
Hosted by Product School · EN
Hosted by Product School CEO Carlos Gonzalez de Villaumbrosia, The Product Podcast drills deep into the minds of Chief Product Officers from Cisco, Lovable, Perplexity, Shopify and many more.
We move beyond high-level theory to reveal how top executives actually lead in the age of AI. We dig deep into their real-world decision-making, strategic frameworks, and the operational playbooks used to build intelligent products.
If you are a VP, Director, or CPO looking to drive innovation at scale, this is your essential listen.

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

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

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

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

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

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

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

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