Podcasts about product podcast

n8n's founder puts the company's GitHub repo, nearly 200,000 stars, right next to the paid signup button, and he's genuinely fine if you never pay. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Jan Oberhauser, CEO of n8n, the open-source automation platform that's crossed $100 million in ARR at a $5.2 billion valuation. Jan breaks down the "fair-code" license bet that let him give the product away and still build a business, how that free version became the on-ramp into enterprises like Meta, Nvidia, Dell, Accenture, Vodafone, Deutsche Telekom, and Mercedes, and why he believes the people with the problem should build the automation themselves, not a centralized team or an outside agency.He also walks through a live build of a personal AI agent (email and calendar), shows how n8n falls back from Claude to GPT via OpenRouter when a model isn't available, and explains how enterprises get automations into production faster because each agent can only do exactly what it's been permitted to do.What you'll learn:Why n8n rejected traditional open source for a "fair-code" license, and how it avoided the community backlash that burned other companiesWhy trust and consistency, not features, are the real center of a communityHow the free, self-hosted version drives bottom-up adoption inside major enterprisesWhy "sprinkling AI on top" kills products, and what to build insteadHow to chain agents so one agent's output becomes the next agent's inputWhy n8n is the "connective tissue" between models, tools, and business systemsHow guardrails (an agent can only do what it's explicitly allowed) speed up enterprise procurement and productionWhy the people with the problem should own the building, not a centralized AI teamHow 10,000+ community templates and 500+ integrations expand what non-technical builders can shipHow one company routes 75% of support through an n8n agent, with customers happier than with humansConnect with Guest (Jan Oberhauser):LinkedIn: https://www.linkedin.com/in/janoberhauserX: https://x.com/JanOberhauserHost: Carlos, CEO at Product SchoolLinkedIn: https://www.linkedin.com/in/villaumbrosia/About Jan Oberholzer: Jan is the CEO of n8n, an open-source (fair-code) workflow automation and orchestration platform for building AI agents. He started the company over seven years ago, before LLMs went mainstream, and has grown it past $100M ARR at a $5.2B valuation.About the Product Podcast: Product School's podcast brings you candid conversations with the founders and product leaders shaping tech.Social Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Je change de format pour un article un peu plus intimiste où je vous partage ma vision du Product Marketing.J'ai eu l'occasion il y a quelques mois d'écrire la préface du livre blanc de WeFiiT dédié au PMM.J'en ai du coup profité pour poser mes idées :- Ma vision du Product Marketing aujourd'hui.- La manière dont j'appréhende ce métier.- Comment je le vois évoluer dans les années à venir.J'espère que ce format vous plaira. Si vous souhaitez plus de contenus de ce type, dites-le moi en MP !

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Amit Zavery, President and Chief Product Officer at ServiceNow. The platform runs more than 75 billion workflows a year with around $15 billion in annual revenue growing over 20%. Its market cap is above $100 billion, yet the stock is down more than 30% this past year, while its AI business is on track for $1.5 billion, ahead of a $1 billion plan. Amit previously ran product and platform at Oracle for over two decades and was a VP and General Manager at Google Cloud.What you'll learn:Why the market can't yet tell AI winners from losers, and why companies that don't transform will get killedWhy the idea of one company becoming the single end-to-end enterprise orchestrator is a fallacyThe spare part approach that makes most enterprise AI projects fail, and what pacesetters do insteadWhy access is shifting from user interfaces to agents, and what taking action actually requiresHow to hold long-term conviction on platform bets while the market judges you on short-term sentimentKey takeaways:Transform or die: the market will separate AI-native platforms from legacy vendorsInteroperability beats domination in the agentic eraGovernance only wins when it accelerates innovation, not when it blocks itCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Amit ZaverySocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Selma, Chief Revenue Officer chez Agorapulse explique sa vision sur la place du Product Marketing dans la performance commerciale.Au fil de son parcours, Selma a construit une vision très business du Product Marketing. Pour elle, cette fonction n'est pas un simple support marketing. C'est un levier qui permet d'aligner les équipes, d'améliorer la conversion, d'attirer les bons clients et de construire une croissance durable.Dans cet échange, elle partage sa vision du rôle du PMM et les signaux qui montrent qu'une entreprise a besoin de structurer cette fonction.Découvrez :

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Saral Jain, SVP of Engineering at Snapchat, the last independent social platform operating at global scale, with 956 million monthly active users closing in on the one billion mark and a community that opens the app more than 30 times a day. Saral joined Snap nine years ago, right around the IPO, after nearly a decade leading engineering teams at Amazon Web Services, and today leads all engineering for Snapchat, spanning product experiences, multi-cloud infrastructure, and the company's machine learning and generative AI platforms.What you'll learn:How Snap lets designers and product managers ship production code, with an AI agent running the first review pass on 90% of code within 5 minutesWhat Casper is: the AI teammate any team at Snap can invoke from Slack or Jira to build a working prototype from a conversationHow Snap turned company-wide AI adoption into business impact after early prototypes were being built and thrown awayHow lean startup squads mix engineers, designers, and data scientists to launch zero-to-one bets inside a mature platformKey takeaways:Quality control does not have to slow down who gets to ship, it has to change what reviews the work firstWidespread AI adoption is not the same as business impact, and the gap between the two is where most AI investment is being wasted right nowSmall, cross-functional teams with blurred roles can move faster than traditional org structures, even inside a billion-user companyCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Saral JainSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

On prend du recul sur le rôle du PMM à travers les yeux d'une responsable Marketing & Revenue.Selma, CRO chez Agorapulse partage sa vision de la fonction et les situations dans lesquelles elle crée le plus de valeur pour l'entreprise. Elle revient aussi sur un choix organisationnel fort chez Agorapulse : déplacer l'équipe PMM initialement au Produit sous son aile, puis faire évoluer progressivement son périmètre vers une équipe Go-To-Market qui ne se limite plus aux recommandations stratégiques, mais qui porte les sujets de bout en bout, de l'analyse du marché à l'exécution, avec des KPI directement liés au business.Selma nous partage des exemples concrets de collaboration avec le content, la lead gen et la brand pour arrêter de se marcher dessus mais aussi de ce qui permet à un PMM d'obtenir une place à la table des décisions.Enfin, elle revient sur plusieurs pivots de carrière qui ont marqué son parcours et partage ses réflexions pour faire des choix professionnels qui semblent contre-intuitif mais qui permettent de progresser sur le long terme.Si vous cherchez à renforcer votre impact business en tant que PMM, à confronter vos idées reçues et à mieux comprendre ce que la fonction Product Marketing  peut apporter à une organisation, cet épisode va vous donner quelques pistes de réflexion.Bonne écoute.RESSOURCES

