Will England, CEO of the ~$10B hedge fund Walleye Capital, explains why he made AI fluency mandatory for all 400 employees. An engineer with a math background from Oxford, England argues that refusing to use AI today is like refusing to use the internet in 1995, and models this stance publicly—including a firm-wide email that opened, "I used ChatGPT to write this email." In conversation with Dan Shipper on Every's AI & I, he covers what pushed him to go all-in on AI, the "AI-first" memo he shared at Walleye, why fear of using AI at work is misplaced, how he uses LLMs to sharpen his thinking, how the firm uses AI to draft memos, select stocks, and reduce risk, lessons from the American frontier about leading through technological change, his first principles for better decision-making, and how daily journaling works with AI. # Channel Presentation Observations ## Audience Addressed **Business leaders and operators navigating AI adoption**, demonstrated through: - The host frames takeaways for executives directly: *"for someone who's watching this and maybe is in finance or maybe is just running another company with a lot of people."* - Discussion topics are aimed at organizational decision-makers: mandatory AI training, culture-setting, data strategy, and governance advantages of owner-operators. **Secondary audience: knowledge workers anxious about AI**, shown by explicit discussion of: - Job anxiety and skill expectations — the guest addresses *"people [who] are anxious about what are all these things going to mean... what skills do I need to have."* - The "is this cheating?" concern, which the host says *"a lot of people have."* ## Claimed Scope - The channel positions itself inside the **AI-adoption-in-business conversation**, citing prior relevant content: *"one of your previous guests talked about the sort of the social nature of AI."* - Guest selection signals scope: a CEO who pivoted a ~$10B firm around AI, plus tangents into quant trading, decision-making, and history — indicating a **broad "how AI changes work and thinking" remit** rather than a narrow how-to format. - The guest explicitly frames his appearance as connected to a consulting relationship: *"you're an every consulting client"* — indicating the channel is tied to a brand called **Every**. ## Self-Description Evidence - The host is named as **Dan Shipper**, called "the captain of the spaceship" in a stylized outro: *"It's not just a show. It's a journey into the future with Dan Shipper as the captain of the spaceship."* - The outro names the show: *"smash that like button and subscribe to **AI and I**"* — establishing the show title with a playful, self-aware tone ("the epitome of awesomeness," "knowledge bombs"). - Sponsor read confirms the brand: an ad for Attio directs viewers to *"atio.com/every"*, tying the show to Every. - The host's editorial voice is demonstrated, not just claimed: he pushes back on the guest ("we'll have to debate whether human nature is static or not") and editorializes about his own management standards (*"if someone's going to publish something on every that sounds like it's AI written... that's just out"*), indicating a first-person, opinionated host format rather than neutral interviewing. ## Format Observations - Long-form interview/podcast format with a cold-open teaser (the AI memo read twice — once at the start, once in context), an mid-roll sponsor read, and a stylized comedic outro. - Recurring-guest structure implied: *"I'm excited to have you back maybe in a year."* # Delivery Observation Document **Video:** *Why This $10B Hedge Fund Made AI Training Mandatory (Best of the Pod)* **Speaker observed:** The guest ("Will"), CEO/CIO of Walleye, in conversation with the host. --- ## 1. Tone - **Direct and declarative.** The guest frequently makes flat, confident assertions with minimal hedging: > "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." - **Moralizing urgency.** He repeatedly frames AI adoption as an obligation, not a choice: > "we should be ashamed to leave money on the table" > "This is not optional for anyone at Walleye." - **Self-aware confidence.** He names his own traits explicitly rather than implying them: > "I'm a I'm a bonafide nerd by background" > "I I hate fluff." - **Antihype positioning.** He distances himself from promotional excess while still making strong claims: > "many people tell tell stories. Sometimes those stories get get hyped... a lot of it comes down to being comfortable with yourself" --- ## 2. Vocabulary and Recurring Phrases Several words and constructions appear with notable frequency: - **"Responsibility"** — the most heavily repeated word across contexts (investors, employees, family, self): > "a great sense of both purpose and conviction" > "we should be ashamed to leave money on the table by ignoring tools" > "leaders have a responsibility to the people working at their their firm to prepare for what's coming next." - **"Lead from the front"** — used twice: > "I absolutely needed to lead from the front" > "You have to lead from the front." - **"Faster, smarter, and more effective"** — appears in the memo, read verbatim at two points in the episode. - **"Lead from the front" / "conviction" / "culture"** — the memo language is re-read nearly identically at the start and middle of the episode ("From the very top, we are building a culture around AI"). - **"Obsolete"** — used about skills and firms: > "you're totally obsolete... then you're also going to be obsolete." - **"Scratching the surface"** — repeated when describing future potential: > "we're just scratching the surface of what what is possible" --- ## 3. Teaching Habits - **Concrete analogies as the primary teaching tool.