In short
Lenny's Podcast Episode Summary
Episode Title Lessons from Scaling Uber and Opendoor | Brian Tolkin (Head of Product at Opendoor, ex-Uber)
Guest Brian Tolkin - Head of Product at Opendoor, former early employee at Uber.
Key Topics Discussed
- Product and Operations Synergy
- Importance of integrating product and operations for efficiency.
- Lessons from scaling Uber and Opendoor with strong operational components.
- Running Effective Product Reviews
- Strategies for conducting product reviews that enhance product development.
- Emphasizing accountability and collaborative improvement.
- Decision Making with Limited Data
- Approaches to making informed decisions when data is scarce.
- Using intuition and creativity alongside data.
- Jobs-to-be-Done Framework
- Application of the framework at Opendoor.
- Understanding customer needs and contexts in product development.
- Leadership Under Pressure
- Maintaining calm and clarity in high-pressure situations.
- How stress affects team dynamics and performance.
- Challenges and Adaptations
- Stories from Uber's expansion, including launch challenges and operational shifts.
- Opendoor's adaptation during the COVID-19 pandemic.
- Strategic Partnerships
- Insights into Opendoor's partnership with Zillow.
- Navigating competitive and collaborative industry dynamics.
Insights and Anecdotes
- Starting at Uber: Brian transitioned from operations to product management, contributing to UberPool's global launch.
- Surge Pricing Origins: Originally a manual system controlled by local teams, emphasizing local knowledge.
- UberPool in China: Faced technical hurdles, highlighting the importance of adaptability under pressure.
- Opendoor's COVID Response: Innovated to virtualize home buying/selling processes amidst the pandemic.
Key Takeaways
- Mutual Respect in Teams: Effective collaboration between product and operations requires mutual respect and understanding of each team's contributions.
- Product Review Goals: Balance informing stakeholders and collaboratively improving the product to avoid a "firing squad" atmosphere.
- Experimentation in Low-Volume Contexts: Use creative alternatives to A/B testing when sample sizes are low, such as qualitative insights and intuition.
- Staying Calm as a Leader: Reflect stress away from teams to maintain productivity and morale.
Recommended Resources
- Books:
- "Shoe Dog" by Phil Knight
- "Black Swan" by Nassim Nicholas Taleb
- "The Design of Everyday Things" by Don Norman
- "Shantaram" by Gregory David Roberts
- Tools and Products:
- Fi Collar for dog tracking
- Particle for news aggregation
Contact Information
- Brian Tolkin: [Twitter](https://x.com/briantolkin), [LinkedIn](https://www.linkedin.com/in/briantolkin/)
- Lenny Rachitsky: [Newsletter](https://www.lennysnewsletter.com), [Twitter](https://twitter.com/lennysan), [LinkedIn](https://www.linkedin.com/in/lennyrachitsky/)
Sponsorships
- Pendo: Product experience platform.
- Explo: Embedded analytics solution.
- Attio: Flexible CRM for startups.
Conclusion Brian Tolkin shares invaluable lessons from his experience at Uber and Opendoor, offering insights into product management, operational excellence, and leadership under pressure. This episode provides practical advice for building and scaling successful tech-driven businesses.
Written by AI. May contain mistakes. Listen to the episode to check what was said.
Transcript
Automatic transcript. May contain errors.0:00You've worked at two businesses that have done incredibly well, combining product and ops. Uber always have this mentality and open door does two of the product aberrations, twin turbine jet plane, where you can like fly the plane on one engine for a little bit if you need to, but it's operating most efficiently and effectively if both are working together. What has having been an ops done to make you a better product leader? Given really deep understanding of how the business actually works is a pretty good foundation for them going on to say, okay, what do we actually want to build in a more scalable technology?
0:31Something else I've heard that you're very good at is staying very calm under pressure. I've slapped on my floor in China before launching UberTool, and like when you reflect the stress onto your teams, everybody taxes them. It counterintuitively doesn't produce better outcomes.
0:50Today, my guest is Brian Tolkien. Brian is currently head of product and design at Open Door, Before that he spent nearly 5 years at Uber where he joined as employee 100 before Uber had Uber X or Uber Pool or any kind of shared rides. He actually started on the ops team at Uber, moved into product, ended up leading product and launch of Uber Pool and then taking it global. He also started the product operations function at Uber before that function was really even a thing which I didn't know until the chat that we had. In our conversation Brian shares a ton of lessons about building products with a heavy operational component.
1:27Also had to run great product reviews, how he implements the jobs to be done framework at Open Door successfully, the story behind Zillow trying to compete with Open Door, failing and then partnering instead, plus a ton of great stories from the early days of Uber in Open Door, and so much more. If you enjoy this podcast, don't forget to subscribe and follow it in your favorite podcasting app or YouTube. It's the best way to avoid missing future episodes, and it helps the podcast tremendously. With that, I bring you Brian Tolkien.
1:57Brian, thank you so much for being here. Welcome to the podcast. Thank you. Appreciate it. Thanks for having me. First of all, just a huge thank you to Kavon Bake 4 for connecting us, introducing us. He said all kinds of amazingly nice things about you. He also gave me some very hard questions to ask you. I hope you've come prepared. Terrific. Put me in the hot seat. Okay. I want to spend a bunch of time talking about product and ops. You started your career in operations at Uber. You actually started on the ops team and you moved into product. You've also worked at both Uber and at Open Door, which have both huge operational components.
2:29I think it's really rare that people one, T, a company scale to the heights of Uber and Open Door with such a heavy operational component that are still tech companies. Also, it's really where someone starts and often then moves into product and ends up where you are, where your G -product officer is a really successful company. So, I have a bunch of questions here. Maybe the first is just what has, having been an ops done to make you a better product leader. How does that change the way you operate as a product leader? Starting on the operations side, give a really deep understanding of like, how the business actually works.
3:04You are truly operating it day in and day out, and the success of the city is, you know, in large part driven by the inputs that you are putting into it every single day on the ground and whether or not those raid net weekend, which was a nice driver of metrics, but talking to customers every single day, like one -on -one onboarding drivers, responding to support tickets, there was no centralized support team, there was no closer to the customer. And so I think that foundation actually for really understanding what moves the business and being super close to the customer. Actually, it's a pretty good foundation for them going on to say, okay, what do we actually want to build in a more scalable technology way.
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5:57Once you're ready, simply embed the dashboard or report into your application with a tiny code snippet. The best part? Your end users can use Explos AI features for their own report and dashboard generation, eliminating customer data requests for your support team. Build and embed a fully white labeled analytics experience in days. Try it for free at explos .co slash leni. That's expl o dot CO slash Lenny. I've seen that a lot of companies and this was definitely true to Airbnb where the product team kind of looks down a little bit on the ops team where they're like, oh, we're gonna We're doing things that are gonna scale to millions of users.
6:36We're doing these things that are gonna play it everyone There's this like ops team over there doing a few things that are gonna Not scale. There's keep asking us for things to build for their one -off ideas What do you think that product teams often maybe miss or don't understand about the ops teams that would help them see them in a different light? Yeah, it's a great question. And I think Uber always have this mentality and open door to us too of kind of like a twin turbine jet plane where you can like fly the plane on one engine for a little bit if you need to, but it's operating most efficiently and effectively if both are working together.
