M&A, competition, pricing, and investing | Julia Schottenstein (dbt Labs)

Julia Schottenstein is a product lead at dbt Labs, a data transformation company, and an active angel investor in data and infrastructure startups. She first got excited about dbt in 2019 when she was a VC at NEA and decided to make the leap from investor to operator by joining dbt Labs. She also co-hosts the dbt Labs Analytics Engineering Podcast, a show about data trends that impact analytics engineers’ work. In today’s episode, we discuss: • Advice for founders hoping to improve their M&A outcome • How to strategically think about competition • How to determine your paid features and have willingness-to-pay conversations • Why Julia lives by “worse is better” and “tech debt is a champagne problem” • Lessons from dbt Labs • What PMs can learn from investors — Brought to you by Vanta—Automate compliance. Simplify security | Superhuman—The fastest email experience ever made | AssemblyAI—Production-ready AI models to transcribe and understand speech Find the full transcript at: https://www.lennysnewsletter.com/p/m-and-a-competition-pricing-and-investing Where to find Julia Schottenstein: • Twitter: https://twitter.com/j_schottenstein • LinkedIn: https://www.linkedin.com/in/julia-schottenstein-25424318/ • Podcast: https://open.spotify.com/show/4BKMMeVXk4jJnAQSqGSJvE Where to find Lenny: • Newsletter: https://www.lennysnewsletter.com • Twitter: https://twitter.com/lennysan • LinkedIn: https://www.linkedin.com/in/lennyrachitsky/ In this episode, we cover: (00:00) Julia’s background (04:15) How Julia went from VC to working in product at dbt Labs (08:24) Four things Julia uses to evaluate a company’s potential (11:10) How to identify whether or not you have product-market fit (12:05) Distribution strategies (13:11) M&A strategies (15:54) Lessons from the Transform acquisition (18:01) Competitive values at dbt (20:25) Keys to dbt’s success (26:35) An offsite exercise Julia used to help her team internalize upcoming changes (29:32) Determining what features are included in open source (31:56) Pricing and willingness to pay (33:34) Lessons from dbt Labs’s first pricing change (36:33) Whether or not to be public about selling your startup (40:08) How to utilize connections during acquisitions (44:57) How to communicate selling your company (46:33) M&A market forecast (47:28) Values at dbt Labs (50:14) Lessons from working with strongly opinionated users (52:02) The importance of shipping, learning, and iterating (54:08) How VC skills translate into product (57:03) Lightning round Referenced: • dbt Labs: https://www.getdbt.com/ • Tristan Handy on LinkedIn: https://www.linkedin.com/in/tristanhandy/ • dbt Labs acquires Transform to enhance Semantic Layer tool: https://www.techtarget.com/searchbusinessanalytics/news/365530993/DBT-Labs-acquires-Transform-to-enhance-Semantic-Layer-tool • Snowflake: https://www.snowflake.com/en/ • Gödel, Escher, Bach: An Eternal Golden Braid: https://www.amazon.com/G%C3%B6del-Escher-Bach-Eternal-Golden/dp/0465026567 • Red strings training clip from Ted Lasso: https://www.youtube.com/watch?v=aVe3Iwy10MA • Monetizing Innovation: https://www.amazon.com/Monetizing-Innovation-Companies-Design-Product/dp/1119240867 • Madhavan Ramanujam on Lenny’s Podcast: https://www.lennysnewsletter.com/p/the-art-and-science-of-pricing-madhavan#details • Pricing survey: https://www.qualtrics.com/marketplace/vanwesterndorp-pricing-sensitivity-study/ • Hunter Walk’s blog post about publicly selling your startup: https://hunterwalk.com/2023/05/13/the-acquihire-market-for-early-stage-startups-is-ice-cold-one-better-strategy-announce-youre-for-sale/ • Range: Why Generalists Triumph in a Specialized World: https://www.amazon.com/Range-Generalists-Triumph-Specialized-World/dp/0735214506/ • The Snowball: Warren Buffett and the Business of Life: https://www.amazon.com/Snowball-Warren-Buffett-Business-Life/dp/0553384619/r • Sam Walton: Made in America: https://www.amazon.com/Sam-Walton-Made-America/dp/0553562835 • Succession on HBO: https://www.hbo.com/succession • In Depth podcast: https://review.firstround.com/podcast • dbt community Slack: https://www.getdbt.com/community/join-the-community/ Production and marketing by https://penname.co/. For inquiries about sponsoring the podcast, email [email protected]. Lenny may be an investor in the companies discussed.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  M and A is always about creating Plan Bs. And the way I would think about it is for any one company, there's only ever two to three buyers that find what you're building to be extremely strategic. And the strategy that I would do in How Do You Get Noticed? Is I would figure out the area that you bring a competitive advantage, and I would inflict pain on that potential buyer. Make it impossible for them to not notice you because that's when they're gonna have their ears perk up and say, well, what's going on with this company? The really important piece here is you want to do that in a way that's still friendly and open. I see a lot of founders get this wrong. And they prematurely will shut down a conversation,

• 0:42Speaker 00

  or they won't talk to an incumbent or a potential future buyer because they take too competitive of a stance. But that's a mistake because M and A is all about creating Plan Bs. And you don't want to shut that door down prematurely because you don't know if you can really go the distance and be an independent company. So you want to have optionality.

• 1:04Lenny Rachitsky?

  Welcome to Lenny's Podcast, where I interview world-class product leaders and growth experts to learn from their hard-won experiences building and growing today's most successful products. Today, my guest is Julia Schottenstein. Julia is a product leader at DBT Labs, where she leads the DBT Cloud product. She's also the co-host of the DBT Labs podcast called Analytics Engineering Podcast, a show about data trends that impact analytics engineers' work. As you'll hear in this episode, Julia actually led the acquisition of a startup that I'm an investor in called Transform from the side of DBT Labs. And in our conversation, we dig into the M and A process and get into a bunch of advice for how to improve your odds of having a good outcome and just approaching M and A broadly. We also dig into the story of DBT,

• 1:49Lenny Rachitsky?

  which is one of the most successful startups out there that you probably don't know about. And we talked about what they did right to get to where they are now. We also cover how to best think about competition, a bunch of frameworks for thinking about product, and advice on how to approach pricing, and also open source. Enjoy this episode with Julia Schottenstein after a short word from our sponsors.

• 2:11Lenny Rachitsky?

