No Priors Ep. 101 | With Harvey CEO and Co-Founder Winston Weinberg

1. 0:00 – 2:39

   Introduction

   1. SGSarah Guo0:05

      Hi, listeners, and welcome back to No Priors. Today, I'm here with Winston Weinberg, the co-founder and CEO of Harvey, which is building domain-specific AI for law, professional services, and the Fortune 500. They've now raised more than $500 million from investors such as OpenAI, Sequoia, Kleiner Perkins, GV, Bloodgill, and me. We're going to talk about how to do end-to-end workflows, how to serve conservative users, impostor syndrome, keeping pace with the blitz of the AI ecosystem, and also what lawyers will do five years from now. Winston, thanks for doing this.

   2. WWWinston Weinberg0:42

      Yeah, of course.

   3. SGSarah Guo0:44

      It has been, like, a wild two and-a-half years for you and Gabe and Harvey. Um, when you started the company in August of 2022, or at least when I met you guys for the seed-

   4. WWWinston Weinberg0:54

      Yeah, we started a little bit earlier, but about then, yeah.

   5. SGSarah Guo0:56

      ... uh, what was the moment of inspiration?

   6. WWWinston Weinberg0:58

      Yeah. So, Gabe and I actually had met, uh, a couple years before, and I definitely didn't know anything about the startup world and didn't have a plan of, of doing a startup. And what had happened was, he showed me GPT-3, which at the time was, you know, public, and, and I was, first of all, just incredibly surprised that no one was talking about GPT-3 and no one was using it in any way, shape, or form. Um, and he showed me that, and I showed him, kind of, my legal workflows. And we started the, the kind of aha moment was, we went on, uh, r/legaladvice, which is basically, you know, a subreddit where people ask a bunch of legal questions and almost every single answer is, "So who do I sue?" Um, almost every single time. And we took about 100 landlord/tenant questions and we came up with, kind of, some chain-of-thought prompts, and this is before, you know, anyone was talking about chain of thought or anything like that. And we applied it to those landlord/tenant questions and we gave it to three landlord/tenant attorneys. And we just said nothing about AI. We just said, "Here is a question that a potential client asked, and here is an answer. Uh, would you send this answer without any edits to that client? Would you be fine with that? You know, is that ethical? Is it a, a good enough, um, answer to s- to send?" And 86 out of 100 was yes. Um, and actually we cold emailed the general counsel of OpenAI and we sent him these results, and his response basically was, "Oh, I had no idea the models were this good at legal." (laughs)

   7. SGSarah Guo2:26

      Nice.

   8. WWWinston Weinberg2:26

      Um, and we, we met with the, the C-suite of OpenAI a co- a couple weeks after.

   9. SGSarah Guo2:31

      And, and the view was just, it's going to be good enough. Um, we should build a company around it.

   10. WWWinston Weinberg2:36

       Yeah.

   11. SGSarah Guo2:36

       For what domains?

   12. WWWinston Weinberg2:37

       I mean, I, I think what happened,

2. 2:39 – 3:46

   Harvey’s founding story

   1. WWWinston Weinberg2:39

      or the reason we were so confident about this, was the models... And, and even with GPT-3, you could get it to do a lot of tasks. You just had to really brute force it, right? Like, you had to brute force the amount of context, telling it which steps to take, et cetera. And the idea was over time this is just gonna get better, right? There are going to be... Either the models themselves are gonna get better or we're gonna be, we're gonna get better over time at figuring out how to provide them the correct context, how to, how to improve them, how to evaluate the results, et cetera. Um, and even just by playing with it for a decent amount of time, you could get that sense.

   2. SGSarah Guo3:16

      You are obviously not focused just on property law now.

   3. WWWinston Weinberg3:19

      Yeah.

   4. SGSarah Guo3:19

      Like, how do you think about the mission or scope of Harvey today?

   5. WWWinston Weinberg3:23

      Yeah. Um, so mostly we're, we're del- developing it for legal overall, but I would say that what we're building is the AI platform for legal and professional services, right? And if that sounds vague or it sounds like there aren't incredibly defined use cases for, you know, the small areas that we're building, that's on purpose. Like, the reality is, if you are using these tools

3. 3:46 – 6:39

   Capability improvement

   1. WWWinston Weinberg3:46

      and you don't think that you can take basically AI and apply to X industry and transform the entire industry, I don't think you're thinking ambitiously enough, right? And I think it's really hard because th- you know, these models can't just one-shot all of these really complex legal tasks, or, or in these other domains like tax and prof- other professional services. And so what you have to do is, you have to build a platform that is kind of constantly expanding and constantly collapsing. And so what I mean by that is, you need to build specific features and maybe agentic workflows, et cetera, that can do parts of a task, and then you need to combine them all together so the UI is simple and it, you don't have this, like, tentacle monster of a platform.

   2. SGSarah Guo4:28

      When did you realize that that was the, like... I think it's a really elegant framing of sort of product strategy for the company.

   3. WWWinston Weinberg4:34

      Yeah.

   4. SGSarah Guo4:34

      Um, uh, first implied in it is just, like, this, you know, and this has been true for y- you guys from the very beginning. I, I did think you were a little bit crazy when you described the level of sophistication of tasks, end to end, that Harvey would be able to do.

   5. WWWinston Weinberg4:46

      I still feel crazy. (laughs)

   6. SGSarah Guo4:48

      Uh, but you appear to be more, you know, like you don't look as crazy when you're right.

   7. WWWinston Weinberg4:51

      Fair.

   8. SGSarah Guo4:52

      Right. Um, uh, but I remember, like, a year and a half, two years ago, um, uh, like, it was very distinct to me how much you guys believed in capability improvement.

   9. WWWinston Weinberg5:02

      Yeah.

   10. SGSarah Guo5:02

       Like, where does that come from? And then also, how do you think about it internally in the company?

   11. WWWinston Weinberg5:06

       Yeah. So where does it come from using the tools?

   12. SGSarah Guo5:09

       Mm-hmm.

   13. WWWinston Weinberg5:09

       I mean, I think... I have been blown away by the amount of kind of C-suite, eh, et cetera, that haven't actually, like, spent that much time using AI. And the, the big moment for me was just the jump between GPT-3 and GPT-4. Like, when we got access to GPT-4, I went into my room, I think for just 24 hours straight, and tried to do every single thing that I couldn't do with GPT-3 or I had to very much brute force and, like, wasn't getting any efficiency gains from, and tried to do it with, with GPT-4. It didn't do all of them.

