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
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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

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

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 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
• Follow Product School on LinkedIn here

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
• Follow Product School on LinkedIn here

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

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