  This episode is brought to you by Vanta, helping you streamline your security compliance to accelerate your growth. Thousands of fast-growing companies like Gusto, Com, Cora, and Modern Treasury trust Vanta to help build, scale, manage, and demonstrate their security and compliance programs, and get ready for audits in weeks, not months. By offering the most in-demand security and privacy frameworks such as SOC 2, ISO 27001, GDPR, HIPAA, and many more, Vanta helps companies obtain the reports they need to accelerate growth, build efficient compliance processes, mitigate risks to their businesses, and build trust with external stakeholders. Over 5,000 fast-growing companies use Vanta to automate up to 90% of the work involved with SOC 2 and these other frameworks.

• 2:55Lenny Rachitsky?

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• 3:10Lenny Rachitsky?

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• 3:55Lenny Rachitsky?

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• 4:15Lenny Rachitsky?

  Julia, welcome to the podcast.

• 4:17Speaker 00

  Super excited to be here.

• 4:19Lenny Rachitsky?

  So you have a really interesting career path in that you went from VC into product management. Usually it's the other way around. Usually PMs become VCs and it's rare to see this kind of version of it. And so I wanted to start with just a question of just how did that, how did that come to be?

• 4:34Speaker 00

  I do have an unusual background, but you know, it doesn't surprise me that people who are interested in product are also interested in investing and vice versa. You know, for me, I've always had three interests broadly, and that's an interest in business, an interest in technology, and an interest in markets. And I get to express those interests, both in investing and in product, but just with different weights. So in product, you go a lot deeper on the tech and markets is less of a focus, but you still get to do all three. So I have an unusual background and I used to be a professional investor at NEA. I did all of, about all my time investing in early-stage startups that built for technical audiences.

• 5:18Speaker 00

  So think dev tools, infra data companies. And in 2019, I first discovered DBT, which was an open-source data transformation framework. And I got really very, very excited about DBT because when I talked to people that were using it, the way that they described their experience on DBT was like unlike anything I had heard before. It was much more of an identity for them than just a tool that they were using to get their, their job done. And that really struck me. And as I kind of thought about what was happening in the market, there was a lot going on. In, in 2019, the markets were changing quite

• 6:00Speaker 00

  a bit. Cloud data warehouses were starting to explode. Like this was the year where Snowflake went from a $4 billion company to a $12 billion company. And I thought to myself, if DBT worked, it could work in a really extraordinary way. And I naturally tried to spend all my time getting close to Tristan, who's the CEO and founder, and I wanted to invest.

• 6:24Lenny Rachitsky?

  So at this point, you're a VC at NEA, you're trying to invest in DBT. And okay, keep going.

• 6:29Speaker 00

  Yeah, so I was very, very excited. I thought if this worked, it could work in a really extraordinary way. And I spent all my time trying to get Tristan to like me so that I could invest in the company. And then in 2020, I finally got the call that I was waiting for. Tristan said, we're going to raise some money. He had a term sheet from a firm that he liked. It was a good venture fund, but he also liked me and he wanted to give me a shot. And I was like, super excited to get that message, like this is, this is my chance. And unfortunately, I ended up losing that deal to Sequoia. It's a formidable partner.

• 7:03Lenny Rachitsky?

  Reasonable, reasonable.

• 7:05Speaker 00

  I was, I was just so convicted that it was going to be a special company that I asked to even put my, my personal money in. And I asked to put like a very irresponsible, irrational amount, nearly like 20% of my liquid net worth into DBT, because I was so convinced that this was, was special. And you know, sometimes when deals don't work out as an investor, you can create this like narrative in your head, like, oh, good. You know, I dodged a bullet or you know, that better off without them or you know, screw them. But for me, like, that was quite the opposite with DBT. I really felt like DBT was this runaway train and it was special and I wanted to jump on board.

• 7:49Speaker 00

  So a few months later, I ended up calling Tristan and, and asked him if I could be a part of the company, company that built the product that I thought was so special. So that was my kind of unique path into product and into DBT.

• 8:02Lenny Rachitsky?

  So you invested in DBT and then you ended up. There are an opportunity opened up where you can end up working there.

• 8:08Speaker 00

  No, I think if I was was able to invest, I wouldn't be here. So I got a no. The board ended up vetoing my personal investment, but it's okay because I ended up dedicating all of my personal time to building the company.

• 8:23Lenny Rachitsky?

  Awesome. Okay. So something you touched on there that was really interesting of what you saw about DBT that was so interesting. And I think this is maybe a broader question of just in your time investing and finding a company like DBT early. What have you learned about just picking well, finding companies early, especially what are signs in your experience of just that this is going to be something really interesting that you might want to join? And this is more for people listening that are thinking about joining a company early on, what do you think they should look for?

• 8:51Speaker 00

  So the way I would look at joining an early stage company would be the same way I would evaluate investing in one. And so there are four things that I care about when I'm looking at really early stage companies. And it's people, market, product and distribution. And I'll touch on each of those four to say a little bit more about what specifically I'm looking at. So for people, this is really the CEO, the founder of the company. Put simply, do you trust this person to lead? And for me, Tristan had this really rare ability to paint a very compelling future of the industry and how DBT was going to be a part of making that vision a reality. But he also was really, really detailed in the day to day work of the analytics engineering work.

• 9:35Speaker 00

  And it was that range and scale that made me feel like this is a founder that's very rare and compelling. The next is markets. We touched on it a little bit, but you know, what I'm looking for in markets is like, is it growing? Is there space for a new entrant to make its mark? And when it came to DBT, it was an explosive time in cloud data warehouses. And it was that chaos that was really the opportunity for DBT because they created some orderliness and structure to the way that people worked with their data in the cloud data warehouse. So that was very compelling. Then the next is product. Everyone who's listening, hopefully either is interested in products or has a product background.

• 10:17Speaker 00

  So I won't say too much there, but it, but can you talk to users or customers, potential customers? Are they building something that's really special, unique? Can you hear that spark, that enthusiasm and figure out if this is going to be special? And then the last, I think this is more important arguably than if they have a good product, but is distribution. Do they have an advantage on how are they going to get to market? Because that's really, really hard. And think about how they think about their competitive advantage on either the ecosystem or distribution and how they're going to ultimately sell the product. You're not going to get a 10 out of 10 on all four dimensions. And so when you're joining a company, you also have the benefit of dedicating your time.

• 10:59Speaker 00

  And so try to think, you know, if they're weaker on one dimension, what is it that you bring to the table? Or what are you special at that could potentially de-risk the success of the company?

• 11:11Lenny Rachitsky?

  In terms of spark with a product, I'm doing a post right now on product market fit. And how do you know if you have product market fit? And a lot of it often comes bound to like, there's like a emotional reaction from someone you're talking to about the product you're building. They're just like, holy shit, I want, I want this now. Is there anything even more specific you've seen of just like, what is a sign that this, there's a spark that people are just like really enthused? You talk about people made DBT kind of part of their identity. Is there anything else there?