   14. SGSarah Guo5:42

       Yeah.

   15. WWWinston Weinberg5:42

       But the improvement was crazy, right? And no one was talking about it. And I, I found that something that also was very weird is, I would show GPT-3 and, and GPT-4 to a bunch of my friends and they would try to get it to do one thing, it didn't do the thing perfectly, and then they'd just stop, right? And so it seems like there was this large gap between...... I log into ChatGPT or I just use GPT-4 from an API or whatever it is, and I try something a couple times, versus I'm going to sit there and just hammer on this until it works, right? Um, and I think if you do that enough, you get the intuition for where things are going and how much better they can get. Um, how do we do that from a product standpoint? You can kinda think about, if you go back to that expand and collapse as, like, two general themes, you need to build productivity tools. And what I mean by this is, things that are useful for the highest amount of seats, right? And then you also need to build things that are streamlined vertical workflow from

4. 6:39 – 9:17

   Building teams around AI capabilities

   1. WWWinston Weinberg6:39

      start to finish, right? And what you can do is you can take those streamlined vertical workflows and you can chain them together to do more (laughs) increasingly powerful things, right? And so that's kind of how we think about it internally at the company, is, you know, there's a bunch of bells and whistles and things to add in terms of, like, sharing, collaboration, things like that. But you also just can basically build certain specific features that will do something from start to finish, like I upload all of my documents, uh, and a target company's documents, and it'll tell me in 72 countries where I need to file antitrust, and what do I need to file, and what other information do I need? And you can take pieces from that and add it to another part of a project.

   2. SGSarah Guo7:20

      How do you organize that effort at Harvey-

   3. WWWinston Weinberg7:23

      Yeah.

   4. SGSarah Guo7:23

      ... because it's, you know, like, I, I think you have a very special instinct and, um, commitment to going on the AI bender, I suppose, to, like, figure out what, to have-

   5. WWWinston Weinberg7:32

      It's gonna be a long bender.

   6. SGSarah Guo7:33

      Yeah, long, you know, multi-year bender, but, you know, one, one day at a time. Um, uh, to develop intuition for, you know, what the models are capable of doing with this, like, expansion, workflows, manipulation, assembly process.

   7. WWWinston Weinberg7:45

      Yeah.

   8. SGSarah Guo7:45

      I imagine that it's really hard to find all of that in a single person that understands-

   9. WWWinston Weinberg7:50

      Yes.

   10. SGSarah Guo7:50

       ... their research, the engineering, the domain, the data available, like, interacting with users. So, like, you know, how do you do that across teams?

   11. WWWinston Weinberg7:57

       Yeah, so I think we're starting to get better at it, um, and the thing that we're starting to land on is basically identify these systems as what we're calling AI patterns. So these are the 30, 50 things that we need to build that will be integrated into all of these different pieces of the product, right? So I'll give you an example of this. If you build an AI system that is really good at case law research, that can go into a motion for summary judgment, that can go into a billion different types of litigation use cases, right? It doesn't do that use case from start to finish, but you can add that on top. And so what we've been doing is we basically have teams that will work on building these other patterns, and then teams that are kind of implementing that across the entire platform. And that has been working really well. Um, it is definitely a work in progress. I think the other interesting piece to this is ha- we have a lot of lawyers (laughs) on our staff, right? Um, and we have a lot of j- we're gonna do this also in the other verticals that we're going into. And the domain experts are very helpful for basically, like, two main reasons. One is as design partners, so they're very good at saying, "Actually, you know, this is what we need to teach the models how to do. This is the step-by-step thinking we need to do. This is the output that the user wants," et cetera. And then the second piece, which is really hard, is eval, right? And so most benchmarks are completely

5. 9:17 – 12:37

   End to end task completion

   1. WWWinston Weinberg9:17

      useless for us, right? And so we'll get a, a model. You know, someone will give us early access to a model, and they'll say, "It's way better on all of these benchmarks," and w- we'll respond, "Well, uh, it actually isn't. Like, it's not use- as useful for us as, as a different checkpoint or something like that." Um, and the reality is, you have to hire very good lawyers who can actually evaluate these systems, and the same within tax and these other areas. And they can't be too junior, because if they were too junior and they were able to eval it, they would be senior, (laughs) right?

   2. SGSarah Guo9:45

      (laughs)

   3. WWWinston Weinberg9:45

      And so I think, uh, the intertwining of the domain experts into the actual, like, product sequence and development, and then evaluation at the end state, is very hard. Um, and it's something we're constantly working on.

   4. SGSarah Guo9:58

      What is the end-to-end task you're most excited about that you think Harvey will be able to do this year?

   5. WWWinston Weinberg10:03

      Yeah, filing an S-4, um, I think is something that is... The, the reason I like that process is it is a combination of external data, internal data, and a million steps, right? Um, and I think of workflows as basically a bunch of agentic systems that need to combine together, right? And, uh, if you think about knowledge work, professional services, legal, uh, honestly any swath of that, what you are doing is manipulating things based off of your internal context, external context, whether that's external data, whether that's data from your, whoever your customer is, your client is, et cetera, and then process of this is how, you know, this is how you do an LBO. This is how you do side-letter compliance. And then there's another step of that which is this is how you do side-letter compliance for this particular private equity firm, right? This is market for this particular clause. And the more complicated the workflow is, the more you have to combine all of those different elements together.

   6. SGSarah Guo11:00

      When you think about, like, having these very senior lawyers internally at Harvey doing eval, I imagine another piece of what is important there is, um, like, the experience that you had with your friends looking at these models, which is, like, you don't get that many shots on goal.

   7. WWWinston Weinberg11:16

      Yeah.

   8. SGSarah Guo11:16

      Right? It works or it doesn't.

   9. WWWinston Weinberg11:18

      Yep.

   10. SGSarah Guo11:18

       Um, the, uh, legal profession, especially, like, um, uh, more senior, more prestigious lawyers, um, you know, billable hour rate is very high-

   11. WWWinston Weinberg11:29

       Yeah.

   12. SGSarah Guo11:29

       ... and expectation of quality from, let's say, like, an associate or a model is very high. Like, how do you, how did you go about building that trust because the, like, you didn't start at the capabilities you have today?

   13. WWWinston Weinberg11:41

       Yeah. I'll start from one kind of, like, high-level distinction between two pieces. So if you go back to the productivity versus, like, specific specialized output, right?