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Jeff Kunins, Chief Product Officer and Chief Technology Officer at Axon, the company that created the Taser and the body cameras federal agencies wear. Axon ingests more video per year than YouTube, and with a market cap of approximately $32.9 billion and $2.78 billion in revenue, growing 33% year over year, it is one of the highest-growth companies in the S&P 500. What you'll learn:How law enforcement agencies are using AI inside body cameras and Tasers to save lives, not just hit metrics.Why Axon declared a public moratorium on facial recognition AI for six years and what finally changed.How Axon embeds external activists and researchers directly into product manager squads as a design input, not a compliance process.Building first-party AI models for real-time license plate detection while using foundation LLMs for everything else.Key takeaways:Axon created the Taser and the body cam, and now ingests more video per year than YouTube. Most people have never heard of them.Build only what you must to be differentiated. Everything else, license from the best available source.Ethics review is not a compliance burden. When embedded in the product lifecycle, external critics help you see around corners and design better products.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Jeff KuninsSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Arnab Bose, Chief Product Officer at Asana. Asana is the work management platform built for human and AI collaboration, trusted by over 170,000 customers including Accenture, Amazon, and Anthropic. The platform's Work Graph maps goals to portfolios to projects to tasks and serves as the foundation for Asana's AI Teammates: collaborative agents that operate inside the graph, learn from human decisions, and compound their intelligence with every cycle. What you'll learn:Why enterprise AI spend keeps returning zero productivity gains, and what is structurally breaking the loopWhy every employee approval, correction, or rejection of AI output is training data that makes the system smarter over timeHow Asana wires its own processes through the Work Graph so that AI decisions write back automatically and compound rather than resetHow PLG, forward-deployed engineers, and AI agents all report to the CPO, each under a GM who owns a revenue numberWhy the future of AI at work belongs to whoever has the richest shared context, not whoever has the best modelKey takeaways:Individual AI productivity gains compound into zero enterprise ROI when decisions never write back into a shared systemEvery human approval or correction is training data. The companies that capture it structurally will pull ahead of those that don'tPLG is an acquisition funnel, not a sales motion. Giving it a GM with a revenue number inside product changes the incentives entirelyCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Arnab BoseSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Jay Choi, Chief Executive Officer at Typeform. Typeform is the AI engagement platform trusted by more than 150,000 customers, including 95% of the Fortune 500. Before Typeform, Jay spent seven years as Chief Product Officer and General Manager at Qualtrics, where the company scaled from $100M to over $1B in ARR.What you'll learn:Breadth of surface area as a stronger AI moat than depth of use case, and why going broad is the right strategic bet right nowThe dual posture Typeform built: a defensive strategy to make their core product impossible to replicate, and an offensive strategy to expand into full customer workflowsResearch Flow, their new product that compresses 50 customer interviews from weeks into hours using AI-moderated researchBeing model-agnostic from day one, and what they learned when switching models without an observability platform in placeThe pricing experiment framework Jay uses: 30 simulations before a single market goes liveKey takeaways:When AI threatens to commoditize your core product, expanding surface area is a stronger defense than adding AI features to what you already havePositioning AI capabilities in plain language, not technical terminology, is the difference between adoption and abandonmentHappy churners are a product problem, not a marketing problem: the fix is finding structurally always-on use cases.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Jay ChoiSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Platform work doesn't look like a typical “one product, one user journey” world, and in this episode, we dig into what that really means with platform Product Leader Ashana Singhania. With a decade of experience across financial services at American Express and Goldman Sachs, Ashana has worked on both consumer-facing experiences and the complex platform layers that power them.She walks Matt and Moshe through how platform products differ from traditional products: instead of a single user flow, platforms support multiple product lines, regions, risk profiles, and entry points, all sitting on shared infrastructure like identity, decisioning, and risk data. That reality changes everything about how a PM does strategy, prioritization, communication, and stakeholder management.Join Matt and Moshe as they explore with Ashana:What “platform” really means in practice, and how horizontal capabilities underpin vertical consumer productsHow platform PMs think differently about impact when results show up indirectly through many dependent productsWhy tools like Productboard, and Jira need to be used differently for messy, non‑linear platform workTechniques for breaking down use cases, mapping the full scope, and prioritizing across multiple product lines and geographiesThe critical role of documentation, especially around variations, so teams don't assume behavior is the same everywhereGovernance and failure modes:Over‑standardization that harms UXToo much flexibility that creates chaosHow to design a strong core plus controlled adaptationPartnering early with compliance, risk, ops, and legal in financial services so platform changes don't get blocked lateHow AI is (and isn't) used today in financial platforms, from fraud detection and behavior insights to reducing manual work, and where trust and regulation slow things downAshana's approach to defining a platform vision, living roadmaps, and reserving capacity for platform evolutionA sneak peek at her new venture on income‑based affordability assessment in real estate and beyondAnd much more!Want to connect with Ashana?LinkedIn: https://www.linkedin.com/in/ashanasinghania You can also connect with us and find more episodes:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproduct/Moshe Mikanovsky: http://www.linkedin.com/in/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

Rory Woodbridge, Product Marketing Consultant, shares why the best PMMs obsess over what he calls radical simplicity.The challenge isn't adding more messaging. It's having the discipline to remove everything that creates confusion.Rory explains why great Product Marketers make tough choices, simplify relentlessly, and focus only on what customers need to understand at each stage of their journey.You'll learn:

For episode 300 of The Product Podcast, Carlos Gonzalez de Villaumbrosia sits down with Ajit Varma, Head of Firefox at Mozilla, the nonprofit behind the original challenger browser that pioneered browser tabs, pop-up blockers, and browser extensions. With 210 million active users and $826 million in annual revenue, Firefox is the only major independent, open-source browser still standing against Google Chrome's 68% share, Apple Safari's 17%, and a new wave of agentic browsers. Before Mozilla, Ajit spent six years at Meta leading monetization of WhatsApp and overseeing its business messaging platform. He has also held product roles at Google, Uber, and Square.What you'll learn:Why LLMs are making browsers more strategically important, and what that means for product teams building in an agentic worldWhy "trust us" is no longer enough, and how open source changes the standard for privacy in AI products- How to compete against trillion-dollar incumbents without abandoning your missionKey takeaways:Privacy claims without open-source inspectability are unverifiable, "trust us" is no longer a sufficient product strategy in the AI eraCompeting against trillion-dollar companies is possible when mission clarity defines what you refuse to optimize forThe agent-driven internet will either democratize access or concentrate it, product choices made today will determine whichSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Why does Product Marketing look so different in Europe, and why copying US playbooks often leads to the wrong outcomes?In this episode, I sit down with Rory, Product Marketing Director consultant, with 13+ years of experience in PMM, across top tech companies such as Google, YouTube and Pleo. Europe Isn't Silicon Valley: Together, we unpack what truly shapes Product Marketing in Europe today, and why this context is driving the rise of fractional PMM roles.In this conversation, you'll learn:

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Cristina Cordova, Chief Operating Officer at Linear, the product development system built for teams and agents. Linear raised $82 million in a Series C round in June 2025 at a $1.25 billion valuation. The company has been profitable since 2021, and serves over 20,000 paid business customers, from seed-stage startups to Fortune 100 enterprises, with a team of just 140 people. Before Linear, Cristina joined Stripe as one of its first employees, and led Platform and Partnerships at Notion.What you'll learn:Why keeping headcount intentionally lean is a strategic advantageReplacing traditional interviews with paid two to five-day projectsWhy PMs are the fastest-growing power users of agentic toolsKey takeaways:A small team is not a small business. Revenue, customers, and growth rate matter more than headcount.If you fully delegate your AI thinking, you lose your native understanding of how these products actually workAgentic workflows are now the default, not a feature. The companies that treat them that way will pull ahead.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Cristina CordovaSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

This time we're diving into a problem almost every product team has felt but rarely names: all the customer research you've already done… and then quietly forgotten. In this episode, Jacob Burghardt joins Matt and Moshe to talk about his new book Stop Wasting Research: Maximize the Product Impact of Your Organization's Customer Insights and how to turn research from a one‑off activity into a real product asset.Drawing on his path from early dot‑com research and UX work through consulting and a principal PM role at Amazon, Jacob shares why teams keep re‑running the same studies, ignoring past insights, and treating “research” as a meeting on the calendar instead of an input into every major decision. His book offers a big‑tent definition of research, which includes UX, market, data science, CS insights, and more, and a practical playbook for making all of it usable, visible, and integrated into product work.Join Matt and Moshe as they explore with Jacob:How he moved from hands‑on research and design into product management, and why he stayed obsessed with the problem spaceWhat “research” really includes today (far beyond user interviews or dashboards)Why so much research gets wasted and the three root causes behind it:Research isn't prepared for future useStakeholders aren't motivated to careInsights aren't integrated into planning, processes, or leadership ritualsA step‑by‑step structure from the book:Taking inventory of the research you already haveDiagnosing root causes in your orgChoosing from a “menu” of tactics that fit your contextWhat good looks like: strong operating models, clear places for research to plug in, and researchers treated as builders of internal productsHow smaller orgs without Product Ops can get started: simple visibility, mapping who's doing what research, and basic communication channelsThe link between org mindset (feature factory vs. empowered teams) and how seriously research is usedPractical ideas for connecting research to go‑to‑market, pricing, packaging, CS, and sales enablementHow AI is changing the research landscape, where it helps and where human judgment is still essentialAnd much more!Want to learn more or get the book?Book: https://rosenfeldmedia.com/books/stop-wasting-researchIntegrated Research: https://www.integratingresearch.com Medium: https://medium.com/@jakeburghardt LinkedIn: https://www.linkedin.com/in/jakeburghardt You can also connect with us and find more episodes:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproductMoshe Mikanovsky: http://www.linkedin.com/in/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

