Lenny's Podcast: Product | Career | Growth
01:07:00 · Tom Verrilli
[01:07:00] S0: Listen, I, for one, welcome our agentic overlords for things like I don't want to have to think about light bulbs, air filters, any of the programmatic stuff that I need to run my life. I'm also pretty great with it for really high intent things. I need a particular cable for my computer. I'm looking for outdoor lights for my house. Things where there are really taxing searches. I think about this, you got to go to a wedding, which means I need black shoes, but delivered by Thursday because if they don't get here before Thursday, they're no good for me kind of things. Absolutely. But most of commerce in America isn't actually high intent. How many years are we into e-comm now? 30 years into e-comm. And e-commerce has never exceeded 20% of retail spend in America. The vast, vast, vast majority of retail shopping in the United States is still people going in person and buying things. In the UK, it's similar. It's like 75-25. And it turns out actually that a lot of shopping is low intent. I'm going to the mall because I've got a wedding coming up, and I don't have anything to wear and I'm going to wander around and see what people have available because I don't actually know specifically what I want. And actually the value of stores is that that person who runs that shoe store has agency and taste, and she curates a selection of shoes. She has a level of customer service. She has a window display, which can show me the types of things she has. And I can wander around the mall and actually work out what it is I want to buy or be educated by it. And as it turns out, it's quite pleasant. There's a reason that the mall is a social thing. And so I think that agentic is going to be huge. Retail is a $7.5 trillion industry in the US though, so I don't think it's a winner takes all thing. What I think Live Commerce does is it's the first time that we've ever managed to bring together scale and convenience of the internet and also that same social cultural experience of physical shopping. Because at Twitch, we used to basically assume that if it's less than 1,000 people in a stream, it's non-economic because you're operating on CPMs. But you can go into a stream on Whatnot and see 30, 50 people in that stream. And you imagine for a moment that you're running a shoe store at a mall and you had 50 people in your store. You'd never close.
01:09:23 · Tom Verrilli, Lenny Rachitsky
You would literally never shut down the store because that's so much more foot traffic than you can ever imagine being in a store because commerce has totally different economics to entertainment, and CPMs aren't the thing that you have to worry about. So I think it's not really in competition with agentic. I think it's a completely different customer need. [01:09:45] S1: Amazing. There's room for everyone. I want to end maybe with a question about Twitter. So you were a Twitter. [01:09:51] S0: Yes, sir. [01:09:51] S1: A PM at Twitter working on growth. I feel like everybody that worked at Twitter as a PM was just scarred from the experience of Twitter. Everyone said, "Do not do things this way." What's something that stuck with you from that experience? What did you learn? What did you unlearn?
01:10:05 · Tom Verrilli
[01:10:05] S0: It is funny. I have said to a friend before that asking someone who was at Twitter in the 2015, '16 era is a little bit like a therapist asking somebody to tell them about their childhood. It's like you know the trauma that you're bringing up. For those who are not familiar with that lore, I think we had nine heads of product in the two years that I was there. It was that level of kind of chaos. I think my favorite quote was from someone on the partnerships team who said it felt like Kara Swisher lived in the air vents. That was how often drama was going on about the place. I think, Lenny, I probably took two overwhelming things away from my time at Twitter. And other than some incredible friends, and I will say that the product diaspora from that era of Twitter is pretty incredible and everywhere. The first one is if you truly find product market fit, if you manage to bottle lightning, doesn't matter how badly you screw up the organization of it. It's huge. And Twitter genuinely had that level of product market fit that you could emotionally feel how much people loved your product. And it's a really powerful litmus test to learn relatively early in your career that that's what PMF is. Not like, hey, the graphs look okay. There's a level of fervor that goes in. I think maybe on the flip side of less positive is what it definitely learned is most of the time you hear it's really complex, it isn't. Leadership's just weak. So the two years that I was there, everyone knew we were going to have to lift the 140 character limit. There was working group after working group. The project beyond 140 was everywhere. Because we knew, for example, that people in Japan Tweeted six times more often than people in Western markets. And it was largely when we spoke to them because Kanji lets you say heaps more in the same number of characters than a romance language did. We knew that was the inevitable end state, but there's obviously a bunch of work that was needed and trade-offs, and just no one wanted to make the call. And so there was just yet another design sprint, yet another cycle. And it was another year and a half after I left, I think it was maybe even almost two years after I left, before someone actually did it. And it turns out nobody died. The soul of the place didn't fall apart.
01:12:16 · Tom Verrilli, Lenny Rachitsky
I imagine the same discussion went on for editing Tweets, which took another two and a half years. Sometimes things aren't actually that complicated. It's just weak leadership. [01:12:26] S1: Yeah, it's funny how far it's come. Now you can write entire blog posts on Twitter. Articles is a big bet. On the product market fit piece, I think even more important there is the network effects of a Twitter, which you spend a lot of time thinking about building marketplaces. To me, watching Elon basically change everything, I forget who Tweeted this, but just everything changed. The brand, the name, the website. [01:12:47] S0: Number of people working there, everything. [01:12:48] S1: Yeah, the people, the team. What was the thing that stayed the same? And it was basically the network effects of Twitter. It's the place to be, so everyone's there. And that's hard to break. Even in spite of how much he tried to mess it all up, it's still kicking. [01:13:03] S0: That's it. If you bottle lightning, genuinely you can tell.
01:13:03 · Tom Verrilli, Lenny Rachitsky
[01:13:03] S0: That's it. If you bottle lightning, genuinely you can tell. [01:13:06] S1: Yeah. Okay. I'm going to take us to a recurring corner of the podcast, Fail Corner. Why I like doing this is because people see people like you coming on the podcast, have this illustrious career, everything's going great constantly, you're just killing it. And they don't see the things that don't work out and the times that you failed. And in their life, things often go wrong. So the question for you is just what's an example of a time in your career where things failed, something you built, some career move you made that didn't work out, and then what'd you learn from that experience?
01:13:40 · Tom Verrilli
[01:13:40] S0: Honestly, mate, and it's very nice of you to say nice things, but I feel like I fail more often than I succeed across the course of my career. Genuinely, to the blog you referenced right at the start, I published in the back of that the actual document we use internally to talk about how we build. And it starts with batting .500 is the goal. So you're hoping to be right as often as you're wrong. So there's probably just too many specific examples of times I've screwed up in my career, but there probably is a really common thread to it. And I think it's probably an easy trap for any PM to fall into, which is averages mean nothing to the individual is probably the thing that I've really scarred by. In any sizable population, it's really attractive to go and look at average utility or average adoption of something. And then you find that only 3% of people use something. And you're like, "Cool, we can probably get rid of that feature. It's not used widely." But if you don't go a layer deeper, and be like, actually it's only 3% of something, but there's a group of people for whom it's 100% of what they do. This is their core use case. And for expediency's sake, because somebody doesn't want to maintain a feature anymore, you're just going to deprecate it. And then it turns out you blow up the use case of that group of humans. And then to your last point about network effects, the ongoing spiral effect of that can be enormous. I think about it a lot in e-commerce of this is somebody's business. If we're just not reliable or we're deprecating a feature, it's kind of like a Westfield Mall just turning off the power in the lead up to Christmas without thinking about it. And so there are real downstream impacts to people's businesses that often come from just a lack of nuance in understanding metrics, particularly averages. They just lie to you all the time. And I think I've probably screwed up in all of the ways in my career, but most of the time I've made genuinely I'm disappointed in myself levels of decisions, it's typically that I've relied on averages without thinking about the individual use cases that are hidden underneath.