Unconventional product lessons from Binance, N26, Google, more | Mayur Kamat (CPO at N26, ex-Binance Head of Product)

**Mayur Kamat** (0:00)
My probably most spectacular failure was, I was the first PM on Hangouts. We had thousands of people working for me. We had entire power of Google. We had Larry literally sitting with us saying, we can do anything we want Chrome to do. And we still didn't manage to build a great messaging product. The main kind of learnings from that is, don't take on projects that are going to be six months a year, because you just generally don't have control over the macro. The challenge of being a product manager is, everybody thinks they can do their job. Anybody who uses the product thinks they have ideas. So at some point in time, you're like, what is my discipline? Like, what is my science? The moment you build experimentation, you're now made it scientific.

**Lenny Rachitsky** (0:41)
A lot of new people in their career are like, I just want to think about strategy. I'm going to think about the big picture.

**Mayur Kamat** (0:45)
Strategy is a little bit overrated for product. For most product managers, your strategy should be, how fast can I go from hypothesis to data?

**Lenny Rachitsky** (0:53)
Today, my guest is Mayur Kamat. Mayur is Chief Product Officer at N26. One of the most successful fintech startups in the world, and which in my research came in amongst the top 5 companies in the world who are hiring and producing the best product managers. Prior to N26, Mayur was Global Head of Product at Binance, VP of Product at Agoda, which is over a $100 billion company based in Thailand, and a PM at Google and Microsoft. In our wide-ranging conversation, Mayur shares what he's learned about hiring and developing great product managers, what he learned from his time working at Binance, which, as you'll soon hear, was one of the wildest and most unique ways of working, what he learned from the failure of Google's early attempts at Hangouts, where he was the first PM, also the pros and cons of working in Asia vs. Europe vs. the US, and why you should be starting your career on the west coast of the US, also why comp early in your career does not matter, and so much more. This episode is so full of golden nuggets and advice for product people throughout every stage of their career. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. Also, if you become an annual subscriber of my newsletter, you get a year free of a bunch of amazing products including Superhuman, Notion, Linear, Perplexity, Granola and more. Check it out at lennysnewsletter.com and click bundle. With that, I bring you Mayur Kamat. This episode is brought to you by Work OS. If you're building a SaaS app, at some point, your customers will start asking for enterprise features like SAML authentication and skim provisioning. That's where Work OS comes in, making it fast and painless to add enterprise features to your app. Their APIs are easy to understand so that you can ship quickly and get back to building other features. Today, hundreds of companies are already powered by Work OS, including ones you probably know like Vercell, Webflow and Loom. Work OS also recently acquired Warrant, the fine-grain authorization service. Warrant's product is based on a groundbreaking authorization system called Zanzibar, which was originally designed for Google to power Google Docs and YouTube. This enables fast authorization checks at enormous scale while maintaining a flexible model that can be adapted to even the most complex use cases. If you're currently looking to build role-based access control or other enterprise features like single sign-on, skim, or user management, you should consider Work OS. It's a drop-in replacement for Auth0 and supports up to 1 million monthly active users for free. Check it out at workos.com to learn more. That's workos.com.
Many of you are building AI products, which is why I'm very excited to chat with Brandon Fu, founder and CEO of Paragon. Hey, Brandon.

**Brandon Fu** (3:41)
Hey, Lenny. Thanks for having me.

**Lenny Rachitsky** (3:43)
So, integrations have become a big deal for AI products. Why is that?

**Brandon Fu** (3:47)
Integrations are mission critical for AI for two reasons. First, AI products need contacts from their customers' business data, such as Google Drive files, Slack messages or CRM records. Second, for AI products to automate work on behalf of users, AI agents need to be able to take action across these different third-party tools.

**Lenny Rachitsky** (4:06)
So where does Paragon fit into all this?

**Brandon Fu** (4:08)
Well, these integrations are a pain to build, and that's why Paragon provides an embedded platform that enables engineers to ship these product integrations in just days instead of months, across every use case, from rag data ingestion to agentic actions.