Transcript: ‘At This $10 Billion Hedge Fund, Using AI Just Became Mandatory’

The transcript of AI & I with Will England is below. Watch on X or YouTube, or listen on Spotify or Apple Podcasts.

Timestamps

1. Introduction: 00:00:51
2. What pushed Will to go all in on AI: 00:03:25
3. Inside the ‘AI-first’ memo Will shared at Walleye: 00:15:15
4. Why you shouldn’t be afraid of using AI for work: 00:17:02
5. How Will uses LLMs to sharpen his thinking: 00:31:25
6. Walleye’s approach to using AI to reduce risk: 00:35:57
7. What history can teach us about leading through change: 00:39:35
8. Will’s first principles to making better decisions: 00:57:10
9. Why Will journals everyday—and how AI makes it easier: 00:59:23

Transcript

(00:00:52)

Dan Shipper

Will, welcome to the show.

Will England

Thanks for having me.

Dan Shipper

It's great to have you. For people who don't know, you are the benevolent dictator of Walleye, which is a close to $10 billion AUM hedge fund. And you're an Every consulting client. We're working with you to help you do AI training and implementation inside of Walleye. And honestly regardless of the stuff we've done, you're I think one of the most impressive examples of a CEO who is pivoting their entire organization around AI and you're sort of leading by example. And so I'm psyched to get to talk to you.

Will England

Yeah, thanks. Maybe I could just give a little more context to that. I guess my technical title is CEO, CIO, managing partner. But I'm both the owner and operator of one of the larger hedge funds out there. I don't do much press. I don't typically speak at conferences. I've only done one other podcast. So this is very deliberate. It's very deliberate for me. And because of the relationship that we had developed on this subject, I do feel a great sense of both purpose and conviction about where our industry's going, where our firm is going. I do believe they're already a leader and that is going to continue to be the case. So I listen to a lot of podcasts. I was curious about some of the motivations for why people do them. So I just want to be very clear upfront. Because I have that conviction that the skills to call lead us into the next phase, and we'll get into that, of course, and ultimately the power to enact that. I really feel that it would be irresponsible of me not to go after it with sort of the maximum amount of discipline and intensity I can muster, which is a lot. So for three audiences: The people at Walleye—we have about 400 people, not big for a normal company, but in our corner of the world, it’s not a small amount. Second, I'm also speaking to people that aren't at aren't at the firm today, but may join us in the future just to understand how serious the firm is about AI. And that ultimately starts with me and then others. And then finally, speaking to people in the ecosystem, whether they be companies, building products that firms can use, or in other ways of working together. You know, that's why I'm here. But it does all start with me having, as I said, an enormous sense of conviction about where the world's heading.

Dan Shipper

How did you develop that? What was that journey like for you? I actually don't even know this.

Will England

So I'm a bonafide nerd by background. I was an engineer at Princeton. I went to Oxford to do a Ph.D. in math. I started my career writing code all day. So we as a firm and I personally have been using, let's just call it advanced statistics, not even AI, for years, a large part of what our firm does is in pure quant trading. So I've thought for many years about how machines increasingly can either augment or do the jobs of humans and finance. That's nothing that's new for me. What has happened of course in recent years is just that a lot of these tools have become more powerful and they've also become more accessible to non-technical people, particularly on unstructured data. And so part of it is just me personally being curious, being interested, if a huge part of this is about curiosity. I've noticed the productivity improvements that I see using these tools just even for, from a writing perspective, let alone some of the sort of more advanced things you can do. So it's a combination of called, having been in the deeply versed in technical background as I said, bonafide nerd, and then noticing what's out there and just the sense of responsibility to the people at the firm, to our investors to say, okay, we understand where this is going if we ultimately get disrupted by AI, that's on me. And so let's get after that. So even two years ago, this didn't make sense. Oh yeah, we're going to do all these things in the future. Two years ago we started an internal AI program today. We're already doing a lot. So it's not just a story about what's to come. And a lot of that does start with me. I mean, that a lot of times leaders of organizations won't sort of say that how much actually matters. You know that in leadership, but this is one where I feel like I absolutely needed to lead from the front.

Dan Shipper

So tell me about that a little bit more concretely. One of the things that I appreciate about you as a communicator is you're just kind of, no bullshit. We were talking three or four weeks ago, and I was telling you something about Every and our strategy and direction, and you were like, you sound kind of afraid. I was like, yeah, I'm a little afraid of this. So you're not afraid to kind of put your finger on the nerve and you're also not particularly hype-y as a person, I don't think. So tell me about the moment where you're like we have to take this seriously vs. it's just tech people nerds are psyched about it, but it's something that we really need to understand.

Will England

Yeah. And I appreciate you saying that. That's definitely the way I try to operate. Many people tell stories. Sometimes those stories get hyped. And for whatever reason, I think a lot of it comes down to being comfortable with yourself, self-confidence of not feeling like you need to convince someone you're not. So that's been a hallmark of mine trying—

Dan Shipper

I would never have done that. So I don't know from experience that's a problem.

Will England

Yeah. Not really. That's a core belief in terms of AI. There have been a couple of moments over the years that have led us to continue to go down and recently accelerate this journey. The first was two years ago. Our most advanced internal AI project is called Current—that's led by someone who was a former analyst in one of our technology stock-picking teams come to me in March of 2023 and say, look, I've built, I've used these tools that are now available to make myself way more efficient, eventually trying to replace what I was doing as an analyst. And I was pretty skeptical at first because that's not typical that someone would just go out and do that.

Dan Shipper

This is with GPT-3?