** He relies on extended comparisons, and flags them as deliberate: - **Merlin / *The Sword in the Stone***: "he lives backwards in time... he can see glimpses of the future uh but he doesn't see the steps in between." - **Jet engine / plane**: "a very powerful jet jet engine... won't fly by itself. You still got to hook it up to the plane." - **Tying shoes**: writing mechanics as "the tying your shoes part." - **Cowboys and barbed wire** (from the host, developed jointly): "there's no barb wire and I'm going to go and build." - **Weightlifting**: "either you pick up the weight or you don't." - **Historical anchoring.** He consistently grounds present claims in history: railroads and transatlantic cables (Civil War to WWI), Alexander the Great and Darius, Roman history, Renaissance-era quant ("full war since at least the early 90s"). - **Specific numbers for credibility.** ~"400 people," "75% of the firm," "about a third of the firm you know use AI coding tools," "a 15-minute process that would have taken me four or five hours." - **Named frameworks.** "Operating leverage," "the Borg," "the collective," "first principles," "build a clock, don't be a timekeeper" (Jim Collins quote). --- ## 4. Communication Patterns - **Verbatim self-repetition.** The memo passage ("Using chat GBT is not cheating... refusing to use the internet in 1995") is delivered nearly word-for-word at [11–35] and again at [854–943]. This is partly an artifact of episode editing ("Best of the Pod"), so it may not reflect live habit — uncertainty noted. - **Doubled words under emphasis.** A consistent verbal tic: > "very very positive," "heavily heavily um you know integrated," "huge huge sense [clears throat] of responsibility," "timeless on a on a different scale" - **Self-interruption to clarify.** He frequently restates to sharpen a point: > "that's that's nothing that's... that's new for me" - **Audience segmentation when explaining intent.** He enumerates listeners explicitly: > "first, you know, three main audiences here is the people at Walleye... second I'm also speaking to people that... may join us in the future... and then third... people in the ecosystem" - **Prefatory throat-clearing.** Many claims open with "so" or "you know": pervasive fillers throughout ("you know," "sort of," "call it"). --- ## 5. Rhetorical Devices - **Direct address / second person imperatives** in the memo: > "You should be using it too and be proud of it." > "Managers, this is now part of your job." - **Rhetorical questions:** > "So, why wouldn't you use it?" > "why did you waste three hours writing this thing?" - **Concession-then-claim structure.** He grants a limitation, then pivots: > "none of them are actually perfect... but the direction of travel is very, very positive." --- ## 6. Patterns vs. Isolated Moments **Stable-looking patterns** (multiple occurrences): - "Responsibility" framing across all life domains (work, family, investing, self). - Analogy-first explanation style. - Historical comparison as evidence. - Directness/antihype self-positioning. **Isolated or thin evidence:** - The **"Borg"/Star Trek** reference appears once in depth; can't confirm it's a recurring teaching device beyond his claim of having "been calling it." - The **journaling practice** is discussed once in detail; no repetition to establish it as a signature message. - The **civil war–to–WWI history frame** appears once substantively. - The near-identical memo readings at the opening and middle may be **editing choices** rather than natural repetition — uncertainty stated explicitly. --- ## 7. Interaction With the Host - Comfortable with challenge: when the host pushes back on whether "first principles" in math equals decision-making, he partially concedes: > "So I agree with you when it comes to decision-m um that's why that the word subjectivity exists." - Occasionally mirrors the host's framing and builds on it (e.g., extending the "frontier/barbed wire" metaphor to VC investing). - Humor is dry and infrequent ("the demo gods were against me"), not performative. # Video Observation Record: "Why This $10B Hedge Fund Made AI Training Mandatory (Best of the Pod)" ## Speakers - **Host ("Dan")**: Identifiable as Dan Shipper via self-reference ("I'm working... on every and our strategy") and closing narration naming him. - **Guest ("Will")**: CEO/CIO/managing partner and owner-operator of Walleye, a hedge fund of "close to 10 billion AUM" with ~400 employees. Self-described "benevolent dictator" (host's phrase), Princeton engineer, Oxford math PhD, quant background. --- ## Will's Positions on AI Adoption at Walleye ### The "AI at Walleye" memo Read aloud on the pod; key claims: - "Using chat GBT is not cheating. That's a non-applicable idea from