7:13And I think that's really true, right? The reality is, operations teams, local teams can iterate faster, can scale talking to customers really much more efficiently, have great qualitative insights. And so if it's seen more as like a harmony instead of a competition, I think that's really, really helpful. where it's like, okay, how do we get the insights that are happening day in and day out in the field on the ground, whatever that may be, and help us build better products because of that, right? Like a PM sitting in San Francisco can't be in open George case, 50 markets, walking houses every single day in Uber's case, you know, whatever 1000 cities, understanding the nuances of safety in South America, right?
8:04It's just like not possible. But what you can do is foster a really good relationship and a really good feedback loop of how people who do deeply understand those things can help give insights. Now it's actually the birth of product operations was sort of that insight as well. Can you say more on that? Yeah, sure. So I should probably define what product operations was at Uber. It was basically this notion that we had centralized. This was later in my career at Uber. but we had a centralized product team building stuff mostly in San Francisco, not strictly true to the roster, but at this point around the world, but mostly in San Francisco.
8:44And then we had a very globally distributed operations team. And there was sort of a bidirectional feedback loop that wasn't super strong in that feedback loop was basically when the EPD teams in San Francisco built new features, how do we effectively put it in global markets, And then how do we effectively get input from global markets to better build features? And so one solution to that problem, our solution at the time, was to start up a new function called product operations, who had accountability and reported into operations, but physically fat with and operated much like a member of the product team to help solve that.
9:23Is that maybe the first time there's a, like, did you invent product operations as a function? I don't think so because at the time, I believe Google had a function. I can't remember what Google called it. It was something slightly different, but I met with a few folks who had been in similar type roles at Google in a couple of other places. So I don't take credit for certainly for inventing it. And other people have sort of actually dabbled in this model at Uber before me. There was just a formalization of it and their actual building of the organization. That sounds like you basically help make it a thing.
9:57You know, you don't want to, you're being very modest, I think. Coming back to your point about decentralized operations team, something I've read is that search pricing came out of one GM and a market just testing, emailing all the drivers. Hey, we're going to give you extra if you drive on Saturday night. Is that true? That would have been probably a little bit before my time. But that being said, one thing that is true is that search pricing for, for actually quite sometimes, probably all of 2012, certainly 2013, probably, I don't know, when we necessarily switched, was very much a human in the loop system or a very manual system where GMs in every city would control basically the parameters in which surge would operate.
10:44And so much of the time that would need, for example, like on the eighth and Friday, there would be no surge. It couldn't flip on, and then Friday nights, and Saturday nights, it would flip on from whatever you said. 7 PM to 3 AM, and the cap was, you know, X whatever the cap was. And then within those parameters, the algorithm would optimize for what the price was. But yeah, GM's controlled whether it was on or off and what geographies were searching. Wow. I didn't know that. Was that out of, we believe we are better than the algorithms or we just don't have time to make them amazing yet. So we're just going to help them.
11:25I think it was probably a function of a bunch of stuff. One of which is like, hey, this is a fairly new concept and it's powerful and dangerous. And so let's like make sure we understand what's happening. The second is kind of this belief that yeah, local city teams know their cities best. And so you might know that an event is happening a baseball game gets out, right? And it's like, oh, I know that this baseball game is going to get out at 10 p .m. So I'm going to set surge at 9 .45, right? And the algorithm may not be, may not be able to pick that up. And then the third is, yeah, the technical constraint of like nowadays, clearly it's all automated.
12:06But it's, it's really hard to build a fully dynamic always on geospatially aware, pricing system and that's just a little bit of time. That makes sense. I feel like you're full of wild stories from your time at Uber. Is there one that comes to mind of just I think you like help scale in China, Uber pool? Yeah. Maybe that's one. I don't know what can you share a wild story from early Uber days? Yeah. So in the early days of Uber one, one kind of fun story is obviously Uber Axis is a and mainstream product, but has a kind of funny silly name. UberX, this product in the early days, was going to be all hybrid and had a bunch of different potential names.
12:54I was not personally attracted to this. This was someone else on the operations team, but they don't model for what this product could be. And there's no name for it yet. So those going to be a placeholder. So what do you plan as a placeholder? X. So UberX, and then the company was moving quickly enough. The product got green light and launched. And here we are, I don't know, 12 years later, 11 years later, whatever it is. And UberX is the name that stocks. That is hilarious. I love it. So it was a placeholder. It's like many products start that way where they're like, this is just the temporary name.
13:28And I'm like, oh, yeah, I guess everyone just knows it. This way now we're gonna stick with it. too expensive to change in rebrand at this point. That's an awesome story. One that is good about scaling Uber, or we're pool in China is, yes, so we were launching Uber pool in China, and this was going to be China. At the time was pretty big for Uber, but Uber pool was not there yet. And so we're gonna launch, and myself and a few other folks were in Chengdu, China, which is the first Chinese market that we're launching a little pool in. And we're going to be on the ground to launch. We wanted to go live at a believe it was 6am for rush hour on Monday morning.
14:14And so we're there over the weekend, getting ready to set up. And at the same time, we were doing some data center testing. And so we flipped on all the testing infrastructure and thought it was going to work, and nothing works. And the matching algorithm just isn't working and working. Oh my god, now it's, you know, whatever. 5 p .m. the day before we're supposed to go live, 6 p .m. 7 p .m. Okay, let's get on the front of the US, try and figure out what's going on. I remember I slept at a 30 minutes that night between 2 and 3 a .m. They were like, okay, we like, we have to go live at 6 a .m. I think there was some press around it.
14:53We were planning on going live. And I think we got everything finally working. It probably about 5, 30 or 6 in the morning and once just in the nick of time and I'll never forget it was we launched. It was great. We monitored everything was good. And then we walked out for breakfast at like 7, 30 in the morning. Everyone sleeped to Brad. No, no, on slept on late. And we got this. These like pancake street food things. And I have to imagine they were not that good. but in my mind, it's like the best meal I've ever had in my life. So, it's like a meal after a marathon or a... Yeah, exactly. Exactly.
15:31Yeah, exactly. So delicious. This comes up a lot of just like these moments that are so incredibly stressful and hard and leap deprived and of being like the best memories and the best stories to tell and things you look back at fondly. It's so weird how human nature is like that. Yeah, I mean, another one more more recent for open door was we... When COVID hit, right, we like physically, we bought in fell homes and so we were physically going into people's homes and you know, suddenly March 2020, like going into people's homes was not, that's something you were people were comfortable with. And you look at the real estate data coming out of China at the time and it looked like sort of coming to a standstill and so we actually turned off the core business and we stopped buying homes for a few months.
16:21Hey, we can't go in and we don't know if anyone's going to be buying any homes. And so what do we do? And we took those few months that came out the other side and had virtualized the whole process. And that was pretty stressful, right? Because you're looking at a business that relies on going into people's homes and suddenly you can't do that anymore. What do you do? So again, a fond memory to look back on a very stressful time in the moment where it feels very, very discol. Just since you mentioned OpenDore, I think many people have heard of OpenDore, maybe just give a quick explanation of what OpenDore does for people that aren't exactly sure.
16:58So we're a digital platform to buy and sell real estate. The core product today is a seller -focused product where people can go online, enter some information about their home, and we'll make an all -cash offer to be able to sell sort of simplicity and certainty. And, yes, so the product really works for people who have a want something that is certain and simple and easy. I don't know if you've ever sold the home, but it can be a very, very successful, difficult process with showing and open houses and how to price it. And will it sell and all of that stuff? And so we offer basically a way to skip the whole process.