Will England

Yeah. This is like two years ago and it was early, but the point was you just sat down and gave me a demo and I was like, wow, this is where we're going. And yes, you need to have a sense of belief. You need to imagine, you need to be able to dream, but if you understand the problem you're trying to solve and the tools that are available, this is absolutely where we're going. And so that's when we started an effort to say, okay, for fundamental investing, absolutely there should be agents that are ultimately helping with analysis and ultimately to provide being to what's going on. So people talk about that now, but that was two years ago. That was a real moment for me. And then more recently this year said, I think a lot of podcasts that consume a lot of information, and I was listening to one actually with Chris Sacca, who's a very entertaining individual sort of talking about with frankly a bit of hyperbole but entertaining hyperbole just about where we're going. And I was like, you know what? That's so true. What these machines can do now is incredible. And it does take a little bit of imagination, but in some ways it's kind of you can see the end point more easily than you can see the steps to get there. I was using this analogy recently. I'll just tell you too, but I really did use this one.

So my favorite movie growing up was The Sword and the Stone, made in the sixties by Disney. And I have three little kids, and that's one of their favorite movies. So I was watching with him recently, and so Merlin in the cartoon version of The Sword of the Stone, he lives backwards in time, and so he can see glimpses of the future but he doesn't see the steps in between and that's kind of how I felt like here. It's impossible for me not to believe that in five years, firms that do what we do won't be heavily integrated with best of breed AI technology across the firm, not just for investment, but for non-investment purposes. And I say that in our industry, because if not the most clear associations between information and ultimately money, right?

The value of having an edge from an information standpoint is huge. And so that's why finances is really going to pick up and actually use these tools and say, okay, what applications actually can gimme an information advantage? So that's very clearly where we're going. but the steps together can be a bit hazier. And so actually it was after this podcast, I said with Chris Sacca that I wrote the team, this is how we ultimately met you. It was like, we're gonna train. Mandatory, every single person at the firm doesn't, doesn't matter what department you're in, how technical or not-technical you are, you're gonna have a base case level of proficiency in AI tools. And as part of this actually does come from a sense of responsibility, people are anxious about what all these things are going to mean? How does that impact my job? What skills do I need to have? And, me saying to the firm, okay, we are going to be a place that is gonna be leading that we will actually train you. We will give the tools available. You still have to learn them, but we'll make it accessible and make it accessible to everyone. So that was when we just started doing a lot more, not just building call it tools using advanced AI. And as I said, we've been doing that in our quant business for 10 years. And not just building essentially digital analysts or replacing the work of humans in long-short stock picking. But then over the past, really this year of saying to everyone across the firm even in accounting, finance, compliance, legal. Yes, you should be using either ChatGPTor Grok or some LLM to assist in anything that you're doing, that's analysis or writing.

(00:11:00)

We record pretty much every bit of information that flows through the firm. A huge part of this is actually having a proper data strategy. And then also just having the culture of, yeah, we're we don't really know all the answers to this, but let's just start talking about it. Let's make it accessible, so simple things like having weekly emails where there's leaderboards of who's using these tools the most? Actually I sent the entire firm an email and said, hey, if you suggest a tool that ultimately we end up pushing out across the firm just like there’s incentive systems for employee referrals, we'll do something similar here too. We have weekly meetups, informal weekly meetups internally just to talk about AI, be it prompts or other use cases. I mean, one of your previous guests talked about the sort of the social nature of AI and how hard it is just to even discover best use cases, which I couldn't agree with more, but just even internally trying to make it a bit more social, a bit more accessible and I'm involved in all of this. And in fact, I'm sort of the chief AI evangelist. And a huge part of that is just my own personal curiosity. But you can already, you can already see it working. People are doing things that they weren't asked to do. It's so cool. And the productivity coming from that, like it's real. This isn't just vapor. So yeah, we're definitely going down this path.

Dan Shipper

One of the things I think you've been so effective at doing is basically, you can think of companies, even 10 people, but 400 people bigger than that the bigger they get, the harder it is to steer. They are like maybe a startup is like a canoe and a 400-person company is like a cruise ship and a 10,000-person company is like a battle cruiser or whatever. And I think you've done a really incredible job of pointing at the cruise ship really quickly. And that's something that's happening a lot now. It’s becoming a meme that CEOs are writing basically the AI first memo. And I think you have the best example of that memo that I've ever seen. Would you mind just reading maybe the first paragraph or two of what you wrote because I think it's amazing.

Will England

Yeah. I can read that. And on that point, as I said, words are cheap, particularly in a world of AI. You can create great world words very easily. To your point around, being a bit of a cruise missile, I do think that's an advantage of ultimately governance. And I'm the owner-operator, so I don't worry about getting fired. I believe I worry about doing what I think is right. I very much believe this is right, and so we can just go and do some of these things, and large organizations just can't operate that way. So, as I said, a huge sense of responsibility because we can act that way to do it. So, yeah, I can read a couple of sentences but here we go. So Walleye has entered a new chapter in its evolution. our multi-strategy platform, the Walleye Opportunities Fund. That’s the name of our fund.

Dan Shipper

Wait. This isn't the one I'm thinking about. I'm thinking about the one that starts with: “I wrote this email using ChatGPT and you should too.” That's my favorite one.

Will England

Here we go. So yeah, this is an email that I wrote to the entire firm, and the subject is AI at Walleye. I challenged all of us. It says, I used ChatGPT to write this email. You should be using it too and be proud of it. I'm writing this as a follow up to the comments I made at the town hall at the start of the month and after our AI senate meeting earlier today, which is a group of forward-thinking AI users from departments across the firm. And the message is simple. Walleye is all in on AI. Not using these tools is like refusing to use the internet in 1995 because it wasn't perfect. That's just dumb and something I can't understand. As a hedge fund, we should be ashamed to leave money on the table by ignoring tools that make us faster, smarter, and more effective. Using ChatGPT is not cheating. That's a non-applicable idea from academia where using AI to do homework or take tests is actually cheating. In the real world. Using AI is like taking a magical elixir that makes you 20 percent smarter instantly, or a lot more. So why wouldn't you use it? From the very top, we are building a culture around AI. This is not optional for anyone at Walleye. If you write research, analyze, build decks, process data, or think for a living, you should be using ChatGPT and/or other AI tools every single day. Managers, this is now part of your job. You need to be pushing this across your teams, starting with being fluent yourself. So here's what's coming, and I'll talk a bit about some of the things we're doing recently that I just mentioned. And then ended this is the beginning, the edge is real, and we'll not fall behind. Let's lead.

