The Exchanges

Q What's like, uh, what's, what's like a context where you had said to someone, Hey, we go play the accordion or we're playing the accordion. Like, like what are they usually doing wrong?

A It tends to be that you're shipping something with in a very local sense without necessarily understanding, uh, impact. So, uh, an example right now is, you know, the core of most marketplaces is listings, right? Like if you try and think about amazon.com without listings, there's basically nothing there. It's a bunch of, you know, it's a left rail or right rail and some videos. Um, in video commerce and live commerce, whatnot, you don't really historically need listings. If I want to sell you a pair of AirPods, I could literally hold them up to screen and show you them and describe them and say, they're AirPods. I'm going to start them at a dollar. And as a buyer, you now have all the information you need in order to kind of like make a purchase decision, which is great. And so you may not have to invest in making listings the way that someone else does. And that's probably net good for a seller because It takes like three and a half minutes to make a listing. Uh, and it takes zero minutes to describe a thing and hold it up. Uh, but you then zoom out and say, oh shit, new buyers are going to come to live commerce and expect search to function. If I don't know what you're selling until after you've sold it, there's no possible way that I can put somebody in the right stream for ear pods because they didn't, we didn't know you have them and I therefore can't direct people to it.…

AI assessment note: “It tends to be that you're shipping something with in a very local sense”

Q scales, engineers having to be in alignment meetings, having to write docs, aligning everyone, uh, taking notes, you know, all these like kind of minutia part of PM. And also just the big, like they also want to, you know, engineers want to build engineers, want to code designers, want to design. How do you think about that element of they may not actually want to be doing that work?

A I think this is where like specialization works both ways, right? It is useful to have folks who are well honed in making decisions. It's totally reasonable as well for someone to say, listen, uh, I'm an infrastructure lead and I want to think a lot about scale and I do not want to have to spend my time debating, you know, alignment or getting those minutiae right. And certain skill sets don't necessarily translate super well, right? If you're really good at building big mental models in your head of how infrastructure should scale, you may not have the skill set of listening to a customer and actually understanding the core problem as opposed to the thing that they said, which again, just a thing that we've built over time. So, uh, my supposition of we regret isn't to say that we don't want product managers. We recognize in those situations that you do need to kind of help other functions specialize, but I think it's We, we articulated that way to kind of force ourselves to remember that you don't hire a PM just for the sake of hiring one. You hire one where there's really specific need. And I think what goes with it, Lenny, is like, you have to build the culture of the organization around that. So for example, when we say we, you know, we regret product management exists, every time we write documents about how we ship or what we're doing, we're very kind of clear that anyone…

AI assessment note: “We recognize in those situations that you do need to kind of help other functions specialize”

Q Um, so there's a few things here I want to talk about. One is just, what is it you look for in the folks that you hire, especially these days? What do you find? What's kind of like trending up in what you find you need in really successful PMs and whatnot. And what's maybe trending down.

A I can tell you what's definitely trending down. It's, uh, folks who spend a lot of the time in their interviews talking about those like alignment meetings and driving alignment and stakeholder management and, and those pieces, because, uh, There's definitely a group of PMs and I certainly used to be one of them earlier in my career whose specialty wasn't technical or customer oriented. It was politics. And so folks who tend to kind of like naturally lean towards like driving alignment, building, building relationships, you know, tell me about a time when you failed and you're like, oh, I didn't keep the CEO up to date with something. And that led to a pivot is definitely kind of a thing that is a bit of an anti pattern that trends down. What we tend to find kind of really jumps in a PM kind of interview is over the course of, of your interviews or your case study, can we see both the macro thinking and the micro thinking? I think the system works something like this and I can describe an end state, but can I You know, almost exude impatience on like, and here's how I would validate that very quickly. Here's where I would push to get that done. And are you specific about the things that you've built?

AI assessment note: “I can tell you what's definitely trending down... What we tend to find kind of really jumps”

Q a little bit, being a little more engineer, engineers are taking on more of the PM work. How do you I think this just kind of maybe plays out over the next couple of years in terms of what product teams look like broadly. Is it still PM engineers, a designer data scientist somewhere? Is there, how do you kind of envision the canonical product team over the coming years?

A Great question. Uh, and I don't know that I know what it looks like everywhere. I think what it'll look like at whatnot is it probably still looks mostly like it has historically, which is, you know, there are reasons that you would have a specialist designer, specialist engineers, specialist product management. I think those kind of very concrete teams will largely be reserved for like very specific projects or like things that we have high confidence or conviction that we need to solve, or we're pretty high confidence conviction that we have a path forward on a scene and we want to make good progress. And I think at the edges around that, there's going to be a lot more free space for people to play on like, Hey, I'm reasonably sure I can go and make a meaningful improvement to this thing. And it doesn't matter if you are A designer, an engineer, a product manager, a data scientist, you can, and you should, right? If you're sitting there on a Friday afternoon and you can't focus on the period you're writing, but you're pretty sure you can go and fix something, go for it. Um, and so I think it probably doesn't morph In the more formal sense, but I do think there's just a lot more free space for people who are well versed in the customer problems, well versed in the code base and understand some of that macro context. We'll just be empowered to do more and more things.

AI assessment note: “it probably still looks mostly like it has historically”

Q Favorite product that you have recently discovered that you really like?

A Uh, this is a very deep cut. So I will apologize to most listeners. Um, uh, Hopefully you've detected the accent. I'm told constantly that my Australian accent is going, but one of the things that I love is every time I go home, I realize actually a bunch of the government services apps in Australia have become phenomenal. You ever had that kind of concept where you're like, I wish the government has all my data. I wish there was just like one place where I could with one click get my driver's license renewed. I could like transfer titles and do all of the admin that slows you down in life services, New South Wales actually nailed bizarre to me that I would ever come on a podcast and say, Actually a government run app in Australia of all places is it, but I was home recently and had to do all of my life admin and it's incredible.

AI assessment note: “services, New South Wales actually nailed”

Q What are the other motivations to do this? Is it just the product ends up being better? Is it fewer people?

A Uh, I certainly think the product ends up being better. One of the things that folks have been telling us for a long time is, yeah, that won't scale. Like, oh, leadership isn't going to be able to stay hands on with what's going on. You're going to need to go and hire tons more layers. And what we found is that's actually not true, right? It requires a different muscle. You have to make an effort to make sure you genuinely understand, you know, like a ground truth. An example we use all the time is we'll be talking in a growth meeting and someone will say, oh yeah, but that was fraud. You know, turn around and be like, how do you know that was fraud? Oh, it's labeled in the dataset as fraud.

AI assessment note: “I certainly think the product ends up being better.”