   14. SGSarah Guo11:50

       Mm-hmm.

   15. WWWinston Weinberg11:51

       On the productivity side, the minimum viable quality of that output can be lower, because you're selling seats, and at the end of the day, there are multiple people reviewing it, right? Um, and so what you wanna do in that state is have... just show your work.... right? Like that is the most important thing. You wanna mimic exactly how a senior associate reviews the work of a junior associate. So you say, "This is why I did this. This is the information that I pulled, and here's an inline citation to the literal sentence that I pulled it from."

   16. SGSarah Guo12:18

       Mm-hmm.

   17. WWWinston Weinberg12:18

       "Is this correct or not," right? And that-

   18. SGSarah Guo12:19

       Make it cheap to check and, um, partially correct is still useful.

   19. WWWinston Weinberg12:22

       Yes, exactly.

   20. SGSarah Guo12:23

       Yeah.

   21. WWWinston Weinberg12:23

       And because, you know, a lot of how these law firms work and, and again, the big four as well is the junior produces some sort of output, the mid-level associate reviews that, and then the senior level associate reviews that, and then the partner reviews that, and then it goes to the client, right? And so you do get a structured

6. 12:37 – 17:21

   Beginning with large industry leaders

   1. WWWinston Weinberg12:37

      pyramid of like a hierarchical review, right?

   2. SGSarah Guo12:40

      Mm-hmm.

   3. WWWinston Weinberg12:40

      Now let's go to the specialized system. The specialized system, at the end of the day, you're actually trying to just from start to finish produce that output, right? So the minimal viable quality on that is much higher, but it's also easier to get higher because you are trying to build systems that just produce the same output and do the same task from start to finish, kind of like a specialist, right?

   4. SGSarah Guo13:02

      It's just much more scoped.

   5. WWWinston Weinberg13:03

      It's much more scoped, and evaluation is much easier, right? Like how do you do evaluation on Copilot or Enterprise GPT, et cetera? That is very difficult. It is much easier to do evaluation if you can do evaluation at each step and make sure that recursively that step was done correctly.

   6. SGSarah Guo13:19

      Okay, so there are different expectations for different pieces of the Harvey product.

   7. WWWinston Weinberg13:22

      Yeah.

   8. SGSarah Guo13:23

      Um, there's still like conservative customers, right?

   9. WWWinston Weinberg13:26

      Massively.

   10. SGSarah Guo13:26

       So, you know, one of the things that was surprising to me in like 2023, early 2024 was the set of people that you decide to work with first. (laughs)

   11. WWWinston Weinberg13:35

       Yeah.

   12. SGSarah Guo13:35

       And that were willing to work with you, right? A&O, PwC, like high quality brands that were generally larger. Like there's been a, um, uh, I think for maybe a decade in technology investing, a, uh, expectation that if you start with the mid-market, you start with your friends and startups.

   13. WWWinston Weinberg13:53

       Yeah.

   14. SGSarah Guo13:53

       Like it's just easier. The requirements are lower. Um, they're willing to take risks. Uh, why do the opposite here?

   15. WWWinston Weinberg13:59

       Yeah, so I think that if you are... I guess going back to what I said in the beginning of the ambition should be (laughs) take X industry, apply AI to it.

   16. SGSarah Guo14:07

       Mm-hmm.

   17. WWWinston Weinberg14:08

       Um, if you are doing that, you need to partner with that industry, and I think you also need to make sure that your brand and what you're building actually makes sense to what they care about. So I'll give you an example of this or, or just kind of like a reference point. A&O Shearman is almost 100 years old and they became famous basically advising on the abdication of, I think it was King Edward VII-

   18. SGSarah Guo14:30

       (laughs)

   19. WWWinston Weinberg14:30

       ... from the throne.

   20. SGSarah Guo14:31

       Okay. Good trivia.

   21. WWWinston Weinberg14:32

       My point is-

   22. SGSarah Guo14:33

       Yeah.

   23. WWWinston Weinberg14:34

       ... these are incredibly old, like have very prestigious and a long line of history, right?

   24. SGSarah Guo14:41

       Yeah.

   25. WWWinston Weinberg14:41

       And so in order to work with them, you actually have to kind of partner with them and say, "These are the different workflows that we're gonna start building with you, like use them as design partners." And you also need to make sure that you are kind of like building a brand around that. So not only is it just actually working with those higher tier firms, but you also wanna work with the data providers that are really important, right? So Lexis is in- is involved in this round and we're really partnering with them to also bring a lot of the kind of goodwill and trust and things that they have brought to the industry and, and really good products and combine that with our AI as well. Um, and so if you are able to do that, if you are able to show that you are working with the industry and get the trust from the folks that are basically seen as the highest, you know, degree in those industries, it is much easier to work with the rest of the industry. And we thought that that was very important. You know, we- we thought for a while that maybe we would do s- you know, a self-serve model, um, and we would kind of try to do PLG and- and things like that, but we found that no matter what, you eventually have to get the trust of the industry. And the best way to do that is to actually go after the hardest people first.

   26. SGSarah Guo15:51

       Yeah. I- I think there's, um, perhaps an opportunity in AI, and we'll- we'll see if this is true. Um, you're already like continually collapsing and trying to simplify the experience-

   27. WWWinston Weinberg16:02

       Yeah.

   28. SGSarah Guo16:02

       ... of using Harvey, right? And this has been like impossible in software to date. Um, one of the reasons people would start like, you know, SMB or mid-market is they'd be like, "Well," like, "once it becomes an enterprise product, we will never have the simplicity required to serve other customers."

   29. WWWinston Weinberg16:18

       The- the training, just the training cost of like implementing that, (laughs) that technology is gonna be impossible. No one will buy it.

   30. SGSarah Guo16:24

       Yeah.
7. 17:21 – 20:40

   Working with users skeptical of automation

   1. WWWinston Weinberg17:21

      user uploads an SPA, Harvey says, "Hey, would you like to do one of seven things to it?" Right? And so you can collapse that back down into a UI that is actually very simple. And if you actually think about how the UI for professional services is just email, like that's it-

   2. SGSarah Guo17:35

      Mm-hmm.

   3. WWWinston Weinberg17:35

      ... right? And so what you can do is, again, you can build all these different features in the system, but then you have to have a really clean and elegant way to combine it all so the user can actually find those things, right? You don't want a system that has 10,000 workflows and you have to somehow filter through them and figure out what you need, right?