• 11:36Speaker 00

  Yeah, it's, can they not stop talking about it? And that's this, like the chatter about a product, they want to share it with like their teammates or to other people at different companies. That just top of mind love and wanting to share what they've found with others is really a great sign that that you're on to something. And then that spark will help do a lot of the work on how do you get to market? Because your evangelists are really your, your users are people that love what you're building.

• 12:05Lenny Rachitsky?

  What about in terms of the distribution bucket? What are some examples of just really important, I don't know, unique or effective distribution strategies or, I don't know, unfair advantages you've seen maybe with DBT, maybe other companies? Like, what are some examples of that?

• 12:20Speaker 00

  So DBT had an ecosystem advantage and they were open source. And this helped really dramatically for lots of people to have low barrier friction to just try it out and spread kind of organically. They first got started with very horizontal. People could just get started without ever even talking to sales and think that was a competitive advantage. But you know, not all companies need to be product led. Some companies are enterprise top down sales. And so in those situations, think about like, does the team really know how to land a complex enterprise sale? Do they have a background in that particular space? Do they have a network of connections?

• 13:00Speaker 00

  Can be different depending on what the company is selling, but you either want to see someone who's a company that's really strong at enterprise or really strong at the bottoms up.

• 13:11Lenny Rachitsky?

  Okay, cool. So I want to shift a bit to talking about an area that you have a lot of experience in, which a lot of people are also really interested in right now, which is M and A. I've invested in a lot of companies and maybe, I don't know, once a month I'm getting an email from a startup I've been invested in that's just like, hmm, we're looking at maybe selling the company. Things aren't working out the way we were hoping. And you've been on, I think, maybe all sides of the table of M and A transactions, including I think you led the acquisition of a company. I was an investor in the DBT acquired that I think is public company called Transform. And so my question is just for founders who are currently thinking about M and A, M and A meaning acquisition, essentially, what's your best advice for them for how to be most

• 13:54Lenny Rachitsky?

  successful in an M and A kind of outcome for themselves?

• 13:57Speaker 00

  When it comes to acquisitions, the time to start thinking about an M and A strategy is hopefully when you don't need one. And the best strategy that I could give a founder is to have a really strong offense in building their company. And when founders start their businesses, they don't usually set out to start a company to sell it to another business. They start it to be an enduring, independent, standalone company. And if you have that path, then you'll have the upper hand in absolutely every single M and A conversation because you have a viable alternative, which is do nothing, stay the course. You don't have to sell. But of course, that's not the case for for most companies. Most companies don't have a viable path to being an independent company.

• 14:43Speaker 00

  Forever. And so they have to think about M and A. And so M and A is always about creating Plan Bs. And the way I would think about it is for any one company, there's only ever two to three buyers that find what you're building to be extremely strategic. And the strategy that I would do in How Do You Get Noticed is I would figure out the area that you bring a competitive advantage, and I would inflict pain on that potential buyer. Make it impossible for them to not notice you, because that's when they're gonna have their ears perk up and say, well, what's going on with this company? You know, we just bought this company, Transform. They were doing a, they were playing a really

• 15:23Speaker 00

  good playbook here. And the really important piece here is you want to do that in a way that's still friendly and open. I see a lot of founders get this wrong. And they prematurely will shut down a conversation, or they won't talk to an incumbent or a potential future buyer because they take too competitive of a stance. But that's a mistake, because M and A is all about creating Plan Bs. And you don't want to shut that door down prematurely, because you don't know if you can really go the distance and be an independent company. So you want to have optionality.

• 15:54Lenny Rachitsky?

  I love this term, inflict pain on your potential acquirers. What are some, what are some examples of that? Like, how, who's done that well? Or what does, what's an example of that?

• 16:03Speaker 00

  Yeah. I mean, I can share the, the Transform stories of the company. We, we just acquired, we announced it in, in February. So, so DBT Labs, we build transformations. That's our kind of main product. And we were venturing into a new product area that we call the semantic layer. And to describe what that is, like, quickly, it's allowing companies to define their business metrics. And so that whenever anyone queries it, we always serve back consistent data on those business metrics. And Transform, they were a pure play company only in this metrics layer, semantic layer. And they, they, they had a really strong product. They had figured out some of the Technical challenges and they had solved it early on.

• 16:47Speaker 00

  They had the benefit of having worked at Airbnb, which you know. And Airbnb in the data world is famous for having a really successful like semantic layer, metrics layer called Minerva. And what we had at DBT Labs is really good distribution and ecosystem. But we were kind of a little behind in bringing a product to market. And we felt that pressure from Transform because they were doing such a great job at being vocal and loud about how their semantic layer solves these really hard technical problems. But they didn't have any distribution and so that was really tough for them. And they were putting pressure, but they were still positioning their company as a partner

• 17:29Speaker 00

  to us because they wanted our community to be excited about what they were building and hopefully lure them over to use their product. And so because they had positioned themselves as a friendly partner, when really we weren't, we were trying to compete for this similar use case. When it came time to do an acquisition, we were really excited because we knew their product was good and they had already done a lot of the work to make integrating with DBT possible. And that helps us post-acquisition do the integration much more easily.

• 18:01Lenny Rachitsky?

  How do you just think about as a startup or even an incumbent about how to think about competition, how much emphasis, how much energy to put into thinking what competitors are doing and just how that informs your strategy?

• 18:15Speaker 00

  So we recently codified our philosophy when it comes to competition. And I'll give Nick Candel, the founder of Transform, who led this exercise at DBT Labs. But we really have like three pillars when it comes to competition. So the first is hold true to our vision. We're really excited about the path and the journey that we're going on at DBT Labs. And we don't want the distraction. So occasionally you'll have competitors maybe throw shade or throw stones, but most of that is just noise. If you have a lot of conviction that you're going in the right journey, you want to just keep your eyes straight ahead and run your best race and not be too distracted by what maybe some critics are saying.

• 19:01Speaker 00

  The second philosophy we have is really a grow the pie philosophy. So we want to work with our partners in our ecosystem to make the opportunity set even larger. And we see that today, like we mostly serve reporting and BI use cases. We're seeing lots of companies start to operationalize their data. Now with this big wave of ML, clean, transformed data assets are being used to train machine learning models. So that the pie continues to grow. Let's, let's focus on that as our target and work with people to make the opportunity set really attractive and not try to slice it up too thinly. And then the last one is, you know, we want to lean into our strengths. So, so we have an ambition to be a platform company and we know what we're good at.

