The Product Podcast
- Épisodes
- 859
- Parution
- hebdomadaire
- Dernier épisode
- 11 Nov 2026
À propos du podcast
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.
Épisodes 859
Marissa Mayer Is Back with Dazzle, the New AI Assistant That Learns From Your Camera Roll
Most AI assistants want your inbox and your calendar. Marissa Mayer wants your camera roll. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Marissa Mayer, Google’s first …
Notes de l’épisode
Most AI assistants want your inbox and your calendar. Marissa Mayer wants your camera roll. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Marissa Mayer, Google’s first woman engineer (employee #20), former VP of Search, former CEO of Yahoo, and the person who started Google’s APM program (the reason Product School exists), to talk about her new startup Dazzle, a personal assistant that learns who you are from your photos.
What you’ll learn:
- Why Mayer believes your camera roll is the richest, lowest-friction source of personal data
- The insight behind Dazzle: ~40% of camera roll photos are tasks, not memories
- How an AI assistant learns your taste from photos, then acts on what it sees
- Why she returned to founding after Google and Yahoo, and why she loves every company stage
- Why she’s betting consumer AI will be bigger than enterprise AI
- How Dazzle blends agentic commerce with a human concierge for high-stakes purchases
- Why the web is still built for humans, and what proper agent-commerce protocols would fix
- The Amazon-vs-Walmart split on letting agents shop, from a Walmart board member’s view
- How a ten-engineer team competes with giants through focus
- Why Dazzle is model-agnostic, running 3-4 frontier models and routing each task to the best
Marissa Mayer:
CEO, Dazzle AI
LinkedIn: https://www.linkedin.com/in/marissamayer/
Host:
Carlos, CEO at Product School
LinkedIn: https://www.linkedin.com/in/villaumbrosia/
About Dazzle: Dazzle is an AI personal assistant that learns from a user’s photos (rather than typed prompts) to understand their life and help them get things done, from shopping to planning to reminders. Founded by Marissa Mayer, it builds on assets from her prior startup, Sunshine.
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
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Cisco President & CPO on Rebuilding Products So Agents Can Use Them, Running a $460B+ Company in Founder Mode & the Rule of Thirds | Jeetu Patel
Agents now consume more tokens than humans do, and Jeetu Patel thinks that breaks almost every product built for people to click through. In this episode of The Product Podcast, Carlos (CEO at Product School) …
Notes de l’épisode
Agents now consume more tokens than humans do, and Jeetu Patel thinks that breaks almost every product built for people to click through. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Jeetu Patel, President and Chief Product Officer at Cisco, for his fifth appearance, to unpack what it actually takes to rebuild products so agents, not just humans, can use them, and how a $63 billion company runs in founder mode.
What you’ll learn:- Why products now have two users, humans and agents, and how to design for both
- The stats behind the shift: agents at 5x human token consumption, 60% of compute going to inference
- Why fewer than 2% use agents today, and why Jeetu predicts 30 to 40% within 12 to 15 months
- How agents disintermediate the middleman, and the new business models that creates
- Founder mode vs. functional mode, and why owner mentality wins during a platform shift
- Why a $63B company runs in “war mode,” not “peace mode,” during a refactor
- Why Cisco has “no product managers, only feature managers,” and sells the platform, not products
- How to become a multi-product company by reusing your route to market, not building new ones
- Cisco’s M&A discipline, why it kills acquired brands, and the promise it makes to founders
- The coming compute, power, and data-center supply crunch, and why it favors Cisco
Jeetu Patel, President and Chief Product Officer, Cisco
LinkedIn: https://www.linkedin.com/in/jeetupatel/
Host: Carlos, CEO at Product School
LinkedIn: https://www.linkedin.com/in/villaumbrosia/
About Cisco: Cisco is a global technology leader in networking, security, and infrastructure, now central to the compute, connectivity, and security demands of the AI and agent era.
