The Product Podcast

Hosted by Product School

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849

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Aug 2026

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About the show

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.

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60 recent

September 9, 202631 min

Bolt CEO on Turning AI Prototypes Into Production Code Engineers Trust, the Story Behind a 5M-to-20M ARR Ramp in Two Months | Eric Simons | E311

One month before Bolt exploded, Eric Simons was preparing to wind the company down. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Eric Simons, CEO of Bolt, to tell the story behind one of the fastest revenue ramps software has ever seen, and what he learned building toward it for seven years first. Eric is a high-school dropout who approaches life from first principles and treats endurance sports as training for the pain of building a company. He and Carlos trace the near-death moment (a board meeting set to start spinning the company down was one month away), the bet on WebContainers (an operating system Eric's team wrote to run in WebAssembly inside the browser, so you can build real full-stack apps from a browser tab, the way Figma brought design to the web), and the ramp that followed: zero to about $5M ARR in the first 30 days, then to roughly $20M ARR within two months, a curve that normally takes companies years. He explains why StackBlitz is now going deep on professional builders (PMs, designers, engineers), how Bolt is solving the hard part of turning AI-generated prototypes into production code your engineering team will actually sign off on, and why he frames the market like the ChatGPT-vs-Anthropic split: pick a specific ICP and workflow instead of spraying money at everything. He closes on the open-weights bet (StackBlitz was the earliest backer of Vite), aggressive usage-based pricing, and why cheaper open models are closing the last bit of distance to the labs. What you'll learn: - The near-death story: one month from shutting down, then a record revenue ramp - Why the WebContainer bet (a real OS running in the browser) took seven years and made Bolt possible - What a 0-to-$20M-ARR-in-two-months curve actually looks like, and why it's so rare - Why StackBlitz is focusing on professional product builders, not just cute prototypes - How to turn an AI prototype into production code your engineering team signs off on - The "ChatGPT vs. Anthropic" framing: why going deep on one ICP beats spraying money everywhere - Why first-principles thinking and endurance sport shape how Eric builds - The open-weights bet, aggressive usage-based pricing, and open models catching up to the labs Connect with Eric Simons, CEO, Bolt LinkedIn: https://www.linkedin.com/in/eric-simons-a464a664/ Host: Carlos, CEO at Product School LinkedIn: https://www.linkedin.com/in/villaumbrosia/ About Bolt / StackBlitz: StackBlitz is the company behind Bolt (bolt.new), an AI-powered web development platform that lets anyone build real full-stack applications from a browser tab, powered by its in-browser WebContainer operating system. StackBlitz was also the earliest backer of the open-source Vite project. 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 here Follow our Podcast on TikTok here Follow Product School on LinkedIn here

September 2, 202625 min

Anthropic Member of Technical Staff on Leading Forward-Deployed Engineers, Turning Down 2x Pay, and Why Leaders Are Becoming ICs Again | Amandeep Khurana | E310

What do you do after you've founded a company, sold it to Databricks, and could coast? Amandeep Khurana went back to being hands-on. In this episode of The Product Podcast, Carlos Gonzalez de Villaumbrosia (CEO at Product School) talks with Amandeep Khurana, now on Anthropic's go-to-market team, about a career built on deliberately choosing the harder path. Amandeep traces the whole arc: training as an engineer, moving to the Valley to go customer-facing at Cloudera, catching the company-building bug "by osmosis," and founding Okera in 2016, which eventually exited to Databricks. He talks about what he learned in the ups and downs of running a startup, why he later joined AWS as a founding PM (on Kiro) to run four zero-to-one initiatives instead of taking a comfortable management track, and how he thinks about the two fundamental jobs in any company: building a product and selling a product. He and Carlos dig into the tension between being a hands-on builder and being a manager, how to decide which domains are worth jumping into when you know nothing, and why he joined Anthropic to work on bringing AI safely to enterprises. It's a candid conversation about career design, first-principles decision-making, and staying close to the work. What you'll learn: - Why Amandeep repeatedly chooses the "harder path," and how first-principles thinking drives his career decisions - What founding and exiting Okera (to Databricks) actually taught him about company building - Why he went back to hands-on building instead of a pure management track - How to think about the two core jobs in any company: building the product and selling it - How to decide whether to jump into a domain you know nothing about - What running four zero-to-one initiatives inside a big company teaches you - Why he moved into GTM and enterprise AI adoption at Anthropic - How to stay hands-on as your career pulls you toward management Connect with Amandeep Khurana: Anthropic (GTM / Enterprise); previously co-founder and CEO of Okera, founding PM for Kiro at AWS LinkedIn: https://www.linkedin.com/in/amansk/ Host: Carlos Gonzalez de Villaumbrosia, CEO at Product School LinkedIn: https://www.linkedin.com/in/villaumbrosia/ 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 here Follow our Podcast on TikTok here Follow Product School on LinkedIn here