• 19:45Speaker 00

  But we also want to leave space for our ecosystem to offer solutions to our users that, that help them out. And we really want to foster an ecosystem where we can partner with lots of companies in the modern data stack. And generally speaking, when it comes to competition, we take a really long-term view. And there are a few areas that we do want to hold our ground and that's in our transformation standard as well as our semantic standard. Because we believe those two are better served together for the user's sake. But for everything else, we really feel like we can work with our ecosystem and accomplish what we want to accomplish. And also help them accomplish their goals too.

• 20:27Lenny Rachitsky?

  It's maybe a good time to just chat about DBT and the success the company's had. Like so many startups have tried to become a standard default layer of what's now called the modern, modern data stack. And I don't know, any startup doesn't use DBT or doesn't think about planning to use DBT. It's just like a incredibly rare success story. Some are just snowflake where it's just like, it's just the default for building large data startups. And, and most startups these days work with a lot of data. So my question is just like, what do you think DBT did most right to win in this and continue to win?

• 21:01Speaker 00

  So I think DBT did a lot of things, right? But I'll point out two that, that really stick out to me. And the first is just power and simplicity. And the second is a commitment to being open. And I'll touch on what I mean by, by those two things. So. When DBT was first getting started, you would hear a lot from companies like, "I don't understand, like, what's so special about DBT? We have a SQL templating tool at our company. We built one in-house. Like, this is really straightforward and simple." And it's true, like, DBT is really simple, but that is the power of it. And so our founders, Tristan, Drew, and Connor,

• 21:41Speaker 00

  they had a belief that the people who do data analysis work that really work closely with their business stakeholders should also be the ones to contribute to creating clean data assets in production, because that data prep work is a necessary prerequisite for any analysis that you do. And so DBT was really this belief that if you know SQL, we want to invite you to do these workflows that were traditionally held by data engineers. But, you know, you had to earn that right. And so DBT has this nice framework where it's harder to mess up, keeps data quality really high. But it is pretty simple to get started and learn. And that was really the unlock in the industry. They were definitely solving a pain point at the right time.

• 22:27Speaker 00

  And then the second thing is this commitment to being open. So DBT is open source, and that's the main kind of guts of DBT, where you write your business logic. And it helps in a number of ways. Specifically, it helps with flywheel, keep the flywheel running, and also with network effects. And I'll explain what that looks like. So DBT is really easy to get started with at your company with reduced friction. You know, we're building a product that people like, so they talk about it. They want to share it, both at their organization and with other companies. Other companies get started with DBT, again, with reduced friction. We now get to see this really diverse set of use cases for DBT

• 23:10Speaker 00

  across company sizes, across industries, and it allows us to build a truly horizontal company.

• 23:18Speaker 00

  As our company grows, we get to invest back into our community and our product and the flywheel begins to spin faster. And then meanwhile, we have a really large user base. So we have 20,000 companies using DBT every single week. And that attracts partners to want to build for DBT. So they share best practices, build workflows. And now if you're a company and you've standardized on DBT, you've really unlocked and integrated modern data ecosystem that wasn't available for you before. So that has a flywheel and also kind of benefits everyone that decides to be on the standard. And so it's those two really important trends that made DBT so powerful today.

• 24:01Lenny Rachitsky?

  So what I'm hearing there is essentially the product was right for what people needed to solve. There's also like a product-led component, open source, free, self-serve kind of piece that people adopted, used, oh, and start working and then kind of scaled and started paying for it. And then there's kind of like an alignment of the vision of where this was going and how it, and it fit with how people wanted this to work for them. Is there anything else? Because a lot of startups do that. And that all sounds really smart and good. But a lot of startups try to do those things and no one cares. Maybe their product isn't necessarily what people are looking for. Maybe they're, they don't get the right distribution. I don't know. Is there anything else that you think they did really well that helped them kickstart this to even be a thing?

• 24:44Lenny Rachitsky?

  Like, is it timing that was really great? Is it like specific influencers early on?

• 24:48Speaker 00

  I think timing was really important with the success of DBT that they were there when the cloud data warehouses were really exploding and growing in an enormous way. And, you know, DBT Labs started as Fishtown Analytics, a consulting firm. So they worked really, really closely and hands-on with all of their consulting partners to get the pain point and really solve firsthand challenges that they saw. I think that combination of being at the right place at the right time and also getting to work really closely with people's day-to-day problems created a really special experience.

• 25:29Lenny Rachitsky?

  I didn't know that. That's a really important element of the story is basically they were focused, like, how long did they do that, Fishtown Analytics?

• 25:38Speaker 00

  Consulting part of the business was. Almost two years.

• 25:42Lenny Rachitsky?

  Okay, so they basically spent two years solving this problem, like basically manually for people. And that's such a, that's such a great way to understand real pain and figure out how to solve it.

• 25:53Speaker 00

  Totally.

• 25:54Lenny Rachitsky?

  Awesome. Okay, so that's a really interesting insight, just like spend a few years, just like manu-, like it sounds like it was almost manual, right? Like manually helping people transform their data using whatever tools already existed.

• 26:05Speaker 00

  Yeah, well, they were building DBT and using DBT to help them do their jobs better in supporting their clients. And whenever they encountered paper cuts or friction or the workflow was taking longer than they expected, they would build that into DBT. And that really matured the experience of the product because the people who were building it, the founders, were also day to day working with these customers, clients that had pain points.

• 26:36Lenny Rachitsky?

  That reminds me of a story you told me about how you made your edge team do some manual work of an algorithm involved in transformation. Can you share that?

• 26:47Speaker 00

  Okay, so I'm going to preface this story by sharing that I'm a huge math nerd. And one of my favorite books on logic is called Godel-Escher-Bach. And in this book, there's a fun scene where there's an ant farm that bands together to do the work of a computer, flipping bits from zero to one to solve logic gates. And so this chapter of that book was really the inspiration for an exercise that I ran my team through. So about a year ago, we were doing a big zero to one new project at DBT Labs. And we were going to change the algorithm for how we built customers' data transformation graphs. And I needed a way for the team to really internalize all of the changes that we were going to make.

• 27:32Speaker 00

  And I needed them to own it because otherwise they wouldn't be able to anticipate all of the edge cases. And it wouldn't be quite as durable. You couldn't copy paste the algorithm. So I showed up to a team offsite with a spool of rope and sticky notes. And I think my team looked at me crazy, went with two heads when I started to tie people up to create a graph. So each node of the graph was an engineer and I, the rope was kind of the edges of the graph to connect them. And then we worked through the new algorithm extremely slowly, step by step. And it was a way that you couldn't leave that exercise without knowing exactly what was going on because everyone had a role to play.

• 28:16Speaker 00

  So I think a lot of times when you're starting something new, you get into a situation where a few people really understand it and they're running way ahead of the rest of the pack. But I needed a way for the whole team to go along for the journey. So I'm constantly trying to create these important moments or memorable moments for the team. So that it's centered around our mission and they can have the ownership of taking the project and making it successful. And so it was perhaps a overly creative or kooky way to spend the day, but it was, was really successful.

