The Product Podcast

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

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

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

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

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