17:41So you basically sell your house to open door and it's just like cool done move on that side of your own you picked your closing day you move out when you want Yeah, there's no no hassle Sounds sounds amazing. I want that Coming back to ops and product just to kind of close this thread Again, you've worked at two businesses that have done incredibly well combining product and ops are there any just broad lessons and as you've taken away from how to make these two teams and functions work well together and to build a business that's very ops heavy, but also offer driven. Yeah, the first one we touched on, which is, hey, there's just gotta be neutral respect, right?
18:20Both functions have their time and their place and their skill sets and you just don't build big, big, build big businesses of this type without respecting the type that both me to exist. The second, particularly on the product and engineering side, is really understanding where and how the technology leverage comes from the business, and then being really focused on making sure generally, especially in your earlier days, you are more limited on the technical resources inside than you might be on the operational resource inside. And so how do you be really focused on where to invest your time, effort, and energy technically, which is why most of the engineering effort for Uber was on the dispatching system in the pricing system.
19:06That's just where the leverage was at the time given the scarcity of resources. And so I think the second one is being really intentional about where those technologies are, and then being really forthcoming and saying, hey, that means all these other places where yes, it can make things easier, more efficient, excited, and excited. and we are okay not investing in right now and that needs to be an explicit decision and very transparent. And then the last bit I would say is a deep understanding that the real world has entropy and it's hard and it's messy. For us, we at Open Door, we go into homes.
19:47Someone may not be homes, scheduling may be off at Uber driver may cancel the radio low GPS. All these things happen, right? computers are deterministic, but humans aren't. And so building products that have a little bit more flex or a little bit more fail safes in case those things happen, becomes a little bit more of a paramount. One last thing I would say is I think that the companies evolve as well. So when I talked about it at the beginning of Uber, being very focused from an end sharing and product side on the dispatching system, the pricing system, obviously over time, not to evolve, now there's essentialized all of these functions as the company got bigger and more mature and scale and optimization started to be more important and expansion and sort of that petri dish of trying new stuff and the tools got better and the tech ideas are and there's more internal infrastructure and so over time things can start one way and shift over time as the business needs.
20:51It's actually spend more time there you keep saying things that I want to make me want to dig deeper. So at Airbnb, we went through the same thing where there was all these local ops teams, driving supply, finding homes, bringing down the platform. And then there's like this tipping point where the product and organic growth or where to mouth ended up driving more and then orders and magnitude more. So there's no need for these folks to spend time doing these sort of things. He just maybe shares an example either who we're open to or when you talk about like there's a time in a place in a skill set for ops, how that evolved, like what was the team doing initially and then what did they end up doing as things grew?
21:25Yeah, I mean, maybe a very easy good example to pick just one part of the Uber process in the early days is at small scale, actually back when there were black drivers, every driver was individually onboarded in like a 90 minute to a two hour in person in the office onboarding with deep setting of expectations. the next version of that, so that's obviously very obstrimin. The next version of that is kind of like a small classroom type setting of three or five or six drivers at a given time, also very obstrimin. And then as we got into more mass market products like Uber Taxi or Uber X, those like, okay, maybe 20 or 30 at a time, okay, so now it's a little bit bigger classroom setting and we said, okay, let's make a video.
22:18So instead of giving verbally the same presentations, let's just make an onboarding video and that was the next set of scale. But now suddenly we have a different problem, which is, okay, you have to validate all of these credentials. So most drivers license, even who they are, all the stuff. At one person, easy, at three to four out of time, easy. 10 at a time, a little more challenging, but fine. At 20 at a time, okay, if you're starting to run up onto it, And now at Fast Forward six months and you're doing a thousand a week or whatever, okay, suddenly your system breaks and it's like, okay, we have reached the point where like operational system improvements is like no longer viable.
22:59So you say, okay, what are they like that? We've gone from the iteration stage to the scale stage and technologies is uniquely good at scaling. Sometimes they say, okay, instead of having a bunch of folks around the world taking pictures of driver's licenses and validating and doing all that stuff, how do we integrate with some type of CR technology or on a recognition of driver's licenses, that feeds to a system that knows what a driver's license is, we can do automatic validation, and suddenly you've done two things, one, you've scaled your system, and two, you've just created a ton of time for that the time was probably dozens, if not hundreds of people running these onboarding sessions all over the country, the world at the time, to do other stuff.
23:40And so now you can sort of level that up and say, okay, do we do more analytics? Do we do more? Figure out the next process that needs optimization or whatever the case may be, and that virtual cycle just continues. The way I like to think about this is do things that don't scale and then scale the things that you're doing. That's the way it's always come back to. Exactly. This reminds me of a hot take that previous podcast guest shared in a newsletter post, Casey Winners, he talked about that operations is usually, and this is kind of, it's a hot take. The operations is a sign of inefficiency, and over time your job is to kind of squeeze that away and make it product software as much as possible.
24:20Doesn't mean you always get their thoughts. Yeah, I actually don't fundamentally, it depends on what the operations is, but I don't fundamentally disagree, but I think the right lens to think about it is. And then those folks can move on to the next challenge. Right. And so there's always another hill to climb. Right. And so I think that was one of the things at Uber and Open Door where there's sort of this culture on the ground experimentation. That's really helpful. Yeah. Like we were just trying to drive our onboarding. We may now be solved with technology. yesterday a few extra hours a day, like how do we get better at optimizing the Ubrax system?
25:03How do you start tinkering with food delivery? How do you start, you know, thinking about higher capacity vehicles? How do you think about better feedback for those manual surge pricing sort of talk about what we talked about, right? So I generally agree. It just generates reason of more progress. It feels like a big part of this is making sure the operations teams understand there's more opportunity even if this ends up being automated, your job is not going to go away. We're going to find something new to try and experiment and do you think they don't skip? Awesome. Okay. Going in a completely different direction.
25:38I hear you're very good at product reviews. Okay. A few people told me this. I'm curious how you set up a product review and any things you've learned, any tips for how to run an effective product review. That's very kind of whoever mentioned that. But yes, big fan of doing them, actually in particular to maybe bridge the conversations in companies that have upstriven cadences because or start out very upstriven because the cadences can sometimes be different. And so the operational cadences that you might have something like a WBR or a weekly business review may not be conducive to always picking your head up and saying like, Okay, where's the product going on a slightly longer time frame?
Read the full transcript
26:20And so I think product reviews in general for all companies are probably really helpful, but actually in particular for some of the product and operations led companies in terms of things of learning, I think being really intentional about what the goals are. I think it's okay to say that there are two goals, a goal of sort of like accountability and inform to an audience, but also most importantly, I think this is the primary, goal is to help make the product better, right? To help the teams think through a problem and to have that again back to our earliest conversation be a very intellectual conversation about the work and how to make the product better and not super scary.
27:03Like product reviews hopefully are not feeling like firing squads. That's a scary environment to be in and not necessarily one that's conducive to how to make the product better. Obviously sometimes the conversations have to get a little in times, but in general, that's what we're shooting for is something that helps the team go back and think through how to make the product down here. So the two goals you try to communicate for your product reviews, accountability, slash informing people what's happening, but also just like we are here to make the product better and setting that context. Is there anything you'd do specifically to make it not feel like a firing squad like you're coming in here to be attacked and criticized?