• 28:49Lenny Rachitsky?

  What was the actual algorithm you were trying to implement?

• 28:52Speaker 00

  Um, we, we were trying to figure out how to make a kind of a flipping the way that we run people's DAGs from an imperative way to a declarative way. So instead of like running things left to right when data arrived in your warehouse, you think about it, is there a first, like what would need to happen to make your data SLAs be materialized in time?

• 29:16Lenny Rachitsky?

  Awesome. And uh, it sounds like the team uh, found that valuable.

• 29:20Speaker 00

  Yeah.

• 29:20Lenny Rachitsky?

  Okay. Uh, reminds me of a clip from this last season of Ted Lasso where they have use red strings and they, I won't get into it, but it's a, if you've seen it, you will know what I'm talking about. I want to come back to your chatting about open source versus not open source. So some part of DBT was, is open source and some isn't. I'm curious how the team decides what is open source and what should be open source, what isn't open source and how, and what to charge for.

• 29:49Speaker 00

  We think about DBT open source, it's really the guts of the data transformation. It's where you describe your business logic. And then on the cloud side, we build proprietary software that supercharges the development lifecycle and the productionization of DBT at scale. So what we think about as leaving for our cloud offering is we deal with state, so stateful interactions. And also any kind of cross-team or structural collaboration. We want to reserve that for our proprietary offering. And I think it's really important to have that distinction of, you know, what, what do you believe should be open source or what is the open standard that really matters?

• 30:32Speaker 00

  Ecosystem to us is really important, so it's important that that remains open source. But then we want to supercharge that and experience with kind of an open core model and build proprietary software that that makes people much more successful at using DBT.

• 30:48Lenny Rachitsky?

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• 31:31Lenny Rachitsky?

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• 31:57Lenny Rachitsky?

  I know you also spend a lot of time thinking about pricing and willingness to pay and things along those lines. Is there anything you could share about what you've learned about how to think about pricing for a tool like this or even in general?

• 32:09Speaker 00

  Pricing and willingness to pay is such a hard conversation, and lots of startups don't do this early enough in their company journey. Likely a side effect of zero interest rates where investors were happy funding GitHub stars and usage, and companies never thought about how are we going to make revenue or make money, which is, it's important. So You know, for us at DBT Labs, I don't claim to be perfect at it, but we're trying to get a better muscle around it. And I always think about Madhavan, who wrote this book, Pricing Innovation. I know you've had him on the show before, but he shares that you don't get to decide if you're going to have a pricing or willingness to pay a conversation. You only get to decide what.

• 32:52Speaker 00

  So it's much better to have that conversation before you build the product than have it when your sales team's trying to sell something and people aren't excited about what you've built, aren't willing to pay for it. And at DBT Labs, we have this value. It's one of our core values that says, we are more concerned with value creation than value capture. And we really mean this. When we talk about what is the value of DBT Labs to our customers, they often talk about how it's either 20 to 35% as valuable as what they spend on their cloud data warehouse. But what we charge our customers is a very small fraction of that 20 to 35%. And that's by design.

• 33:34Speaker 00

  And last year, we did our first ever pricing change in the company history. And you learn a tremendous amount when you have that event because you get to test the price elasticity of your customers. And it's so important to learn that lesson while the company is still smaller or the stakes are lower because pricing is always evolving. It's not a fixed thing. It gets more complex over time. And so we have to think about it quite a bit because

• 34:04Speaker 00

  my team builds proprietary software for DBT Cloud. And when we lose a deal, we most often lose it to DBT Open Source. And we like it that way. We're happy to lose to ourselves. But we have to really think very deeply about what are people willing to pay for and what moves the needle for them and focus on that.

• 34:26Lenny Rachitsky?

  I'm so curious what that pricing process was like to figure out what to change. Is there anything you could share about just like what that was for you? Or what are some just surprises that came out of that process? Or just like, oh, wow, we didn't expect that in these conversations?

• 34:42Speaker 00

  It's really like an all hands on deck conversation. Pricing is so cross cutting because it's a finance discussion as well. You're kind of modeling out things in spreadsheets and figuring out how that might impact the business. But you can't just solve these problems in spreadsheets. You have to go talk to customers, test the waters, understand where people's appetites are. And sussing that out is really hard. And then, of course, there's a product piece to it, too, where you have to affect it and communicate it as well. So it was very cross cutting. We learned a lot. We track our conversion rates really carefully. We track our turn rates very carefully.

• 35:23Speaker 00

  And I think largely we were, we were happy with the, the change that we made. And we, we felt like one of the big things that we were trying to solve for was have our pricing catch up to how people valued the tool.

• 35:40Lenny Rachitsky?

  How many people did you end up talking to? Who is doing these conversations? And is there anything really important you learned about how to ask these questions in these sorts of leniency pay conversations?

• 35:50Speaker 00

  So we talked to dozens. It was a combination of product and product marketing, having the conversations. And, you know, people aren't very willing to share explicitly like what they will pay. But there's some tools that we use on relative value. People most think about what is the relative value of DBT in their cloud warehouse? And we also tried to employ some of the tactics that we tried to suss out. What, what do people view as very inexpensive? What's a price point that's very cheap or a no brainer? What price point is maybe fair or comfortable for them? And what would be kind of too expensive? And then we had all the data back to figure out where we landed.

• 36:34Lenny Rachitsky?

  I want to come back to M and A for a bit. I had a few more questions there and I kind of moved on from that. And so again, you've done a lot of work within the M and A realm. Something that I saw recently, and this connects to the fact that a lot of startups now are looking to get sold. This VC Hunter Waugh, he's a founder of Homebrew Ventures, had this interesting blog post where he basically suggested, you should actually think about being public about the fact that you're selling your company, which is kind of crazy because in the past, you never want to come across as too selly. Like, I don't want people to think I'm desperate. And his point is like, many startups are desperate right now, and that's, it's okay to be public about that. And then in theory, creates more of a bidding

• 37:18Lenny Rachitsky?

  situation where many people know versus keeping it secret and kind of in enclosed rooms. So my question is just, what do you think of that? Do you think that's effective strategy? Is it not?