// Le 2 juillet prochain à Paris, rejoignez Diffly, Lucca, Tomorro, Crossbeam, Partoo, Advizeo, Skillup et 100+ leaders Sales, Marketing & Product pour une après-midi dédiée aux nouvelles dynamiques de décision B2B, à l'impact de l'IA dans les équipes Revenue et aux insights qui font vraiment la différence sur vos deals. Réservez votre place ICIC'est 100% gratuit (mais place limitées !) //Recruter un PMM, est souvent perçu comme un “nice to have”. Mais à quel moment cela devient une nécessité pour structurer sa stratégie marketing et accélérer la croissance ?Olivia Jorel, CMO chez Trainme, partage les coulisses de la structuration de son équipe marketing et les raisons qui l'ont poussée à créer un premier poste de PMM.Elle revient sur un contexte initial avec un marketing peu structuré et très cloisonné avec les sales, jusqu'à la mise en place d'une organisation plus alignée et orientée performance. Dans cet échange, Olivia nous explique :

Anthropic just closed a $65 billion Series H round at a valuation approaching one trillion dollars — and has crossed $30 billion in annualized revenue, driven largely by enterprise demand. Claude Code alone became generally available in May 2025 and reached $2.5 billion in annualized revenue in February 2026, with that figure more than doubling since the beginning of 2026. Meaghan Choi, Head of Design for Claude Code and Cowork at Anthropic, was in that room. This conversation goes inside the operating model behind that growth.What you'll learn:Claude Code's evolution from an internal feature into one of the fastest-growing revenue products in historyAnthropic's secret sauce to shipping products at an incredibly high cadence while ensuring qualityHow product teams get structured into small pods of 5 AI Builders and a fleet of agents, where non-engineers ship code into productionDriving enterprise adoption through PLG from technical teamsHow organizations can measure AI ROI beyond AI adoption and token usageDesigning user interfaces for agentic capabilities, including CLIKey takeaways:Titles and role boundaries matter less than contribution. At Anthropic, designers ship code and engineers design, and the pod owns the output collectively.Quality gates have moved downstream. The richest product learnings come from working software, not from reviewing mocks or PRDs.Managing a team now means managing both people and a fleet of AI agents. The skills are more similar than they appear.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Meaghan ChoiSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

// Le 2 juillet prochain à Paris, rejoignez Diffly, Lucca, Tomorro, Crossbeam, Partoo, Advizeo, Skillup et 100+ leaders Sales, Marketing & Product pour une après-midi dédiée aux nouvelles dynamiques de décision B2B, à l'impact de l'IA dans les équipes Revenue et aux insights qui font vraiment la différence sur vos deals. Réservez votre place ICIC'est 100% gratuit (mais place limitées !) //Le PMM doit-il être rattaché au Marketing ? Et surtout : comment mesurer concrètement son impact business ?Olivia partage le retour d'expérience très concret de TrainMe sur le recrutement d'une PMM : clarification des responsabilités avec les équipes Marketing, collaboration avec les Sales, évolution du messaging… mais aussi la fameuse question de la mesure de l'impact du PMM.Olivia nous explique comment son équipe a structuré cette collaboration au fil des mois, les ajustements nécessaires et les résultats observés côté business.

This conversation with Gil Broza goes straight at a question many product leaders are quietly wrestling with: how do you bring AI into product development without breaking everything that already works? Gil, author, coach, and long-time agility expert, returns to talk with Matt and Moshe about “reshaping product development for AI's impact,” focusing not on building AI features, but on how AI is changing the way product and engineering teams work day to day. He argues that while AI massively increases speed and output, it doesn't change the fundamentals of good product development: clear direction, evidence-based judgment, solid technical foundations, and healthy teams. Join Matt and Moshe as they explore with Gil: - Why AI is a “turbo engine in a car with old brakes” if you drop it into a system designed for human speed. - How leaders confuse more output with more value, and why faster code can just mean “legacy code years ahead of schedule”. - The difference between real agility and “performative Agile” (ceremonies, Jira theater) when AI tools are doing more of the work. - How to think in systems: what you're actually optimizing for (predictability, innovation, time-to-value) and how AI changes the constraints and feedback loops in your org. - Practical blind spots leaders miss with AI adoption: - Treating AI as an implementation, not a transformation - Ignoring cognitive load and burnout when people work all day with agents - Shrinking teams for “efficiency” and accidentally increasing isolation - The three main ways to use AI in product development, and why you should be explicit about each: - As a pairing partner (thinking, coding, design) - As an autonomous agent - As “just” automation (summaries, note-taking, etc.) - Why skipping prototyping and experiments is now “less excusable” when AI can create testable prototypes in hours instead of weeks. - What changes (and doesn't) in roles like PM, engineer, and scrum master when AI becomes a real team member. - Concrete steps leaders can take: apply systems thinking, revisit mindset and values, redesign ways of working for AI-speed conditions, and invest in continuous improvement again. - How Gil's new courses (“Reshaping Product Development for AI's Impact” and “Leading AI-Enabled Product Teams”) help product and engineering leaders do this work intentionally. Want to go deeper or work with Gil? - Website & courses: https://3pvantage.com/  - Newsletter & articles: https://3pvantage.com/subscrib.../  - LinkedIn: https://www.linkedin.com/in/gi.../  You can also connect with us and find more episodes: - Product for Product Podcast: http://linkedin.com/company/pr...-podcast  - Matt Green: https://www.linkedin.com/in/ma... - Moshe Mikanovsky: http://www.linkedin.com/in/mikanovsky  Note: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way. Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

Eric Ries wrote The Lean Startup — a book that has sold over 2 million copies and reshaped how a generation of founders and product teams build products. Fifteen years later, he's back with a new book, Incorruptible, and a harder question: not how to build a great company, but how to keep it that way.What you'll learn:Why the forces destroying great companies are structural, not moral — and what that means for how you buildHow Saul Price built FedMart, and Costco's Jim Sinegal each solved half the problem, and why you need both halvesHow Anthropic used a purpose trust structure, the Long-Term Benefit Trust, to protect its safety mission from investor pressureWhy values on the wall fail and what the Johnson & Johnson asbestos scandal reveals about how incentives quietly overwrite principlesHow builders at any level of an organization can start influencing governance without a title or authorityKey takeaways:Success makes you a target: the more valuable your company becomes, the more pressure it faces to betray the mission that made it valuableEthos is the real moat: the intangible system of principles that makes a company trustworthy is harder to copy than any product or contractGovernance is not a legal formality; it is the active, ongoing practice of protecting what you built from the forces that will try to extract itCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Eric RiesSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Snowflake is the AI Data Cloud behind some of the world's largest enterprises — $4.68 billion in annual revenue, 29% year-over-year growth, and over 760 Forbes Global 2000 companies as customers. Baris Gultekin, VP of AI at Snowflake, leads the product efforts that sit at the center of how those enterprises actually operationalize AI. Before Snowflake, he co-founded Google Assistant and scaled it from 10 million to 500 million monthly users.What you'll learn:Why our data isn't clean enough is a delay tactic — and the scoped approach to move past itWhat the semantic layer is and how it lets AI answer business questions accurately, not just fluentlyWhy running AI next to data (instead of sending data to models) makes governance dramatically easierHow Snowflake deployed AI internally: a CEO-level non-optional mandate combined with bottom-up access to their own Cortex coding agentWhy context — not just data — is what agents need to operate reliably at enterprise scaleKey takeaways:Start with one scoped use case, build the semantic model around it, layer governance — don't wait for perfect dataContext is a shared reality for agents: unified data + business semantics + codified workflowsAI adoption compounds when leadership sets a hard mandate and simultaneously gives everyone a tool to experiment withCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Baris GultekinSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