   4. SGSarah Guo17:52

      Kind of what we have in business software, et cetera.

   5. WWWinston Weinberg17:54

      Yeah. That's exactly what we have.

   6. SGSarah Guo17:55

      (laughs)

   7. WWWinston Weinberg17:55

      Yeah. And it's awful and it takes forever to learn how to use it.

   8. SGSarah Guo17:59

      I know how to use email.

   9. WWWinston Weinberg18:00

      Yeah. It's still hard, but...

   10. SGSarah Guo18:02

       Um, I- I think it takes a, like a particular attitude to play with GPT-3 and then as a, you know, young lawyer be like...... "We should do this."

   11. WWWinston Weinberg18:12

       Yeah.

   12. SGSarah Guo18:12

       Versus, like, be threatened by it. Um, uh, you guys now serve, you know, more than 250 clients, more than $50 million in ARR. People are obviously adopting it. I look at the, like, weekly user charts. Um, what is the reaction you get from users and how do you talk to them about the impact of automation for them?

   13. WWWinston Weinberg18:29

       Yeah. It changed massively over time. Um, I think that there was a lot of fear of automation when there was a lot of press, but they haven't used it basically. Um, and I think, like, I- I- I am more bullish on model capabilities and just capabilities in general on the application side and- and- and everything.

   14. SGSarah Guo18:49

       So you still think you're crazy, but you're gonna go in that direction. (laughs)

   15. WWWinston Weinberg18:51

       Yes. I still think I'm crazy. Um, but I do think that one thing that not just our customers are realizing, but I think a lot of people that haven't worked in legal or professional services are realizing is these industries are very messy in the sense that all of this is not kind of a simple, "Oh, I know how to draft an SPA. I'm a lawyer. Like, I'm done," or, "I'm gonna grab all of the legal data on Earth and just train on top of it and the model works somehow." That's not how any of these industries work, right? Um, and so I think that from the lawyer side, once you have used the product, you start saying, "Oh, wow, this is really good and I can see that this is going to get better," especially if you're someone who used Harvey a year ago and you use it now, right?

   16. SGSarah Guo19:34

       Mm-hmm.

   17. WWWinston Weinberg19:34

       But it does seem like no matter what, we're gonna need a bunch of lawyer collaboration involved in the process, right? And so they're very happy about that and the junior folks are incredibly happy about this because what ends up happening in the legal industry and other professional services is, you know, you go to a really good school, you study a bunch of things that have nothing to do with, by the way, like th- practicing law.

   18. SGSarah Guo19:54

       Okay.

   19. WWWinston Weinberg19:55

       Um, and you come out and you're in a new kind of vertical and you're trying to figure out how to do private equity or an LBO or something like that and it's- you spend a very long time kind of doing repetitive tasks, right? So whether that's in, you know, reviewing documents in discovery or it's reviewing documents in a data room, et cetera, and you end up not being able to do the strategic level things until, like, 10 years into your career.

   20. SGSarah Guo20:16

       Mm-hmm.

   21. WWWinston Weinberg20:16

       You know, if you're lucky, five. Um, and so I think that a lot of-

   22. SGSarah Guo20:19

       You did complain about that grind work.

   23. WWWinston Weinberg20:21

       Yeah.

   24. SGSarah Guo20:21

       You were like, "I should not be doing this." (laughs)

   25. WWWinston Weinberg20:22

       There was a- a joke that, um, I- where I was presenting to the firm I used to work at, that was O'Melveny & Myers, and this was I think maybe a year ago, and one of the partners said, you know, "Winston, there are way easier ways to get out of doc review than trying to automate doc review." (laughs)

   26. SGSarah Guo20:36

       (laughs)

   27. WWWinston Weinberg20:36

       Which I- I don't know if that's true. Um, but my point

8. 20:40 – 26:02

   Being a lawyer today and in the future

   1. WWWinston Weinberg20:40

      is there are all these lower-end tasks that you end up having to do just because the industry is really complex and legal is getting more and more complex, right? And these tools allow you to do that stuff faster. And so what I think will end up happening is the timeline will compress, so you will start being able to actually do the high-level strategic work and interact with clients, which is what r- people really wanna do-

   2. SGSarah Guo21:02

      Mm-hmm.

   3. WWWinston Weinberg21:02

      ... earlier on in your career, and so they're happy about that. And so I don't think there is as much displacement fear. It is not job displacement, it is task displacement, and I think that's a super important distinction because getting rid of those tasks does not mean the legal industry falls apart. It will evolve.

   4. SGSarah Guo21:20

      My, uh, younger sister, Camilla, um, is an engineer by background and works at an AI and robotics company. She still wants to go to law school.

   5. WWWinston Weinberg21:28

      Yeah.

   6. SGSarah Guo21:28

      She's thinking about it. What advice would you have for somebody who wants to be, like, a star lawyer five years from now?

   7. WWWinston Weinberg21:34

      Yeah. I would actually have given the same-

   8. SGSarah Guo21:36

      Ten years from now.

   9. WWWinston Weinberg21:36

      I would have given the same advice before doing this startup actually.

   10. SGSarah Guo21:39

       Oh, okay.

   11. WWWinston Weinberg21:40

       Um, eh, I would say that now spend even more time on it, but the most important thing in legal and professional services is how well you can deal with client requests. Like, how much you can navigate and figure out what the client... what is actually best for the client. And so I would try to get as much hands-on experience, even if that's at something that isn't as prestigious, it isn't the, you know, bet-the-company litigation, 'cause you're probably not gonna get hands-on experience, or the massive $100 billion merger, et cetera. Like, get as much hand-on experience because that is the skill that is most important is figuring that out. And now I would just say that isn't the main skill that is gonna matter over time, but even f- three, you know, three, four years ago, I think I would have given the same advice.

   12. SGSarah Guo22:24

       What do you think happens to the structure of law firms that have been built on the backs of, you know, junior associates doing these repetitive tasks?

   13. WWWinston Weinberg22:31

       Yeah. Um, so I- I think there's a- a bunch of ways this can evolve. I think the most likely one is... I don't think the billable hour is gonna just completely disappear.

   14. SGSarah Guo22:39

       Okay.

