Lenny's Podcast: Product | Career | Growth
01:00:45 · Tara Seshan
[01:00:45] S0: Sutter Hill is an iconic firm and is intentionally a very illegible firm. If you go to the Sutter Hill website, you will see nothing on the website. It is a firm that doesn't operate loudly. It tries to operate as under the radar as possible, as modestly as possible, yet is somehow responsible for some of the most iconic successes that Silicon Valley has seen. And they have this very unusual incubation model, which Mike Speiser, who is one of the amazing partners there, started and has rolled out success after success. I think the thing that was most iconic to me about Sutter Hill is that people look at finding product market fit as a dark art or building a tens of billion dollar company as a dark art, like, "Oh, it's luck. Oh, it's chance. Oh, it's all these things that must come together." Yet Mike Speiser has done it multiple times. And so there's clearly a way to do it. There's clearly a roadmap for making that possible. There is a set of things one can do to get this repeatably. It's not just luck. It's not just a dark art. There is a playbook, as it were, and that playbook lives inside of the firm Sutter Hill. And they have figured out how to be right a lot in terms of calling shots and making bets. And they've learned how to be right a lot in terms of the daily compounding things that one does to create a successful company, whether that's how you set up your enterprise sales team, how you position your product, how you build the initial founding team. The recruiting at Sutter Hill is an unparalleled, excellent thing. They have a secret tool called Redical where they have a map of everyone that they've interacted with and the 10 best people that those people have interacted with that helps them be so, so effective at this. So I went to Sutter Hill because in some way my career has been about how do I try to find product market fit as many times as possible, whether that was as a founder or in starting new products at Stripe or in joining a startup like Watershed. And so Sutter Hill is the place where they've figured out how to find product market fit on B2B products, and I wanted to learn what I could from them.
01:02:57 · Lenny Rachitsky, Tara Seshan
[01:02:57] S1: What'd you learn? What's one thing you took away from that experience other than they know how to do it? [01:03:01] S0: They definitely know how to do it. I think one thing that was very surprising to me that I learned there is that product market fit is, sure, important, but actually I really underrated product marketing fit. The idea that the way you talk about the product and the way you market it can proceed actually even building the product. It should probably come from some sort of bringing together of understanding the technology deeply and then understanding the enterprise sales process. And then that product marketing fit, that narrative, that positioning, is actually even before you build a product experience the right thing to test. So you should go pitch a hundred people, figure out how to refine that pitch as much as possible, get the marketing narrative of why this thing is transformative right. And then and only then go commit the, okay, this is exactly the product shape. And Mike Speiser is unbeatable at this art. Previously, I'd always underrated PMM work. I was like, "It's whatever. It's the glue between these functions. It's fine." And then I realized how transformative that work done excellently is to a company's outcome, and in fact can be the element that makes a company successful. [01:04:12] S1: Amazing. I so agree with that. Positioning, we talk a lot about that on this podcast. Okay. I'm going to show you what sites got created real quick. It was running while we were talking. Check this out. Look at this. [01:04:22] S0: Oh man.
01:04:22 · Tara Seshan, Lenny Rachitsky
[01:04:22] S0: Oh man. [01:04:24] S1: I was like, "Make it more awesome," and it made it more awesome. [01:04:26] S0: That's- [01:04:27] S1: Multi-product. Beautiful. Look at this. This is like a legit design. [01:04:32] S0: Wow. [01:04:32] S1: Look at it. You got quotes, big conviction, small teams. [01:04:35] S0: It's true. [01:04:36] S1: [inaudible 01:04:36] the buyer. How do you feel about this being your website, your new website? [01:04:40] S0: I do think that the picture of me at maybe 19 years old at the top is really funny. But yeah, otherwise I love the site. [01:04:48] S1: Okay, good job. [01:04:49] S0: It's looking good. [01:04:51] S1: Good job Sites. [01:04:52] S0: I think that was my badge photo from Stripe. [01:04:54] S1: Oh wow. Amazing. I already unshared it, but I love that it built the whole little thing around your head. So cute. Tara, is there anything else that you wanted to share? Anything else you want to touch on before we get to our very exciting lightning round?