We're joined by Bhavesh Ratanpal. product leader, author, and long‑time practitioner of yoga philosophy, for a unique conversation about his book Product Ashtangi and how ancient Vedic wisdom can change the way we build products and lead teams.Bhavesh shares his journey from growing up in a family of priests in India, to a career in software development and product management at places like TD Bank, Citibank, and TELUS, and now to founding human‑centric AI startups in Canada. Along the way, he kept returning to one insight: a calm, clear mind makes better product decisions. Product Ashtangi is his attempt to codify that, combining the eight limbs of Ashtanga yoga with modern product practice.Join Matt and Moshe as they explore with Bhavesh:What “Product Ashtangi” means and why the first product you work on is yourselfHow the eight limbs of yoga (starting with Yama - truthfulness, ethics, ego‑awareness) translate into everyday product decisionsThe difference between building from ego and cosmetics vs. focusing on real user pain and social welfareHow to shift between observer and experiencer modes so you can see problems clearly instead of reacting emotionallyStories of applying these principles in practice, from enterprise migrations and platform decisions to Bhavesh's current AI products (pet adoption and strata governance)Treating your life like a product: personal sprints, self‑retros every two weeks, and continuously “shipping” a better version of yourselfHow karma yoga and product management align when you see products as vehicles for societal good, not just business metricsThe structure of the book:Part 1 – theory connecting yoga sutras, Bhagavad Gita, and product thinkingPart 2 – practical ways to adopt the eight limbs in your product workWhere to start if you're curious: books, practices, and small mindset shifts you can apply this weekAnd much more!Want to learn more or get the book?Website: http://bhaveshratanpal.caLinkedIn: https://www.linkedin.com/in/bhaveshratanpalYou can also connect with us and find more episodes:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproduct/Moshe Mikanovsky: http://www.linkedin.com/in/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

Pourquoi vos utilisateurs sont déçus alors que votre produit tient ses promesses ?C'est souvent là que se cache le vrai problème : un décalage entre ce que vous racontez… et ce que vos utilisateurs vivent réellement.Dans cet épisode, je reçois Hélène et Doriann, qui travaillent main dans la main sur des sujets de Product Marketing et de Product Design pour aider les entreprises à aligner promesse, expérience et adoption.Ensemble, ils partagent leur approche terrain pour faire collaborer ces deux fonctions souvent silotées.Vous allez notamment découvrir :

Superhuman Mail users respond to 72% more emails per hour and save an average of four hours every week — numbers backed by a case study from one of the Big Three strategy consulting firms. Rahul Vohra, CEO at Superhuman Mail, built the world's fastest email engine over three years without launching, held the line until the product was ready, and then productized product-market fit into a repeatable, measurable science. Following Superhuman's acquisition by Grammarly in 2025, Rahul is now steering the company toward a unified AI-native productivity suite spanning email, calendar, tasks, and agents.What you'll learn:The 5-step PMF Engine: how to survey, segment, analyze, implement, and track your way to product-market fit with a numerical scoreWhy you should ignore the not disappointed and most somewhat disappointed users — and which signals actually tell you who to build forHow to use the High Expectation Customer (HXC) framework to narrow your market without changing your productWhy PMF is a moving target and how to defend it against commoditization and copy-cat competitionHow Rahul operates as the editor of the product — using 20 verbatim quotes to push PMs and designers to sharper decisionsKey takeaways:If more than 40% of your users would be very disappointed without your product, you have an initial PMF — and you can measure your way thereChanging your market is faster than changing your product — segmentation alone can jump your PMF score 10 points overnightBuilding for your highest-expectation customer is not the same as building for your ICP — confuse the two, and you'll optimize for the wrong signalCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Rahul VohraSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Je reçois un duo d'exception : Hélène Chomienne, fondatrice de son agence 365 degrés et PMM et Doriann Defemme, Product Designer. Ensemble, ils partagent leur manière de collaborer au quotidien pour garantir une cohérence entre ce qui est vendu… et ce qui est réellement vécu dans le produit.On parle d'un sujet souvent sous-estimé : l'alignement entre message et expérience, et son impact direct sur l'adoption, la rétention et la croissance.Dans cet épisode, vous allez découvrir :

Découvrez pourquoi baser son messaging sur être "le meilleur" peut freiner votre croissance, et comment redéfinir votre positionnement pour captiver votre audience sans rivalités inutiles. Avec Gaspard, nous explorons la puissance de se différencier à travers une narration claire, plutôt que par des adjectifs subjectifs. Apprenez comment devenir une référence pour vos prospects, sans entrer dans la compétition de qui est le plus "top".Un épisode clé pour ceux qui veulent repenser leur différenciation et booster leur influence, sans se mettre en compétition frontale. RESSOURCES

GoFundMe has facilitated over $40 billion in help since 2010, powering a community of more than 200 million people across 20 countries. Arnie Katz is the Chief Product and Technology Officer there — and a three-time CPTO, having previously led product and engineering at StubHub and TheRealReal. In this episode, he brings the rare perspective of someone who has built and scaled marketplaces at every stage, across multiple industries.What you'll learn:The three failure modes every marketplace must solve — cold start, imbalance failure, and false positive growth — and how to fix each oneHow GoFundMe is using AI agents to reduce friction for fundraisers, resulting in an expected $125 million in additional funds raisedWhy AI is driving revenue growth at GoFundMe, not just developer productivity — and how they sequenced that deliberatelyThe real trade-offs of the CPTO model: what you gain in speed, and what you have to mitigate through hiringHow GoFundMe is building demand-side and matching mechanisms to grow donation volume beyond viral sharingKey takeaways:Marketplace liquidity isn't just about having enough supply — it's about designing the right matching and demand mechanisms at every stage of scaleAI unlocks revenue opportunities that were previously uneconomical to pursue, especially when the customer is already in a vulnerable, high-friction stateThe CPTO structure enables faster decision-making, but requires consciously strong functional leaders underneath to offset the natural lean toward one sideCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Arnie KatzSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

On this episode of the Product for Product Podcast, we're joined by Ran Erez, product leader, podcaster, and founder of Re.focus, for a highly practical episode on competitive intelligence tools and tactics for product managers.With over a decade in B2B, B2C, and cyber (including three years on the mobile pod at monday.com), Ran has seen the same pattern repeat: teams either copy competitors blindly or ignore them entirely. He argues there's a better way, treating competitors as a massive time‑saver for validation and strategy, without letting them drive your roadmap.Join Matt and Moshe as they explore with Ran:How Ran went from QA manager in cyber to owning product and driving millions in salesThe biggest mistakes PMs make with competition: copying feature lists, believing marketing at face value, and doing “one‑and‑done” competitive intelligence Why focusing only on direct “budget competitors” misses the real job‑to‑be‑doneThe Competitive Intelligence Pyramid:Feature level – how others solve the same problemProduct capabilities – pros/cons at whole‑product levelMessaging – how value is communicated and evolvesProduct strategy – what bets they're makingCompany strategy – where the business is actually headingConcrete methods and tools at each level, including:Finding real users of competitors through screeners, communities, and support/KB pagesRunning “SUSHI” competitive user research: side‑by‑side tests of your product vs. theirs over timeTalking to integration partners and freelancers who implement multiple competing toolsUsing Wayback Machine, screenshots + Gemini, and Perplexity to track how sites, pricing, and positioning changeMining public earnings calls for strategic signals in the language leaders useHow to systematically identify your true competitors (and what it means if you can't find any)Treating CI as a muscle: what “small start” looks like and how to keep learning over timeUsing competitors to validate your ideas by putting their products in front of your usersAnd much more!Want to connect with Ran or learn more?LinkedIn: https://www.linkedin.com/in/ran-erezYou can also connect with us and find more episodes:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproductMoshe Mikanovsky: http://www.linkedin.com/in/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

Dans beaucoup d'entreprises SaaS, le problème n'est pas le produit.Le problème est que personne ne comprend vraiment ce qu'il fait… ni pourquoi il est différent.Quand le positionnement est flou, tout devient plus difficile : acquisition, cycle de vente, pitch commercialJ'ai le plaisir de discuter avec Gaspard Pastural, consultant en Product Marketing, spécialisé en positionnement et messaging pour les entreprises SaaS B2B.Après plusieurs années en growth marketing et en agence, il accompagne aujourd'hui des entreprises tech pour clarifier leur positionnement et transformer cette clarté en résultats marketing et commerciaux.Gaspard partage sa manière très pragmatique d'aborder le Product Marketing : partir du business, comprendre les besoins clients… puis construire un positionnement qui impact vraiment les ventes.Dans cet épisode, vous découvrirez :