   15. WWWinston Weinberg22:40

       I think what is gonna happen is a lot of these tasks that are going to get... You know, AI can automate a lot of that task with a lawyer in the loop. Those tasks will end up being kind of a fixed-fee model and I think the high-level advisory work on top will still be billable hour and will be actually maybe more expensive. Like, there's an argument that the specialist at a law firm who has seen all of these different mergers in the pharmaceutical industry, their rate s- should- hours should not be actually 3X the junior associate in the data room, maybe 10X. I- I don't know. My point is there is a specialization in professional services that is incredibly valuable and is going to be more valuable over time, and so I think it'll be a mix of those two. And we're also already seeing this. We're seeing law firms willing to do things like, you know, take a bunch of their domain expertise and turn it into software, and we're starting to do that. We're starting to work with firms and basically take, you know, the special things that they do and the way that they practice law and turn it into their specialized system in Harvey and then they go and sell that to their clients, right? And so that's a completely new business model.

   16. SGSarah Guo23:47

       Uh, how does that happen? Who drives that at one of your partners and-

   17. WWWinston Weinberg23:50

       Yeah.

   18. SGSarah Guo23:50

       ... what's the incentive?

   19. WWWinston Weinberg23:52

       Um, I mean, it is massively based off the law firm. Um, I think that you will find a couple partners that think that this is the future and they will rally the entire firm behind them, and that's what we have seen, and it's really started snowballing in the past kind of three to six months. And the way that it works really is it's a combination of, you know, they provide the domain expertise and we provide the translation of the domain expertise and then the tech, right? Um, the incentive for them is there is so much legal work...... that law firms actually do at a loss. And they do it at a loss so that-

   20. SGSarah Guo24:26

       It doesn't feel like that.

   21. WWWinston Weinberg24:27

       I know, I know, but there actually is. Um, there's a lot of legal work that they do at a loss in order to get the big deal.

   22. SGSarah Guo24:33

       Mm-hmm.

   23. WWWinston Weinberg24:33

       So, you know, a lot of law firms will do work for private equity and they will do that work at a massive discount or even, again, even at a loss in order to get the LBO-

   24. SGSarah Guo24:42

       Mm-hmm.

   25. WWWinston Weinberg24:42

       ... or the M&A, right? And so I think these systems are a way for law firms to compete in these spaces and it... Also another way for law firms that maybe aren't as large and don't have as much of those resources and they can compete in these others 'cause they have software margins for this work, and then they can get the really intense strategic deal afterwards.

   26. SGSarah Guo25:00

       Mm-hmm. Yeah, that, uh, feels analogous to, like, the client service work-

   27. WWWinston Weinberg25:05

       Yeah.

   28. SGSarah Guo25:05

       ... um, in an investment bank-

   29. WWWinston Weinberg25:07

       Yep.

   30. SGSarah Guo25:07

       ... in order to work on, you know, large transactions that really matter.
9. 26:02 – 26:58

   Adapting product for other domains

   1. WWWinston Weinberg26:02

      trouble figuring out how to do that. Now with recent models you can start unlocking those steps, right? And so the best way to think about this is we are constantly building all of the steps that we can and being on the cutting edge, and then when a model improves, that just pushes our ability to go out the next cutting edge more. Um, and then the other thing too is just cost going down is incredible for us, right? We try... You know, we're not optimizing for cost at all times right now. We're optimizing for quality. And if the prices go down, that makes it so that we can increase our quality across every single user base much faster.

   2. SGSarah Guo26:38

      Uh, how do you think about the domains that are not legal, right?

   3. WWWinston Weinberg26:41

      Yeah.

   4. SGSarah Guo26:41

      You have, um, announced, like, research and work and tax and audit now.

   5. WWWinston Weinberg26:46

      Yeah.

   6. SGSarah Guo26:46

      Um, what makes this the right time to do that?

   7. WWWinston Weinberg26:48

      Yeah. So, uh, the, the way that we think about it is there's so many areas where legal is kind of the tip of the spear.

   8. SGSarah Guo26:55

      Yeah.

   9. WWWinston Weinberg26:55

      And then you can actually just kind of paralyze

10. 26:58 – 30:39

    Hiring philosophy at Harvey

    1. WWWinston Weinberg26:58

       the same things that you're building and tweak them, and it works really well in other industries. Um, so an example of this is, you know, you do tax diligence and then you do commercial diligence and then you do financial diligence, right, over all of these documents. And tax and legal diligence, there are a lot of similarities in terms of what is the high-level problem that you are trying to solve, right? It is basically apply all of these rules to these documents, right? Um, and so we have found that there are a bunch of ways to take what we have learned and the things that we've built in legal and then just improve on that and apply it to tax or deals or these other areas.

    2. SGSarah Guo27:36

       So I'm thinking about, like, how unique it feels, um, in terms of just the product effort, uh, at Harvey. I think it's, like, very first of its kind and feel very lucky to be involved. When you think about, like, the team that goes and works on this, like, does your, like, new, um, engineering hire understand, like-

    3. WWWinston Weinberg27:56

       Yeah.

    4. SGSarah Guo27:56

       ... tax diligence after a whil- how do you think about, like, what makes somebody, like, the right next person to add to Harvey?

    5. WWWinston Weinberg28:01

       We're working on it. Um-

    6. SGSarah Guo28:02

       You are hiring.

    7. WWWinston Weinberg28:03

       Yes.

    8. SGSarah Guo28:03

       Okay.

    9. WWWinston Weinberg28:03

       Yeah, tons. Um, we're working on the contact sharing.

    10. SGSarah Guo28:07

        Yeah.

    11. WWWinston Weinberg28:07

        I think that is something that's really important. One thing that was really nice that I actually think we did get right is the respect is incredibly high.

    12. SGSarah Guo28:15

        Mm-hmm.

    13. WWWinston Weinberg28:15

        And so what I mean by that is a lot of engineers don't have experience in legal and professional services, and we had a couple talks that were basically talking about these... The structure of these really complex, like, take private deals and you could just see the engineers basically saying, "Oh, wow. This is... The work that all of these folks are doing is really impressive."

    14. SGSarah Guo28:34

        Mm-hmm.

    15. WWWinston Weinberg28:34

        Right? Um, and so that I think we've done well. I think on the contact sharing, it is a difficult problem where the f- a lot of the folks building the product, they haven't actually used it in the sense of in their past career.

    16. SGSarah Guo28:48

        Sure.

    17. WWWinston Weinberg28:48

        You know, they ha- they haven't done tax diligence or, or whatever it is. Um, and so that's-

    18. SGSarah Guo28:52

        Do you guys do, like, a weekly Suits viewing or something? Is that how it works? Yeah.