• 37:28Speaker 00

  I think it's good advice. If you're in a hail mary situation where you're, you're looking for a home or you need an exit for your business, it's better to be transparent and cast a wider net. And you're right. And like, previous times, founders tried to be a little bit cute or obfuscate that they were evasive of the situation that they were in because they wanted to drum up some competitive interest when there, there really wasn't any. But, you know, unfortunately, in today's climate, too many companies are in that spot. So it's impossible to hide it. And so the better approach is just to be transparent. And I see it pretty regularly and it, there's absolutely no shame in sending a note that says something like,

• 38:09Speaker 00

  "Hey, we're looking for an exit for our company. X, Y, and Z didn't pan out as we expected. We built a really interesting product and we want to keep the team together. We're running a process. Are you interested?" Really, just as simple as that.

• 38:23Lenny Rachitsky?

  I've seen a lot of companies put together these really detailed decks or even websites of just like, here's the team, here's what we built, to be very kind of promotional about it. Is that something you've seen? Is that something you'd recommend?

• 38:35Speaker 00

  Yeah, usually in this, these situations, people are acquiring the teams. And so having your data room together, really the most important thing is, this is, these are the team members that are going to come along with the acquisition is the biggest motivator for why a buyer would get excited.

• 38:52Lenny Rachitsky?

  You made this point earlier that a lot of the seeds need to be planted early for you to have the best outcome. And this reminded me, so I had a startup, LocalMine, that we sold to Airbnb. And I met Airbnb initially at a year before we actually started exploring the process at a random party at South by Southwest, where I was, I actually have no memory of this party, but the head of product at Airbnb, Joe Bott, remembered it and came back to us a year later and was just like, hey, what are you guys up to? Maybe we could collaborate on some stuff and that lets you an acquisition. So I think that's just, just wanted to touch a band on that point of just the power of, the way I thought about it is let a thousand flowers bloom, just like meet everyone, get the word out that you're around and what you're doing so that in the future, when someone has that problem, like, oh, that company, maybe we should talk to them.

• 39:37Speaker 00

  Yeah, you want to make sure that the buyer knows you are before the acquisition moment. And, you know, hopefully that's because you've made an impact and they like what you're building. Maybe you've inflicted some pain on them. But yeah, certainly creating those connections well ahead of an exit event is important.

• 39:58Lenny Rachitsky?

  And specifically there, it's like meet people at your competitors, potentially. For us, like Airbnb was never even a potential company we would sell to because it had nothing to do with it, but ended up making sense down the road. What's like the realm of the companies and people that you think people should think about meeting?

• 40:12Speaker 00

  If the company is buying a lot or they're active, they often have corp dev teams. And so use that corp dev team to your advantage. Like, it's their job to meet absolutely every company that could be potentially interested. So take that meeting, say you're not interested in an acquisition just yet, but push them to make an introduction to someone that could sponsor the deal. So usually that's someone in product or maybe a GM. And use that as a starting point for maybe a, just a conversation, maybe something more like a partnership, but get the corp dev team to work for you.

• 40:50Lenny Rachitsky?

  What if you're at the other end of the spectrum and you're in kind of dire straits right now? And you're just like, oh, man, what do we do to potentially sell this company? I know odds are not going to be great, but just, what do you suggest folks do in terms of, I guess, finding connections to potential companies that might be acquirers?

• 41:07Speaker 00

  Yeah, I mean, use your, use your network. Usually your venture capitalist has a really big network. And one of the things that I hear founders feeling the most nervous about is like, A duty to return the money to the investors and maybe this is unpopular thing to say on a podcast, but like your investors understand that they're not making their money back. And what they want to do instead is have you end up at a really great company like an Airbnb, because that will help them down the road. It's all about the long game, but use your investors to help you find connections at different companies that could be buying and don't worry so much about disappointing them

• 41:49Speaker 00

  or being really realistic about where you are in your company journey.

• 41:53Lenny Rachitsky?

  Yeah, to build on that, like I'm just an angel investor. I'm not like the lead fund and they feel differently, I imagine. But the last thing I want for founders to get stuck at a company they hate and just so that they could return some money or have some kind of outcome. Like I'd rather they just, just give up, move on, like life is short.

• 42:11Speaker 00

  Yeah, I think founders forget that it is so risky investing in early stage companies that portfolios, 50% of portfolios don't return, investments don't return anything. And that's just part of the game and it's, it's a very acceptable path where, you know, hey, we gave it our best shot, it didn't work out and moving on.

• 42:36Lenny Rachitsky?

  Which is tough a lot of times for founders that are told like it's all about grit and not giving up and don't quit. Sometimes, sometimes you should quit.

• 42:43Speaker 00

  Oh gosh, yeah, I don't want to be, I don't want to say that. I love that, you know, people, I think being founders, it's, it's an extremely lonely role sometimes. And it is very hard to, to know what your next chapter will look like or what the journey will look like. And sometimes you really are out of cash and you do have to find a home. But you know, I hope, I hope that you can continue to fight and find a way forward.

• 43:08Lenny Rachitsky?

  Agreed. Specifically for people thinking about selling their company, are there any companies you think are good companies for people to look at right now that are actively acquiring or open to M and A?

• 43:19Speaker 00

  This is a tough one. I think a lot of companies are on the sidelines for a number of reasons.

• 43:26Speaker 00

  They could be on the sidelines because they just did an acquisition and they're trying to digest or integrate that company. They could be on the sidelines because they're not growing headcount as much. And M and A is often a work chart gymnastics of folding the target company's headcount into your budget and plan and maybe just don't have a lot of space. Or probably more common right now is there's just a general uncertainty about the future. And in highly volatile markets, people want to take care of their own and even the best M and A deals add a level of complexity that a lot of buyers are just not looking to take on right now. And so there are a number of reasons why

• 44:08Speaker 00

  people might sit out. But what I would do if I were in a position of wanting to sell my company is I would come up with a buyer set of maybe a dozen. And really, there aren't more than a dozen companies that will find what you're doing to be a very good fit. Start with your buyer set and then start calling the list by looking at some of the criteria that might count people out. And then go have those conversations. And if you're in a hail mary situation, be very transparent about it, maybe open up the buyer list. But if you still have some room, I would maybe focus on two to three partner or buyers and really play the different playbook, which is inflict pain, make it

• 44:50Speaker 00

  really hard for them to not notice you, but but do it with a smile and be friendly while you do that.

• 44:57Lenny Rachitsky?

  Sometimes with M and A discussions, there's a lot of like subtlety to the way you communicate where you don't come out and be like, please, we'd love to sell our company to you. Any advice on just the phrasing and how to approach it? Or do you think it's just, it's fine, just tell us, we're looking to sell our company. Are you interested in being a buyer?

• 45:15Speaker 00

  Yeah, I just wouldn't be too clever here. Like, everyone understands, like, oh, I'm evaluating strategic alternatives. It means you're looking to sell your company. And it depends, like, are you looking, do you have time? If you if you have time, yeah, don't don't come out and say, hey, I'm for sale. Like, that's not going to end up in a good outcome. But depends where you are in your your company journey. If you have time.