Robinhood posted $4.5 billion in revenue in 2025, up 52% year-over-year, while growing its Gold subscriber base 58% to 4.2 million paid members. Abhishek Fatehpuria, VP of Product at Robinhood, joined the platform as an intern in 2016 and has built the brokerage business from a single-product equities app into a multi-product financial platform. This episode is a detailed look at how Robinhood structures product thinking at scale — without sacrificing the UX moat that made it win in the first place.What you'll learn:How Robinhood uses two leading indicators, net deposits and Gold subscriptions, to measure long-term customer commitment before revenue shows upWhy treating legal and compliance partners as product owners, not blockers, is the unlock for shipping fast in a regulated marketThe "barbell strategy" for UX: design for the newest user and the most advanced user simultaneously, and let the middle take care of itselfHow the early-stage ideation sprint has compressed from 4–5 weeks to 2–3 days with AI toolsWhy Robinhood Social is built on verified identity and real trades — and what that unlocks for the future of retail investor relationsKey takeaways:Paid subscriptions aren't just a revenue line — they're the connective tissue that drives multi-product adoption across a platformPride is a scalable quality standard: when teams enforce it themselves, quality and speed stop being in conflictAI embedded into workflows moves faster than AI bolted on as a standalone featureCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Abhishek FatehpuriaSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Zoom generates $4.87B in annual revenue and powers modern work for hundreds of millions of users worldwide. In this episode, Carlos González de Villaumbrosia, CEO at Product School, sits down with Jeff Smith, Chief Product Officer at Zoom.Jeff joined Zoom in 2019 and has led product through three distinct eras — COVID hypergrowth, multi-product expansion, and the current agentic AI shift. In this conversation, he breaks down what actually changes when AI becomes core infrastructure for how teams work.What you'll learn:How Zoom tripled headcount in under a year during COVID and what breaks at that scaleWhy expanding into mail, calendar, and documents was never about copying Google or Microsoft — it was about owning the full work lifecycle around meetingsHow AI Companion 3.0 performs agentic retrieval across first- and third-party tools to surface insights and produce work product from a single promptWhy MCP and open integrations are non-negotiable when you can't afford to be siloedHow to move from personal AI productivity gains to real, measurable business outcomesKey takeaways:When engineering velocity is abundant, strategic direction becomes the scarce resourceThe right engagement metric isn't more meetings — it's whether users produced something valuable as a resultAgentic AI is the first real opportunity to disrupt entrenched productivity tools that switching costs have protected for decadesCredits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Jeff SmithSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

We're joined by Thomas Hartmann, co‑founder of Product Masterclass and co-author of From Project to Product Mode: A Game Plan to Unlock Scalability for B2B Software Products, for a candid look at why so many B2B software companies get stuck in “project mode” and what it really takes to become product‑led.Thomas shares his journey from entrepreneurship and lean startup experiments in San Francisco and Munich and to working with large organizations trying (and often failing) to scale. Over years of coaching and transformation work, he and his co‑founder and co-author, Sebastian Borggrewe, saw the same pattern: teams with a strong product mindset trapped inside companies that still behave like project shops, where sales and single big clients dictate the roadmap and success is measured by project delivery, not product outcomes.Join Matt and Moshe as they explore with Thomas:- How to recognize whether your company is truly in project mode or product mode- Why B2B software behaves very differently from B2C when making this shift- The “egg” analogy: product teams as the yolk, surrounded by an environment (the egg white) that often doesn't care how things get built, only that they ship- The seven areas that fundamentally differ between project and product companies: segmentation, pricing, discovery, prioritization, engineering, configuration, and product management structures- Concrete signs of project mode: sales defining what to build, time‑and‑materials pricing, no real discovery, prioritization driven by the loudest customer, and PMs blocked from end users- Why not every company needs to become a product company, and why it's a strategic choice, not dogma- A step‑by‑step path to move from project to product mode:- Step 1: Align leadership and name the current state (you are a project org)- Step 2: Find alignment among all product leaders on what to change- Step 3: Prioritize which of the seven areas to tackle first (you can't fix everything at once)- Step 4: Enable the workforce and shift the surrounding “egg white,” not just product team skills- How AI fits differently in project vs. product organizations: as a delivery accelerator in one, and as a strategic validation and discovery tool in the other- Why tools like Claude Code can help PMs brainstorm, validate, and visualize, but won't fix a broken mindset or culture- And much more!Want to learn more or work with Thomas?- Product Masterclass: https://www.product-masterclas...- From Project to Product Mode book: https://www.product-masterclass.com/book-project-to-product- LinkedIn: https://www.linkedin.com/in/th... You can also connect with us and find more episodes:- Product for Product Podcast:http://linkedin.com/company/pr...- Matt Green:https://www.linkedin.com/in/ma...- Moshe Mikanovsky:http://www.linkedin.com/in/mik...Note: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

Vous passez des entretiens PMM… mais vous n'êtes jamais sûr(e) de comment vous devez vous préparer et ce que vous devez vraiment démontrer?Le Product Marketing est un métier pas toujours bien compris des entreprises qui recrutent.Résultat: les attentes sont souvent floues, les process varient d'une boîte à l'autre, et les candidat·e·s les plus compétent·e·s passent parfois à côté à cause d'erreurs évitables.Avec:Marion Darnet - co-fondatrice de Pachamama, collectif de recrutement spécialisé métiers ProductSébastien Millanvoye - fondateur de Graines de Produit, fractional PMM, auteur du Baromètre Emploi PMM 2025 (850+ offres analysées)Ecoutez le replay du live pour un tour de table sans langue de bois sur tout ce que vous avez toujours voulu savoir sur le recrutement Product Marketing, côté candidats et côté recruteurs.__Le 23 avril à 11h retrouvez en live Diffly, Diane (@Figures), Louise (@PMM For Good) et Julie (@Alma) en Live- 3 références du PMM en France parler de ce que font les meilleurs PMM différemment. Pour s'inscrire c'est par ici .__✅ Les erreurs classiques qui éliminent même les bons profils✅ Comment se préparer (vraiment) à un entretien PMM✅ Business cases: ce qui revient, ce qu'on attend, comment briller✅ Vendre un pivot de carrière sans se saborder✅ Négo salariale: timing, tactiques, erreurs à éviterChapitres03:00 État du Marché du Recrutement en Product Marketing06:04 Préparation à un Entretien en Product Marketing08:57 Cibler sa Recherche de Poste12:03 Spécialisation et Évolution des Rôles en Product Marketing15:01 Tendances et Colorations dans le Product Marketing18:05 Formation et Ressources en Product Marketing et IA21:06 Questions et Réponses sur le Product Marketing25:51 Les parcours variés vers le Product Marketing31:22 L'importance des certifications et formations en PMM38:13 Préparation aux entretiens et cas pratiques en PMM48:41 Perspectives d'avenir pour le Product MarketingRESSOURCES

TikTok has officially crossed 200 million monthly active users in the US — but the real story is what they've built underneath the surface.In this episode, Carlos González de Villaumbrosia, CEO at Product School, sits down with David Kaufman, Vice President of Product at TikTok, to go deep on the platform's transformation into a full end-to-end commerce engine. David breaks down how TikTok is using AI to automate everything from creative generation to affiliate-based promotion — so merchants can upload a catalog and let the platform handle the rest.If you want to understand where social commerce is heading, this one is essential listening.What you'll learn:Why removing steps from the purchase funnel is the single biggest growth lever for modern product teams.How TikTok's generative AI tools allow merchants to produce high-performing video creative at scale without a production team.The shift from spontaneous live streams to scheduled commercial events driving $1M per hour in sales.How TikTok balances feed, commerce, search, and messaging as four distinct monetization pillars.Key takeaways:The most successful products in the AI era put the user directly at the point of transaction.Organic creator content consistently outperforms traditional high-production advertising.A long-tail creator ecosystem can promote a 100,000-item catalog automatically through affiliate-based commission.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: David KaufmanSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

