How Winston Weinberg built his $11 billion AI Company | Term Sheet

13:28Winston Weinberg:Yeah. I think for me, the biggest thing was, can you get these models to generalize? Right. So at first it was basically, OK, with a lot of work, I can get the models to do certain things. But the bigger question was, in order to create a real product here, can you get the models to actually generalize and be good at all of these other types of legal tasks? and until we went outside of a domain that I understood as well and we got good results there I thought oh maybe this is just something you can tinker with but you can't build a product around what were your fears at that time did you have any reservations uh I no um I think like the I mean part of this is like I don't have a tech background and before Gabe actually I had almost no friends in the tech industry and so a lot of this is just ignorance right like you don't you You have no idea how hard any of these things are.

14:18Winston Weinberg:You don't know how hard it is to build a tech product. You have no idea how hard it is to build a tech company. And so you jump into these things mostly with ignorance. And I think what ends up happening from there is you find out things are harder and you learn from it, which I think it's been somewhat of an advantage, I think, to not have that background because you try to do things differently and think from first principles, et cetera.

14:42Allie Garfinkle:Well, there's something very interesting about the idea that this is your first company. Yeah. Legal AI now is hot. But at the time this all started, it absolutely wasn't. It was not. Yeah. It's hard to overstate. And I think memories in tech are very short. But if you said legal AI in what, 2023, people were like, I don't know. Yeah.

15:03Winston Weinberg:There were two massive problems. One was people thought that because the models hallucinate, that legal is a bad area because everything needs to be insanely accurate. Right. Which was a reasonable thought, by the way.

15:15Allie Garfinkle:Totally a reasonable thought.

15:16Winston Weinberg:I think that was A. B, I don't think people really were bullish on the models getting better really fast. They weren't. And if you look at, and to both of these two things, for the first one, actually the legal process and a lot of professional services are perfectly situated for these models making mistakes. The reason why is they already have a pyramid system. And so what ends up happening is you have the client that asks a question, and then the partner sits here, and they get that question, and they break that question down into 10 sub-questions. And then they give that down the pyramid, right?

15:51Winston Weinberg:And the bottom rung of the pyramid does some of the work, right? They do that work. It gets reviewed by the next level of seniority, then the next level of seniority, then the next level of seniority. Then the answer goes to the client. And actually, that's a perfectly ingrained review flow, right? Like you already have that. And I think that a lot of people didn't realize that.

16:10Allie Garfinkle:And so backstops are already built into just how law specifically works, how law works.

16:15Winston Weinberg:And a lot of professional services are this way. Right. And so I think that it was perfectly situated for that. And then the second thing is, I think that people have really for a long time until honestly, probably the past two months have constantly gone back and forth between us, AI, a bubble. Like, does this technology actually work? and my co-founder Gabe and I have been just incredibly bullish on the models getting better from day one and we've constantly designed the company with the idea in mind that eventually long term you're competing against the models because they're really good.

16:48Allie Garfinkle:Well one of the things that you've said over and over here is that this has all happened a lot faster than you thought. Let's do like an expectation versus reality. What was your expectation for how fast it could go and what has actually happened?

17:00Winston Weinberg:Yeah. So some things have happened faster and some things have happened way slower. So actually, let me start with the slower one. The one that I do not understand is we still have folks that are kind of like, I'm not totally sure what the value of AI is. I do not understand that. Like I when ChatGPT got released, I genuinely thought that it would be integrated into every single business within a month.

17:24Allie Garfinkle:You actually thought that like

17:25Winston Weinberg:every single use case, 100%.

17:27Allie Garfinkle:You're not accounting for human nature, Winston.

17:30Winston Weinberg:My brain was basically just, wow, these systems are so good. They can do a certain percentage of every single task. People are going to figure out how to use them. They should go everywhere. So that I was pretty wrong about. The thing I think, and so that was definitely, we were wrong in terms of how long it would take for that. What I was surprised by was how fast adoption at law firms happened once a couple law firms started using it. Right. And I think that that has moved way faster than I thought. And it was really hard in the beginning, incredibly difficult to get any law firms to even try our product or jump on a call with us or anything like that.

18:09Allie Garfinkle:So for a while, no one was taking your call.

18:10Winston Weinberg:No one would take our call at all.

18:12Allie Garfinkle:So when was the moment that you saw that shift?