Dan Shipper

I love that. You hit on a couple things there that I really love. One is this, the sort of cheating question that a lot of people have. I have that too, it's just an internalized sense of, oh my god, this might be too easy. And when something's too easy, you're like, am I cheating? And also sort of addressing this fear that I think a lot of people have, which is like, am I gonna be replaced? And I think the way that you're talking about it, actually this is now part of your job. It's not that your job's gone, it's that your job is changing to include this as an expectation.

Will England

Yeah. So I have very strong views on both of these. As I've gone on in my career my role has changed, and I believe that for all effective leaders as they go on, they should evolve as well. I love the Jim Collins quote, build a clock, don't be a timekeeper. And so this is an example of that, where if you can have a tool that makes you more effective, it's the same thing as sort of hiring someone to replace part of what you were doing so that you can move on to the next task. So your context level shifts up. And so I'm not embarrassed at all that I can write emails that used to, or long memos that used to take me hours that maybe I could do that in a half hour or less. and that to some extent, people have this insecurity that if I didn't put my blood, sweat, and tears into it that somehow it's not real.

But at the end of the day results are what matter. I think I spent a lot of time as an athlete, and I still do a bunch of stupid stuff in the gym as my hobby. And at the end of the day, either you pick up the fucking weight or you don't. And I think that's just the attitude that people need to have in the business context, as I mentioned. And there's this huge difference between academia where people are like, oh my god, it is ruining school, which in the existing paradigm, you can certainly argue that, but that's not business. And just being very clear about that, you should be trying to be as efficient as possible, not so that you can just leave work at 2:00 p.m. so you can actually spend time thinking about next level tasks, higher level contexts, be a bit creative, and ultimately think of yourself even if you're an individual and you don't manage any human you're still gonna be managing employees. A lot of those employees are just going to be AI robots. And that's a skill in and of itself. The reason I wrote that to the entire firm is just to make people feel comfortable and not kind of embarrassed about what it's like, because what I was seeing before is. People were using ChatGPT or another similar product to create an email and they were trying to like dust it up.

It's like I don't want to be seen as doing that. So they're like, that's just fucking stupid. You should be doing that. And if you aren't, why did you waste three hours writing this thing? So again, I have very strong feelings about that. And at the same time, you're commenting around this anxiety of what my job is going to be? When spreadsheets came out or an email came out, you name it. Yeah, you have to learn how to use these tools. And I see this all the time very deliberately. We hire people or we say are at an inflection point of their career typically mid-career where they know enough to be dangerous. The competency is there, but the hunger is still there. And the ability to be dynamic, to learn new skills is also still there. That matters a lot. And I don't think there's any different, if you're just using an example, if you're a long-short stock picker and you can't use Excel on a company model, you're totally obsolete and in future years you're gonna have sort of the same thing where if you don't know how to use these tools or you're not at a firm that to give you access to the tools to give you operating leverage, then you're also gonna be operate obsolete.

And so that phrase is what I use a lot, is just this concept of operating leverage and not being afraid of that. but yes, absolutely, I see that all the time. And it goes back to my earlier comments around feeling a sense of responsibility to put people in a position to say, don't be afraid of this stuff, embrace it. And another thing that I was seeing Dan a lot of these tools aren't, they're not perfect. I mean, none of them are actually perfect. They all have their flaws. They all do stupid things. but the direction of travel is very positive. And so I wanted to set the culture and environment where instead of people being like shit didn't do exactly what I wanted, so I'm just gonna ignore it until it's perfect. It's kind of going the opposite way of being like, let's have a demo with a third of the company joining, which is real. That's how many people join. And if that demo screws up, who cares? I basically had one last week that the demo gods were against me, but it was totally fine.

(00:20:54)

And having people accept that and embrace that and be like, some of this stuff isn't perfect, but you can see where it's going. as opposed to just almost using that imperfection as an excuse to ignore it. So all those things combined into one there's no other person besides me, and I think this is true of all leaders. The organization, like you, has to lead from the front. no one. No one can set that tone besides the leader. And once that tone has been set, it's kind of incredible how much you can unlock people to be like, yeah, have at it. And it's okay setting that tone and flipping it outside, be sort of you need to be afraid or a lot of people are afraid not to or to make a mistake, kind of need to be more afraid of getting left behind.

Dan Shipper

And what have you seen? For someone who's watching this and maybe is in finance or maybe it's just running another company with a lot of people and is thinking about it, okay but really what productivity gains has it actually unlocked for you? Concretely, what are a couple things that have been useful for you or for the fund?

Will England

So there's a couple things you have to put this into categories of what's recent and what's not. So as I mentioned we do run a big quantitative trading business as a multi-strategy firm. We won many different strategies, but quantitative equity training is a big part of what we do. Those models have used non-linear statistics AI or some of the underlying models in AI for years. More recently with the advent of large language models comes the ability to process unstructured data of course, and incorporate that into signals, which historically is called sentiment analysis. You know the ability to do that at scale has gone dramatically. So that's one improvement just from a pure money making standpoint.

Dan Shipper

And you're doing that? You're using language models to do sentiment analysis?