27:39You've set context at the beginning of the meeting. Is it just a part of the culture? Yeah, I think definitely part of the culture, but also I'm a firm believer in general that the people closest to the problems also have the best context to solve that problem. And so as a more senior voice in the room, often the job is probing asking questions throwing out ideas in a way that says, hey, this is an idea. This is not a mandate, right? This is a thought, right? And if there's context missing, that would inform the product direction and providing that context in not a question asking sense, but hey, this is context that you might not be aware of.
28:22And so I think it's all in how you show up as a leader and what that looks like in terms of probing and pushing the team on dimensions or being made. That they may not be thinking about and then understanding that the team is bringing in perspective that you don't have, which is they think about this problem 40, 50, 60 hours a week, and you might think about this problem three hours a week, right? So you bring them a breath, the team brings the depth and honey marry them. I don't know if you heard Darmesh Shah's episode or his thing on flash tags. Have you seen this? I have not. No. Okay. He has a whole system.
28:57So you talked about how as a leader, you want people to not take everything you tell them as feedback as I need to do this. So he has a whole set of hashtags that communicate how important this is to him from hashtag FYI to, uh, to suggestion to, uh, plea. Yes. I pleaded you. This was actually explaining to me. I don't, I don't think I've seen the original source. Uh, so I'll go back and, and watch it. But this was explained to me as this. I'm actually big fan. I think that's, I think that's great. Yeah. I just said, get everyone on the same page. Okay, maybe one last question here. Who do you try to invite to product reviews?
29:32Do you have any frameworks and ways of thinking of who to invite, who not to invite? Yeah, good question. We, I would say, have oscillated over time, but in general, big subscribers of the best conversations happen when they're relatively small, so try and keep it under 10. Could be wide distribution of the document, right? The artifacts created are actually really powerful, and they're powerful for the whole team to understand and to secret power is they're very powerful for new people who are onboarding. So we've got here the last 20 product reviews. You've got a pretty good idea of what's going on, right?
30:10But generally the conversation itself trend to be relative. I'm trying to give you the number 10. And these are effects, you mean the recordings of the meeting that people can watch? Yeah, or just the document. To vent on what the company culture is, whether you want to record it or just have the document. How to eat either way. And then is there some kind of specific cadence you operate on? Is it like a weekly product review that people can sign up for? Does everything have, how do you like to set those up the cadence? Yeah, obviously it's geels are with the size of the company for us right now.
30:38What's working well is our, yeah, sign up cadence. We have two slots a week that anyone can can turn up or as their product area needs it. And then if there's something that we'd love to see that we haven't seen that we do a a lot of them are all endowing to make sure that the work is generally second cycling through on a quarterly basis. This episode is brought to you by Attio, a radically new type of CRM. There's a world where your CRM is powerful, easily configured and deeply intuitive. Attio makes that a reality. Attio is built specifically for the next era of companies. It syncs with your data sources, easily configures to their unique structures and works for any go -to -market motion from self -serve to sales -led.
31:24Atio automatically enriches your contacts, sinks your email encounter, gives you powerful reports, and lets you quickly build zap your style automations. The next era of companies deserves more than an inflexible, one -size -fits -all CRM. Join modal, replicate 11 labs and more, and scale your startup to the next level. head to atio .com slash Lenny. And you'll get 15 % off your first year. That's atiti .com slash Lenny. A Jason topic. I hear you're a big fan of jobs to be done, which is okay. So it's a fun recurring topic on this podcast. We've had many people that love it. And many people that hate it, I love seeing both sides of it.
32:07I love that you find it helpful and you implement it at OpenDore. I'd love to hear just how you actually apply it. it opened to our what you've learned about how to apply jobs to be done effectively. Yeah. I think like all frameworks, um, the right answer is to to pick your standard frameworks, have more tools in your toolbox and then actually understand when and and how to apply them. So we try to avoid, um, be being a hammer and everything's a nail. Uh, we try to, you know, for course, the framework, if it's not working, but I think what we, what I really like about it is, It forces you to put yourself in the customer shoes, I think in a slightly deeper way, and be a little bit more empathetic.
32:47When I think about building that open door versus a building at Uber or when you're building at Airbnb, is we are not most people at open door, are not homes to sell every week, or every month, nor do we buy homes every week, or every month, right? This is the average in the US is something people do want to be saying. And years, I'm sure the average had opened or something similar. And so it's a little bit harder to be a customer. I took Uber every day. You probably used every and be a number of times a year. And so in some senses for some of those companies, you can build for yourself. You would intuit the job to be done because you're just doing it for yourself.
33:32We don't necessarily have that context. And so a framework that forces us to be really thoughtful and intentional about how a customer might perceive or product is really helpful. The other thing that I like about it is sort of the canonical version of it encourages you to think about the context in which the user is operating or the other things outside of your product that they might be going through. And in our case, combing or selling journey often is there? certainly multi -week, if not multi -month or multi -quarter journey with a lot of complexity and a lot of conversations outside of our product.
34:13You may be talking to an agent, you may be talking to a friend, you may be driving around the city, trying to find a house, and the framework is very flexible and encouraging of saying what is actually the job to be done of this user when they're thinking about our product and what is the context in which they're operating. I love to go one level deeper to talk about how you actually implemented. Do you have like templates of like, you have a startup project. There's like, as a blank, I blank, blank, blank. How do you? So we do have, I would say we're medium, rigorous on sort of template standardization or adherence.
34:47So we do have a template, the standard product review template talks about jobs to be done and sort of has a section for like, what is the problem statement and what are the jobs to be done? And this is a doc that when you're coming to a product review, the person running it and coming is like filling out this document. Correct. Prefilling it up. I'm pretty filling it out. And again, I think we are not sticklers about always using that template. But I think the beauty of the template is yes, it sets expectations of what you expect, but it's also just easier often for people to work off something.
35:23And so yeah, it's part of our product review template and then part of our planning process as well. Because we've used it for a while, I think there's been an internalization of the culture where people also just start commenting about it or writing about it and say, hey, what is the job to be done here? What if the user trying to do it, which is another colloquial phrase in it? So, yeah, I think there's a cultural seeding that has had to do with it. For memory, just like, what is in this template? So, like, what's the phrasing that you try to use for setting up a problem? Yeah, yeah, I mean this specific framing I would have to go remind myself on the grid itself, but generally it looks like you know context problem potential solution risks risk slash premortal and measurement of success and then we also try to sort of bucket or product reviews by stage so you could be in Asian stage, which might look very different than the very end of the process.
36:27Like, hey, we're getting ready to ship, speak now for our whole to piece. Those two artifacts, well, well, so. Okay, so it's not like I, as a blank, like the standard jobs to be done language, it's not exactly how you implemented it. It's more just make sure we're thinking of it. What is the problem for the customer? What is the context of the problem? Correct. Yeah, yeah. We're not, we're not living art. Okay, awesome. Any other tips or lessons about just working well with this concept of jobs to be done? Maybe like when you come into open door and like, hey, everyone, we're going to be thinking this way.
37:01Is there anything there that would be useful to people if they're trying to operate this way? Recognizing that correctly implementing a framework, any framework, but times to be done in particular, we can talk about, takes a little bit of time and getting you Sue and understanding. And so I don't think you can just like, okay, we're gonna make the template, and then that makes the content better. That just takes people's content and they wedge it into the template. It's actually the cultural internalization of like, hey, this might be phrased as the job to be done, but is this actually the job to be done?