    19. WWWinston Weinberg28:56

        (laughs) Yeah, and then you're, and then you're done. Um, yeah, if y- if you watch all of Suits we actually just make everyone watch every season, every season of Suits and then they're good. Um, no, it, it, I- i- it's a very difficult problem. I would say that the way that we look for hiring folks is basically agency, right? Like, this is one of the biggest things, is there are so many things that we are doing that is new.

    20. SGSarah Guo29:19

        Mm-hmm.

    21. WWWinston Weinberg29:19

        And I have found that over time hiring folks that might not have a bunch of experience in this particular thing doesn't matter. Like, it is so important that you hire people that are really smart, hungry, care about what you're doing and are willing to, you know, be very decisive in what they decide to ship, and if it doesn't quite work, iterate on that and, and, uh, go again. That is better than necessarily someone who has tons of experience, and I am very much doubling down on that as a company and I... I think this is probably always the case, but I think it's more the case now because everything changes every six months and you have to be able to adapt to that change. And if you can't, you're not gonna make it regardless of how much experience you have.

    22. SGSarah Guo30:07

        Yeah, I, I think that's true even in the experience of, like, the founders that we are working with.

    23. WWWinston Weinberg30:12

        Yeah.

    24. SGSarah Guo30:12

        Right? In terms of, like, well, like, y- your ability to predict or follow somebody else's pattern for more than two months at a time is, is very bad.

    25. WWWinston Weinberg30:21

        Yes.

    26. SGSarah Guo30:21

        Right? Um, I mean, some things are monotonic, like, uh, you know, capability improvement-

    27. WWWinston Weinberg30:25

        Totally. Yeah.

    28. SGSarah Guo30:25

        ... but still, figuring out, like, I'm gonna pick this point in the future-And like, put engineering resources on solving a particular task, 'cause I think it'll be possible. I think it's just very, very different from building, uh, deterministic SaaS

11. 30:39 – 32:53

    Lessons and mistakes as a founder

    1. SGSarah Guo30:39

       workflows-

    2. WWWinston Weinberg30:39

       Yeah.

    3. SGSarah Guo30:40

       ... from a few years ago.

    4. WWWinston Weinberg30:41

       I think you have to pay more attention. So I think like, that's one of the biggest things is I have found that the people that have been very successful in this space so far are like, very obsessed. Um, and it's not just obsessed with your problem, but you have to pay attention to what's happening with all the model providers as well. Like, you have to pay attention to all of these different facets or I think you're gonna miss out on something.

    5. SGSarah Guo31:03

       What you have, you know, now been a founder for two and a half years.

    6. WWWinston Weinberg31:06

       Yeah.

    7. SGSarah Guo31:07

       Uh, I'm sure that's a learning experience. You feel like you got a focus on agency, right, in, you know, hiring and the business. Like, what did you get wrong?

    8. WWWinston Weinberg31:17

       Yeah, I mean, s- I don't think we have like, 12 hours to do this. Um, a lot- a lot of things. I think if I had to say there's one thing that I got wrong over everything else, it is figuring out when to scale yourself. Um, I have a certain kind of like, tendency for how I work and there are some things I- I wanna keep. So, one of the lessons that I definitely wanna keep is I do think you should do every single role for a certain amount of time before you hire for it. Almost all of my mis-hires were because I did not understand what that role was, and maybe it's a lack of my experience, I don't know, but there's a hands-on piece. Having said that, you can't scale a company by wanting to be hands-on (laughs) in everything at all times, right? Um, and I think that I didn't spend enough time transitioning from... I mean, the beginning of last year we were 40 people. Transitioning from everyone knew what was going on, everyone had all of the context because they were working with me directly, right? Um...

    9. SGSarah Guo32:15

       And you touched every single customer all the time.

    10. WWWinston Weinberg32:16

        Touched... Yeah, basically, right?

    11. SGSarah Guo32:17

        Yeah.

    12. WWWinston Weinberg32:17

        And like, all pieces of the product, et cetera. And I took a long time to f- and I w- I mean, sorry, I haven't solved it at all. I ha- took a long time to even think about solving it, of you just need to learn how to scale yourself and you can't be in every single thing. Having said that, I do think that you wanna be in as many things as you can because you are... or it's an environment where you have to m- be very decisive and make very quick decisions. And the easiest way to make quick decisions is you're paying attention to everything, right? You're kind of monitoring everything at all times. And then your gut is normally actually

12. 32:53 – 40:21

    Personal drive

    1. WWWinston Weinberg32:53

       pretty right because it's not your gut, it's you have taken all of these different stimuli and you're just absorbing them at all times, right? And so I guess balancing how important that piece is with actually learning how to share context with the team, how to make sure, you know, upleveling everyone, how to transition yourself as a founder has been hard for me, and I think it is continuously hard. And I'm sure if you ask anybody they say that it's, you know, it's going okay but it still needs work. (laughs)

    2. SGSarah Guo33:19

       So when, uh, you agreed to do this podcast you were like, "Okay, okay. Sure, Sarah, but, um, we're gonna talk about the company and not me."

    3. WWWinston Weinberg33:26

       Yeah.

    4. SGSarah Guo33:27

       And, uh, I lied.

    5. WWWinston Weinberg33:28

       Oh.

    6. SGSarah Guo33:28

       Um, so I'm gonna ask you just a couple things. Um, uh, one is like, you- you work continuously. You obviously really, like, think that there's, um, something important to be built here. Uh, as far as I can tell you don't do a lot else, like maybe work out.

    7. WWWinston Weinberg33:43

       Yeah. That's like, basically it.

    8. SGSarah Guo33:44

       Yeah. Um, where does- where does the, like, drive come from?

    9. WWWinston Weinberg33:48

       I mean, as simple as possible, like, this is the most fun thing ever. Um, I don't think... you know, I started this company when I was 27. Um, there was nothing in the 27 years leading up to there that was even close to as much fun as this is. I- I think that it is just so much... you get so much energy from things moving so quickly, and you being able to actually have the agency to come up with an idea and then see it built. That is a crazy experience, and I think that you can do that faster than you used to be able to and it is addicting. Like, it is incredibly addicting. Um, and so I actually think that it's- it's less like, where do you get the drive or where do you get the inspiration? I think that most people that I've met that have been successful in this space, they just have it. Like, it's just naturally they love the moment or the like, very compressed timeline of you can have a very large impact.