Will England

Yes. We absolutely are doing that and have been doing that for years. And frankly, all world-class quant firms are doing that, but it's hard. That's why quant trading is one of the things that definitely benefits scale. Some of the things that are called more recent are newer. And I do believe that the explosion that we've seen. It empowers the less and less call technical people that the technical side where really you just have to be creative. So some of us, 75 percent of the firm, are active ChatGPT users every single week, actually almost every single day. That's pretty cool. About a third of the firm use AI coding tools such as Windsurf that's sort of very real. Our, as I said, internal product for fundamental launch or stock pickers. That's also a big part of our business. Every single team uses this tool. It's called Current. It spikes dramatically during earnings. We have people that come here from our competitors and tell us that this is both way better but really an essential part of their job. And I believe that, and I think our competitors probably do have good products as well. I think we've just been doing a little bit longer and are further down the path of using these tools actually to provide meeting and real analysis as opposed to just summarization. But yeah you kind of can't go through earnings period now as a long first stocker without some of these tools if you're going to be competitive because, one of your competitors, someone here is gonna be able to process all of them in real time and then have a machine going look at we basically impute things that humans can't do as fast. So how do we actually measure that?

Of course having benchmarks, that's kind of nonsense in a real company. But just sort of seeing the level of adoption. just seeing people suggesting products like, okay, we want a we talked about last week one of our meetups to have a product that can do summarization via podcast to make it more accessible to people that want to listen to something. And then that day we had five different products in beta and then the next day was pushed out across the firm. So some of these sort of cultural elements of just having actually set up the process where we can both incorporate third-party products and build some of them ourselves. That's pretty cool and I don't know how much smarter, more efficient that's making people. I certainly could speak from personal experience. A big part of running an organization is communication. My communication is dramatically and in a lot of cases written, and that's dramatically more efficient now than when I was using these tools, and I think that's probably true for literally every single person in a firm.

Dan Shipper

What does that actually look like for you? When you're using it to communicate, what are you doing?

Will England

So I think best when I write out my thoughts I tell people that my education is very expensive, so I better be able to write or else what the hell is all that for. And so historically I really would write to convey what I'm thinking, where the firm is going, why, and I just believe that leaders should be able to really communicate okay now, and I believe in the power of high quality prose. And it's actually one of the things in general, before LLMs came about, that it was pretty fucking depressing that younger people just were terrible writers. So for me, when I want to write an email as an example, write a memo, I do it in bullet point form. I type out, here's what I'm thinking, here's why. I work on my prompts. And maybe I'll give a bunch of context of, hey here's all the stuff that I've written on a similar subject and I want you to give something in my own voice. And that can be no exaggeration, a 15-minute process that would've taken me four or five hours historically. That's why I have such almost religious views on this stuff because it's pretty wild. So that's one example of where 'm using that personally.

Another thing that we do. And yes, there are always the questions on what can or can't be recorded, kind of going back to the governance element where I can say, this is what I believe is the right thing we're to do. So internally with a few exceptions, we really record every single Zoom, every single call. That's just the nature of our industry. And frankly, I think the whole world should get used to doing that. You’re seeing these articles about people wearing wristbands, recording everything they say for months and months at a time. You extend that forward without sounding too much like a nut job, I think people are gonna have essentially recording devices implanted in their bodies that record everything. So just getting comfortable with the fact of, yeah, all this data is going to get captured. So we're trying to do as much of that internally and then of just being able to go back and process that. because so much of the power of this is do we actually have a data strategy, get all the data into a lake, which you can then, put a straw into and get it out.

So a big part of my job overseeing the risk of the firm, the chief investment officer title, every single morning, me and my risk team, sort of in the control center of running this giant process we have our risk calls and those are all recorded and we can go back and say, hey what were we talking about at this time? And continually have LLMs that are, that are processing those transcripts and helping us to both remember and provide insights and ultimately be a bit predictive, which has been hugely helpful just in that exercise, which is— We haven't sort of talked about where I think this is going in the power of all this. And I mean, I do believe that we're that we're a leader. I don't want to say we're the leader because I definitely don't know what other firms are doing, but I certainly think that we are a bit more advanced in our thinking of how to use these tools, but we're just scratching the surface of what is possible once you actually start connecting all bits of information within the walls of the firm. And this is not just Walleye, not just hedge funds, really any company saying, hey, let's actually put all of our data together into effectively a collective and then that information can get processed, we're totally discretionary in service there, but we're certainly working towards that.

Dan Shipper

I want to go back to something you said earlier about writing as thinking and using language models to turn a four or five hour task into a 15-minute task. What is your one of the things I worry about, for example, is maybe I'm not thinking it through as clearly, if the language model has like written a bunch of stuff that it's coming from my bullet points, but I haven't really gone through every single thing and been like, I stand behind that.

(00:31:23)

Will England

Yeah, I'm sure. I think you have to separate this out in terms of thinking through the concepts vs. the linguistic syntax. What I was knowing, at least personally, and I do think a lot of people do this is when they're writing, they're trying to be both consistent to some extent, clever and to some extent unique to their own style. And so a lot of editing can be, I think less about the concept and more. What are some of the nitty gritty details of how you stitch sentences together? Even simple things like it drives me absolutely nuts when someone ends a sentence in a proposition and everyone heard the firm knows that. But you don't, so you don't have to spend as much time again, I think on the important but not as powerful tasks of writing. A lot of it is just sort of stitching these pieces together, the tying your shoes part, so the principles, the elements of writing, what are the concepts that I'm looking to convey. That's what I spend my time on now. So what I've found with these tools is really trying to be clear that this is the concept that I want you to get across. and this is how, and then yes, it will suggest a string of words that convey that. And particularly with the way the recent models are architected, it has everything that I've written so it can do it to some extent in my own voice. I just don't have to spend as much time, frankly trying to be clever. And that's what a lot of writers do. They try to say a lot of relatively straightforward concepts in a clever way. I just don't think we need to waste time on that anymore.

