growing high performance computing (HPC) industry.Discover the distinctions between traditional and high-power density data centers, and learn how competition for electricity is shaping the industry.Explore the diverse customer personas in the AI infrastructure market, from hyperscalers to Gen.AI startups, and gain insights into the future of compute for AI. Wes also shares valuable tips for companies venturing into GPU compute and finding the right partners. We Cover:Why do AI infrastructure demands necessitate high-power density data centers, and how do they differ from traditional ones?What's driving the escalating demand for compute power in the AI market, and how does it fuel competition for electricity?Who are the key customer personas shaping the AI infrastructure landscape, from hyperscalers to Gen.AI startups and enterprise giants?What are the diverse purchasing options for AI infrastructure, ranging from ownership to cloud services, and what choices exist for GPU compute?What are the common pitfalls to avoid when venturing into GPU compute, such as accessibility issues and hardware management challenges?How can you effectively locate GPU compute companies, whether through online searches or exploring smaller vendors alongside major cloud providers?What does the future hold for data centers as the gatekeepers of AI compute deployments, and why is there a growing focus on their power consumption?Connect with Wes Cummins here:Linkedin Applied Digital Episode References:Nvidia’s H100 – What It Is, What It Does, and Why It MatterskW, MW and GW: How electricity units work and how to convert themThe State of Digital Assets Data and Infrastructure: 2023 Edition Sponsored by AmberdataNvidia H100s shipped 2023Hugging Face: The platform where the machineEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Ben Parr is a tech industry veteran with a career spanning from award-winning author to influential editor at CNET and Mashable. He's also the co-founder of Octane AI and the driving force behind the AI Analyst, a decade-long voice at the intersection of tech, business, media, and society. 💼🚀📱🎙️ Looking for daily strategies on how to integrate AI into your life and work? Then this episode is for you. Ben shares his take on where we are in the story (these tools are the worst they will ever be right now), the mindset for success (using AI vs being AI-first), and why the changes in this past year are comparable (or outpacing) the mobile revolution.Key takeaways from our conversation with Ben:📦 AI's Impact on E-commerce: AI plays an increasingly important role in e-commerce. For example, companies like Octane AI are already being used to enhance customer experiences through product recommendations and personalized interactions.🧠 Embracing an AI-Native Mindset: The concept of being "AI-native" or having an "AI-first" mindset is crucial for individuals and organizations. You need to integrate AI into everyday workflows and tasks to stay competitive and adapt to the evolving technological landscape.🌍 Global AI Competition: You cannot ignore the geopolitical aspects of AI development, such as the competition among countries and companies to maintain leadership in AI. This includes potential risks and challenges associated with global AI competition.🚀 AI Across Industries: AI's influence extends across various industries, including social impact, governance, ethics, sustainability, finance, healthcare, education, and government.💥 The importance of personal brand in the age of AI: Personal branding is key in this evolving AI landscape, and it can set you apart for long-term success.📚 Stay Curious, Stay Ahead: It’s essential to invest in continuous learning and stay informed about AI trends and tools. Ben recommends daily experimentation with AI technologies to adapt to the changing AI landscape effectively.Connect with Ben here:BenParr.comBen Parr on LinkedinThe AI Analyst NewsletterCoWorking with AI on Maven In this course Ben teaches you the fundamentals of incorporating AI into your work: tips, tricks, tools and optimizations that will save your company and careerCaptivologyIn this book Ben examines the psychological phenomena that captivate our attentionEpisode References:Octane AISubscribe to the AI Analyst hereGenerative AI Cheat SheetAI Code of EthicsEvenUp LaEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Engineers and data leads engaged in grassroots AI projects or tackling challenges related to AI headcount, budget, and ROI expectations might find this episode particularly resonates. Hadrian's Klaas Meinke and Jasper Insinger join us to share their experiences in founding AI projects at Hadrian, collaborating across functions, and achieving business ROI in AI deployments.Klaas, an aerospace engineering graduate from TU Delft, made a significant transition from astronomy research to Hadrian. Recognizing the transformative potential of AI and big data, he has been an integral part of Hadrian for almost a year, working as an AI machine learning engineer and data scientist.Jasper, a TU Delft electrical engineering graduate, brings his unique background to the conversation. With hands-on experience in solar car engineering and a remarkable win in the Sasol Solar Challenge, he smoothly transitioned into cybersecurity, becoming a founding member of Hadrian's data team.Key Takeaways:Mindset: Maintaining the right mindset is crucial role. Technical expertise alone is insufficient, and success hinges on a positive and critical mindsetTaking Ownership: Underscoring the importance of assuming ownership of one's work and refraining from attributing blame to others, teams should focus on proactively seeking opportunities for improvement and drive positive changePrioritizing Continuous Improvement: The conversation consistently highlights the value of ongoing advancement, stressing the significance of identifying areas for improvement, actively seeking feedback, and striving to enhance outputEmbracing Feedback and Constructive Critique: Examples are shared of how soliciting feedback from peers, embracing criticism, and fostering self-critique have played a pivotal role in deploying and validating critical AI deploymentsPromoting Teamwork and Collaboration: The discussion indirectly underscores the importance of teamwork and collaboration. The focus on seeking feedback and