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
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Replit CEO on The Self-Driving Company: How AI Agents Learn to Operate Themselves While Humans Set the Destination | Amjad Masad | E317
Replit spent eight of its first ten years just searching for product-market fit. Then it 100x’d its revenue in a single year. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down …
Notes de l’épisode
Replit spent eight of its first ten years just searching for product-market fit. Then it 100x’d its revenue in a single year. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Amjad Masad, founder and CEO of Replit, to unpack how a decade of patience turned into one of the fastest growth stories in software, and why he thinks not knowing how to code is becoming an advantage.
What you’ll learn:
- Why the classic product-market-fit timeline was a SaaS-era myth, and what patience really takes
- The four long-term trends Amjad bet the company on: cloud, AI, mobile, and collaboration
- How Replit Agent (the first coding agent) was built right after a layoff, and why conviction held
- What 100x revenue in a year, 50M+ users, and a $9B valuation actually came from
- Why 75%+ of Replit users are non-engineers, and why not knowing how to code can be an advantage
- Why frontier models reward simple prompts, and why micromanaging the AI makes results worse
- How to keep oversight of parallel agents without falling back into micromanagement
- Why Amjad thinks “code,” not “chat,” is the real AI breakthrough for getting work done
- Why Replit went compute-maximalist with built-in code review and security to earn trust
- Why the future of building a company looks more like an open-source community
Guest: Amjad Masad, Founder and CEO, Replit
LinkedIn: https://www.linkedin.com/in/amjadmasad/
Host: Carlos, CEO at Product School
LinkedIn: https://www.linkedin.com/in/villaumbrosia/
About Replit: Replit is an AI-powered software creation platform where anyone can build, deploy, and run apps from the browser, powered by Replit Agent. It serves over 50 million users, from individual creators to enterprises and governments.
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
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MrBeast CPTO on How the World's Biggest YouTuber Uses AI to Run Every Video Like a Product Launch | Shiva Rajaraman
Mr. Beast makes YouTube videos the way most companies ship software: with product reviews before, retros after, and a daily build cycle. In this episode of The Product Podcast, Carlos (CEO at Product School) …
Notes de l’épisode
Mr. Beast makes YouTube videos the way most companies ship software: with product reviews before, retros after, and a daily build cycle. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Shiva (Chief Product and Technology Officer at Beast Industries) to unpack how a channel with 520M+ subscribers and 1.6B views in the last 90 days treats every video like a product launch, and how AI is now rewiring the whole operation.
Shiva has built products inside some of tech’s most iconic platforms (Google, Spotify, WeWork, Uber), but this role is fundamentally different: here the product is the output itself, not just the platform that enables it. He explains why that lets his team do something a platform never could, get deep into the actual workflow and change it, and why off-the-shelf enterprise SaaS kept falling short for a company that regularly attempts first-ever-in-the-world productions. So, about three months ago, they started building their own internal operating system instead, and now they ship every day.
He and Carlos get into the mechanics that make that possible: forward-deployed engineers embedded inside functions (the studio, marketing) who prototype solutions overnight and ship the next day, why it’s now so cheap to try ten versions of something and throw away the nine that don’t work, and how an issue spotted on set at midnight becomes a meeting that night, a vibe-coded prototype, and a live feature by morning. Shiva also reframes what AI really unlocks for product people: not just speed, but the superpower of exploration, the ability to build three variants instead of betting on one, which finally fixes the oldest failure mode in product (shipping what the founder wants instead of what users need). He shares how working with Jimmy (a creator who thinks like a product manager, breaking creative wins into analytical recipes) shapes the culture, how he builds an institutional memory layer so one person’s hard-won knowledge becomes available to everyone on day one, and how the business thinks about turning attention into revenue through a new consumer app, sponsorships, merch, and testing monetization differently across markets like the US and India.