    10. SGSarah Guo34:47

        It's the most fun you've ever had. Uh, uh, some people like, they just have that like, the- the, uh, desire to like, know what's happening, have the leverage, see that like, really fast impact-

    11. WWWinston Weinberg34:59

        Yeah.

    12. SGSarah Guo34:59

        ... cycle. Um, is that the expectation you have of everybody at Harvey culturally?

    13. WWWinston Weinberg35:03

        Good... Yeah. Good- good question. Um, I think the expectation that I have for everyone at Harvey, um, we- we have a line that we have kind of like, talked about a lot and it actually comes from Kobe Bryant. Um, and it's, "Jobs not finished."

    14. SGSarah Guo35:16

        This is good. Okay.

    15. WWWinston Weinberg35:17

        Basically he was in an interview and I- I forget which game it was but, you know, they're up like... I think it was like, 3-0 or 2-0 or something like that. And a reporter asked him, he's like, "You know, how- how do you feel right now? Like, how- how are you feeling?" He's like, "You know, I feel good. It's- it's not done." And he's like, "Well, shouldn't you be excited? You're up like, 3-0." And he's like, "Well, the job's not finished. Like, we're- we're not done, like, we haven't won, right?" Yeah.

    16. SGSarah Guo35:38

        "The- the thing's not over." Um, and I think that what I'm trying to convey when I say that or... and hopefully what Kobe was trying to convey when- when he said that was there are certain moments when you need to give it your all, and if you give it your all in this massively compressed timeline, it will serve you for a very long time afterwards. And so that's what I- I think I expect of everyone that we hire at Harvey is look, you need to recognize and trust us. So it's maybe a combination of either recognize or trust- Mm-hmm.

    17. WWWinston Weinberg36:12

        ... that we are on that timeline, that we are on an incredibly compressed timeline for honestly just all of humans (laughs) -

    18. SGSarah Guo36:20

        (laughs)

    19. WWWinston Weinberg36:20

        ... right? I'm serious.

    20. SGSarah Guo36:21

        Yeah, it's a very special moment. Yeah.

    21. WWWinston Weinberg36:22

        Like, it's a very special moment, and there are going to be insane expectations and the company isn't always going to be there. I'm not always going to be there at all times to tap you on the shoulder and be like, "Hey, remember those expectations. Remember this is true." And so you have to be able to do that to yourself and you have to have that mentality, right? Um, and so I think what that looks like is some combination of recognition...... and a willingness to keep up the intensity and keep raising the bar. Um, and that is an expectation of anyone who joins.

    22. SGSarah Guo36:54

        Yeah. That, that resonates very strongly for me because I think in a, like a very parallel journey.

    23. WWWinston Weinberg36:59

        Yeah.

    24. SGSarah Guo36:59

        Like, this opportunity's gonna happen once and so for me and my team and even, you know, Mike who joined us a little while ago, he's like, "How can I not do it right now for one?"

    25. WWWinston Weinberg37:09

        Yeah.

    26. SGSarah Guo37:09

        Right? Like, you know, m- land of many different options, but I can't sit this one out and then if we're gonna play, we're gonna fully play.

    27. WWWinston Weinberg37:15

        Yeah. And it, and it, that-

    28. SGSarah Guo37:16

        Yeah.

    29. WWWinston Weinberg37:16

        ... that is maybe a really good way to look at it. "I can't sit this one out."

    30. SGSarah Guo37:19

        Mm-hmm.
13. 40:21 – 44:35

    Advice to other founders

    1. WWWinston Weinberg40:21

       you start to absorb that intuition, you start making bets on your own, and then you see it work. And all of the sudden you get a little bit more confident. Hopefully not too confident, um, but a little bit more.

    2. SGSarah Guo40:30

       Mm-hmm. So you're saying you and the people at Harvey feel the AGI just-

    3. WWWinston Weinberg40:33

       (laughs)

    4. SGSarah Guo40:33

       ... enough?

    5. WWWinston Weinberg40:34

       J- just enough. Not too much.

    6. SGSarah Guo40:36

       Not too much.

    7. WWWinston Weinberg40:36

       Yeah.

    8. SGSarah Guo40:37

       Yeah. It's not clear what too much is, actually.

    9. WWWinston Weinberg40:38

       Yeah. I don't think there is a limit at this point.

    10. SGSarah Guo40:40

        So like the, uh, y- you guys have been on like the right side of a, uh, raging debate in the investing and tech community for a long time, which is just like, is there value in the application player?

    11. WWWinston Weinberg40:53

        Yeah.

    12. SGSarah Guo40:53

        Like it's pretty clear there is now. Um, what advice would you have for the many like founders, tech business people that, um, are gonna listen to this about, uh, like a good application to build?

    13. WWWinston Weinberg41:04

        Yeah. Um, so I, one thing that I look at is, uh, you can look at this by industry and you can look at it by task, which is how expensive is the token? Um, and I, I, I've come up with like different ways to call this, but basically if you look at something like that share purchase agreement or a merger agreement, or just legal in general, the cost or the price of producing each part of a word (laughs) -

    14. SGSarah Guo41:28

        Mm-hmm.

    15. WWWinston Weinberg41:28

        ... in a 50 page document can be incredibly expensive. Right? And so I think those areas, like that is one of the tests that I would do for these things. The thing I would stay, I, I would make sure you don't discourage yourself from is this industry has never been, you know, touched by tech or, or this is not something that I know that ton- tons about, et cetera. Y- you can really figure out a lot about what people do by just talking to them and asking a bunch of questions. Right? And it, it might not... You know, you might have to talk to a lot of people and that might not be exactly what you thought it was gonna be as a founder. You know, you might not just be sitting in, uh, I don't know, like a construction firm for, I don't know, 20 hours a day. But it's insanely useful. Right? And so whatever the area is that you're interested in, I would look at does this have long-term value in the sense of, you know, what is the price per token? Things like that. And then actually spend time with it and you'll get a much better sense for it.

    16. SGSarah Guo42:26

        Yeah. I have a lot of, you know, friends who are talented product and engineering folks, um, and, um, and business folks who wanna start a company. And I, I think people generally start by like ideating in their underwear in their house.

    17. WWWinston Weinberg42:39

        Yeah.