• 45:43Speaker 00

  Then don't talk about M and A at all. Like, that's the last thing that you want to speak about. Instead, you're talking about maybe collaborating or partnerships, how do we work together? Knowledge sharing and M and A is a dirty word if you have like a lot of runway and you're and you're going to try to continue to pursue an independent path. But if you're, if you're out of time, you're, you're out of time.

• 46:08Lenny Rachitsky?

  That's such good advice. I remember the term we used was, uh, we want to explore a strategic partnership. And everyone's just like, and knows what you mean by that, but you just kind of don't want to say it.

• 46:18Speaker 00

  Yeah, it's like everyone, everyone in the room is kind of looking like, oh, yeah, yeah, okay. Strategic partnership or a strategic alternative. It's like, we all know these code words and we understand the situation you're in.

• 46:30Lenny Rachitsky?

  Yeah. When do you think that many market might pick up again? I know it's impossible to predict. Do you have any sense?

• 46:37Speaker 00

  Yeah. I wish I had a magic ball. That'd be pretty sweet. Uh, I think what is happening though, is we're like far enough out from the peak of the markets. So the, the peak was really like November of 2021. And why does that matter? Uh, two things. One, founders are coming to terms with valuations that they maybe received at the highs of the market are no longer going to hold in this market. And companies are out of cash or maybe out of options. We'll be better assets entering the market soon. And at a certain point, the opportunities will just be too great. That that will incentivize a lot of the buyers that have been on the bench to start participating again in the M and A market.

• 47:22Speaker 00

  And I don't know exactly when that will be, but I think we're, we're pretty close. I think we're pretty close.

• 47:28Lenny Rachitsky?

  You mentioned a value that you have at DBT. I forget exactly what it was, but I'm curious. What are the other values that you have at DBT, whatever you can share? Always curious what principles and values companies come down to, to help drive the way they think.

• 47:42Speaker 00

  The value that I shared is we are more concerned with value creation than value capture. And that really like drives everything that we do. We try to put a lot of good out into the world and it pays back, um, kind of slowly. The whole mission of DBT Labs is to help analytics engineers disseminate organizational knowledge through data. So we really believe in also being participants of sharing that information and getting more people knowledgeable about that, about all sorts of things. Transparency wins. We're a really transparent company. Like, we share our board decks. We have lots of communication and participation in all of our slacks. We're a writing culture. We

• 48:25Speaker 00

  have hard conversations in the open. So that's another, a big one. Transparency always wins. We are humble. Like, we don't ever feel like we're successful. Like, we kind of come at this from a very humble space where we feel like we have to serve our community and our users, and that really motivates us. And then another one is just work done well is its own end, and it's really focusing on the journey and not the end destination.

• 48:56Lenny Rachitsky?

  Awesome. I want to do a post someday of just like, here's the values all these different successful companies have come to and see if there's any patterns. I'm actually doing a post right now on Snowflake and on Figma. And what you touched on, there's such a connection and a thread of obsessing with your users and making sure they're happy. At Figma, I forget exactly what it is, but it's just like, they're just like, in this article, it's going to come out tomorrow, actually, so people get a sense of when we recorded this, where they think of their company of software as a service, where service is their number one goal. They actually provide service, and software is just a way to do that. And then at Snowflake, their number one core value is put customers first. And they talk a lot about how that just actually informs of their prioritization and all their

• 49:41Lenny Rachitsky?

  thinking. And so it's interesting that also comes up a lot in what you're talking about, which I think it's easy to say, but I think what actually separates companies that succeed is they actually put this into practice.

• 49:51Speaker 00

  It's really interesting, too, because a lot of the people who work at DBT Labs came from the community. So they feel this real ownership in making the experience an excellent one because they were so compelled to come join DBT Labs because the product changed the way that they work or changed their lives. And so that commitment to the community and product experience is really, really strong.

• 50:14Lenny Rachitsky?

  This is another thread, maybe we'll go down real quick. I'm working on a different post around Reddit and how to work with really opinionated users that have strong opinions about changes to the product. And the way they described it, these guys were there for five years, working with the community on the product, is that like to your users, the product is their baby, basically. It's like, they think it's theirs versus the company's. And I'm curious, having a really strong opinionated community is what it sounds like you also have. What have you learned about just working with them to build product that makes them happy and avoid, you know, revolts and, and really upsetness?

• 50:51Speaker 00

  It's hard as, as you grow. I think it's just a challenge because our community gets bigger. You can't service like everybody's needs. But I think what we've done is like, everyone is very deep in our own product. I think one of the cool stats is at DBT Labs, we have over 30% of our employee headcount has contributed to our data transformation workflow. And so that's across like every discipline. It's in, obviously product, obviously in our data team. Like our marketing team also contributes to data transformation and our engineering team will also contribute to our internal DBT analytics project.

• 51:32Speaker 00

  And that sense of like really understanding what the experience is like and then soliciting as much feedback as we possibly can. We have a DBT Slack community of 50,000 and all of our employees are like in that Slack

• 51:49Speaker 00

  channel regularly and can feel when we like mess up or we don't quite deliver an experience that we're, we're proud of. Like you will just see like dozens of people trying to jump on board and, and try to make it better.

• 52:02Lenny Rachitsky?

  Is there any other frameworks or just general processes that you found to be really useful in building awesome product, running teams?

• 52:10Speaker 00

  I'm not a big framework person, but there's kind of two sayings that I find myself repeating or either to myself or to others. And it's,

• 52:19Speaker 00

  Um, worse is better and tech debt is a champagne problem. And what do I mean by that? It's really to help me combat this perfectionism because perfect doesn't exist. And you should instead go with good enough because when you ship, that's the moment when you get to learn a lot from your users. And you just can't anticipate it. You try very hard to understand exactly how people will use the product and get all the edge edges ironed out, but you can't until you ship. And I'll, I'll share an example. So my team helps support the DBT cloud scheduler. And the initial version of the DBT cloud scheduler was pretty naive. Like, we were a little embarrassed by it.

• 53:02Speaker 00

  It was a big old for loop over a big old jobs table. And so we would look like, is this job, is it time for this job to run? Okay, yes, run this job. Okay, it's not time for this job to run. Next, continue on like, is it time? Yes, run this job. And it would just loop over and it's extremely naive and very simple, but it got the job done. And I tried to remind the engineers, like, we would be so lucky to have tech debt because that means people are using the product. And, you know, now we've had to rebuild our scheduler several times over because we do have meaningful scale. We have 8,000 companies using our scheduler. We have to manage 10 million runs per month.