Dan Shipper

I would never do that. As a writer I'm curious but let's flip the table a little bit to like, when you're reviewing someone else's work. So for example, for me as a manager, I think, let's accept for example, if someone's gonna publish something on every page, that sounds like it's AI-written, that's just for different reasons. But if I get an internal report that looks like it's written by ChatGPT and I did this actually last week because everyone internally is using these tools all the time. It’s not that I care that the voice sounds like ChatGPT, it's that it's not clear to me that the person has thought through the thing that is being presented to me. And I don't want to spend time reading something unless. I know that a commensurate amount of time has been spent thinking about it first. So how do you like to deal with that?

Will England

Look, these tools don't negate the necessity to think. And I say that all the time. If anything they should just give you more time to think. If you say, okay, you have an hour to complete this task. And it used to be historically 50–60 percent of that time, it was just gonna be mechanically typing out and now I don’t know, 5 percent of the time is spent doing that. So you have more time to think just in a fixed amount of time. So you should really think, you should really read, you should proofread and say, does this make sense to me? Is this what I'm trying to convey? And so I can definitely tell as well, when something was written by a machine sometimes that's just the way that the text appears, the bolds, clearly a human didn't go and bolded in exactly this way. That's fine, but it's not enough. It's not sufficient. You still need to convey the concepts clearly. In an ideal case, someone has clearly used these tools, but the concepts still come from them. And I can tie it back to that person. And there's a why of, okay, why are you doing this? Why does this make sense? And you didn't waste your time doing something that wasn't necessary, but at the same time, you didn't just outsource all of your brain to a machine. And there's that optimal point on the curve that we're trying to get to and that's again why I don't think people should be totally afraid of using these tools because of themselves. I don't think they're sufficient. I think that it's like having a very powerful jet engine. And you use that analogy with me as well. A jet engine won't fly by itself. You still have to hook it up with a plane and there's a hell, lot of things that matter when it comes to aerodynamics and whether they make a plane efficient or not. So humans can kind of design the plane a little bit more and someone else brings the engine. You can use that engine in very powerful ways but you, but you need to be a part of the process for sure.

Dan Shipper

I want to talk about that, the thing you brought up next, which is sort of this data lake idea of, sort of recording everything. You've been calling it the Borg, as a Star Trek fan. So where you're recording all the meetings now, which I think is awesome. And you said it's already helping, for example, in your risk calls, you can tell how you made a decision. Can you give us a concrete case where having all those recordings has actually been helpful?

Will England

So, yeah, the Borg, which has come from Star Trek. And I'm kind of sad now that when I say the word Borg — even some real nerdy people don't even know it, which means I'm getting a little bit older. And the collective, which gets all the information together, that's at least our spirit animal, our spirit guide for the future. It is really hard. I think all companies are going to have this, and some of this is not at all particular to finance. It's just there isn't even a great way to process all of a firm's emails right now using AI, which I'm sure will be solved soon.

So the most salient example of where we've done a miniature example of this goes back to said our internal product current, which it takes analyst notes all information coming in from brokers and these PDFs that get emailed around all the time earnings transcripts really any bit of information that's germane to a stock that's our most advanced call it org example. And, as I said, that really is real. All of our PMs view this as an indispensable tool that saves them a ton of time, particularly when information flow is very fast. Again, quantifying that exactly—there's no perfect metric. A lot of it is definitely subjective, but I can see internal use case numbers. And I can also see— All external firms know that we've built this and are doing it. And over 50 of them have asked, hey, can we be a beta user of current and we'll give you feedback to help make the product better, which we've done in some cases. And it also makes sense, right? That a huge part of the job of a human is synthesizing information. And until recently, when it comes to reading documents, machines couldn't do that very well. Reading documents or listening to voice essentially in other text forms, but now machines can. And now the servicing, the second order, the third order effects of that, again, not just summarization. That's what machines are starting to do. And that said, that's our main use case. And so this is the broader idea of the Borg.

I look at what we've done to just help our long-short stock pickers and say that the same concept should be able to help every single department at the firm, generating text is a simple example. Through emails, through Slack messages, through live calls, live conversations. And then ultimately the ultimate goal is to tie that back to numerical data, whether that be market data internal data, accounting data, you name it. So the applications, as I said, do take time to imagine, to design, but it, what I mentioned earlier, it's not that hard to see where this could go in the future when you do have these sort of miniature collectives across all departments of the firms and other firm, of any firm, and then linking them together like that will happen. It's just a matter of how to get there that I think everyone is still trying to figure out.

Dan Shipper

I know that you're a student of history. Do you have any historical knowledge periods or examples that you're turning to kind of help you navigate what's going on right now and this transition that you're going through?

Will England

I’m a student of history. I do love, basically, the period between the Civil War and World War I is a time when I think the whole world changed dramatically. And then part of that is that my office looks out on a train station built by one of the robber barons. So I do think about it all the time so it's certainly not the only period of history, but definitely in a time period where things changed dramatically. I'm not a VC, thank god, because I think most of them don’t know what the fuck they're doing. But certainly this idea that when you look at an exponential curve humans sort of knows, hits up against that, doesn't realize how fast things can change. So there are periods of time, like how fast the railroads got connected or how fast transatlantic cables and what that actually meant. As I said, the period between the Civil War and World War I, just huge amounts of change. And people within their own lifetimes sort of went from having relevant skills to obsolete skills that are gonna happen faster this go round. And then when I said I thank god I'm not a VC because I hear a lot of people, investor types, predicting about the project case about this, but they aren't actually involved in any operating companies and don't realize that someone still needs to go out and build all this stuff. but I do think the sort of first-principle arguments of, yeah, things are going to change dramatically. Corporations, collections of humans, let's just say companies in the future that want to operate in a world class manner at scale are still going to need them. Many thousands or more of employees, but if fewer of those employees are going to be humans a lot more of them are going to be machines. And so you've certainly seen that level of disruption in other areas that just have it a little bit faster this time. But at the same time, I'm sort of an optimist in general. I think that's very important for leaders to actually have an optimistic tone. I don't think the world is going to end because all of a sudden people are gonna have their jobs disrupted by AI that they need to adapt to.