self-improvement supports a collaborative approach to problem-solving and skill developmentEpisode References:South Africa's Sasol Solar ChallengeDutch Team's Sasol 2022 WinHadrian.ioMore from Klaas: How Generative AI is Shaping CybercrimeConnect with Klaas and Jasper here:Klaas on LinkedinKlaas on How Generative AI is Shaping CybercrimeEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Joseph Reeve from Amplitude Analytics' AI R&D team explores the world of building intelligent digital products using AI and ML. In our conversation we cover:Data Governance: Discussion on the importance of data governance, including proactive and reactive strategies. Proactive governance involves planning data collection, while reactive governance focuses on fixing data issues after they occur.Interdisciplinary Collaboration: Highlighting the interdisciplinary nature of AI projects and the significance of collaboration among different roles to achieve success.AI in Digital Products: Delving into the role of AI in the future of digital products, emphasizing integration into every feature for personalized experiences.Key Takeaways: Exploring lessons learned from their journey, such as the importance of trust in data, robust data governance, and rapid iteration.Team Structure: Describing the team at Amplitude, consisting of product engineers and machine learning scientists, and their unconventional formation from a data governance sub-team.Collaboration: Emphasizing the importance of shorter feedback loops, tight collaboration, and a clear product roadmap in achieving success.Large Language Models: Discussing the introduction of Large Language Models (LLMs) internally, with a focus on smaller features that garnered more adoption.Stakeholder Management: Addressing the challenges of managing stakeholders and effectively communicating the scope and impact of AI projects within the organization.Overall, the conversation provides insights into building intelligent digital products with a strong focus on data governance, collaboration, and the evolving role of AI in the digital product landscape.Episode References:Iteratively on Product Hunt (Acquired by Amplitude Analytics)Sustaining vs Disruptive Innovation (HBR)Passive vs Active Data GovernanceTarget Fixation ProblemPageSpeed InsightsWhat is Prompt Engineering?What is Prompt Architecture?Amplitude Analytics x Iteratively AcquisitionMore about Amplitude AnalyticsConnect with Joe here:Joseph Reeve on LinkedinEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

You can view screen-share from Paul on Youtube hereIn this episode, Keeper's Founder and CEO Paul Koullick explores the transformative impact of AI for tax preparation software. He discusses the limitations of rules-based systems and how AI, as exemplified by Keeper, simplifies tax preparation with machine learning.Paul also delves into the changing perception of AI, from being a novelty to a valuable tool for various industries, emphasizing its broader applications in user interfaces and product development.Additionally, the podcast addresses the role of AI in job markets, emphasizing its potential to enhance productivity rather than replace jobs. Paul provides practical advice for job seekers assessing AI technology in companies and offers insights into personal AI use cases, including travel planning and customer support.Tune in for a comprehensive exploration of AI's evolution, impact, and practical implications in various domains.Episode References:Choosing between a rule-based vs. machine learning systemGPT 3 vs. 4: Know The DifferenceCLIPPYAsk an AI Account Research Paper (Keeper)More Whitepapers on KeeperMore about KeeperConnect with Paul here:Paul Koullick on LinkedinPaul Koullick on MediumEnjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.

Amin's journey into the world of artificial intelligence (AI) began around 2006 when he became captivated by the potential of neural networks to learn from data. He noticed that AI experienced periods of intense hype followed by quieter moments.Amin delved into AI by building neural networks from scratch in C. This hands-on experience enabled him to understand AI models thoroughly and create complex applications.In his industry work, Amin applied AI knowledge to real-world applications.In business discussions, Amin highlights the challenge of balancing quick wins and long-term investments when adopting emerging tech like AI.Amin identifies five pillars that companies should consider when evaluating AI investments:Investment in Data Infrastructure: Focusing on data governance and infrastructure to enable smarter applications.Data Collection, Processing, and Storage: Establishing best practices for data collection, labeling, and reliable model training.Cleaning Data and Validation: Recognizing the challenge of data cleaning, validation, and labeling, particularly as GDPR regulations emphasize ethical data usage.Ethical Framework for Data Usage: Ensuring transparency and compliance with data privacy regulations like GDPR.Creating an AI Supporting Ecosystem: Building an ecosystem that goes beyond technology, fostering organizational cultures that understand AI's value and prioritize trust and transparency.Amin also emphasizes the need for companies to develop a clear AI roadmap aligned with their business objectives and integrate AI into their products and services strategically. While the AI hype can be beneficial in motivating companies to adopt AI, the associated risks lie in not having a well-defined plan or understanding of how AI can genuinely add value. To become AI-ready, companies must prioritize the business value of AI over its "coolness factor" and invest in the right talent to guide their AI initiatives.Episode References:Turbo PascalNeural NetworksMachine LearningJürgen SchmidhuberLSTM'sVanishing Gradient ProblemGDPR (EU's Data Protection Laws)Gradient Boosting Machines (GBMs)Graphcore AIGeoffrey HintonConnect with Amin here:Enjoyed the episode? Drop us a ⭐️⭐️⭐️⭐️⭐️ — it helps more builders find us. 📺 Watch on YouTube 🔥 Subscribe for weekly drops 📲 Follow us on socials here 🎙️ The AI-First Business Podcast AI isn’t coming—it’s already built. 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. Disclaimer: Views are personal and do not reflect any affiliated organizations. Content is for informational purposes only.