What you’ll learn:
- Why MrBeast runs every video like a product launch, with reviews before and retros after
- What changes when the product is the output itself, not the platform behind it
- Why they ditched off-the-shelf SaaS and built their own internal operating system in three months
- How forward-deployed engineers prototype overnight and ship to the team the next day
- Why “try ten, keep one, throw away the rest” is now a viable way to build
- How AI gives product teams the superpower of exploration, not just speed
- Why founders so often ship products built for themselves, and how AI finally fixes that
- How to build an institutional memory layer so knowledge isn’t trapped in one person’s head
- What it’s like to work with Jimmy, a creator who thinks like a product manager
- How Beast Industries thinks about converting attention into revenue across global markets
Connect with Shiva:
Chief Product and Technology Officer, Beast Industries
LinkedIn: https://www.linkedin.com/in/shivar/
Host:
Carlos, CEO at Product School
LinkedIn: https://www.linkedin.com/in/villaumbrosia/
About Beast Industries: Beast Industries is the company behind MrBeast, the world’s most-subscribed YouTube creator, spanning its flagship channels, a growing studio of new channels, and consumer products.
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
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Deel Head of Product on How AI Agents Do the Work of 600 Employees and Added $140M in New Revenue Without Hiring | Aaron Goldsmid, SVP of Product, Deel
Deel found over $140 million in ARR through AI optimizations, work equivalent to 600 employees, now done by agents. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Aaron …
Notes de l’épisode
Deel found over $140 million in ARR through AI optimizations, work equivalent to 600 employees, now done by agents. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Aaron Goldsmid, SVP of Product at Deel, to unpack what that actually looks like in practice, and how a company goes from roughly $250 million to $1.5 billion in ARR across 150+ countries while staying profitable for nearly three years.
What you’ll learn:
- The story behind the stat: $140M in ARR and 600 people’s worth of work now handled by AI agents
- Why software was “the last artisanal craft,” and what changes when building gets cheap
- Why building is easy but maintaining is hard, and why the rewrite is now a real tech-debt strategy
- How Deel scaled from ~$250M to $1.5B ARR and stayed profitable for nearly three years
- Why growth and profitability aren’t opposite ends of a pendulum, and the “always do the math” discipline
- Why the signal a leader receives gets more filtered at scale, and how to fight it
- How every-two-weeks business reviews kill pairwise conversations and improve decisions
- How Aaron scales himself with a chief of staff, internal bots, and a semantic layer
- Why Deel’s real AI moat is compliance expertise and a global-work corpus, not the model
- Why no company is as sticky as it used to be, and why judgment is the ultimate differentiator
Connect with Aaron Goldsmid, SVP of Product, Deel
LinkedIn: linkedin.com/in/aarongoldsmid
Host: Carlos, CEO at Product School
LinkedIn: https://www.linkedin.com/in/villaumbrosia/
About Deel: Deel is a global work platform that helps companies hire, pay, and manage teams anywhere, spanning payroll, employer of record (EOR), compliance, and contractor management across 150+ countries.
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
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HP President on Replacing Middle Management and Cutting Tickets 40% with AI Agents | Faisal Masud | E314
HP is best known for hardware and printers. Faisal Masud is turning it into a software and AI company, and he thinks the era of stacked management layers is ending. In this episode of The Product Podcast …
Notes de l’épisode
HP is best known for hardware and printers. Faisal Masud is turning it into a software and AI company, and he thinks the era of stacked management layers is ending. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Faisal Masud, SVP and President of Worldwide Digital Services at HP, for a candid conversation about building enterprise AI, and what it does to how companies are actually run.
Faisal has a rare vantage point: two decades across Amazon, eBay, Groupon, and Alphabet's Wing (the drone delivery moonshot, where he was COO), then CEO of the $1.5B commerce platform fabric, and now running all of HP's commercial software business. He explains why a hardware giant deliberately built a standalone software unit, how the thesis (collect telemetry from HP's devices, turn it into insights that serve customers) became the Workforce Experience Platform, and why HP stopped reselling third-party software to sell its own owned-IP products instead.
The heart of the conversation is what AI is doing to organizations. Faisal argues that AI is demonstrably making extra layers of management unnecessary, because the monitoring, data collection, and aggregation those layers existed to do can now be handled by individuals and agents. His provocative framing: the future "manager" is managing agents, not people, and managers will have to know far more than just how to manage. He's equally blunt about the hype, AI is part of your strategy, not your strategy, adoption metrics alone prove nothing, and "everything is easier with AI until you go to production, which is a whole different ball game," where token budgets and real ROI bite. He also gives a working leader's read on the competitive landscape (OpenAI on the frontier, Amazon's moat, Microsoft Copilot's gains) and how his own PMs and developers use Claude, Codex, and Cloud Code every day.