AI is collapsing the silos between design and engineering. In this episode, Carlos Gonzalez de Villaumbrosia, CEO at Product School, sits down with Ed Bayes (Design Lead, OpenAI) and Matt Colyer (Product Director, Figma) to discuss their groundbreaking integration that enables a seamless round-trip workflow from code to canvas.Matt Colyer walks us through a step-by-step demo of the new code to canvas and right to Figma capabilities. You'll see exactly how OpenAI's Codex and Figma's Plugin API allow builders to move fluidly between development and design environments, using AI agents to update design systems and iterate faster than ever before.What you'll learn:Step-by-step demo: Moving from a code component in Codex to a live Figma design.How the round-trip workflow eliminates lossy handoffs between designers and devs.Strategies for using AI agents to update design libraries autonomously.The impact of Model Context Protocol (MCP) on product team interoperability.Key takeaways:Velocity as a Moat: How AI-native tools are accelerating the speed of prototyping.The Evolving PM Role: Why curiosity is now more critical than technical hurdles.Human Judgment: Why AI increases the premium on high-level design taste.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuests: Ed Bayes and Matt ColyerSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

We're excited to welcome Lea Khasidi, product management freelancer, founder and CEO of MaPott, and soon‑to‑be author, for a powerful conversation on gender-based data analytics for product managers.Lea shares her journey from intelligence work in the IDF, through product roles in EdTech, cybersecurity, and beyond, to founding a health management app for women with chronic conditions. Along the way, one pivotal discovery while consolidating four cybersecurity platforms, seeing men and women use the same filtering feature in completely different ways, sparked her deep focus on how gender shapes behavior in our products, especially in B2B contexts where it's often ignored.Join Matt and Moshe as they explore with Lea:How a real-world analytics puzzle revealed stark gender differences in workflow, and changed how she thinks about usage dataThe three pillars of context we can't change (who users are, how they act, where they work) and the one we can: what we give them in the productHow “hacks” and workarounds used by different genders can hint at your next featuresA practical system for existing products: using analytics to segment by gender, spotting behavioral differences, then following up with observation and interviewsHow to approach gender representation when validating new products, and why balanced samples matter even for seemingly “neutral” toolsWays to lean on existing research about gender patterns in your domain (health, education, finance, etc.) instead of guessing from scratchWhy early-stage startups should ship faster and learn from usage, while mature products might rely more on A/B tests and targeted outreachThe risk of building solely from our own biases and assumptions, and why gender should be on the PM checklist, even if it's not always the first lensLea's upcoming book on gender-based analytics for PMsOne piece of advice she has for founders learning to trust their insight while staying open to the dataAnd much more!Want to connect with Lea or learn more?LinkedIn: https://www.linkedin.com/in/lea-khasidi/ Website: https://leakhasidi.comMaPott: https://www.ma-pott.com/ You can also connect with us and find more episodes:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproduct/Moshe Mikanovsky: http://www.linkedin.com/in/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

In this episode, Carlos Gonzalez de Villaumbrosia, CEO at Product School, sits down with Diya Jolly, CPTO at Xero, the global accounting platform trusted by over 4 million customers. Diya shares how Xero is redefining B2B software by building JAX, an agentic AI platform that intelligently manages specialized sub-agents to streamline business operations.What you'll learn:How Xero built an agentic AI platform that orchestrates multiple agents across payroll, payments, and bank reconciliation workflows.The strategy for implementing strict guardrails to ensure accuracy in highly regulated, AI-driven accounting processes.How to design a global product that scales common services while adapting to hyper-local tax and payment requirements.The two-way door framework for accelerating product decisions and course-correcting with imperfect data.Key takeaways:Why the future of SaaS interfaces is conversational, transitioning users away from static dashboards into review and insight roles.The strategic advantage of combining product and technology leadership into a single CPTO role to drive tighter cross-functional alignment.Why deeply serving the SMB market requires specialized product design that balances consumer-grade simplicity with enterprise-grade workflow depth.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Diya JollySocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

In this episode, Carlos Gonzalez de Villaumbrosia, CEO at Product School, interviews Vanessa Lee, Vice President of Product at Shopify, the engine of global commerce powering over $1.1 trillion in sales. As the most senior product leader at Shopify reporting directly to the CEO, Vanessa oversees the product strategy for a platform with a $165B+ market cap and recent 30% year-over-year revenue growth. A two-time YC founder, Vanessa brings a builder's mindset to leadership, emphasizing the need for technical fluency and courage as a service when making high-stakes decisions.What you'll learn:AI-Native Playbook: How Shopify transitioned from traditional SaaS to agent-led commerce.Internal AI Evals: How to use LLM-based judges to grade and ensure product quality.Technical Product Leadership: Why staying involved in API details and technical cohesion is critical for senior roles.The Versioning Framework: The strategy Vanessa used to successfully push back and convince her CEO to version Shopify's API.Key Takeaways:Beyond the PRD: Shifting focus from rigid specs to training AI models for non-deterministic outcomes.Courage as a Service: How to leverage deep domain expertise to find your screw it moment and drive organizational change.The Founder Mindset: Maintaining autonomy and an experimental spirit within a 10,000-person global organization.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Vanessa LeeSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

We're delighted to welcome Radhika Dutt, product leader, founder, and author of Radical Product Thinking, for a deep dive into her newest work: the OHLA (formerly OHL) Toolkit. In this episode, Radhika joins Matt and Moshe to challenge how product teams set goals, measure progress, and use frameworks, proposing a puzzle‑driven alternative to traditional OKRs and “framework-following” culture.Drawing from her journey from electrical engineering and startups at MIT, through painful “product diseases” like Hero Syndrome and Obsessive Sales Disorder, Radhika shares why recipes and templates alone don't create real progress. Instead, she introduces OHLA as a lightweight but powerful way to cultivate a Jedi mindset, one that keeps teams grounded in first principles, context, and learning rather than chasing vanity metrics and rigid targets.Join Matt, Moshe, and Radhika as they explore:Radhika's path from engineering and founding to Radical Product Thinking and now the OHLA ToolkitWhy classic goal‑setting and OKRs often backfire, creating “alibi progress,” outdated goals, and incentives to hide bad newsOHLA in practice:Observe – what's really happening in your product, team, or marketHypothesize – what might explain it and how you'll test those ideasLearn – what the results actually tell youAdapt – how you'll change course based on evidence“Puzzle setting” vs goal setting: defining puzzles with Observation, Open Questions, and an Objective summary to stay longer in the problem spaceHow OHLA complements design thinking by forcing teams to remain curious and uncomfortable before jumping into solutionsPractical stories, from maritime platforms to enterprise teams, where puzzle thinking led to very different solutions than OKR‑driven targetsHow managers can shift conversations from “Did we hit the number?” to “How well did it work? What did we learn? What will we try next?”A realistic path to transition: starting with your own puzzle, then introducing OHLA within your immediate sphere of influenceAnd much more!Want to explore the OHLA Toolkit or connect with Radhika?OHLA Toolkit: https://www.radicalproduct.com/toolkit/#OHLToolkitRadical Product site: https://www.radicalproduct.com/LinkedIn: https://www.linkedin.com/in/radhikadutt/You can also connect with us and find more episodes:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproduct/Moshe Mikanovsky: http://www.linkedin.com/in/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

In this episode, Carlos Gonzalez de Villaumbrosia, CEO at Product School, sits down with Robby Stein, VP of Product at Google Search. Google Search serves billions of users and holds over 90% of the global market share, acting as the engine behind Alphabet's $400 billion in annual revenue.Robby is steering the most significant shift in Search history: the transition to AI. He oversees a massive portfolio, including the new AI Mode, which has already scaled to 75 million daily active users. Drawing from his time building Stories and Reels at Instagram, Robby breaks down how to build zero-to-one products inside a tech giant and why you need high conviction to push through early bad data.What you'll learn:Building Like a Startup: How to maintain crazy speed and focus on zero-to-one initiatives while protecting a massive core business.True Product-Market Fit: Why flat or J-curve retention in early cohorts is the only reliable indicator that a product is actually working.The Value of Colossal Disasters: The untold story of how early failures with Instagram Reels and Close Friends were necessary steps to global success.Agentic Search: How Google is moving beyond providing links to executing complex, multi-step tasks by deeply understanding personal context.Key takeaways:Start Small to Win Big: Even at Google's scale, massive AI products begin with just 500 trusted testers and a focus on solving specific user complaints.Look for the Golf Shot: When building AI, look for that rare moment when the whole system works perfectly to build the conviction needed to keep iterating.Leaders Must Co-Create: To move fast in a large org, leaders shouldn't just approve from the top; they need to form working groups and operate in the details.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Robby SteinSocial Links: Follow our Podcast on Tik Tok here Follow Product School on LinkedIn here Join Product School's free events here Find out more about Product School here