18:15Winston Weinberg:The biggest shift was we had a large announcement with a big law firm that's now called A &O Sherman. And they actually announced that they had trialed us and were deploying it across the law firm. And I think that we needed that one moment of a firm that has an incredible brand saying, hey, this is actually real, like this product works, right? And once that happened, I think most things snowballed after that. And then I think in terms of the speed of adoption, it took longer than I thought for it to get to enterprises and to get to all those things. but now it's going faster. And the industry is starting to adapt to this faster than I thought.

18:55Winston Weinberg:So we have law firms that are literally building software on top of us and trying to resell that software to their in-house customers. We have law firms that are pitching completely new ways of doing work for customers, doing completely different types of tasks, right? And I think that that has happened faster, actually, in the past six months than I thought it would. So it's been strange where it's like the initial part was slower than I thought. And then the past six months, the adoption rates have been much higher than I thought.

19:26Allie Garfinkle:Tell me a little bit about how you keep up, because one of the things I found very interesting about this moment when we think back on it is everything is just moving so much faster than we ever expected. Like Harvey was founded a few years ago. Three and a half. I was to say we're at less than five years. Easy. Right. I was I was being generous. Perfect. Now worth$11 billion. Right. What does it actually mean to build a company in an environment where not only can you grow that fast, but you have to pivot that fast?

19:53Winston Weinberg:Yeah, I mean, the thing that I care the most about with our culture is decisiveness. And I think like, you have to basically build a company that has a culture of making decisions very quickly, and being okay to make mistakes, and like learning that. But the reality is the folks that I have found that haven't scaled and when I myself think that I'm not scaling, it's because I haven't learned enough in the past couple of months. Right. And you basically have to like one thing I say a lot is you have to re-earn your position every six months. You need to re-earn your role at Harvey every six months.

20:31Winston Weinberg:And that includes you. Yeah, 100 percent. Oh, it includes me 100 percent. It includes you the most. Yeah, potentially the most. And I think that if you don't reinvent yourself as a company and as a leader and whatever your role is at a company right now, an AI company, fast enough, you will lose. And that involves making a lot of mistakes. And that's okay. It is okay to make mistakes as long as you pivot after that mistake and you don't repeat the same mistake again and again. And so when I look for folks that I say, oh, wow, this person is going to scale, this person is going to go from never managing a team to managing a team of 20 to a team of 100, et cetera, the main thing I look at is can they make decisions, own that decision, and then pivot when they make a mistake?

21:18Winston Weinberg:Like instead of penalizing the mistake, penalize not making the decision or not learning from that mistake going forward.

21:25Allie Garfinkle:So you are perfectly OK with a series of mistakes. What you are not OK with is a lack of decisiveness.

21:30Winston Weinberg:Exactly. And on the mistake side, if you continue to make the same one.

21:36Allie Garfinkle:Definition of insanity.

21:37Winston Weinberg:Yeah, exactly. Right. Yeah. Yeah, exactly. And I think like even more importantly, what I'm starting to see is there are folks that are able to say, what do I need to get done in six months? Like, can you have a very good plan for what are the top three things that you need to do that are not a problem right now at all? But in six months, they're going to be an astronomical problem. Can you predict that and start taking movements toward that right now?

22:03Allie Garfinkle:So I'm going to pull this thread a little bit. How do you figure that out, especially for you personally, where everything changes in AI every six months and even six months seems like it might be a little long?

22:14Winston Weinberg:So there's maybe two ways to do this. One is everything is changing, but a lot of company building, I think, is quite the same. In terms of can you hire the right people? Can you put those people in the right roles? And can you create a culture that actually works for your company and for your customers, right? And that part of the job is exactly the same as I think it's always been. At least when I talk to mentors and things like that, it seems like it's exactly the same, right? You have to be able to do that at a faster rate, though. And so you have to be able to say, hmm, is this person going to scale into this or not?

22:49Winston Weinberg:Or are we going to have to completely have a different type of org here because the communication between EPD and GTM isn't going to work for this product line or whatever it is, right? Those things are quite similar. Like they have nothing to do with AI, right? On the product side, that's where you have to just assume that the models are going to get even better than you think they're going to get. And how do you do a product roadmap that makes it so you don't get destroyed by the tsunami of the models? That's a harder skill set to learn. But I do think the first limiting gate factor for it is do you actually believe that?

23:23Winston Weinberg:Do you believe that the models are going to get this good that fast? If you don't, there's no way for you to ever plan for that. So that's like number one.