(00:41:44)

It’s sort of having a level of realism around that's what I mean. Our firm is a microcosm of that if yeah, you have to learn these tools or in whatever time period you're just not gonna be competitive. And we are at the tip of the spear from a competition standpoint, just given the nature of what, of the industry and what our types of firms actually do. But I think it's gonna be true across the wider swath of the population where you’ve got to be efficient and at some point if you don't, That’s your choice. And that just is what it is.

Dan Shipper

I think that period of history is actually really relevant. And coincidentally, I told you this already, but I'm sort of in my cowboy era and I've been reading a lot of cowboy stuff.

Will England

You watch the Netflix thing, Wyatt Earp and the Cowboy War?

Dan Shipper

No. Should I?

Will England

Yeah, it's really good. It's really good.

Dan Shipper

It just came out? Okay. I'll check that out. I just finished Deadwood, which I was telling you about.

Will England

Yeah. Deadwood is good. I never watched any TV, but this one came out and I also love sort of the old West. It was a good story.

Dan Shipper

Do you know why the cowboys disappeared? I just learned this and it's a really interesting fact.

Will England

You tell me. I have a hypothesis, but you go first.

Dan Shipper

Barbed wire.

Will England

Yeah, I was gonna say the broader— Well, in that documentary, The Cowboy War, what basically the answer was civilization kind of came in, you had the railroad come in, which brought a lot of people and then eventually barbed wire. And you couldn't steal cows. I mean, the cowboys were a gang in Arizona in the 1870s and 1880s stealing cows especially from.

Dan Shipper

I didn’t know that.

Will England

Oh yeah. The cow. So it is fascinating, but the Cowboy War and Wyatt Earp, who is this historical figure of legend gets in this huge fight like the movie Tombstone, which is kind of historically accurate, but not really. It was sort of the wider posse vs. the cow bo— two words— posse, and it was this big, it ended up being this big deal. That's the gunfight at the O.K. Corral, because it stirred up all this sort of north vs. south sentiment 20 years after the Civil War. But in the broader historical context there are people sort of wanting to bring about change because the tombstone where the O.K. Corral was, and where the airport was a silver mine. So it brought in all these people from across the country, both north and south, but there's this huge tension between those wanting to modernize and those wanting to get stuck in the ways of the past. So yeah, it's that period of time that I find fascinating too because you had a sort of land with no laws all of a sudden becoming civilized at various different paces and a lot of cool things or interesting things at least happening because of that.

Dan Shipper

Yeah, I think that's it's for me, I love that because I think it's such a good metaphor for technology and technology frontiers and kind of this trade off between, you have the individualists who are going out and exploring and there's no laws and there's a lot of creativity and all that kind of stuff. But then you kind of need the civilization that comes behind them. But that sort of thing. It's at odds with that frontier spirit. So there's that tension between structure and creativity and I think there's something very similar there about technology.

Will England

Similar levels, man. I mean that's even true with sort of at least historically of the why does VC investing exist? You know, why is it that you go and read about the story of you pick any company from Nvidia on down where they're like, I can't do this at a big company, so I'm gonna go and push the frontier in a world in which I'm less constrained there's no barbed wire and I'm gonna go and build. And then at some point those companies become successful to become institutionalized and then someone does that again. And so that's not a geographic frontier, but a technology frontier. and as I mentioned earlier, I feel a sense of responsibility because we can kind of do both and they're just not that many companies that can say that. And we want to push the frontier, but with resources. And you know, those ultimately are, I think the businesses that when you look at any technology transition are able not just to adapt but to thrive off having that mentality but not being not using single action rifles when other people have machine guns.

Dan Shipper

What do you think about how the past informs the future? And I'm asking this both from a kind of a late 1860s to now perspective, but also from an investing perspective. and I think this layers into the AI stuff where it strikes me that a lot of— Or I'm curious what you think about this, but a lot of investing has to align to some degree on the idea that certain things that happened before are gonna happen again. And part of investing, part of being good at it is knowing which one's gonna happen again and which one's not. Do you agree with that characterization and how do you do it? How do you think about when to rely on past patterns to help you understand the future?

Will England

I don't think human nature has changed in 10,000 years. And maybe it's evolved a little bit, but you go back and my son who's eight he's really into Egypt right now. I love Roman history because I took Latin and I'm a real nerd. So I know a lot about Rome, but you can read a lot about that too. Human nature hasn't changed in a long period of time. You know, you go and just to use a famous example, the old always wants to, or the new always wants to replace the old. The son wants to outdo the father. These are timeless. When Alexander the Great was conquering Persia, the King of Persia sent him a note and he was like, hey, how about we have the truce? And he responds like I'm coming for you. And so this concept of yeah, no, that's a good story, right? But this concept of the new wanting to replace the old and this continuous evolution, you find it in nature everyone sort of knows the analogy of a forest fire burns the trees so the new brush can grow. This concept renewal is always going to be there. It's in human nature. It's nature. I think it's just a pattern that we're going to see. And it's the same place here.

There's gonna be a group of people, a group of firms, a collection of individuals that are going local and embracing that. And then there's going to be groups of people that are gonna hold onto the past. And there's gonna be conflict of varying degrees because of that hasn't changed a lot. So when it comes to investing, when we look for patterns, when quant investing of course is built on this concept. That there are patterns in history, in stock prices and information that was predictive. And there's a structure to that data, even if that structure is so complex that humans can't understand it. And in world class quant investing we've moved past what humans can understand many decades ago if people forget how long and what the book on Renaissance came out.

But, some people still don't realize that quant investing has been going full war since, at least the early nineties. And so absolutely that whole class of strategies, which is a huge part of the markets today. It's built on this concept that historical patterns do repeat themselves. When most people think about investing, they think about sort of human driven intuition and investing. I also believe that's timeless. It's just timeless on a different scale. And that is where on a go forward basis, I still very much believe that human investors will have an edge, particularly on low law of large numbers, situations where a machine hasn't exactly seen all the priors and the precursors that would lead it to make an informed decision, but a human can be better at dealing in the fuzzy mess.