• 53:44Speaker 00

  But what we didn't need at launch was a distributed scheduler with Go workers and Rabbit MQ. We just didn't need it because we had no users. And so these two sayings that worse is better and tech debt is a champagne problem just really reminds people like, let's ship, let's get it out into the user's hands. And then we'll learn and iterate and it'll be a better experience for them.

• 54:08Lenny Rachitsky?

  That's a good segue to my last question. So you were a PM before this role. You have strong experience in investing, investment banking, business in general. I'm curious what you think product managers should maybe focus on more or learn more or lean into to become stronger product leaders, based on the experience you've had moving into product.

• 54:30Speaker 00

  So I pull a lot on my experience, or some of the things that I did was as an investor in my current role in product. And maybe I'll touch on like, what is the skill of a venture capitalist? It might be a little bit foreign for people, but venture capitalists, they spend all their day meeting lots of different companies, context switching. They have to know like a little bit about quite a lot of different things. And they do this to like refine their investment taste or refine their investor judgment. And they're also investing a lot in their network and connecting people, supporting people and mining people for ideas that are way smarter than they are. And so you do that all the time in venture.

• 55:11Speaker 00

  And I've brought a lot of those skills with me into product and it translates really well. The first is I still spend a lot of time investing in my network. And I think it's an underrated way for a PM to spend their time. And I try to build a network of operators at other companies that are like DBT Labs, that are growing nicely, maybe a little bit ahead of where we are. And I ask them questions like, how did you navigate open source? How did you navigate pricing? How did you navigate acquisitions? And I take kind of the best ideas, figure out which ones I can apply and bring it back to DBT Labs. The second thing is I really think my specialty or my superpower is that I'm a T-shaped generalist.

• 55:53Speaker 00

  And so I know a lot about, I know a little about a lot of things from, from finance to business to product. I have to go a lot deeper in product in the areas that I specialize in. That's where the kind of tail of the T comes in. But it's precisely because I've had a diverse background that makes me more effective when I'm trying to get things done within the organization. Cause I have just more credible experiences that I can pull from. And then the last thing that I think maybe doesn't show up day to day in my product work, but in investing, you're constantly thinking about risk and the power laws. And we touched on this before, but like most investments don't work out, you lose the dollars that you put in, but all the returns come from these rare events that

• 56:38Speaker 00

  make up for all the losses. It's you have to think about what are the uncapped upside opportunities in investing? And I think in product, you still have to do the same thing. Like you can't, if 50% of the things I worked on went to zero, like we'd have a problem. But it encourages me to continue to make bets for the company that has the chance of bending the trajectory of our business.

• 57:02Lenny Rachitsky?

  We've reached our very exciting lightning round. I've got six questions for you. Are you ready?

• 57:07Speaker 00

  Yeah, let's do it.

• 57:08Lenny Rachitsky?

  What are two or three books that you've recommended most to other people?

• 57:11Speaker 00

  Okay, so two books that helped me learn a lot about myself, a range. It's a book about generalist and also Quiet. It's a book about introverts. And then I like a lot of biographies. So a few of my favorites are Snowball about Warren Buffett, Made in America about Sam Walton and Leonardo da Vinci.

• 57:30Lenny Rachitsky?

  What is a favorite recent movie or TV show?

• 57:33Speaker 00

  Okay, so I almost watched a movie in preparation for this podcast, but I really don't watch things except in the holiday, during the holidays. I like Succession, but I have not seen the latest season.

• 57:46Lenny Rachitsky?

  Wow, you're in store for a treat. Favorite interview question you like to ask?

• 57:52Speaker 00

  When's the last time you had to teach yourself something new and how'd you do it? And so I like to test for growth mindset and a thirst for learning. And then also why DBT Labs? I think a lot of people who come to DBT Labs have very authentic reasons why they're drawn to the company. And in moments where things are tough, it's the answer to that question of why, why are you here? It's going to make all the difference.

• 58:17Lenny Rachitsky?

  And sounds like what you look for is just like, like genuine enthusiasm.

• 58:21Speaker 00

  Yeah.

• 58:22Lenny Rachitsky?

  Awesome. What are some favorite products you recently discovered that you really like?

• 58:27Speaker 00

  I like Belly. It's a consumer social app that lets you find and discover restaurants and rate them and with your friends. It's been a lot of fun looking at the New York City restaurant scene.

• 58:37Lenny Rachitsky?

  Hmm, I've not heard of that. Awesome. What is something relatively minor you've changed in the way you all do product that has had a lot of impact?

• 58:45Speaker 00

  Do fewer things and try to single thread the team as much as possible.

• 58:50Lenny Rachitsky?

  And single thread meaning like one main priority?

• 58:53Speaker 00

  One mission. Yeah, we're all working, rowing in the same direction.

• 58:57Lenny Rachitsky?

  Final question. You have a podcast. First of all, tell us what it's called. But second of all, what's a favorite podcast of yours other than this podcast and your podcast?

• 59:05Speaker 00

  Yeah, it's called the Analytics Engineering Podcast. So if you want to learn more about the data industry, I host it every other week with our CEO Tristan Handy. It's a lot of fun. Check it out. Other podcasts that I really like are in-depth. It's First Round's Podcast by Brett Barson. He interviews a lot of operators about how they do their very best work. And another podcast that I really like is the Logan Bartlett Show, which touches on timely trends in tech.

• 59:34Lenny Rachitsky?

  And in-depth, I think Todd Jackson actually hosts a lot of the episodes too. Also, he's a fan of the podcast. Definitely check it out. And then name, say your podcast again, and how can folks find it?

• 59:43Speaker 00

  It's called the Analytics Engineering Podcast.

• 59:46Lenny Rachitsky?

  And it's just on podcasting apps?

• 59:48Speaker 00

  Yes.

• 59:49Lenny Rachitsky?

  Amazing.

• 59:49Speaker 00

  Check it out.

• 59:50Lenny Rachitsky?

  Julia, we've talked about inflicting pain and strategic partnerships and why work is better. Thank you so much for being here. Two final questions. Where can folks find you online if they want to reach out? And how can listeners be useful to you?

• 1:00:03Speaker 00

  You can find me on Twitter, J underscore Schottenstein. And you can also find me in the DBT Community Slack, also Julia Schottenstein. Send me a note, reach me there. And I'd love to hear from you. If you're have data problems or we can help serve your needs better, would love to chat.

• 1:00:22Lenny Rachitsky?

  Thank you so much for being here, Julia.

• 1:00:24Speaker 00

  Awesome. Thanks, Lenny.

• 1:00:25Lenny Rachitsky?

  Bye, everyone.

• 1:00:28Lenny Rachitsky?

  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 lennyspodcast.com. See you in the next episode.