37:34Like let's talk about why the customer might be in that situation or not be in that situation. Or I think the job to be done might actually be something else. You might say, hey, the job to be done is, you know, maybe an early day version will be like, the job to be done is to get an offer from OpenDorm. It's like kind of, but like the broader job to be done might be like, price discovery for the customer, right? And so you can have a rich conversation where it's like, well, one might be like, a little bit influenced by our business goals, right? And I don't think you just write around and people are like, yeah, I'm gonna sell my house, my job, my goal is to get an offer from OpenDorm.
38:12And it's like, well, like, you know, and so that's like, okay, the template might be the same, but like, it's actually the content that takes a little bit of culture and stanchation. Got it. And it sounds like people talk from what is the job to be done? That feels like a core part of the way you think about it. What is the job to be done? Yeah. Just that language alone feels very, very powerful. Is there a resource or a book that you point people to to help your team learn about the way job to be done work? Is there like one kind of thing you find useful? Not about jobs to be done. And we have, I point people, I do a lot more printing people towards like internal examples of where I saw other games maybe do this well or blogs and stuff, but your blog is at common more than you pass around.
38:52Not about job city, but just about many topics. So I'm flattered. Thank you. Yes. I really appreciate that. I was also thinking as you were talking, your friends with Kavon and job city, be done at Twitter was quite the journey for them. Yeah. Traumatic for a lot of people, I think it went very far to the extreme of the, yeah, I think they're more dramatic about it. Very dramatic. And so I guess it's a lesson here. Don't maybe don't take it that far. Yeah, and I think it probably, and I don't know if K -Von wrote a degree that I'd mentioned. He would, the generalized version of like, you pick the right framework for the right job.
39:28And if you say, there's one framework to rule them all and this is the only framework that works and we enforce every problem into it, then we jump. The way I think about jobs to be done is exactly the way you're describing it, where it's just think from the lens of the job to be done for customers this. So for my newsletter, like, what is the job to be done at my newsletter? It's to help you become better at your job as a product person, building product. And that actually ends up being really helpful. And it feels like that's kind of the way you guys think about it. I don't know. Absolutely.
39:57And you're crushing it, Natalie. Thank you. Sorry you. You talked about, I'm going to go into another question to deflect your compliment. And you mentioned that Uber, there's a million transactions happening every second. It's massive scale. Open door is completely different. You have like very few, very large transactions. Yeah. I'm curious how you do experiments if you do experiments. You do A, B tests. What have you learned about just how to think through low sample sizes plus A, B testing? Yeah. Very hot topic of conversation. We do AB test. It is obviously that we'll cold standard until we do as much as we can.
40:41Of AB testing, there are parts of our funnel and flow that have more volume than others. So top of all, testing method easier than down funnel. A .B. testing, surely product or tech features easier than A .B. testing process these operational processes, but you're totally right. We are not doing hundreds of millions of transactions a year and so experimentation can be more challenging and so I think one way to think about it is A, knowledge lives the problem. Right. It was just to say, don'ts. And we've made this mistake many, many times, but don't just force yourself into A .V. testing without running the power analysis and say, like, hey, are we going to get results?
41:32What is the size that will detect? And what is the runtime of that experiment? And is that, and be honest, like, is that acceptable? For there are certain, so a second once in years, there's certain experiments that are important enough, and it's hard to try and do it signal in any other way, that you may say six month one time is an acceptable outcome. And we're going to start it in June, and we will be smarter for it for 2025 planning. And we're going to set it and forget it, and we're grateful we did. Right? And that's okay. But the only mistake here is like thinking you'll get any answer in a month, when you want and then pretending you do and then waking up a month later and being like, well, it was insignificant and mess and that and we could have known that.
42:23Right? And so, and then the third thing is like experimentation is all about increasing your conviction in the problem or the solution. Right? So the generalized version of the statement is if there are parts of your funnel or flow that are low -end and you can't run a canonical AB test. How might you otherwise increase your conviction in the solution that you're building? And there turns out there a decent number of other ways to do that. The first best, most obvious is talk to more customers. But there are other sort of statistical techniques that again are less rigorous or good, but maybe possible.
43:02Maybe will be used on situational data, you would do a different death, you may be able to do what gets it at sister cities or twin cities, you may be able to segment by GEO, you may be able to reduce your power and say, hey, we're going to run at 80 % confidence for all of our experiments instead of the traditional 95 % because that's a worthy trade -off and if we're wrong one more kind out of 10, that's okay. You can do a long -term holdout to match your intuition. And so, So there's a lot of other techniques to, sorry, to hone your intuition. There's a lot of other techniques to build conviction and confidence.
43:39And so we try to be very creative on doing that. And then the last last bit, I would say, is if you're not going to get significance, there's no other techniques at your disposal, then sometimes you just got to press your intuition. We ship it. And if that's what you believe, when that's what you believe in, you shouldn't spend time trying to get false precision. I want to spend more time in my last point, but real quick, the power analysis you talked about. There's people don't know. There's calculators out there that you could just plug in. Here's how much traffic I'm getting. Here's how much of an impact difference I want to see.
44:14Here's how long it'll take to find out. Yep, exactly, totally. And suddenly calculators are great where you can also plug in the traffic and you're acceptable runtime. And it will tell you the minimum impact. And then you can gut check your own intuition. So you can you can play around with it. Awesome. We'll try to link to one of those in the show notes. So on the intuition piece, is there anything more there just like how you think about when you, you know, you run the product team, just how you recommend people leverage intuition versus not because some companies are like, we're just going to address the data.
44:48I don't really trust your opinion. You don't know. Like, I like you don't know. You don't know this customer exact like you talked about opener. I'm not buying houses. was myself, so I don't know how much I can trust my intuition. Just what's your general advice to your product team of how to think about their intuition and when to rely on it versus not? So at Open Door, for example, I'd say on the relative spectrum, we're quite data -driven, and then it's when we come into this challenge, right? We're going to say, OK, like, that is another technique or tool in the toolbox. I think the generalized version of that That is customer products, people can surprise you, right?
45:26And so this happens all the time for people who build products. I'm sure you've got great stories from Airbnb. We saw something, put it out there. It just was very big. All the time. All the time. And so I think there's definitely a humility to say, you know, if you can, if it's relatively easy to test your assumptions or test your hypotheses, that is always better to get checked yourself. And yeah, that takes a little bit of humility to say that, but like, we've all been wrong plenty of times. But if that's just like not on the table, I think the reality is you can't pretend it is, and sometimes you gotta use taste and judgment, and then you say, okay, what is my conviction level?
46:08And do I have, you know, just medium, lower high conviction? And if I have anything lower medium conviction and it's a decision of consequence, ones, I should, yeah, talk to more customers, got check it with another person and see if their intuition matches something that gets me personally to the high high bucket category. And then I think the last card, which is some part of experimentation is if you just ship something because you're, it's your intuition or to where you long see the product, go, do you have a reasonable feedback loop to understand whether or not you are correct? right? So that could be customer support or ticket volume or feature adoption.
46:48Whatever the case is, it may not be an Alpert metric in the traditional AB test, but like some more rigorous system that says, Hey, I had this hypothesis. We just shipped it for XYZ constraint reason for when right. I think that's awesome advice. We agree with everything you're saying. You mentioned this word humility. Yeah. It's a good segue to something I want to talk about, which is zilo. And the most interesting things that's happened in your space is Zillow basically decided, hey, we're just going to do what OpenDour is doing. They launched it. You're basically frenemies for a while. And then they're like, no, we're not working.