01:05:08 · Tara Seshan
[01:05:08] S0: Yeah. One thing that we've been thinking about a lot in product building, especially with ChatGPT Work in this new era, is how knowledge work and coding are actually fundamentally different. And one of the surprising things we learned as a part of that is that coding is so output oriented that when you ask it to do a coding task, you can verify whether it did the task correctly or well via tests. You can try it out and see if it works. There is a way to validate it based on the output. But knowledge work is different in that I can't simply look at the deck in the end and see the numbers, like, oh, it's like 90% success or whatever in the deck and actually believe that. I really need to think about the process and the inputs and the reasoning and how it went along the way. And so in terms of how that looks in the product, a lot of work that we have done and have to continue to do is continue to adapt the product to knowledge work, which means way more focus on making ChatGPT your collaborator, allowing you to see all the in-progress work, see its citations and inputs, help you go on the journey with the model to get to that end output, such that you know in the end that, oh wait, this thing is right, this thing is good, this thing is useful. And that shows up certainly in the UX of the product quite a bit, but also should show up in things like the reasoning in the chain of thought. Should you see more citations along the way, for example, of how it got to that end state in that data? Is the surface of a thread which is so suited to coding the right place for you to see all of that for knowledge work as well? There's so many big important product questions. And so as we think of maybe bringing in human collaborators into your work, we also need to think about how we can make the model more of a collaborator with you as you get things done together.
01:06:58 · Lenny Rachitsky, Tara Seshan
[01:06:58] S1: That is such a good point. I'm imagining an exec meeting where you're trying to pitch the exec on, here's what the plan is, here's what I think we should be doing. So much of that is helping them see here's the work I did to get there, here's all the steps. And so it makes sense that you need the AI to show you that same sort of work. That it did the proof of work essentially versus engineering where like, "Okay, I don't need to know all of the little architectural decisions you made, just what does it look like? Is it passing all the tests that we have?" So that is a really good point, just how different those two models are. And also there's the context. Does it have the context it needs to do the thing that you want it to do? Does it know? Can it see your email? Can it see all your notion docs? Such a good point. So I see the challenge in your job to make all this work is one product. Tricky, tricky. Amazing. Anything else before we get to our very exciting lightning round? [01:07:54] S0: Yeah, let's jump into it. [01:07:56] S1: With that, we've reached our very exciting lightning round. I've got five questions for you. Are you ready? [01:08:00] S0: Yes. [01:08:02] S1: What are two or three books that you find yourself recommending most to other people?
01:08:06 · Tara Seshan
[01:08:06] S0: One book I really recommend to people is Barbarian Days by William Finnegan. I don't know if you've read it. It's about a life of a man who is a New Yorker reporter, but how he fell in love with surfing as his passion. The thing I took away from the book is that one can be deeply passionate and dedicated and have something be your life purpose without you being good at it. And it is about the art of falling in love with surfing and his striving for excellence and perfection whilst knowing that he will never reach it. It is such a compelling and transformative story for how I think one should continue to live our lives. I really, really love that book. Another book that I might recommend as a book that people should read, I really love Anna Karenina. I've been rereading the classics lately, and I love Anna Karenina because it's a book of layers. And I think that a huge part of what we're going to have to do in this new era is transform ourselves or take ourselves on a journey to do different things than what we were used to. And when I think about that book, I think about when I was 13 and I read it, I understood basically the plot. When I read it at 17, I understood the European history dynamics and the class warfare. And then when I read it at 30, I was like, oh, this is a story about a woman and humans. And it just reminds me of growth and that it is possible to look at the same thing through multiple different lenses as you continue to grow, which I think is the challenge that's ahead for all of us as we consider our careers as well.