academia." - "Not using these tools is like refusing to use the internet in 1995 because it wasn't perfect. That's just dumb." - "As a hedge fund, we should be ashamed to leave money on the table." - "This is not optional for anyone at Walleye." Managers are responsible for pushing adoption, "starting with being fluent yourself." - He acknowledges "words are cheap, particularly in a world of AI," and argues his **owner-operator governance** lets him act without fear of being fired. ### Mandatory AI training - After a Chris Sacca podcast, he decided every employee—technical or not—would receive mandatory AI training to a "base level proficiency." - Framed as a **responsibility** to anxious employees: "we will actually train you... we'll make it accessible to everyone." - Culture mechanisms: weekly emails with usage leaderboards, incentive systems for tool suggestions (like employee referrals), informal weekly AI meetups, and an "AI Senate" of users across departments. He calls himself the firm's "chief AI evangelist." - Claims **~75% of the firm** are active ChatGPT-like users weekly/almost daily; ~a third use AI coding tools such as Windsurf. ### Origin moments (stated reasoning) 1. **March 2023 ("Current")**: A former TMT analyst showed him a demo using then-available tools (he notes "this is with GPT-3" era, "early") to replace his own analyst work. Will was initially skeptical, then convinced. 2. **Chris Sacca podcast (recent)**: Prompted mandatory training firm-wide. ### Concrete productivity claims - Writing memos: from "four or five hours" to a "15-minute process" via bullet-point prompts plus context in his own voice. - Current (internal tool for fundamental long/short stock pickers): used by every team, usage "spikes dramatically during earnings," viewed by PMs as "indispensable"; over 50 external firms have asked to beta-test it. - Quant business: LLM-based sentiment analysis on unstructured data at scale, "for years"; he claims all world-class quant firms do this. - Risk calls and most meetings are recorded; LLMs process transcripts for memory, insights, and prediction. He calls the firm-wide data-lake vision "the Borg." - He qualifies: "quantifying that exactly... there's no perfect metric; a lot of it is definitely subjective." ### On "cheating," job anxiety, and quality - Separates **concepts vs. linguistic syntax**: AI handles the "tying your shoes part"; humans should spend time on the ideas. - On host's concern about AI-sounding work: "These tools don't negate the necessity to think." Machine-written text "is not sufficient"—good work shows the concepts come from the person, "not just outsource all of your brain to a machine." Uses a jet-engine analogy: the engine "won't fly by itself." - Analogizes to Excel: "if you're a long short stock picker and you can't use Excel... you're totally obsolete"—the same will apply to AI tools. Key phrase: **operating leverage**. - Acknowledges tools "all have their flaws. They all do stupid things," and argues against using imperfection "as an excuse to ignore it." - On job replacement: cites Jim Collins ("build a clock, don't be a timekeeper"); individuals will manage "AI robots" as employees. ### Predictions and historical framing - Believes in five years firms like his will be heavily integrated with best-in-class AI, investment and non-investment alike; finance has "the most clear association between information and money." - **Merlin analogy** (*The Sword in the Stone*): he sees the endpoint clearly but "the steps to get there can be a bit hazier." - History: the 1865–WWI period as parallel transformation; "people within their own lifetimes went from having relevant skills to obsolete skills... that is going to happen faster this go around." - "Thank God I'm not a VC, because I think most of them don't know what they're doing"—they prognosticate without operating responsibility. - Future firms: "many, many thousands or more of employees, but few of those employees are going to be humans." - On investing and history: "human nature hasn't changed in 10,000 years" and is "stationary across time"; "history doesn't repeat itself. It rhymes." Quant investing is built on historical patterns repeating; human investors retain an edge in "low of large numbers" / fuzzy, novel situations. - On quant opacity: world-class models' nonlinear combinations are "way past what a human mind can understand," though firms want some rationale for features. - On first principles: math first principles are objective within a model; decision-making first principles involve **subjectivity**—"what could be first principles to one person might be totally opposite of someone else's." His top personal ones: **the power of incentives** and **intellectual honesty** ("you can't manage what you can't measure"). ### Journaling practice - Daily AI-assisted journal (speech or bullets, ~30 seconds) across three areas: family, work, personal health; motivated by wanting to remember what he was actually thinking on a given day. ### Responsibility - People endowed with skills/resources have a duty "to use that to the maximum extent possible." - To investors (pass-through structure, "blank check," comparable to Citadel—only "maybe a dozen" such