    18. SGSarah Guo42:40

        And like almost, like-

    19. WWWinston Weinberg42:42

        (laughs)

    20. SGSarah Guo42:42

        ... almost universally, um, some, some ideas happen that way. Right? But almost universally like it helps to see the problem in real life.

    21. WWWinston Weinberg42:49

        It does. Massively.

    22. SGSarah Guo42:49

        And I'm like, "Just go hang out with-"... one of your friends or at any industry that you, like, have some fundamental interest in-

    23. WWWinston Weinberg42:58

        Yeah.

    24. SGSarah Guo42:58

        ... and just, like, watch what people do. Um, because if you have a really general hammer that is getting better all the time, like, now is the time to do that and then you- you're gonna be much more inspired by, um, ideas of what is possible by, like, being faced with the problem.

    25. WWWinston Weinberg43:12

        I think that's right. And I might say something that might upset some people, but spend some time out of Silicon Valley too. I think it's important. Like, I- I think that, you know, there, and I don't necessarily mean... By the way, if you're building a tech company, like, I think it needs to be in San Francisco. (laughs)

    26. SGSarah Guo43:26

        Yes.

    27. WWWinston Weinberg43:26

        To be clear. Um-

    28. SGSarah Guo43:28

        Harvey's in SF, in New York-

    29. WWWinston Weinberg43:30

        And London.

    30. SGSarah Guo43:30

        ... and London.
14. 44:35 – 49:35

    Prediction for next ChatGPT moment

    1. WWWinston Weinberg44:35

       of surprised everyone. I'm really proud of that, like incredibly proud of that. Um, and I think, you know, maybe part of it is my background as well of I don't have experience in this and so I'm willing to take bets on people that do not have maybe, like, the perfect resume or the perfect experience. Um, and we've seen it work out really well. Um, and I- I guess maybe it's been s- s- it's surprising because everyone said that's not gonna happen. (laughs) Um, and so that's maybe why it's surprising.

    2. SGSarah Guo45:02

       Uh, like if you could pick, like, top two, three signals of, like, why this person should be a leader for you?

    3. WWWinston Weinberg45:08

       Yeah. Um, they, I mean, care is one of the most important things. Like, there is a sense of ownership. Whether that ownership shows itself in obsession, whether that ownership s- shows itself in doesn't make excuses and, like, says, "I got this wrong-"

    4. SGSarah Guo45:23

       Mm-hmm.

    5. WWWinston Weinberg45:23

       "... these are the things that I got wrong. I'm gonna fix them." One of the best ways to tell this is there are a few folks that will come up to me and basically just not ask for positive feedback and just say, "What did I get? Like, what do I need to improve?" That is a massive signal. Because I think that something that happens as you get more senior in your career is you don't want to look like you made a mistake. Like, a lot of what you're doing is kind of, like, covering and protecting your position. And it's really hard to learn that way and get better. And the reality is, like, you learn from success, you also learn from mistakes, I think, a lot. Or you learn from a- really, like, taking mindfulness with your mistakes. Um, and so that's maybe one of the best signals ever is how do they take ownership? Is it an obses- whether that's a combination of obsessiveness plus, like, self-reflection plus I just wanna get better.

    6. SGSarah Guo46:10

       Okay. Uh, last question for you. If you look outside of your own ecosystem of legal and professional services or maybe just, you know, one concentric circle-

    7. WWWinston Weinberg46:20

       Yeah.

    8. SGSarah Guo46:20

       ... legal- professional services is fair game, biggest change you think happens this year?

    9. WWWinston Weinberg46:25

       Um, I think we will end up seeing work completion done in very sophisticated manners. Like, in medicine and in coding, like a lot in coding, um, and a lot also in, you know, other areas too, that will kind of bring us back to the ChatGPT moment but it will be specialized. And so there will be a doctor that sees something or a researcher or something and it will be like it was the first time they saw ChatGPT but they'll show it to everyone else and they'll just be like, "I don't get what's going on here." Right? My point is I think these systems are gonna get to the point where they're doing things that are incredibly impressive even though we're used to them now. And it'll be kind of a new version of impressive but it'll be impressive to very verticalized and specialized people.

    10. SGSarah Guo47:11

        I agree with that. If I think about the, like, implication for, um, us or for founders, like, one of the things that has just felt really, um, impenetrable about industries that Silicon Valley folks don't spend a lot of time in-

    11. WWWinston Weinberg47:24

        Yeah.

    12. SGSarah Guo47:25

        ... is they're like, "Oh, well, you know, the- the customer won't buy," or "There's a lot, a bunch of regulation," for example, healthcare.

    13. WWWinston Weinberg47:32

        Yep.

    14. SGSarah Guo47:32

        Um, or, uh, uh, or, like, we can't... It- it's not obvious how to cut the task in a way where the minimum viable quality is, like, something that can be made.

    15. WWWinston Weinberg47:41

        Is there or it's enough of a value add.

    16. SGSarah Guo47:44

        Yeah. Where, like the, like the- the ROI is there. And I think, like, I think we're gonna get an accelerating pace of people saying, like, "I can figure out how to shape the capability to a, like, task completion-"

    17. WWWinston Weinberg47:55

        Yep.

    18. SGSarah Guo47:55

        "... that people want." And actually, like, these industries are far more open to that change than- than we thought. Right? At least that's been, that's been my experience where I'm like, "Oh," like as, maybe as we were saying earlier, like, the ROI just weren't, wasn't there.

    19. WWWinston Weinberg48:07

        Yeah.

    20. SGSarah Guo48:08

        Lawyers or doctors or whatever else, they, um, they want it, like, you just have to fi- figure out the shape.

    21. WWWinston Weinberg48:13

        That I think is the biggest piece-

    22. SGSarah Guo48:15

        Mm-hmm.

    23. WWWinston Weinberg48:15

        ... is I think people are confused and they don't think that they want it.

    24. SGSarah Guo48:20

        Mm-hmm.

    25. WWWinston Weinberg48:20

        And the reality is a lot of these folks do. Like they don't want... When you talk about AI and it's like a first blast or whatever, it's like Skynet and all these things and it's-

    26. SGSarah Guo48:27

        Yeah.

    27. WWWinston Weinberg48:27

        ... yeah, no one wants that.

    28. SGSarah Guo48:28

        Skynet replacing your job.

    29. WWWinston Weinberg48:29

        Someone- someone-

    30. SGSarah Guo48:29

        Of course people don't want that. Yeah. Yeah.

Episode duration: 49:35