The Product Podcast

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