23:32Allie Garfinkle:Why is that belief so important?

23:33Winston Weinberg:Otherwise, you get trapped by ego. So you get trapped by, oh, there's something that we can build that they can't. And in six months, that's going to, you know, there's no way they're going to be able to do that. It's much healthier to actually say, huh, these models are going to double every six months and get, you know, that much better at reasoning capability, tool use, etc. What are the things in our domain that are really hard to replicate? That is a much better mindset. And I think that's hard because a lot of times when you try to think about like what you're building, you think, oh, we'd be able to do something generalized better than somebody else.

24:10Winston Weinberg:But it has to be vertical specific.

24:12Allie Garfinkle:When you think about situations at Harvey where someone has scaled successfully for a while and then stopped.

24:17Winston Weinberg:Yeah.

24:17Allie Garfinkle:What does that look like?

24:19Winston Weinberg:It's the six month problem. It's the six month problem. It's always the six month problem. It is basically. Define the six month problem. Yeah, the six month problem is you look at your org right now and your customer base and your product and you go, there aren't problems right now. Everything's going great. And you can't do this is about to break. This is going to break in one month, three months, six months, right? people are usually good at this is going to break in one month and then about 80 percent of people fall off when you ask them to do three months and then 99 percent of people fall off when you ask to do six um and so that is like the main skill set and i think the problem with it is it's really hard to learn how to do that unless you've messed it up before and so like the the number one thing that I try to focus on is every week I want to do something that is hard and like makes me really anxious.

25:15Winston Weinberg:Like every week there should be one night where I can't sleep because the next morning I'm nervous to do something. Right. And a lot of the times the thing that people are the most nervous to do is the thing that's the most important and the hardest. And I think people like to rotate on busy work. They like to say, oh, I've done 12 meetings today or 15 meetings today. And this This week I worked 100 hours, but they don't do, well, what are the top three things that I need to do so that we win in six months? And how many of these meetings have anything to do with those top three things? People, it's really hard, right?

25:48Winston Weinberg:And I think that it's a different type of discipline where it's not just about performative work. It's can you do the right things? Can you spend the time on the right things? And that's hard for people.

25:59Allie Garfinkle:Well, it's a form of forecasting, but it's a form of psychological discipline. It is. And not getting lost in, well, I did 12 meetings, I can't think about this anymore. I guess the thing I would wonder for you is as you think about keeping all those balls in the air, all of the juggling, I'm sure you do, on the days where you can't sleep at night, how do you go back to center and say, these are the only three things that actually matter?

26:24Winston Weinberg:I find it really hard, personally. It's really hard. So I do have a tracking system. So I have a document that's just called The List. and on it I have what I need to do every day. I have like all of our customer metrics, our financials. What platform is this on? It's just Google Docs. It's just a Google Doc. It's just a Google Doc and I update it every single day and I've been doing that since I started the company. So I have like, and then it breaks at around 200 pages. Google, if you're listening, if you could please fix that, that'd be great. So I basically have to like, I have to like legacy out and then come up with a new list from date to date or something like that.

26:58Winston Weinberg:It's really annoying. Once you've broken Google Docs. Get Google if you're listening, please. Help me with this. Winston has a request. But so I track everything on there. But the most important thing is I have a top three goals. And I literally bold them and nothing else on the document is bolded. And what I try to do is at the end of every single day, I go, what was my list of like 15, 20 things that I did? And how many of them actually like back up into that list? and I actually like try to penalize myself if I've done too many things that have nothing to do with that top three list, right?

27:31Winston Weinberg:And then you rotate that list and you have to be able to rotate it, right? And I think it honestly is a discipline problem, but when I hear people talk about discipline, I feel like they're mostly talking about like how many hours I worked or how many meetings I took. But the harder discipline is actually these are the three things that matter and how do I stay focused? And that's what I've definitely found is the hardest part with people, whether they scale or don't scale is those three things like stay the three things for too long they either stay the three things for too long or they turn into four things and then five and then ten right i mean i remember we i was reviewing uh we were doing like quarterly planning and someone put p0 and then they wrote above it p00 and i'm like okay so nothing is the priority right like there is no priority.

28:21Winston Weinberg:If everything is the priority, then nothing is the priority. And then it's going to be like P000, right? And I think that like, that's also really hard to do as a founder. Like, it's really hard.