August 26, 202631 min

Mural CPO on How to Put AI in Multi-Player Mode for Your Team; Why AI Made Work Lonelier, Not Better | Elaina O'Mahoney

Visual collaboration is missing from the AI era. That's the provocation Elaina O'Mahoney, Chief Product Officer at Mural, brings to this episode of The Product Podcast with Carlos (CEO at Product School). We spend all day alone in our tools, typing or talking to an LLM, and when it's time to collaborate we drop words into a doc instead of thinking together visually. Elaina makes the case that AI has quietly turned work into "solo-player mode," and that the teams who win next will be the ones who rebuild shared context and multiplayer collaboration on top of it. Elaina and Carlos get into why ideas are now cheap (you can go from a thought to a working prototype in hours) and why that makes shared context, not idea generation, the real bottleneck. She argues that everyone is a designer at heart, that product leaders should replace the five-page strategy doc with a fast prototype that conveys the North Star, and that "shipping" can mean a workflow or an agent, not just a production release. They also dig into the crowded "where work happens" landscape (Slack, Teams, Jira, Linear, Notion) and the blank-canvas gap around how and why decisions actually get made, how to create safe spaces for people to try AI and fail inside large enterprises, and the pricing tension between legacy seat-based SaaS and AI-native usage models. What you'll learn: - Why Elaina says visual collaboration is "absent" in the AI era, and why that matters - The "solo-player mode" problem: how AI made work lonely, and what multiplayer should look like - Why ideas are now cheap, and how that shifts the bottleneck to shared context and faster decisions - Why the real blank space isn't planning or chat, but how and why decisions get made - The case that everyone is a designer, and how visual thinking speeds up decisions - How a CPO ships to demo a direction (a prototype instead of a strategy doc) - What's still scarce in an AI world: data science, taste, and synthesizing analytics - How to create safe, low-risk spaces for teams to try AI and fail inside big enterprises - Why smaller "champion" teams beat top-down rollouts, and how internal builders spread practices - The pricing dilemma: seat-based SaaS vs. AI-native usage models Chapters: 00:00 Intro 00:59 Intro: Elaina O'Mahoney, CPO at Mural 01:31 Mural's origin as a collaboration canvas 03:01 Multiplayer vs. AI's solo-player mode 04:23 Ideas are cheap now: idea to prototype in hours 05:44 The competitive landscape and convergence 08:31 The blank space nobody owns: how decisions get made 09:22 Lowering the bar so everyone can design 11:33 Everybody should be shipping now 12:25 Shipping to demo, not to production 14:04 Creating safe spaces to try AI in the enterprise 17:10 Forward-deployed engineers 19:14 Building a community around Mural 22:11 The pricing dilemma: SaaS vs. AI-native usage 24:07 Measuring real AI impact 26:19 How Elaina structures her team 28:20 The innovator's dilemma 30:03 From annual QBRs to monthly loops 31:05 Ten years of Mural, and a World Cup sign-off Connect with the Guest: Elaina O'Mahoney, Chief Product Officer, Mural LinkedIn: https://www.linkedin.com/in/eomahoney/ Host: Carlos, CEO at Product School LinkedIn: https://www.linkedin.com/in/villaumbrosia/ About Mural: Mural is a visual collaboration platform built for teams to brainstorm, converge, and make decisions together on a shared canvas. Originally created by co-founders in Argentina, it scaled rapidly during the shift to remote work. 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 here Follow our Podcast on TikTok here Follow Product School on LinkedIn here

August 19, 202628 min

Square Global Head of Product on: How to Build AI Agents People Actually Use, Why $49B Company Got Rid of General Managers | Willem Avé

