The Product Podcast

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Amit Zavery, President and Chief Product Officer at ServiceNow. The platform runs more than 75 billion workflows a year with around $15 billion in annual revenue growing over 20%. Its market cap is above $100 billion, yet the stock is down more than 30% this past year, while its AI business is on track for $1.5 billion, ahead of a $1 billion plan. 
Amit previously ran product and platform at Oracle for over two decades and was a VP and General Manager at Google Cloud.
What you'll learn:
Why the market can't yet tell AI winners from losers, and why companies that don't transform will get killed
Why the idea of one company becoming the single end-to-end enterprise orchestrator is a fallacy
The spare part approach that makes most enterprise AI projects fail, and what pacesetters do instead
Why access is shifting from user interfaces to agents, and what taking action actually requires
How to hold long-term conviction on platform bets while the market judges you on short-term sentiment
Key takeaways:
Transform or die: the market will separate AI-native platforms from legacy vendors
Interoperability beats domination in the agentic era
Governance only wins when it accelerates innovation, not when it blocks it
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Amit Zavery
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In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Saral Jain, SVP of Engineering at Snapchat, the last independent social platform operating at global scale, with 956 million monthly active users closing in on the one billion mark and a community that opens the app more than 30 times a day.

Saral joined Snap nine years ago, right around the IPO, after nearly a decade leading engineering teams at Amazon Web Services, and today leads all engineering for Snapchat, spanning product experiences, multi-cloud infrastructure, and the company's machine learning and generative AI platforms.

What you'll learn:
How Snap lets designers and product managers ship production code, with an AI agent running the first review pass on 90% of code within 5 minutes
What Casper is: the AI teammate any team at Snap can invoke from Slack or Jira to build a working prototype from a conversation
How Snap turned company-wide AI adoption into business impact after early prototypes were being built and thrown away
How lean startup squads mix engineers, designers, and data scientists to launch zero-to-one bets inside a mature platform

Key takeaways:
Quality control does not have to slow down who gets to ship, it has to change what reviews the work first
Widespread AI adoption is not the same as business impact, and the gap between the two is where most AI investment is being wasted right now
Small, cross-functional teams with blurred roles can move faster than traditional org structures, even inside a billion-user company
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Saral Jain
Social Links:
Find out more about Product School here
Follow our Podcast on TikTok here
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In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Jeff Kunins, Chief Product Officer and Chief Technology Officer at Axon, the company that created the Taser and the body cameras federal agencies wear. 
Axon ingests more video per year than YouTube, and with a market cap of approximately $32.9 billion and $2.78 billion in revenue, growing 33% year over year, it is one of the highest-growth companies in the S&P 500.

What you'll learn:
How law enforcement agencies are using AI inside body cameras and Tasers to save lives, not just hit metrics.
Why Axon declared a public moratorium on facial recognition AI for six years and what finally changed.
How Axon embeds external activists and researchers directly into product manager squads as a design input, not a compliance process.
Building first-party AI models for real-time license plate detection while using foundation LLMs for everything else.
Key takeaways:
Axon created the Taser and the body cam, and now ingests more video per year than YouTube. Most people have never heard of them.
Build only what you must to be differentiated. Everything else, license from the best available source.
Ethics review is not a compliance burden. When embedded in the product lifecycle, external critics help you see around corners and design better products.
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Jeff Kunins
Social Links:
Find out more about Product School here
Follow our Podcast on TikTok here
Follow Product School on LinkedIn here

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Arnab Bose, Chief Product Officer at Asana. Asana is the work management platform built for human and AI collaboration, trusted by over 170,000 customers including Accenture, Amazon, and Anthropic. The platform's Work Graph maps goals to portfolios to projects to tasks and serves as the foundation for Asana's AI Teammates: collaborative agents that operate inside the graph, learn from human decisions, and compound their intelligence with every cycle.

What you'll learn:
Why enterprise AI spend keeps returning zero productivity gains, and what is structurally breaking the loop
Why every employee approval, correction, or rejection of AI output is training data that makes the system smarter over time
How Asana wires its own processes through the Work Graph so that AI decisions write back automatically and compound rather than reset
How PLG, forward-deployed engineers, and AI agents all report to the CPO, each under a GM who owns a revenue number
Why the future of AI at work belongs to whoever has the richest shared context, not whoever has the best model

Key takeaways:
Individual AI productivity gains compound into zero enterprise ROI when decisions never write back into a shared system
Every human approval or correction is training data. The companies that capture it structurally will pull ahead of those that don't
PLG is an acquisition funnel, not a sales motion. Giving it a GM with a revenue number inside product changes the incentives entirely
Credits:
Host: Carlos Gonzalez de Villaumbrosia
Guest: Arnab Bose
Social Links:
Find out more about Product School here
Follow our Podcast on TikTok here
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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 Choi
Social Links:
Find out more about Product School here
Follow our Podcast on TikTok here
Follow Product School on LinkedIn here