47:25It's not working. Now you partner and say, now you work with Zillow on the stuff. So are you able to share what went down there with the story of what happened, how it went and other things are at now? Yeah. I mean, we do partner with Zillow. So it was been a fantastic partner for us, and we've really enjoyed sort of a working relationship with them. I think when you think about it, he has a tremendous amount of reach and all the ends and all the other online platforms have tremendous reach and audience. And we happen to have a fairly exiling solution. And so they're sort of nice, not to use a business school word, but there's a nice synergy, so to speak, between a high intent at the end who's doing a lot of browsing and searching and discovery and starting their process on one of these online platforms.
48:25And what we offer, which is, you know, transaction services, that allow people to actually move particularly on the seller side and so there's just a pretty nice symbionic relationship there with the Z -Z -Z -O -Z -M, and the red chunks of the Walden, so both of those components have been great. What do you think Zillow maybe underestimated or didn't get about the space that made it harder than they anticipated? Because it seems obvious. Of course, let's go down funnel, let's just do it all. And they're like, oh shit, not working. What do you think they didn't get or what do you think they missed?
48:57I guess continuing on the humility point. I won't necessarily pretend to be in their shoes, but I will say the business is challenging and it's complex from a number of different dimensions. It's not a traditional software -only product. You have to be really good at pricing. You have to be really good at the operations. You have to be really disciplined at risk. You have to be really good in the capital markets. And so you have to put all of these functions together to build a vertically integrated product. And that's the reality. And so that is something that's been in OpenDurus DNA from day one, because we started with a vertically integrated product.
49:38And so we can't deliver unless we get all of those things. And so I think that that's something that continues to help us to this day. Is that vertical integration requires all of those pieces coming together. That makes a lot of sense. I think it's a good reminder of there are adjacent markets and businesses that always feel like, oh, we could expand to that someday. Such a big opportunity this business could be so much bigger. Then you realize your business is completely not set up to operate this way. Zillow is very software driven, right? Just like I'm not going to simplify what they do, but it's like a website, very software.
50:17And obviously as we talked about, we opened a huge operational component. and then as you said, the pricing piece and the debt stuff. Yeah, totally. Yeah, so I think it's really going to remind you, that just like when you're taking on something completely different, you may not fit into the way your company operates and partnering makes sense. Anything else there that's interesting? Share on the Zill thing. I guess one is maybe it was just like, imagine it was very stressful. Zillow's getting into it. Oh, shit. What are we going to do? They got all the traffic. Yeah. Anything there? Yeah, I mean, it's certainly stressful.
50:48I think in general, we try to live by, well, in Zillow or anybody else, being competition aware, but not necessarily competition focused. And the reality is fast, fast, fast in our space. And vast majority of people still move the traditional way. And so this isn't something that's like the size of the prize is into particularly large an offshore or anything like that. Yeah, it is the largest asset loss in the United States. And if we just say she were focused on like, hey, who are the customers that we serve really well? We talk to every day. There's a little bit of confidence that comes from being able to stay focused on that with some competitive environment again, because it's not like the market is fully saturated.
51:39This is the same thing back in the Uber days as well. Well, transportation is almost infinitely large. And so, yes, it feels like they're seated competition. It'll be true, over and over, and ever back from the day. But the reality is there's plenty of trips that happen. And people need to get around city in plenty of different ways. That's neither Uber nor Lent. And staying focused on how you can go for your customer. I think it's the destiny of the focus. There's a podcast that will come come out before this episode with Jeff Weinstein from Stripe whose building strip Atlas. They had a similar experience with Angelist launched direct competitor to Angel to Atlas and then they realized Atlas is so much better.
52:26Forget it. We're just going to send everyone to Atlas. Really? Yes. And I think it's the same exact lesson that if you just stay focused on jobs to be done, let's say, what is the job to be done and do the best possible job? And knowing that the market is much bigger, that you're not really competing with someone else, another company, it's like, it's the default behavior in your case. It's like people are just buying our house the old fashioned way. That's the actual competition. Exactly. Yep. Yeah. Okay. So kind of along these lines, something else I've heard that you're very good at is staying very calm under pressure and staying very level headed when things are really crazy.
53:03There's something that a lot of people are not good at, especially leaders. they stress everyone out, things go crazy. They don't create a good vibe. And then two, something people want to get better. Leaders and non -leaders are like any lessons, anything you've learned about just how to develop this skill. You know, I think part of this may have been sharpened in the early days of Uber, where everything's like a fire drill all the time, and so the only way to operate. But you know, I think you almost hit the nail on the head in the question, which is like a little bit of an intellectual answer of when you reflect the stress onto your teams, everybody tensed up and tightened up, right?
53:44And so it doesn't counterintuitively, it doesn't produce better outcomes. And so I think the other reality to sort of remind ourselves, and these are a bunch of like mantras that just like are half full in these moments is, you're never as good as you think you are, you're never as bad as you think you are. And so, sort of that more even keel demeanor, I think, allows you to have a clear head when they're operating under the pressure. And to think more clearly, I think we want to be maybe least helpful in certain, but unfortunately, is sort of a reality is, you kind of got to be in some stressful situations to also have the perspective that cycles past the things pass and that remaining calm is what matters.
54:31And so maybe the advice there is reflecting on one of these situations happen, exposing yourself to that and not running from them and then learning from them so that the next time it comes around, you can say, hey, I've been here before. I've slapped on the floor in China before launching, you know, We were cool and thinking we're gonna miss a launch deadline and like what were the tools in my toolbox and my tool kit that works You mean Intense of getting it done or not and what Love that so part of it is just go through this experience many times and you will start to realize okay It's not actually gonna be as bad as people may think You mentioned this tool kit instead of tools or anything else there that you come back to that ends up being helpful You mentioned this mantra of like, it's never as bad as people think it is, never great, as people think it is.
55:23Yeah, I think exposing yourself to other people's stories or however you may learn is really, really helpful. So, again, whether it's your podcast or books or biographies or one of the podcasts that I love is Founders Podcast. It mostly talks about historical famous entrepreneurs. And obviously these are elevating like very famous people already, but there's a lot to learn from a lot of these stories as well and Understanding that the journey in the pack is non -many or it never is for anybody, right? And so I think being able to expose yourself to other stories that even may if you don't have those personal experiences and then Understanding how others navigate.
56:10So just hearing of other people's crazy experiences and kind of building on this muscle of like, okay They've gone through crazy stuff. Things work out. Yeah, we'll make it through. I have this note here that I think either someone mentioned about you or me, you may have mentioned that product is finding the kernel of truth in a sea of ambiguity and signals that mean anything to you. Yeah, absolutely. I think in most organizations, and to do the job effectively, you're going to get signals from anywhere, right? And good ideas come from everywhere. It may be your CS team or CS team. It may be a customer directly.
56:48It may be a conversation you had. It may be a YouTube video you watch that sparked an idea. It may be feedback from an executive. It may be whatever you went out and did a field visit. Like you are going to get a lot of inputs around what people think about your product or people think you should do next. And I think the core job is to understand and what really matters, right? Like what is noise? What is a good idea? What is a suggestion? What is, and what is, you know, back to the jobs we've done for, like what is really gonna move the customer forward? And unfortunately that means, you know, saying no to maybe what sounds like some good ideas, you know, along the way.