28:31Allie Garfinkle:And you're getting pulled a thousand different directions. Right. The company gets bigger. There are more requests of all kinds.

28:36Winston Weinberg:You have to start saying no to things. And again, I think it's really hard to figure this out without failing. Like, you just have to fail like a million times.

28:44Allie Garfinkle:Like, what is your relationship to failure at this point in your life?

28:47Winston Weinberg:Marriage. No, I think like you're married to failure. I think like it's a very good way to learn. And I think you learn a lot, by the way, from winning, too. And we've had a lot of success. And I'm very grateful for that. And I've learned a lot from that, too. But I think you learn from both. Right. And I think that one of the problems with the with either of these is like, what was the thing that contributed to you failing? What was the thing that contributed to learning? Right. Right. And so it's not just you have to, you know, have a bunch of wins and then have a lot of failures, but you have to get good at taking some time to actually like analyze what did you do?

29:24Winston Weinberg:Right. What did you do wrong? And most of that is like destroying your ego 24 seven.

29:29Allie Garfinkle:Like that's mostly it's just constant ego death. It is. Yeah.

29:32Winston Weinberg:And I think like one way to do this is just have very high ambitions and very high standards. Right. And if you have very high standards, then a lot of the successes, you don't get trapped in them. Right. You don't kind of get obsessed with what is the valuation of your company or how much revenue do you have or anything like that. You just stop caring about it because it's so far from like what you're trying to build long term. And if you have a really long term mindset for what you're trying to do and you're really ambitious about it, all of the wins don't really look like wins. They're just like, okay, next thing, right?

30:10Winston Weinberg:And I think it's actually better to, and by the way, I think that's the same with failures where you wanna just move on really fast, right? And I've definitely have been given feedback for people that I work with that sometimes it's like an adjustment working with me because I will call out like 15 failures a day. And I think that a lot of people aren't used to getting that feedback. Like they aren't used to it. And the reason they aren't used to it is because they wanna be perfect. And I do not care about perfection. I care about rate of improvement. That's it. Like, I only care about rate of improvement.

30:43Winston Weinberg:Right.

30:43Allie Garfinkle:Only rate of improvement. That's it.

30:45Winston Weinberg:Yeah. That's all that matters. Right. Because otherwise what you're going to end up doing is you're going to hire a bunch of people that are really good for six months. And then if they aren't improving, then it's irrelevant because your business has changed massively. Right. They'll stall out. Yeah. They'll stall out. So rate of improvement is the only thing that matters. And I would also argue right now, like, with how fast the technology is changing, all that matters is rate of improvement and team. That's it.

31:05Allie Garfinkle:I was going to say sort of on the subject of success, Harvey's become a darling among venture capitalists. Right. Eleven billion dollar valuation. It's not nothing. Right. Was there ever a time where fundraising was on that list of three things or has it always found you?

31:21Winston Weinberg:Um, yeah, I think that if fundraising is on your list, you're not going to do a good job fundraising.

31:27Allie Garfinkle:Why?

31:28Winston Weinberg:There's basically, I think there's kind of like two ways to raise. You can either I know people say you can raise off of vision, basically, or numbers is what people have said. I don't know if that's necessarily true. I think you can raise off of like performance, right? Numbers, whatever you want to call it, or resume. Those are like basically the two ways. I don't have a very good resume. And so there's only kind of one option. I had one option. Right. And so I think that I've just kept that right where I have always thought of fundraising as something that will happen if you tell people you are going to do something and then you do it.

32:05Winston Weinberg:And so for every single fundraising round is a downstream effect.

32:09Allie Garfinkle:Yeah.

32:09Winston Weinberg:And I've always actually known who I want to do the next round. And I build a relationship with them and I tell them this is what I think. These are the products that we're going to ship. this is the DAU over MAU that I think we're going to hit, et cetera. And I start that relationship six months before I raise. And I don't go do a process. I don't do all of those things. And then what I do is every month I just update them on our progress. And I don't think there's any pitch or anything that you could ever do with someone that builds more trust than saying you're going to do something and then do it.

32:42Winston Weinberg:And I actually think this is the same with customers. The number one thing you can do with customers is say that you're going to do something and then deliver on it. That's it. Like, and at the end of the day, almost everything is trust-based, right? And so I think that that is a much better way to build a customer base that cares about you, investors that care about you, rather than, you know, kind of pitch a bunch of vision and things like that, that you might change a lot and that might not actually be what you're trying to do.