What you'll learn:- Why AI is making additional layers of management unnecessary, and what replaces them
- The shift from managing people to managing agents, and why managers will need to know more
- Why a hardware company like HP built a standalone software and AI business
- How device- and OS-agnostic telemetry became the Workforce Experience Platform
- Why HP stopped reselling third-party software to sell owned-IP products
- Why "AI is part of your strategy, not your strategy," and why adoption metrics aren't enough
- The real wall: AI makes building easy until you hit production, budgets, and token limits
- How Faisal pushes PMs on what should be done with AI vs. what needs a human in the loop
- A working read on OpenAI, Amazon, and Microsoft Copilot in the enterprise
- What Faisal predicts for headcount and org structure in the mid-term
Connect with Faisal Masud: President, HP
LinkedIn: https://www.linkedin.com/in/faisal/
Host: Carlos, CEO at Product School
LinkedIn: https://www.linkedin.com/in/villaumbrosia/
About HP Digital Services: HP's Digital Services division builds the commercial software HP sells into enterprises and channel partners, including the Workforce Experience Platform, which uses AI to anticipate and resolve employees' IT needs across a device- and OS-agnostic fleet.
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
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Toast VP of Product on Building Agents Into Pre-AI SaaS; Shipping AI Into a 14-Year-Old Platform and Building for the Real Economy
Toast was built long before generative AI existed. So how do you weave AI agents into a platform that thousands of restaurants already run their business on, without breaking the thing that works? In this …
Notes de l’épisode
Toast was built long before generative AI existed. So how do you weave AI agents into a platform that thousands of restaurants already run their business on, without breaking the thing that works? In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Maggie Crowley, VP of Product at Toast, to unpack what it actually takes to build AI into mature, pre-AI SaaS.
Maggie is a former Olympic speed skater (fifth at the 2006 Winter Olympics) turned product leader, with an MBA from Harvard and product roles across Drift, TripAdvisor, and Charlie Health before Toast. She was also a Product School contributor years ago, back in her Drift days, which is what makes this a fitting return. At Toast she leads product on Toast IQ, the company's AI layer for restaurant and retail operators. In this conversation, she and Carlos get into the genuinely hard parts: why the quality bar for building on an established platform is punishingly high, how her team actually shipped their first assistant (sitting in WhatsApp groups with real customers and turning it on for a few of them), and why you have to physically bring the AI to the user instead of assuming they'll discover it.
Maggie is refreshingly blunt that restaurant operators have zero tolerance for "AI for AI's sake." They don't care whether it's Anthropic, OpenAI, or an open-weight model under the hood; they only care whether you helped them run their business. She explains how the tight P&L of a restaurant forces real discipline about what's worth charging for, how Toast IQ Grow (an agent that drives demand and fills seats) became a breakthrough use case by slashing the cost of marketing work, and why she still manages a frontline team directly to stay close to how AI is changing the way products get built. The episode closes with a live demo of Toast IQ.
What you'll learn:
- How to build AI agents into a platform designed years before AI, without lowering the quality bar
- The scrappy build process: WhatsApp groups with customers and turning an assistant on for a few
- Why you have to bring the AI to the user, and why AI onboarding is an unsolved problem
- Why context (where the user is, what time, what role) is everything for an AI product
- Why restaurant operators have zero tolerance for "AI for AI's sake"
- How the tight P&L of a restaurant enforces discipline about what's worth building and charging for
- How Toast IQ Grow uses AI to cut the cost of marketing and drive real demand
- Why abstracting model choice (Anthropic vs. OpenAI vs. open weights) away from the user matters
- Why a product leader should keep a hand in how teams build, and manage close to the work
- A live look at Toast IQ answering real operator questions in plain language
Connect with Maggie Crowley:
VP of Product, Toast
LinkedIn: https://www.linkedin.com/in/maggie-crowley-42a97112/
Host: Carlos, CEO at Product School
LinkedIn: https://www.linkedin.com/in/villaumbrosia/
About Toast: Toast is an all-in-one platform built for restaurants and retail, spanning point of sale, payments, operations, and marketing, now including Toast IQ, its AI layer for operators.