57:29But if you can really figure out, like this is really what matters? That's the core part of the job. And it dovetails even back to our earlier conversation, if you don't, in the early days of building tech and ops companies, is where's the tech leverage? Like a thin question. Where's the kernel of what really matters that tech can immediately solve? And must go do that and be comfortable with other shires made in learning? That's what really really matters. It's a hard discipline. I love that. But if there's not an example that's totally fine, but what you talk about, this fighting this kernel where tech could be highly leveraged as an example that comes to mind that working out really well.
58:13I mean, I think back in the in the Uber days, I think it was like, hey, we're not going to build sophisticated, tooling infrastructure. We're not going to build centralized growth team. We're not going to build any of that because like if you think about the early Uber network from the simplest form. You've got a writer and a driver and you need to connect them, price of the transaction, and issue some receipts probably, you know, collect payment. So it's like, okay, do we do that really well? And until we do that really well, like all the other stuff is noise, right? It's actually, it's immaterial how efficiently the answer support tickets.
58:52Like that's not critical, right? And so now it's super critical, right? But like in the early days, it's not that critical. And like even like customer acquisition costs may not be like super critical, like in this case, scroll on those things. And so, you know, pouring fuel on the fire may not be super efficient there. So I think that's like a very good generalized example. On one other tip that that maybe is helpful here, that I frankly constantly work on and try to get better at is all these ideas and feedback that comes from everywhere. Make sure it's written down for a number of reasons. One, you can then go reference it.
59:35But two, part of the job is making sure the people who present those ideas are heard and respected and know that it's at least somewhere where it was considered. Right. And then you can look at it all and say, OK, but what actually really, really matters here. And yeah, that's another tip. When you say written down, is there tools you find really helpful here? Is it just like put in a big dock that we're keeping? Is there anything you find to actually operationalize that? I've seen different companies do it differently, but wherever you tend to try and keep a backlog, whether that's Google Sheet or your actual backlog.
1:00:11Cheers. This, but at least it feels like the context was captured and the idea is there. Awesome. Okay, I'm going to take us to a recurring segment on this podcast called Failure Corner. Is there a story you can share of a time you failed in your career, how to big failure, and how that experience made you better? We can talk about the very early days of Uber Pool and kind of the first launch, if you will, in San Francisco. So car pulling products, multiple riders in the same car. And we had this idea that it would be effective to for commuters. This was very, very early days. And so part of the launch was, okay, we're gonna beta it with just some popular sort of commuting corridors with specific companies.
1:01:09So maybe the Marina had to Google whatever, right? And try and match people according to their companies and that's how they're going to have liquidity. And we very quickly realized that back to sort of what the kernel truth is here is like, liquidity is the only thing that matters. And there just wasn't enough. There was never going to be enough to sort of do this company -based thing. That wasn't the strategy that was going to work for Chermas. And so, you know, the reason I don't know if it's like a full failure is like, maybe this is true. All failures is you learn from it, you pivot, you go on to the next thing.
1:01:51And obviously we did that and then spent a lot of our time in effort trying to say, okay, what are the bounds of liquidity and driving liquidity that we can do to understand and what the most important or what the sort of limits of the product are. So as an example, we launched and many people in San Francisco. Remember this sort of $5 anywhere in San Francisco, the work for all promotion, which obviously a great deal. Obviously cost a lot of money. But the whole idea here is like, okay, liquidity is what really matters. If we were to juice that and really drive liquidity, how high can our metrics gather and we can go chase?
1:02:31you know, more sustainable ways to do that. But it was a sort of an interesting fail case from launching and learning to say, hey, this initial strategy just didn't work. We got to go, we got to go and any of the part that was a hedging strategy, we're going to have a small audience and there'll be a big population and say, well, this one you just got to go. I think, I listen, there's also don't over think it, don't try to get too cute. Just like, like this is a, yeah, we're trying to make a perfect beta test versus like realizing, okay, we just need a lot more of people in it. Top. Also, your $5 promotion made me think of the early promotions of like the ice cream and the bunnies, delivery and all that stuff.
1:03:13Yeah. Those are the way. Now's by the way, a example of like fully distributed, the benefit of having those early petri dishes, is someone, a local marketing manager, it's like, hey, this would be fun. It would be really fun. The platform can support it. And those promotions were fantastic, right? And it started out, I can't remember, I left first one with ice cream or puppies, I think it was ice cream. But yeah, branched into all sorts of stuff, boats, ice cream, puppies, kittens, I think. And all credit goes to sort of like local ideas as an inspiration just being focused on trying to grow within.
1:03:56I love that we've circled back to the beginning of our conversation. Product and Ops working together in the benefits of both. Before we get to a very exciting lightning round, is there anything else that you wanted to share? Any last nuggets of wisdom that you think might be useful to people when they're trying to build product companies teams? This was great. We covered quite a bit of ground. I think the only, I don't know if this is a generalized wisdom, but something I've been thinking about. as as microers progress a little bit, especially going out on the, you know, pranker rotations, especially as more tools come online.
1:04:31It's very clear that there's different types of pms. And we spent a lot of time talking about once we can operate in the physical and the digital or the product and operations worlds. But even within that, there's more, you know, technical pms who grew up in a engineering discipline where people came from ops and there are people who came from from designing and grew up in in certain more user experience background. And one thing that I've been been drawn on as he built out on the team is thinking, you know, similar to a product roadmap is like, it's not really about like, is this person good or bad or whatever it is, is this person's skillset and contacts matched into the problem that is Israeli -medied.
1:05:20And so back to that conversation on, hey, where do we get tech line regents? It's like, hey, is this person who has this unique skillset as a PM, well -suited for this problem type? I don't know if that's helpful, but it's something I've been spending a lot of time thinking about, especially in this view, the job -posting niche view. Not a command and chair, or a reminder, but it's actually like, well, like, how could we be a little a little bit more thoughtful about what the actual skill that needs out of this type of thing. Awesome, it's kind of like a person product fit. There you go. And I think it's, because a lot of companies hire generalists and they're just like, we'll hire someone smart, ambitious, and with experience and general experience, and then we'll pull up them on different things.
1:05:59So I think these are two different philosophies. And it probably makes a lot of sense for an open door, with like very unique type of business, very specific skills that are necessary to be really good there. Okay, amazing. Brian, with this we've reached our very exciting lightning round. Are you ready? Let's do it. Can't wait. Let's do it. First question. What are two or three books that you recommended most to other people? Shudog, Black Swan, design of everyday things, and for fun one, Shunter on. Amazing four books with four books for the price of two to three. I love it. Oh, jeez. I'll stick to the rules.
1:06:42No, no. There's no rules. There are no rules. Yeah, yeah. Next next question. Do you have a favorite recent movie or TV show that you've really enjoyed? I like the sports sort of docky ones on Netflix. So full swing, draft to survive, breakpoints, tennis golf, F1 while. And was there that Nike documentary recently with Ben Affleck? There is, which I have not seen. So if it's good, I don't know if that's a recommendation or just an acknowledgement. It's worth watching. If you like shoe dog, I feel like you have enjoyed. I think it was entertaining, Michael Jordan, things like that. Next question.