Two years ago, Square tore up its general-manager model and rebuilt the entire company around functional excellence. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Willem Avé, Global Head of Product at Square (part of Block), to unpack why they made that bet, what it costs, and how AI is now reshaping the org itself. Willem started at Block as a CTO whose company was acquired, grew up through engineering, and has seen every era of the company from the little white card reader to today's multiple product ecosystems. He explains why orgs should be built around customer outcomes (and how quality degrades the further you drift from that principle), why hardware demands a different kind of craft than software, and how Jack Dorsey's thinking pushed them toward the idea of running Block like a "mini AGI company," where AI encodes institutional knowledge instead of red tape and process. Then he opens up a live demo of "manager bot," an agent that lets a small-business owner delegate real tasks (like an inventory workflow for a bakery) without worrying about memory, connectors, or prompts. He closes with a genuine hot take on TAM and what AI agents mean for the size of the market Square can serve. What you'll learn: - Why Square replaced general managers with a fully functionalized org, and what "functional excellence" buys you - How to organize teams around customer outcomes, and why quality drops the further you drift - Why hardware craft (approachable, reliable, "it just works") differs from software craft - What it means to run a company like a "mini AGI," and how AI can encode knowledge instead of process - Why the era of the simple question-answer chatbot is ending, and what replaces it - A live look at "manager bot": delegating real business tasks to an agent - Why small-business owners want outcomes, not memory, connectors, or prompt-craft - Willem's hot take on TAM, and how agents expand who Square can serve - Why economic empowerment and democratizing advanced technology is the throughline Chapters: 00:00 Trailer 01:32 Inside Square and Block: how the teams are designed 03:34 The four orgs: audiences, platform, growth, money 04:46 Marrying hardware and software in one function 05:56 Finding leaders who understand both worlds 07:25 The DRI model and killing the silent veto 09:16 Can everyone report to one person? 11:12 Why flat orgs still need great managers 12:41 Building for people who are not on X every day 14:41 The loneliness of running a business 17:24 Demo: Manager Bot doing real work 20:19 Why AI should not create more work for sellers 22:13 Hot take: TAM is almost infinite 24:22 Killing the fragmented point solution stack 26:06 WhatsApp, Instagram, and the comms problem 27:54 Buzz and what nobody has solved yet 28:34 Closing Connect with Willem Avé: Global Head of Product, Square (Block) LinkedIn: https://www.linkedin.com/in/willem-ave/ Host: Carlos, CEO at Product School: LinkedIn: https://www.linkedin.com/in/villaumbrosia/ About Square: Square, part of Block, builds payments hardware and software plus a broader ecosystem of tools that help sellers and small businesses run and grow. Block also includes Cash App and other brands. 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 here Follow our Podcast on TikTok here Follow Product School on LinkedIn here

August 12, 202632 min

How Skydio Ships Flying Robots With Just 20 Product Managers

Most people think of drones as toys. Alden Jones thinks of them as infrastructure. In this episode of The Product Podcast, Carlos (CEO at Product School) visits Skydio's California office to sit down with Alden Jones, VP of Product at Skydio, the autonomous drone company building "flying robots" for public safety, defense, and infrastructure inspection. With a history degree and a military background (he was a truck-driving officer running supply convoys in Iraq) rather than an engineering one, Alden explains how a vertically integrated company of nearly 1,000 people builds everything in house, from chip-level design to hardware, embedded software, and cloud, and why autonomy, not just flight, is the real product. He breaks down Skydio's "Drone as First Responder" (DFR) program, where a drone often reaches the scene before human officers, and the outcomes dashboard cities use to track response times. He compares the economics against police helicopters (roughly $3,000 an hour to operate and $10-25M to buy), walks through the defense and tactical ISR use cases shaped by the war in Ukraine, and explains how thousands of cheaper camera drones could democratize air support while saving lives. He covers physical security (where 90-95% of alarms turn out to be false), the work of earning FAA trust to unlock groundbreaking waivers, and why Skydio's $3.5B, five-year investment in US and allied supply chains is funded by revenue instead of debt. He also opens up the product org itself: roughly 20 product managers across the entire stack, "strike teams" that work like forward-deployed engineers, and a customer-first culture where PMs are expected to go watch the robot fly in the real world. What you'll learn: Why Skydio calls its products "flying robots," and the "toys to tools to infrastructure" thesis What full vertical integration looks like: chip-down design to cloud, all in house How "Drone as First Responder" changes 911 response, tracked in a live outcomes dashboard The real economics of drones vs. police helicopters How the war in Ukraine reshaped Skydio's thinking on tactical ISR and democratizing air support Why 90-95% of physical security alarms are false, and how autonomous drones clear them at near-zero marginal cost How Skydio earns FAA trust to fly beyond visual line of sight and win first-mover waivers Why a $3.5B, five-year US manufacturing commitment is funded by revenue, not debt How one pilot flying multiple drones becomes possible only through real autonomy How Skydio runs product with ~20 PMs, "strike teams," and a customer-first org design Why shipping hardware plus software (the Tesla comparison) shapes a roughly two-year program cycle Connect with Alden Jones, VP of Product, Skydio: LinkedIn: https://www.linkedin.com/in/aldenljones/ Host: Carlos, CEO at Product School LinkedIn: https://www.linkedin.com/in/villaumbrosia/ About Skydio: Skydio is a US-based manufacturer of autonomous drones ("flying robots") for public safety, defense, security, and infrastructure inspection. Founded in 2014 and headquartered in California, the company is vertically integrated across hardware, autonomy software, and cloud. 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 here Follow our Podcast on TikTok here Follow Product School on LinkedIn here