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
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Hinge CPTO on Building an App Designed to Be Deleted, Merging the CPO and CTO Roles, Chasing $1B in Revenue Without Chasing Engagement | Ben Celebicic | E312
Most apps optimize for time on screen. Hinge optimizes for you leaving. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Ben Celebicic, Chief Product and Technology Officer …
Notes de l’épisode
Most apps optimize for time on screen. Hinge optimizes for you leaving. In this episode of The Product Podcast, Carlos (CEO at Product School) sits down with Ben Celebicic, Chief Product and Technology Officer at Hinge, the dating app "designed to be deleted," to unpack how you build a product whose North Star is great dates, not engagement, and still chase a billion dollars in revenue.
Ben has been at Hinge for 11 years, since the 2015 relaunch, and recently became one of a growing number of leaders to hold both the product and technology mandate in a single CPTO role. He and Carlos get into the healthy tension between the CPO instinct (ship fast, innovate) and the CTO instinct (protect quality and infrastructure), and how he now runs that debate inside one person and across a team of nearly 300. He lays out Hinge's monetization philosophy in two principles: build the free experience so everyone can succeed, and only charge for things you can't give away free without breaking the ecosystem (which is why fewer than 15% of users pay). He explains how a dedicated culture and consumer insights team studies real daters to find core needs, how generative AI now enables per-user profile coaching that was impossible before, why trust and safety makes up roughly a third of the entire Hinge organization, and where he draws the line on AI-assisted engineering today. He closes on Hinge's mission to reach $1 billion in revenue in 2027.
What you'll learn:
- Why "designed to be deleted" is a real product principle, and how an anti-engagement North Star works
- How to run the CPO-vs-CTO tension, even when both roles live in one person
- Hinge's two-principle monetization model, and why fewer than 15% of users pay by design
- Why you should only charge for things that would break the ecosystem if they were free
- How a culture and consumer insights team turns real dater problems into features
- How generative AI enables personalized profile coaching that wasn't possible before
- Why trust and safety is about a third of the whole org, and how AI powers it
- Where an engineering-background leader draws the line on AI-built product today
- The mission to hit $1B in revenue in 2027, and the "obsess over user needs" formula behind it
Connect with Ben Celebicic: CPTO, Hinge
LinkedIn: https://www.linkedin.com/company/lrb-podcasts/about/
Host: Carlos, CEO at Product School
LinkedIn: https://www.linkedin.com/in/villaumbrosia/
About Hinge: Hinge is the dating app "designed to be deleted," built to help people get off the app and out on great dates. Founded by Justin McLeod and relaunched in 2015, Hinge is part of Match Group's portfolio of dating and social discovery apps.
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
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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 …
Notes de l’épisode
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
Chapitres
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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 …
Notes de l’épisode
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
Chapitres
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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 …
Notes de l’épisode
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
Chapitres
Chargement des chapitres…
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 …
Notes de l’épisode
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
Chapitres
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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 …
Notes de l’épisode
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
Chapitres
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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 …
Notes de l’épisode
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
Chapitres
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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 …
Notes de l’épisode
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 ZaverySocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
Chapitres
Chargement des chapitres…
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 …
Notes de l’épisode
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 JainSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
Chapitres
Chargement des chapitres…
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 …
Notes de l’épisode
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 KuninsSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
Chapitres
Chargement des chapitres…
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 …
Notes de l’épisode
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 BoseSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
Chapitres
Chargement des chapitres…
Typeform CEO on Why Breadth Beats Depth as an AI Moat and How to Build a Defensive and Offensive AI Strategy | Jay Choi | E301
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 …
Notes de l’épisode
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 now
- The dual posture Typeform built: a defensive strategy to make their core product impossible to replicate, and an offensive strategy to expand into full customer workflows
- Research Flow, their new product that compresses 50 customer interviews from weeks into hours using AI-moderated research
- Being model-agnostic from day one, and what they learned when switching models without an observability platform in place
- The pricing experiment framework Jay uses: 30 simulations before a single market goes live
Key takeaways:
- When AI threatens to commoditize your core product, expanding surface area is a stronger defense than adding AI features to what you already have
- Positioning AI capabilities in plain language, not technical terminology, is the difference between adoption and abandonment
- Happy churners are a product problem, not a marketing problem: the fix is finding structurally always-on use cases.
