The Product Podcast

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 Gultekin
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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 Vohra
Social Links:
Find out more about Product School here
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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 Katz
Social Links:
Find out more about Product School here
Follow our Podcast on TikTok here
Follow Product School on LinkedIn here

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 Fatehpuria
Social Links:
Find out more about Product School here
Follow our Podcast on TikTok here
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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 Smith

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