July 29, 202646 min

How to Know Your AI Feature Actually Works (n8n's Founder's Metric) | Jan Oberhauser, CEO n8n

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 companies Why trust and consistency, not features, are the real center of a community How the free, self-hosted version drives bottom-up adoption inside major enterprises Why "sprinkling AI on top" kills products, and what to build instead How to chain agents so one agent's output becomes the next agent's input Why n8n is the "connective tissue" between models, tools, and business systems How guardrails (an agent can only do what it's explicitly allowed) speed up enterprise procurement and production Why the people with the problem should own the building, not a centralized AI team How 10,000+ community templates and 500+ integrations expand what non-technical builders can ship How one company routes 75% of support through an n8n agent, with customers happier than with humans Connect with Guest (Jan Oberhauser) : LinkedIn: https://www.linkedin.com/in/janoberhauser X: https://x.com/JanOberhauser Host : Carlos, CEO at Product School LinkedIn: 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 here Follow our Podcast on TikTok here Follow Product School on LinkedIn here

July 22, 2026Episode 30554 min

ServiceNow President & CPO on Why the Market Can't Tell AI Winners From Losers, and How to Transform Before It Kills You | Amit Zavery | E305

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 killed Why the idea of one company becoming the single end-to-end enterprise orchestrator is a fallacy The spare part approach that makes most enterprise AI projects fail, and what pacesetters do instead Why access is shifting from user interfaces to agents, and what taking action actually requires How to hold long-term conviction on platform bets while the market judges you on short-term sentiment Key takeaways: Transform or die: the market will separate AI-native platforms from legacy vendors Interoperability beats domination in the agentic era Governance only wins when it accelerates innovation, not when it blocks it Credits: Host: Carlos Gonzalez de Villaumbrosia Guest: Amit Zavery Social Links: Find out more about Product School here Follow our Podcast on TikTok here Follow Product School on LinkedIn here

July 15, 2026Episode 30432 min

Snapchat SVP of Engineering on How a Billion-User App Lets Everyone Ship Code Without Breaking Quality | Saral Jain | E304

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 minutes What Casper is: the AI teammate any team at Snap can invoke from Slack or Jira to build a working prototype from a conversation How Snap turned company-wide AI adoption into business impact after early prototypes were being built and thrown away How lean startup squads mix engineers, designers, and data scientists to launch zero-to-one bets inside a mature platform Key takeaways: Quality control does not have to slow down who gets to ship, it has to change what reviews the work first Widespread AI adoption is not the same as business impact, and the gap between the two is where most AI investment is being wasted right now Small, cross-functional teams with blurred roles can move faster than traditional org structures, even inside a billion-user company Credits: Host: Carlos Gonzalez de Villaumbrosia Guest: Saral Jain Social Links: Find out more about Product School here Follow our Podcast on TikTok here Follow Product School on LinkedIn here

July 8, 2026Episode 30341 min

Axon CPTO on Building AI for Law Enforcement, Selling to Governments, and Using the Body Cam and Taser to Save Lives at Scale | Jeff Kunins | E303

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 Villaumbrosia Guest: Jeff Kunins Social Links: Find out more about Product School here Follow our Podcast on TikTok here Follow Product School on LinkedIn here

July 1, 2026Episode 30224 min

Asana CPO on Why Every Employee Is Now an AI Eval and What That Means for How Enterprises Actually Capture AI ROI | Arnab Bose | E302

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 loop Why every employee approval, correction, or rejection of AI output is training data that makes the system smarter over time How Asana wires its own processes through the Work Graph so that AI decisions write back automatically and compound rather than reset How PLG, forward-deployed engineers, and AI agents all report to the CPO, each under a GM who owns a revenue number Why the future of AI at work belongs to whoever has the richest shared context, not whoever has the best model Key takeaways: Individual AI productivity gains compound into zero enterprise ROI when decisions never write back into a shared system Every human approval or correction is training data. The companies that capture it structurally will pull ahead of those that don't PLG is an acquisition funnel, not a sales motion. Giving it a GM with a revenue number inside product changes the incentives entirely Credits: Host: Carlos Gonzalez de Villaumbrosia Guest: Arnab Bose Social Links: Find out more about Product School here Follow our Podcast on TikTok here Follow Product School on LinkedIn here