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Jay ChoiSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
Chapitres
Chargement des chapitres…
Mozilla Head of Firefox on The Future of Agentic Browsers and Fighting for the Open Internet Against Google Chrome, Apple Safari & Microsoft Edge | Ajit Varma | E300
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 …
Notes de l’épisode
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 world
- Why "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 mission
Key takeaways:- Privacy claims without open-source inspectability are unverifiable, "trust us" is no longer a sufficient product strategy in the AI era
- Competing against trillion-dollar companies is possible when mission clarity defines what you refuse to optimize for
- The agent-driven internet will either democratize access or concentrate it, product choices made today will determine which
Social Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
Chapitres
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Linear COO on Rebuilding the Product Development Lifecycle for Teams and Agents — From Issue Tracker to Shared Operating System | Cristina Cordova | E299
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 …
Notes de l’épisode
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 advantage
- Replacing traditional interviews with paid two to five-day projects
- Why PMs are the fastest-growing power users of agentic tools
Key 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 work
- Agentic workflows are now the default, not a feature. The companies that treat them that way will pull ahead.
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Cristina CordovaSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
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Anthropic Head of Design on Claude Code's Evolution from an Internal Feature into the Fastest-Growing Revenue Product in History | Meaghan Choi | E298
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 …
Notes de l’épisode
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 history
- Anthropic's secret sauce to shipping products at an incredibly high cadence while ensuring quality
- How product teams get structured into small pods of 5 AI Builders and a fleet of agents, where non-engineers ship code into production
- Driving enterprise adoption through PLG from technical teams
- How organizations can measure AI ROI beyond AI adoption and token usage
- Designing user interfaces for agentic capabilities, including CLI
Key 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 Villaumbrosia
Guest: Meaghan ChoiSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
Chapitres
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The Lean Startup Author on New Book Incorruptible: Why Good Companies Go Bad and How Great Companies Stay Great | Eric Ries | E297
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 …
Notes de l’épisode
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 build
- How Saul Price built FedMart, and Costco's Jim Sinegal each solved half the problem, and why you need both halves
- How Anthropic used a purpose trust structure, the Long-Term Benefit Trust, to protect its safety mission from investor pressure
- Why values on the wall fail and what the Johnson & Johnson asbestos scandal reveals about how incentives quietly overwrite principles
- How builders at any level of an organization can start influencing governance without a title or authority
Key takeaways:
- Success makes you a target: the more valuable your company becomes, the more pressure it faces to betray the mission that made it valuable
- Ethos is the real moat: the intangible system of principles that makes a company trustworthy is harder to copy than any product or contract
- Governance is not a legal formality; it is the active, ongoing practice of protecting what you built from the forces that will try to extract it
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Eric RiesSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
Chapitres
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Snowflake VP of AI on Why Enterprises Hide Behind Governance to Avoid Real AI Transformation | Baris Gultekin | E296
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 …
Notes de l’épisode
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 it
- What the semantic layer is and how it lets AI answer business questions accurately, not just fluently
- Why running AI next to data (instead of sending data to models) makes governance dramatically easier
- How Snowflake deployed AI internally: a CEO-level non-optional mandate combined with bottom-up access to their own Cortex coding agent
- Why context — not just data — is what agents need to operate reliably at enterprise scale
Key takeaways:
- Start with one scoped use case, build the semantic model around it, layer governance — don't wait for perfect data
- Context is a shared reality for agents: unified data + business semantics + codified workflows
- AI adoption compounds when leadership sets a hard mandate and simultaneously gives everyone a tool to experiment with
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Baris GultekinSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
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Superhuman Mail CEO on Rediscovering Product-Market Fit in the Age of AI, Renaming Post-Grammarly Acquisition & Competing against Google Workspace | Rahul Vohra | E295
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 …
Notes de l’épisode
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 score
- Why you should ignore the not disappointed and most somewhat disappointed users — and which signals actually tell you who to build for