33:10Allie Garfinkle:Well, the other thing you're saying here is what you're setting up is a system of accountability and a system where you make mistakes and say, actually, we didn't hit that goal. But I'm telling you now.

33:19Winston Weinberg:I'm going to tell you a month ahead of time. Yeah. Right. And so and I think that's another thing, too, is this is something that I have found that people that have been very successful and we've hired a lot of people with incredible backgrounds who have been very successful. And I think something that they struggle with is this, where they have never failed before. And so they hide it and they wait until the end. Right. And if there is one thing that I have struggled with, with hiring folks that come from incredible backgrounds, is this is something is dying or something is rotting at the company and they hide it and they won't tell me until three months and then it's like very hard to solve.

33:57Winston Weinberg:Versus, oh no, I think this thing is becoming a problem. Tell me and my bad, I should have hired XYZ or built this part of the feature set first.

34:06Allie Garfinkle:Or I think this whole thing just doesn't work.

34:08Winston Weinberg:Yeah, exactly. And that's totally fine too. And I think that being transparent about it early and then moving it along really helps, right? It's the same thing with customers. The best thing you can possibly do is tell them that you're going to do something and do it. The second best thing you can do is say, we aren't going to do that. That's actually very important. And I think that that's actually a huge mistake that a lot of vendors are making right now is because you can build so many things and there's so much noise, you can just promise everything.

34:38Allie Garfinkle:A lot of vendors in legal AI? In general. Or in general?

34:41Winston Weinberg:I think in general. And it's because it's just there's so much chaos out there and so much noise that a lot of folks are going around kind of promising. Yeah, we'll build that. Of course, we'll build that. Of course, we'll build that. And the problem with that is if you don't deliver on that, if you're trying to build a company that lasts decades, people will remember and they're smart. And I have always tried to be very honest about, hey, we aren't actually going down that path or that's six months from now. And if that's not helpful to you, I'm sorry, but let's talk in six months. And I think that in the long run will help.

35:13Allie Garfinkle:How has this applied to agents? Because I feel like we've been talking about AI agents for a while, and I am on the record saying I am still skeptical about how this applies to the enterprise in the near term. But I know that's something you're thinking about. How do you know when it's working?

35:28Winston Weinberg:Yeah. So this is, again, iterative. Like, the best way to do this is what we're doing is we're picking use case by use case. Like, what's an example of a use case where you're like, this works? Yeah. So one of the ones we're focused on right now is, so we're focused on M &A and fund formation are two of the ones that we're really focused on. And in fund formation, you break that down into like 50 different pieces, right? And one of the pieces that we've gotten pretty comfortable with automating parts of is the comment letter piece. And basically what that is, is if you're raising a fund and you have 80 LPs, right?

36:01Winston Weinberg:They all care about like different terms and you have to negotiate with all the LPs simultaneously.

36:06Allie Garfinkle:All 80 of them. Really easy.

36:07Winston Weinberg:Yes. It's super easy, but it takes a really long time. And because you have to basically like it's hard to negotiating with one party. Imagine negotiating with 80 and like making sure that they're all sounds like my personal nightmare.

36:17Allie Garfinkle:It's really hard.

36:19Winston Weinberg:But what we've done is we've said, OK, what you can do is take like the historical comment letters for the LPs that you have again in this round, compare it to what they're asking for now and then create like a massive chart that compares every single one of the 80 LPs and like what they want now. how that's different than what the other ones want and how that's different than what they've done in the past, right? And then what you need to do is create a bunch of synthetic data to get evaluation. And I think one of the huge unlocks that people are not talking about enough is one of the reasons why coding models are so good is the data is out there, right?

36:55Winston Weinberg:The data is out there and it's easier to evaluate whether it's correct or not.

36:58Allie Garfinkle:Well, code is binary. Correct.

37:00Winston Weinberg:It works or it doesn't. Right. And the models, though, are getting to the point where they're so good at generating synthetic data that you can use that synthetic data to create eval sets. And that's like one of the huge unlocks that we have recently is a lot of this data isn't available for like how do you do common letters or X, Y, Z. And it's not public, right? And so it's really hard to get access to it. And one of the things that we're starting to figure out is what if you just create synthetic data sets for all of this, right, and use the models to create that synthetic data set and then get a bunch of lawyers and have the lawyers use that synthetic data sets to actually try to create the fund formation or the M &A.