In this episode, Carlos Gonzalez de Villaumbrosia interviews Chris Geoghegan, VP of Product at Zapier. As the company's first-ever Product Manager, Chris has spent nearly a decade scaling Zapier into a $5 billion automation giant that serves over 3.4 million businesses and 69% of the Fortune 1000.Zapier is not just building AI tools; they are powering their entire company with them. Chris reveals that his team currently runs over 800 active AI agents internally to manage everything from calendar prep to engineering triage. He breaks down the Code Red moment that shifted their strategy and how they are defining the future of Agentic Workflows.What you'll learn:Agentic vs. Deterministic: Why standard workflows follow a set path, while agents can reason, access knowledge, and change course to solve problems.The Orchestration Layer: How to hire and onboard AI agents using Context Engineering and Model Context Protocols (MCPs).Adoption vs. Transformation: Why adoption is just doing old tasks faster, while transformation unlocks business models that were previously impossible.Building a Moat: How Zapier uses its vast data on user intent to stay ahead of commodity LLM features.Key takeaways:Treat Agents Like Employees: You can't just deploy an agent; you must onboard it with specific context and tools to be effective.Lead by Building: Transformation fails if leaders don't use the tools. Zapier's execs do show-and-tell sessions to prove they are hands-on.AI Governance is Key: To move up-market to the enterprise, you must solve for Observability (who sent what data) and Access Control.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Chris Geoghegan Social Links: Follow our Podcast on Tik Tok here Follow Product School on LinkedIn here Join Product School's free events here Find out more about Product School here

We're wrapping up our AI Tools series with a special episode featuring just the two of us—Matt and Moshe—looking back at what we really learned (and where we're still confused) about AI in product management.Across this conversation, we revisit the core themes that emerged with our guests and in our own experiments: from “vibe coding” and no‑code builders, to LLM assistants, enterprise privacy, agentic workflows, and the evolving role of the product manager. We share candid stories of using tools like Google Stitch, Figma/Figma Make, FlutterFlow, Base44, and others to design and prototype a real mobile app; what worked, what broke, and why credits, pricing, and model limits matter far more than the glossy demos suggest.Join Matt and Moshe as they explore:How our AI Tools series evolved, from “let's review tools” to “AI is not one thing, it's many different problem spaces”Why “vibe coding” is a misleading umbrella term, and how it means something different to devs, PMs, and designersLessons from using AI for design and prototyping: inconsistent outputs, beta‑stage rough edges, and the pain of credit-based modelsBuild vs. buy for AI: integrating foundation models vs. building your own, and what that means for pricing, UX, and reliabilityEnterprise realities: privacy, security, and why tools like Copilot/Gemini have such an advantage where data and IT policies matterHow conversations with our guests (Sani, Eva, Elena, Stav, Yaron, Marcos and Adir) shifted our thinking about workflows, orchestration, and agentsThe future of agent-to-agent interactions: what happens when AIs negotiate purchases and workflows with minimal human promptsWhy first principles and business outcomes still matter more than any single AI toolHow the PM role is changing: less tool‑chasing, more orchestration, strategy, and clarity about what problem we're actually solvingWhat topics we'd tackle next, like pricing, packaging, and credit models for AI products, and how this series is shaping our own careersAnd much more!You can connect with us and keep following what comes after this AI Tools series:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproduct/Moshe Mikanovsky: http://www.linkedin.com/in/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

In this episode, Carlos Gonzalez de Villaumbrosia, Founder & CEO at Product School, interviews Tim Simmons, Chief Product Officer at Walmart International, the retail giant serving 255 million customers weekly across 18 countries. Tim is leading a massive transformation to move from decentralized tech stacks to global platforms that empower local innovation.Tim explains why complexity is actually a competitive advantage when training AI. He dives deep into Agentic AI and the concept of Orchestrators—systems that manage workflows between agents to automate tasks like user story generation with 88% accuracy. He also shares the strategy behind the Walmart Translation Platform (WTP), which has cut translation costs by 99% while increasing speed and trust.What you'll learn:The Orchestrator Strategy: How to build AI systems where project manager agents coordinate tasks for maximum efficiency.Global vs. Local: A framework for building core platforms that scale while allowing for hyper-local customization.The ROI of AI: How Walmart tracks adoption and accuracy, not just productivity.Human in the Loop: Why keeping humans involved in AI workflows actually makes the models smarter over time.Key takeaways:Complexity is Data: The more you expose AI to your organization's complexity, the more resilient and accurate it becomes.Trust Through Nuance: Successful localization isn't just word-for-word translation; it's about capturing intent to build customer trust.Platform Discipline: Moving from bespoke builds to multi-tenant codebases is essential for scaling innovation globally.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Tim SimmonsSocial Links: Follow our Podcast on Tik Tok here Follow Product School on LinkedIn here Join Product School's free events here Find out more about Product School here

We're keeping the AI Tools series rolling with Adir Traitel, entrepreneur, product leader, and early adopter of just about every vibe coding tool out there. Adir joins Matt and Moshe to share hard‑won lessons from building real apps with v0, Bolt, Replit, Figma Make, and more, all while running his own startup and consulting on product builds across industries.From his early days in project management and mobile app startups, through work with companies like Moovit and across FinTech, AgTech, and credit scoring, Adir has consistently been the “try it first” person for new build tools. In this episode, he breaks down what these platforms actually do well, where they fall short, and how product managers can use them responsibly for experiments, prototypes, and beyond.Join Matt, Moshe, and Adir as they explore:Adir's journey from PM and founder to heavy user of vibe coding tools in his current startupHis 3-layer view of the ecosystem: AI dev assistants (Cursor, Antigravity, Claude Code), front-end mockup tools (v0, Figma Make), and full‑product builders (Lovable, Base44, Bolt, Replit)V0: where it shines for quickly building functional UIs (like his electricity consumption app) and where it starts to crackLovable: great for sites and simple flows, but not ideal for complex SaaS or CRM‑like productsBolt: fun and fast for concepts, but why it never got him close to productionReplit: stronger agents and capabilities, but weaker UI output and surprising backend defaults that can get very expensive very quicklyFigma Make and Google Stitch: when design quality trumps everything else, especially for SaaS interfacesThe real costs of vibe coding: AI token spend, hosting/pricing traps, and why production economics matter as much as build speedWhat his “dream product” would look like, including multi‑agent environments, better security/privacy, and built‑in QA and CI/CDHow all this is reshaping the product management role, and why curiosity and tool fluency are becoming must‑have skillsAnd much more!Want to connect with Adir or learn more?LinkedIn: https://www.linkedin.com/in/adirtraitel/ Website: https://adirtraitel.com/You can also connect with us and find more episodes:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproduct/Moshe Mikanovsky: http://www.linkedin.com/in/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

In this episode, Carlos Gonzalez de Villaumbrosia, CEO & Founder at Product School, interviews Aparna Sinha, SVP of Product at Vercel, the cloud platform recently valued at $9.3 billion following a $300 million Series F. Aparna joins us to discuss how Vercel is powering the next generation of AI-native applications.Drawing from her experience at Google Kubernetes and Pear VC, Aparna reveals how Vercel empowers Teams of One to ship faster than ever. She explores the cultural shift required to build in the AI era—moving from rigid planning to rapid experimentation and iterating to greatness.What you'll learn:How Vercel's Team of One philosophy maximizes developer leverage.Why shipping imperfect products early is crucial for AI strategy.The mechanics of Hybrid Pricing to balance AI costs and value.How to use internal dogfooding to accelerate product quality.Key takeaways:Speed is Survival: In the AI era, waiting for perfection means falling behind.Agency over Hierarchy: Small, autonomous teams outperform large structures.Price for Value: Align AI pricing with user outcomes, not just compute costs.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Aparna SinhaSocial Links: Follow our Podcast on Tik Tok here Follow Product School on LinkedIn here Join Product School's free events here Find out more about Product School here