So all these tools that we're building can be built to enable that human to make a prediction more accurately. Yeah, there's patterns that come with history. History doesn't repeat itself. It rhymes, for humans. So I guess summing all that up just saying this is the way things happened in the past is silly because they never repeat themself. Exactly. you have to sort of more go to they aren't underly mechanics particularly around human nature. I think human nature is constant, it is stationary across time. If you just look at it in the right way, where you're gone lies all the other crap that's happening.

Dan Shipper

We'll have to debate whether human nature is static or not because I'll take the opposite on that one, but I have another direction I want to take this, which is, I didn't realize that now you're— Now I'm nerding out. I didn't realize that there are things happening in quant trading that are in principle, not explainable, not like humans can't understand it at all. Is that what you're saying? Or they could, but it's just so complicated that no one takes the time to do it because it's not worth it.

Will England

Well there's so many different flavors of quant investing. But, generally speaking, the higher sharpe ratio or the more consistent strategies that you get that aren't pure arbitrage, it's not just based on speed. It’s just, why does an LLM do what it's going to do? People kind of understand that, but not really. They're all these non-linear relationships.

(00:51:35)

A lot of those techniques have been used on structured data in these models for years. I mean, you go back and read the book about when the guys from IBM came over to Renaissance what they were doing. They're doing speech recognition, like a lot of that sort of pattern matching and sort of predicting what comes next. Yeah, for a human to actually sit down and walk me through all the different layers of the neural network and why did a machine do what it's going to do with the dimensionality of that problem, just its way past what a human mind can understand. So I'd say generally speaking, world-class plot models while the signals that go into them of saying this is something that I ultimately, this feature makes sense how those features get and which I do think is important and that, again, there's various different ways in which firms go about this. Generally speaking, we want to understand at least some rationale to our features, even if there are many thousands of them. But how those ultimately get combined and understanding nonlinear relationships from that's very complex and that's totally fine.

Dan Shipper

So it's interesting that you brought up intuition a little bit earlier as something sort of separate from the more algorithmic and it is a helpful addition to the more algorithmic quant decision making. Because I actually think of neural networks and intuition, human intuition as being analogous and maybe even helping us to understand how valuable and important intuition is despite being unexplainable because it's kind of unexplainable in the same way you're working on a very high-dimensional basis with problems that you can kind of talk about why you make a decision here or there. But it's really just kind of a feeling that you've built up over many experiences. And I think neural networks are the same way.

Will England

I do think intuition is very important for building a process. And really another term that you could say analogous to a situation is first principles. and there's a very famous guy that uses first principles all the time. But I very much believe that it actually sort of understands it's really a math term, right? If you can understand some of the core concepts, the first principles in math, then. You can take any test and get 100 percent. So I was a math guy. I like talking from first principles. And I think it's the same way, but when you interface that with machines what machines can really help you to do is say, I might actually help you come up with something intuitive, but you wouldn't necessarily come up with yourself kind of having a coach where they could watch you doing a movement or lifting weight and did you actually realize that these things are connected? So I don't think they're antagonistic, but it is entirely consistent that a machine can give you a very intuitive answer that you wouldn't necessarily have been able to think of yourself, if that makes sense.

Dan Shipper

Do you think that first principles, and this is a leading question because I have an opinion on this, but do you think that first principles. In this I don't think that first principles in the math sense are the same thing as first principles in the let's say decision making sense. in the sense that when you, when you use the word first principles in a math sense once you adopt them, you can just work out all of the implications of those principles without, like you said, you can take the test and you can just figure out what all the answers are. But first principles in a kind of a decision making sense, they're not at the bare level of axioms in math. They're already many layers up above and can be filled in many different ways.

Will England

The real world, the difference is in a mathematical model. And math is just a model for the way that things operate. And within a model you have rules. And so there's real objectivity to what the rules are. Sometimes those rules can be very complicated, but there's an underlying structure. In organic systems that sometimes they're structured, sometimes they aren't. So I agree with you when it comes to decision making. That's why the word subjectivity exists and what could be first principles to one person might be totally the opposite of someone else's first principles. They both call them ground truth and axioms whatever. So, there is an element of subjectivity in the real world. When it comes to decision making and what I believe and what I believe really good decision makers try to do is understand their own decision making process. Both to discover what's led to good decisions and what areas and their decision making has been subpar. So, in some ways you can kinda apply it more to your own closed system, but to say there's a universal truth around how decisions are gonna get made. Yeah, that kind of falls down at some point. Because people might just totally be schooled and first principles that are so different that would lead them to make completely different decisions.

Dan Shipper

What are those for you? As you've learned to improve your decisions over time, what are the things that you've learned to take as good, reliable, first principles and what are some of the ones that you've thrown out?

Will England

At the top of the list would be the power of incentives when you're dealing with humans and not in a negative sense, like everyone is greedy, although a lot of times that does drive behavior. But actually understanding the right incentive decision for why an individual or group of individuals is doing something and trying to align that as much as possible, whether you're running a company or making an investment. That’s extremely powerful just to say are the incentive vectors all pointing in the same dimension? So that's a big one. You mentioned earlier, I hate fluff. I hate bullshit. Sometimes it gets me into trouble but I wish that people would be more that way. And so that's whether that's an axiom or rule, but whenever I sense that my antenna goes up, that's sort of a negative sign. And really just trying to be intellectually honest and so not trying to reduce everything into a math problem, but a lot of times there is structure that you can pull out of a situation and it might just require hard work.