37:42Winston Weinberg:And that's starting to look like it'll work. And there you can get just incredible performance from agents when in the past really all you were doing was just like a random model call and that's kind of it.

37:53Allie Garfinkle:Why do you think that that particular task is especially good for agents?

37:57Winston Weinberg:Well, I think a lot of legal tasks are especially good for agents because most of them are text-based, right? And if you think about, like, one of the biggest problems with agents is there's all these different bottlenecks, right? And in legal, at least what you have is a lot of it is text-based. You're either analyzing text or you're writing text or you're comparing text. And the data might be all over the place, and that's a separate problem. And that's a lot of what you have to do is put all of the data in the right spot. But it at least exists, right? Whereas there are a lot of other areas where if you take a task from start to finish, part of it is some conversation you have to have with someone or something like that.

38:42Winston Weinberg:And so it's really hard to have the agents get access to that data ever, really.

38:45Allie Garfinkle:So one thing I sometimes say is that I think an industry can sometimes develop in the image of its customers. And I've heard a lot of stories about shenanigans in legal AI that competitors can get very vocal about one another sometimes perhaps. What is your relationship to your competitors?

39:06Winston Weinberg:Yeah, good question. So I actually really agree with how you started, but I would even take it a step further. I would say that in order to be a successful vertical AI company, it is really important that you take on the brand and the honestly morals, principles of the industry. Right. And so something that I have massively tried to push with our team is even if you get into competitive agreements and there's a lot of noise and things like that, you just take the high road every single time. And I think that maybe that causes you some damage in the short term. But in the long run, I think that's what's going to win.

39:48Winston Weinberg:And legal is an incredibly trust based industry. It is a very relationships-based industry. And it is a very moral industry, right? Or at least, I mean, that is what we are trying to do as a lawyer, right? Well, if you're a lawyer, you're interested in justice. Right. You care about this. And I think that in the long run, the companies that have the same type of moral or principles as the customers that they serve are going to be the most successful. So I think it can be noisy kind of there. But to be 100 % honest, I mostly think about our competitors as the big labs almost entirely. And they are very above board, to be clear.

40:29Winston Weinberg:Both of them are. All two of them. Yeah, they are. They're not going around making market noise and things like that. And really, with them, it is going to be best product wins. That's it. If we can build a better product than Anthropic or OpenAI can for lawyers, we will win against them. That's it. Like that is the end of the story.

40:50Allie Garfinkle:Well, in the origin story of Harvey involves open AI. Right. What is your relationship to this partner and compete model?

40:57Winston Weinberg:Yeah. I mean, I think like the best way to say it is as the models get better, if we're doing our job, our product gets better. Right. If the models get better and we're scared, we're not doing a good job. Right. And this, again, goes back to my piece of can you look six months into the future? Right. And not just for your team, but also for what your product is supposed to look like and what are the underlying capabilities of the model so that you don't get eaten by a tsunami. And so right now we have a very good relationship with them. And to be honest, the model that's getting better is so far good for us.

41:27Winston Weinberg:So far we've been right. I'm not saying we'll always be right, but so far we've been right.

41:31Allie Garfinkle:At what point does it stop getting good for you?

41:34Winston Weinberg:I think that if you live in a world where the models have access to every single data source on Earth, can breach every single security system, and have perfect recall, accuracy, and memory, we're probably in trouble. But I would argue that every single business on Earth is in a lot of trouble. I also think the reality is there are just so many things in this particular domain, in every regulated domain, that you have to be able to build around. Right. Like security, ethical walls, permissioning a huge problem. Like go back to the fund formation with ADLPs. Sometimes like you'll set up that fund formation in like Luxembourg and the data can't leave like Luxembourg for tax reasons.

42:15Winston Weinberg:And then you have to coordinate the handoff from the agent to one of the ADLPs. And then there's a huge coordination problem within the product as well. And that's why I like to think of our company more as like building infrastructure. Like how do you get to the point where you coordinate the entire M &A with all of the law firms on one side plus the private equity firms on the other?

42:34Allie Garfinkle:Do an entire deal with Harvey.

42:35Winston Weinberg:Do the entire deal, right? And by the way, humans are going to be in the loop during that deal, right? And a lot of what we have to build is how do you review all of these things, right? Like we talked about how these agents can get to the point where they can create synthetic data sets, right? okay, well, if they can create synthetic data sets and everyone is also using them to negotiate contracts, what isn't data room going to look like for an M &A in 10 years? I'm not totally sure humans are going to be able to process that information at all. I think you will probably need to have agents working with humans in order to process the data.