- How to use the High Expectation Customer (HXC) framework to narrow your market without changing your product
- Why PMF is a moving target and how to defend it against commoditization and copy-cat competition
- How Rahul operates as the editor of the product — using 20 verbatim quotes to push PMs and designers to sharper decisions
Key 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 there
- Changing your market is faster than changing your product — segmentation alone can jump your PMF score 10 points overnight
- Building for your highest-expectation customer is not the same as building for your ICP — confuse the two, and you'll optimize for the wrong signal
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Rahul VohraSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
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GoFundMe CPTO on Building Marketplaces Across StubHub, TheRealReal & GoFundMe | Arnie Katz | E294
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 …
Notes de l’épisode
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 one
- How GoFundMe is using AI agents to reduce friction for fundraisers, resulting in an expected $125 million in additional funds raised
- Why AI is driving revenue growth at GoFundMe, not just developer productivity — and how they sequenced that deliberately
- The real trade-offs of the CPTO model: what you gain in speed, and what you have to mitigate through hiring
- How GoFundMe is building demand-side and matching mechanisms to grow donation volume beyond viral sharing
Key takeaways:
- Marketplace liquidity isn't just about having enough supply — it's about designing the right matching and demand mechanisms at every stage of scale
- AI unlocks revenue opportunities that were previously uneconomical to pursue, especially when the customer is already in a vulnerable, high-friction state
- The CPTO structure enables faster decision-making, but requires consciously strong functional leaders underneath to offset the natural lean toward one side
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Arnie KatzSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
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Robinhood VP of Product on Prediction Markets, AI-Native Investing Tools, and Social Trading for the Next Generation | Abhishek Fatehpuria | E293
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 …
Notes de l’épisode
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 up
- Why treating legal and compliance partners as product owners, not blockers, is the unlock for shipping fast in a regulated market
- The "barbell strategy" for UX: design for the newest user and the most advanced user simultaneously, and let the middle take care of itself
- How the early-stage ideation sprint has compressed from 4–5 weeks to 2–3 days with AI tools
- Why Robinhood Social is built on verified identity and real trades — and what that unlocks for the future of retail investor relations
Key takeaways:- Paid subscriptions aren't just a revenue line — they're the connective tissue that drives multi-product adoption across a platform
- Pride is a scalable quality standard: when teams enforce it themselves, quality and speed stop being in conflict
- AI embedded into workflows moves faster than AI bolted on as a standalone feature
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Abhishek FatehpuriaSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
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Zoom CPO on Rebuilding the Future of Work Collaboration with Agentic AI — From Meeting Transcripts and Recordings to a System of Action | Jeff Smith | E292
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 …
Notes de l’épisode
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 scale
- Why expanding into mail, calendar, and documents was never about copying Google or Microsoft — it was about owning the full work lifecycle around meetings
- How AI Companion 3.0 performs agentic retrieval across first- and third-party tools to surface insights and produce work product from a single prompt
- Why MCP and open integrations are non-negotiable when you can't afford to be siloed
- How to move from personal AI productivity gains to real, measurable business outcomes
Key takeaways:- When engineering velocity is abundant, strategic direction becomes the scarce resource
- The right engagement metric isn't more meetings — it's whether users produced something valuable as a result
- Agentic AI is the first real opportunity to disrupt entrenched productivity tools that switching costs have protected for decades
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Jeff SmithSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
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TikTok VP of Product on Turning Video-First Feeds into a Full E-Commerce Platform | David Kaufman | E291
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 …
Notes de l’épisode
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 Villaumbrosia
Guest: David KaufmanSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
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Chargement des chapitres…
OpenAI & Figma Product Builders on Killing the Design-to-Code Handoff and Vice Versa | Ed Bayes & Matt Colyer | E290
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 …
Notes de l’épisode
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 Villaumbrosia
Guests: Ed Bayes and Matt ColyerSocial Links:
- Find out more about Product School here
- Follow our Podcast on TikTok here
- Follow Product School on LinkedIn here
Chapitres
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