So you can't manage what you can't measure so try to measure a lot of things and personally, I try to do that. I evaluate myself. I keep a journal every single day with AI. Now, by the way, which is great for efficiency and highly recommend everyone do that. Every single workout that I do for years I track. I have a log and there's a lot of numbers in that just to see these trends evolve across time. And again, none of these are perfect, but I feel like because it's hard, a lot of people just don't do things like that. and I actually, on a go forward basis, I think that's one of the things that's so exciting about this world of really data and making meaning out of data is it's gonna be so much easier to do that and a lot of it's gonna be around are you collecting the right data to help people with that? So yeah the biggest first principles, I said power of incentives and intellectual honesty and those would be the top for me.

Dan Shipper

What goes into your journal?

Will England

Well, there's three components of my life which would be my family. I have three kids and I've been with my wife who's amazing for 15 years and I love being with them and that. It's not just a platitude. So my personal life and how I'm interacting with the family, and I feel a huge sense of responsibility to my family, to provide them with a great life. So there's a section on that. There’s a section on— And by the way, none of these are mutually exclusive. I don't believe in balance.

I believe in harmony across different areas of life. so there's, but there's a section on that. There's a section on work, which for me at this point is this great big challenge that's fun. I think sometimes people don't even use the word fund and I guess one of the things with AI, like this, is that it doesn't need to be scary. This is fun to tell.

If you look at it the right way, it's really important that people have that view. and I'm working because I get meaning out of it. I enjoy it. And it's different than— And I feel fortunate in that than most people where I can say I'm doing this because I certainly want to, so there's things on work that I talk about, and then there's things just on my personal health that I talk about, how I'm feeling was a good day or bad day. How did my dead lifting session go in the morning—stuff like that. I'm a bit of a crazy person on that subject. So if I try a new supplement or try some new technique or something, I'll write about that. But I'm just trying to capture what's going on in my mind. I started doing this because I look back and in finance, we're dealing with time series and so we could say like on this day you made or lost money, or such and such happened.

But I really wanted to remember what I was actually thinking on that day. And just trying to keep it all in your head, even for someone that can have a lot of hard drive space is impossible. So getting that outta my head a bit more. was why I started doing that. And it's been really helpful both as an exercise in itself, even of just writing it, but then going back and saying like, oh yeah, this is what I was taking on that day.

(01:00:00)

Dan Shipper

That’s interesting. And help me understand that more. Maybe now you're typing this into ChatGPT, you're speaking it, you're writing it into Google Doc and then putting it into ChatGPT?

Will England

I'm trying to capture the concepts of what I felt that day. So I can either speak or just write bullet points of what's on my mind in these three categories. On the date, this is what's on my mind. Some days that's a lot, some days that's a little, and then because I've been doing this and the machine knows my voice, that can be a one minute, even a 30-second exercise. It's just so easy to do. And I feel the reason most people don't journal is because historically I sit down, it would take time. But this is a perfect example of the thought that's on your mind, just get it out there very easily, and then it can be captured, processed in a way that is accessible once in the future. It's just this tiny little use case that's sort of so powerful with these tools. And there was no way that could have happened in the future.

Dan Shipper

One word that you brought up a lot in the context of work, but also you just brought it up also in the context of family that I'm curious about, is the word responsibility. What does that mean to you?

Will England

I do think about this word a lot in the context of work and family. Slightly different, but overlapping of course. I feel that people that either are endowed with certain skills, like their clock speeds really fast or they have a lot of resources or they have great networks just to generally speak to people with that. That the world has entrusted upon them skills or capabilities have a responsibility to themselves and to their community to use that to the maximum extent possible. If you run 100 meters in one 10 seconds and you don't, it's a fucking travesty. And because not everyone can do that. So historically, and this is before I met my wife and years ago when it was really just me, I'd say that sense of responsibility was to myself to try to get the most out of my own capabilities. And then as I went on in my career and felt that I was able to do that, and I was like, okay, well my kids are 10 and eight and two and a half, and we haven't even talked about what it's like to be a parent in a world of AI, but having a sense of responsibility to have them grow up and to flourish and have a relationship with them that can evolve as they become adults, but ultimately to set them on a path huge sense of responsibility.

As a parent, this is just amazing how much kids look to you for guidance and then responsibility for the firm like in our world, in the investment world you have sort of two sets of responsibilities. One is, and this is by far and away at the top and take this very seriously, is: People give you money, or typically in our case, institutions give you money. And because of our type of hedge fund, we're a pass through structure, which is not an operational nuance that gets buried in documents. That means that we have a blank check from our investors to spend money whenever we want.

There's only a very small number of firms that have that type of structure. The biggest ones who were most famous are Citadel. But there's really only maybe a dozen, probably less than that are, that are really so huge funds of responsibility for our investors to do what's right, to not abuse that privilege and ultimately to we're we're in the money making business, let's just be honest about that. But also responsibility to our people too. And I think this is what's generic across all leaders in all companies in the world of AI. Leaders have a responsibility to the people working at their firm to prepare for what's coming next. And then I definitely feel that and all of it's tied together. I have a responsibility to our investors to do the best job as it can for them. And I have a responsibility to our people to be as efficient as possible. And those two coming together mesh very nicely. But yeah, I think for me, and I'm 40, so I'm not that old. I do want to be doing this for a long time, but as I say, as you, sort of go higher up as far as responsibility. I think that the notion of being a little bit more of a steward and helping others accomplish what they want to accomplish, like that's something that successful people talk a lot about. And I very much feel that. And it is very much aligned with what we talked about today in the world of AI.

Dan Shipper

I love it. Well, always a pleasure. Thank you so much for coming on. I'm excited to have you back maybe in a year when we have more results on how everything has been going. I always learn a lot from our chats, so thank you.

Will England

All right. You bet, man. Thank you.

Thanks to Scott Nover for editorial support.

Dan Shipper is the cofounder and CEO of Every, where he writes the Chain of Thought column and hosts the podcast AI & I. You can follow him on X at @danshipper and on LinkedIn, and Every on X at @every and on LinkedIn.

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