43:07Winston Weinberg:It's just going to be too complex. So I think that there is a very large place for a player like us in this vertical just because of the complexities of the domain.

43:17Allie Garfinkle:One thing I would be curious about really pinning down, you're suggesting at it, but I think it's worth saying it directly. In a world where open AIs, chat GPT, where Anthropics Cloud can get really good, why does there need to be a Harvey?

43:31Winston Weinberg:Yeah, I think the orchestration layer is really, really important. And what I mean by this is, what part of your, say you're doing that large M &A, right? How do you review all of the outputs of the agents? How do you coordinate all of the review processes? How do you make sure you're connecting to all the correct data sources instead of using online data, things like that, right? And how do you make sure that all of that is done securely, right? And so I think a lot of what you're going to see is in these really, really complex fields and regulated fields where you're going to need a human in the loop, you're going to need humans revealing, you're going to have a lot of multiplayer, right, where you're going to have like 17 different parties working on the same project.

44:10Winston Weinberg:There's a lot to build. There's an incredible amount to build. And even if the models kind of get access to all of the reasoning data in these different domains, they don't know the data for that particular deal. Right. And they don't know the processes and preferences of, OK, we're going to hand it off to this law firm to review this. And then we're going to have this in-house team produce that output, et cetera.

44:30Allie Garfinkle:It's not binary. Exactly.

44:32Winston Weinberg:No. And I think these companies are going to start looking closer to like the underlying infrastructure for how these verticals are ran. Right. And that maybe is closer to an operating system for a law firm. But for an enterprise, that is, if you are going to spin up an M &A, you use Harvey to spin that up and to coordinate that process. And I think in a way you also are kind of like absorbing the liability here without actually being a law firm, because you need to make sure that's secure. You need to make sure the correct parties have reviewed everything. You need to make sure the data is in the right spot.

45:02Winston Weinberg:And this gets really hard for these complex pieces of work.

45:05Allie Garfinkle:That's actually a great segue to one of our reader questions. I sent out a call to term sheet readers saying, hey guys, I'm interviewing Winston. Do you have questions? I got to tell you, they came in hot. One of them from Demir said, what guarantees do clients have that their cases, data, and sensitive information do not leak?

45:22Winston Weinberg:Yeah, so I think this is really important. One thing that's different for us is we basically, so A, we're multimodal, so you can use basically any model you want. But in general, we have our own instance. We have dedicated capacity. So what's happening is instead of like using the normal systems that are used by everyone. We have a dedicated instance and then we have BYOK and all of the security concerns for each one of our particular customers. We also don't train on any of the data. So the only time we train on data is when it is like a general purpose thing, like improving citations within Harvey, right, which has nothing to do with any client data, or we have a client that asks us to do that.

45:58Winston Weinberg:And we do have some clients that are asking us,

46:00Allie Garfinkle:hey can you create custom solutions now I wanted to turn to you as a person um what do you read these days how do you spend your time when you're not

46:14Winston Weinberg:harveying I don't have tons of time when I was gonna say I suspect you I suspect you don't yeah there's got to be something um I mean I think like the one of the things that I still do is I still pay an incredible attention to like what cases are being decided and things like that so I'm very much Like I still, you know, listen to a lot of the oral arguments for the Supreme Court and things like that, too. So I pay a lot of attention to the industry. I still pay a lot of attention to antitrust law. That was like the area that I was really interested in. And then I still less than I'd like to. But I've been a huge fantasy fan forever.

46:49Winston Weinberg:And so when I do have time to read.

46:52Allie Garfinkle:Tell the audience what are some of your favorites because they will want to know.

46:54Winston Weinberg:I mean, definitely like all the OGs things like Lord of the Rings, Malazan series is incredible. Kingkiller Chronicles are really good. But I haven't read a lot of stuff recently. I go back and I kind of like reread things that I've read in the past. I'd like to have more reading time. And if there is any reading time that I'd like to spend more time on, it's fantasy. Also, if there's anyone that is building like an AI World of Warcraft, please let me know. I'd love to invest in that too. I literally just watch Twitch.

47:25Allie Garfinkle:Winston has a request.