1:07:19Do you have a favorite product that you have recently discovered that you really love? So we just got a puppy and we are about to have our first child. And so all of my purchases recently are puppies and children and focus. We've been my buddy gifted us the the fire collar for our dog. And so we have been really, really enjoying that. Another one as I'm getting busier for news and stuff is particle, which Yeah, it was great. It was news, these are the motivation to AI news. So. Okay, Vaughan's wife's business. We've, I'm a huge fan actually. They, I think it just came out of beta and now it's like a full app that anyone can download.
1:08:03I've been, I just actually installed it yesterday again and I love it. I get these pushes every, every feature top. I don't know. It's like a couple of times a day of just like, here's what's happening in the, also congratulations I should have set on your pending child. Thank you. Lucky for you. I have a newsletter post with all the products you should buy. It's called new parent gift guide for product managers. Love it. I will Definitely probably buy all of them. If you don't already have them all and now everyone's probably sending either spreadsheets of all their favorite stuff. Exactly. Okay, next question.
1:08:36Do you have a favorite life motto that you often come back to share with people either in work your life? Well mostly just stay curious. Stay curious. Yes, I love it. Two more questions. Who has most influenced you in the course of your career? One of the people who inspired me very early on in my product journey, I've been fortunate to have a number of very good mentors. And obviously, they talked about early while I was a founder, so dogs are a mentor, so it would be a lot for more people's journey. But one person who was personally important to me early in my product journey, very supportive of this guy, I named Jeff Holden, who was the chief proctor officer at Uber back in the day, and it was sort of like a young PM transferring into product.
1:09:25Really, you know, took me under his wing, and I think, I'm forever grateful for that, for asking for helping grow my career, but also kind of pay it forward a little bit in terms of people who are really on the career. That was around me, in fact, for me. Last question. I hear that your interview at Uber was pretty wild. Can you tell that story? Yeah, I can. So, long story short, I was starting a company, my senior spring, before graduation, and I had to go our separate ways. So I hadn't done, you know, traditional recruiting, ever. And my buddy called me up and was like, okay, we're looking for smart, hardworking people at this Uber saying, are you interested?
1:10:08And quick as I note, I had actually done some very early diligence work on these taxi apps back in 2011 looking at what a time was Uber cab and cabulous and taxi mentioned probably something new stays. And so I knew what Uber was. And so I said, yeah, sure, what's, you know, I would love to. And so I had the first round of interview, went well, and they said, great. And then that stage is come outside sort of sure the full -man to all of one works. And this was post graduation. I was helping out some companies, but didn't have full -time job. So I said, hey, I'm pretty flexible. How about next Tuesday?
1:10:55It's great. So he scheduled that. And then on the Friday or Saturday over the weekend, I looked and I was, Oh, Tuesdays July 4th. I'm like, I scheduled my interview for July 4th. And so I called my buddy, and I'm like, hey, I'm so sorry, I don't wanna make people commit on July 4th. Should I cancel, share each out? Like everyone's sort of accepted. Whatever you do, do not cancel your interview. So, okay, I'll be there on July 4th. And so I went in to the office on July 4th. And there was a very small handful of people there. It was actually launching that day was launching Cooper's second ever product type, which was Cooper SEV And I sort of had this was probably five hour gauntlet interview on July 4th from from noon to five and miss my July 4th barbecue and it was it was quite the experience But I think maybe maybe set the stage for some of the early days Okay, I'm very glad I didn't cancel me and it was Travis involved in that interview or is it just Travis was was involved in the interview.
1:12:02She was one of the, I think there are four or five people, the two who were who were generally guiding my interview process and Travis and one other person starting that day. And part of the compliment interview was sort of a simulation of the job, if you will. And so some of that was buildings to novels on all the computers. And it was sort of writing potential emails to drivers. then actually had the driver come in and we did chat. So I was in this room by myself typing away on the first part, which was building the model. And I hear him knocking on the door. And Travis comes in and we just sit down and says, I'm Travis.
1:12:46I'm Brian. And we have a 45 minute chat. Or maybe it's been about half hour, 45 minutes. And clearly I'm not producing the work that I'm supposed to of the interview, right? I'm supposed to be building this model, I'm supposed to email it back to the person who sent it to me, clearly have done nothing. Chat, chat with the CEO and hear knock on the door and the door opens and the person sees that I'm trying to... Oh, continue, continue. And it was very good. Also, pretty intense conversation with Travis, then definitely set the expectations. I was like, what, what, what, what, what, what, what?
1:13:23and clearly worked out and Travis was happy. It was my hope to imagine. Yes. Amazing. Brian, thank you so much for being here. We went through everything that I was hoping to get through. Two final questions. Working folks find you online and is there anything you want them to check out that you might be up to and how can listeners be useful to you? Super kind. They can find me online on Twitter, LinkedIn, both just Brian Token, my name. In terms of being useful, if you have a home to sell, feel free to go on to OpenDore. More importantly, if you have feedback on the product, we'd love to hear it.
1:14:00Otherwise, if you'd like to learn more about what we chatted about, it would be super great. So, we'd love to hear from you. Brian, thank you so much for being. I really appreciate it. This was great. Bye, everyone. Thank you so much for listening. If you found this valuable, you can subscribe to the show on Apple Podcasts, Spotify, or your favorite podcast app. Also, please consider giving us a rating or leaving a review, as that really helps other listeners find the podcast. You can find all past episodes or learn more about the show at Lenny'sPodcast .com. See you in the next episode.
From the publisher
Brian Tolkin is the Head of Product at Opendoor. Previously, he was one of the early employees at Uber, where he was instrumental in launching and growing UberPool, UberHop, and UberExpress and started one of the first product operations teams in tech. In our conversation, we dive into:
• How to enable product and ops to work well together
• How to run great product reviews
• How to make good decisions with limited data
• How he uses the jobs-to-be-done framework at Opendoor
• How to stay calm under pressure as a leader
• Wild stories from his time at Uber
• Challenges faced at Opendoor during the pandemic
• Much more
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Brought to you by:
• Pendo—The only all-in-one product experience platform for any type of application
• Explo—Embed customer-facing analytics in your product
• Attio—The powerful, flexible CRM for fast-growing startups
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Find the transcript and references at: https://www.lennysnewsletter.com/p/scaling-uber-and-opendoor-brian-tolkin
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Where to find Brian Tolkin:
• X: https://x.com/briantolkin
• LinkedIn: https://www.linkedin.com/in/briantolkin/
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Where to find Lenny:
• Newsletter: https://www.lennysnewsletter.com
• X: https://twitter.com/lennysan
• LinkedIn: https://www.linkedin.com/in/lennyrachitsky/
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In this episode, we cover:
(00:00) Brian’s background
(02:14) Career beginnings at Uber
(02:49) Transitioning from product operations to product management
(06:47) Product and operations synergy
(10:00) Surge pricing at Uber
(12:18) Scaling challenges, and stories
(15:47) Opendoor and Covid adaptations
(25:38) Product reviews and Jobs to Be Done
(40:30) The challenges of A/B testing
(42:23) Increasing conviction in solutions
(44:33) Leveraging intuition in product decisions
(47:07) Partnering with Zillow
(52:55) Staying calm under pressure
(56:25) Finding the “kernel of truth” in product management
(01:00:21) Failure corner: Early days of Uber Pool
(01:06:11) Lightning round and final thoughts
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Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email podcast@lennyrachitsky.com.
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Lenny may be an investor in the companies discussed.
This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit www.lennysnewsletter.com/subscribe