We're continuing our AI Tools series with Marcos Polanco, engineering leader, founder, and ecosystem builder from the Bay Area, who joins Matt and Moshe to introduce CLEAR, his method for using AI to build real software, not just demos. Drawing on decades in software development and his recent research into how AI is reshaping the way teams ship products, Marcos shares how CLEAR gives both technical and non‑technical builders a production‑oriented way to work with vibe coding tools.Instead of treating AI like a magical black box, Marcos frames it as an “idiot savant”: incredibly capable and eager, but with no judgment. CLEAR wraps that raw power in structure, guardrails, and engineering discipline, so founders and PMs can go from prototype to production while keeping humans in control of the last, hardest 20%.Join Matt, Moshe, and Marcos as they explore:Marcos's journey through engineering, founding, and AI research, and why he created CLEARWhy AI tools like Bolt, Cursor, Claude, and Gemini are fabulous for prototypes but risky for production without a methodCLEAR in detail:C – Context: onboarding AI like a new hire, using stories and behavior‑driven design (BDD) to articulate requirementsL – Layout: breaking work into focused, scoped pieces and choosing a tech stack so AI isn't overwhelmedE – Execute: applying test‑driven development (TDD), writing tests first, then having AI write code to pass themA – Assess: using a second, independent LLM as a QA agent, plus a human‑run 5 Whys to fix root causes upstreamR – Run: shipping to users, gathering new data, and feeding it back into the next iteration of contextHow CLEAR lowers cognitive load for both humans and AIs and reduces regressions and hallucinationsWhy Markdown (with diagrams like Mermaid) is becoming Marcos's standard format for shared human–AI documentationHow CLEAR changes the coordination layer of software development while keeping engineers central to quality and judgmentPractical advice for PMs and founders who want to move from “just vibes” to predictable, production‑grade AI developmentAnd much more!Want to go deeper on CLEAR or connect with Marcos?CLEAR on GitHub: https://github.com/marcospolanco/ai-native-organizations/blob/main/CLEAR.mdCLEAR slides: https://docs.google.com/presentation/d/1mwwDtr7cCP5jLUyNVgGR5Aj-MBq8xsMlhSc0pvSQDks/edit?usp=sharingLinkedIn: https://www.linkedin.com/in/marcospolancoYou can also connect with us and find more episodes:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproduct/Moshe Mikanovsky: http://www.linkedin.com/in/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

In this episode, Carlos Gonzalez de Villaumbrosia, CEO & Founder at Product School, interviews Anique Drumright, General Manager and VP of Product at Rippling, the workforce management platform valued at $16.8 billion with over $570 million in ARR.Anique is a product veteran who has shaped high-growth teams at Uber, TripActions, and Loom. Now at Rippling, she helps lead a workforce of over 4,000 employees, including 100 former founders, to maintain the speed and ownership typically lost at scale. In this conversation, Anique breaks down how Rippling successfully operates as a compound startup and why product leaders must evolve into General Managers.What you'll learn:How to pivot from managing a backlog to owning a P&L as a GM.The Compound Startup framework for consolidating enterprise categories.How to build high-performing teams by hiring for "founder-level" curiosity.Strategies for proving ROI to enterprise customers to drive platform adoption.Key takeaways:Go and See: Why leaders must personally investigate customer issues to set the bar for quality.Singular Obsession: How to organize teams to maintain focus and velocity as you scale.Automating ROI: How Rippling uses product efficiency to justify headcount reduction for clients.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Anique DrumrightSocial Links: Follow our Podcast on Tik Tok here Follow Product School on LinkedIn here Join Product School's free events here Find out more about Product School here

We're excited to continue our AI Tools series with Yaron Lavie, a veteran product leader with over 25 years of experience in FinTech, InsurTech, and now retail tech at Nexite, where he helps fashion retailers unlock unique in-store data. In this episode, Yaron joins Matt and Moshe to share how he used Base44, an AI-powered, full‑stack vibe coding platform, to take a completely new product idea from concept to a deployed prototype without touching his R&D team.Yaron walks through why traditional approaches like Figma mockups and static visuals weren't enough for the kind of validation he needed, and how he experimented with tools like Gemini, Claude, and ChatGPT before landing on Base44 for an end‑to‑end, fully hosted solution. He explains how Base44's conversational, chat-based builder let him model user personas, flows, and entities, then iteratively refine an interactive analytics dashboard with real (anonymized) data, all inside a time‑boxed, low‑risk experiment that still respected security constraints.Join Matt, Moshe, and Yaron as they explore:Why Yaron needed to validate a new product idea without pulling scarce R&D resources off other prioritiesHow he moved from static mockups to interactive prototypes with real data, and where Gemini helped and fell shortWhat made Base44 stand out versus other vibe coding tools like Lovable: full-stack, hosted, and truly end-to-endThe importance of “context engineering” over simple prompt engineering when building with LLM-based buildersUsing Base44's discussion mode, live preview, and QA test generation to shape the product before committing to codeReal-world limits: hitting a ceiling on UX depth, inflated code, and friction with design systems and engineering standardsHow he transitioned from a Base44 prototype to a ground-up rebuild with the core dev team, using the prototype to generate user storiesPractical pros and cons: integrations, multi-currency support, database control, and when full-stack vibe coding is “good enough”Where Yaron sees vibe coding going next, and how PMs can use it responsibly for experimentation and usability testingAnd much more!Want to connect with Yaron or learn more?LinkedIn: https://il.linkedin.com/in/yaronlavieYou can also connect with us and find more episodes:Product for Product Podcast: http://linkedin.com/company/product-for-product-podcastMatt Green: https://www.linkedin.com/in/mattgreenproduct/Moshe Mikanovsky: http://www.linkedin.com/in/mikanovskyNote: Any views mentioned in the podcast are the sole views of our hosts and guests, and do not represent the products mentioned in any way.Please leave us a review and feedback ⭐️⭐️⭐️⭐️⭐️

In this episode, Carlos Gonzalez de Villaumbrosia interviews Andrey Khusid, Co-founder and CEO of Miro, the visual collaboration platform valued at an estimated $17 billion with over 100 million users. Andrey reveals how Miro transformed from a simple browser whiteboard into a central hub for innovation, serving 250,000 customers worldwide. He discusses the critical shift from best-of-breed tools to platform suites and how Miro is aggressively integrating AI to support agentic workflows.What you'll learn:How to apply day one thinking to constantly reinvent your product strategy.Why speed of learning is the only true competitive moat in the AI era.How to navigate the tension between market consolidation and AI experimentation.The role of acquisitions in scaling a product team to 1,600 people.Key Takeaways:Reinvention is Mandatory: Why you must risk short-term revenue to secure long-term relevance.AI as a Teammate: Moving beyond features to humans and AI working together to solve problems.Fast Fashion Software: How to build a Lovemark brand to survive rapid commoditization.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Andrey Khusid Social Links: Follow our Podcast on Tik Tok here Follow Product School on LinkedIn here Join Product School's free events here Find out more about Product School here

In this episode, Carlos Gonzalez de Villaumbrosia speaks with Rachel Wolan, CPO at Webflow, the visual development platform valued at $4 billion that empowers over 3.5 million designers worldwide. Rachel discusses Webflow's bold strategy to evolve into an AI-native experience platform with the launch of AppGen, a tool bridging the critical gap between AI prototyping and true production for enterprises like The New York Times and Spotify.What you'll learn:The ICCPO Framework: Why modern leaders must remain patient zero and use their own tools to understand the systems they build.From SEO to AEO: Why Product Managers must now own Answer Engine Optimization as a primary distribution channel.AppGen Strategy: How to move beyond simple wrappers to generate full-stack, on-brand web apps directly from prompts.Key Takeaways