47:26Winston Weinberg:I can't play, I don't have time to play video games, so I just like watch other people play video games sometimes before I go to bed and like that's like the closest I have. So I would love to invest if you're building an AI World of Warcraft.

47:36Allie Garfinkle:And the last thing that's sort of I'd be really curious about from your perspective is the legal industry is clearly changing and I think that does actually matter to the average person. So I was curious about your perspective about how you think AI is going to change our daily lives?

47:52Winston Weinberg:Yeah. I think it's a really good question. I think one of the biggest things I care about is, and maybe this is just because of my age, but is like education, A. And when I say education, I don't just mean school. I also mean like, how do you get educated in the professional world? And the thing that I am actually weirdly confident in is I think this will be a massive forcing function in how we train young professionals. Like it will just force us to do this and I'll give you an example of this so at a law firm right now they spend a decent amount of time training folks but a lot of the best attorneys that I have spoken to they've kind of just like learned how to do it themselves or they've they've found a particular mentor and they learn

48:37Allie Garfinkle:through them right it's an apprenticeship as yeah exactly but I

48:40Winston Weinberg:think it's gonna become more of one and one thing I like to talk about is firm should start thinking about time to partner and reducing that in other words what makes someone a really good lawyer and how do you train them how to do that earlier on. And the reality is like you do learn a lot from doing document review, discovery, all of these different things. But by the 20th time you've done it, I'm not sure how much you're learning. And I think it's going to force the legal industry and force a lot of other industries, by the way, to actually think about what makes people good at their jobs. Like actually, what is it?

49:10Winston Weinberg:Like, what are the human elements that make people good at their jobs? And how do we promote based off of that and how do we teach people that earlier on in their career it's a weird thing where you know all of the visuals around ai are like robots right they're like okay we're going to become like mesh with the machine and whatever we're going to become a robot terminator-esque yeah i weirdly have like an opposite opinion on this which is i think the way that most of the corporate world right works right now is a robot like most of the corporate jobs today you are a robot like you are in a Ford factory line and you're a robot.

49:44Winston Weinberg:And I think that this is going to be so disruptive to that type of work and that type of organization in a large enterprise or a law firm or anything like that, that is going to be a reckoning. And it is going to force people to actually think about like, what are the most, what are the top three things?

50:02Allie Garfinkle:I was going to say, this all goes back to your top three things. What are the top? It's not that eventually work will be about that.

50:07Winston Weinberg:Yeah, it's going to be about that. It's going to be, you know, what are the things that actually move the needle, what make our business who we are. And I think if you think about every company that like you start small and everyone talks about that, everyone talks about the mission. And the bigger you get, the more you're kind of caring about like internal politics, who like looks the best managing up all of those things. These models are just going to get rid of all of that. Like you're going to be able to use the models for so many different things that you can't really like hide the busy work anymore.

50:35Winston Weinberg:And I think that's going to be actually really good, especially for the younger generation, because a lot of the corporate world, I think, is going to start rewarding creativity, focus, discipline, and not just, well, I work this many hours and I produce this many documents. And it's like, well, AI can produce that many documents, who cares? And actually what matters is I decided to try something and part of it worked, part of it didn't. I learned from that. Now I'm going to try something new. And do you have people and do you have a system at your company that iterates and supports that. And if you don't, if what you mostly reward is whoever writes the most documents, well, I can tell you one thing, Claude can write way more documents than you can and way better than you can.

51:17Winston Weinberg:And so that doesn't really matter. And I don't know, to me, that was something that I was frustrated when I joined the workforce. And I think that that's actually a really positive thing that's going to happen. Like, I think it's going to make us less robotic, because it's going to make us focus on like, what actually we can do as humans uniquely.

51:33Allie Garfinkle:Winston, thank you so much. Thank you. So a week after, I am still thinking a lot about Winston's sort of process around finding the three things that matter most to win in the next six months. And I think part of the reason I'm thinking about it is because it is so symptomatic of this era. What Winston's effectively suggesting is a method of finding focus in an environment that's inevitably going to change on you and a competitive environment that could crush you. But I think his central idea is that if you find focus, that's how you really have a fighting chance. If you should decide to take the Winston Weinberg method to heart, let me know if you start your own Google Doc or come with your own top three priorities to win the next six months.

52:15Allie Garfinkle:I would love to hear about it. I think I'm going to try it. In the meantime, thanks for watching and I'll see you soon.