firms), to employees (prepare them for AI), and to family. Later-career shift toward being "a steward." ## Host's (Dan's) Positions - Sees CEOs writing "AI first memos" as "becoming a meme," and calls Will's the best he's seen. - Admits sharing the "is this cheating?" instinct ("when something's too easy you're like am I cheating?") and job-replacement anxiety reframed as job change. - Worries AI-drafted writing may mean the author "hasn't really gone through every single thing and been like I stand behind that"; rejects obviously AI-sounding published work at Every. - Suggests **neural networks and human intuition are analogous**—both unexplainable, high-dimensional pattern recognition. - **Pushes back on Will**: "We'll have to debate whether human nature is static or not because I'll take the opposite on that one." He also distinguishes math first principles from decision-making first principles (the latter are "many layers up above" axioms and "can be filled in in many different ways")—Will largely concedes the distinction. - Draws a frontier/civilization analogy from cowboy history (barbed wire, the OK Corral as tension between modernizers and those "stuck in the ways of the past"); Will extends it to VC-backed disruption of incumbents. ## Unresolved Tensions / Qualifications Preserved - Will explicitly declines to claim Walleye is *the* leader: "I don't want to say we're the leader because I definitely don't know what other firms are doing." - Productivity gains are partly acknowledged as unquantified ("benchmarks... kind of nonsense in a real company"). - The host-vs-guest disagreement over whether human nature is static is left open. - Will's claim that AI is "fun as hell" and not scary sits alongside his acknowledgment of employee anxiety and obsolescence risk—both stated, not reconciled. ## Non-substantive content - Mid-roll advertisement for Attio (agentic CRM) and a closing promotional outro for the "AI and I" show; excluded from substantive claims. # Video Attribution & Provenance Record **Video ID:** 01a0f15a-48ee-733b-b284-b7b57585d420 **Title:** Why This $10B Hedge Fund Made AI Training Mandatory (Best of the Pod) ## Speakers & Roles | Speaker | Role | Basis in Transcript | |---|---|---| | **Dan Shipper** | Host / interviewer | Addressed by name ("Hey, if you... Dan"); outro references "Dan Shipper as the captain" of the show **AI and I** | | **"Will" (first name only)** | Guest; CEO/CIO/managing partner and owner-operator of **Walleye**, a hedge fund with close to ~$10B AUM | Introduced by host as "the benevolent dictator of Walleye"; guest confirms tactical titles and describes firm of ~400 people | | **Unidentified narrator** | Outro voice | Third voice in closing promotional segment ("smash that like button and subscribe to AI and I"); role not otherwise identified | Speaker labels within the transcript are not named per-turn; attribution above relies on turn-taking context. Full legal identity of the guest beyond "Will" is not provided in the transcript. ## Cited Sources & Referenced Works (as claimed by speakers) - **Guest's internal memo/email**, "AI at Walleye: A challenge to all of us" — read aloud on air - **"The Sword in the Stone"** (1960s Disney film) — guest's Merlin analogy - **Chris Saka podcast** — guest cites it as a catalyst for the mandatory-training decision - **Jim Collins quote** — "build a clock, don't be a timekeeper" (paraphrased by guest) - **Books on Renaissance Technologies** (referenced, not titled) — quant trading history - **Netflix documentary on Wyatt Earp / "the cowboy war"** — discussed by both speakers - **Deadwood** (TV series) — host reference - Historical references: Civil War–WWI era, robber barons, Alexander the Great/Darius anecdote, Star Trek (the "Borg") ## Third-Party Claims (unverified within transcript) - Walleye AUM ("close to 10 billion") — host's characterization - ~75% of the firm are weekly/daily ChatGPT users; ~a third use AI coding tools ("Wind Surf") — guest's own figures - Over 50 external firms have asked to beta-test the internal tool **Current** — guest's claim - Competitor comparison: guest says he does not know what other firms are doing; leadership claim is hedged - Pass-through structure comparison to Citadel and "maybe a dozen" similar firms — guest's estimate ## Promotional Segments - **[Mid-roll ad]** Advertisement for **Attio** ("adio.com/every," 15% off first year) — an "agentic CRM" pitch; clearly demarcated ad break inserted mid-conversation. Guest not present. - **[Outro]** Promotional call-to-action for the show itself ("AI and I"), including like/subscribe exhortation; tone is satirical/hyperbolic. ## Comment Availability No information about comments or audience interaction availability appears in the transcript or supplied metadata. **Not recorded — unavailable.** ## Provenance Caveats - Transcript is machine-style with speaker markers (`>>`) but no timestamped attribution; some turns are ambiguous. - Guest's surname, firm's exact legal spelling ("Walleye" per transcript), and the show's platform are not established in the source. - Curated metadata beyond title was not supplied. It's becoming a meme that CEOs are like writing basically like the we're AI first memo. You have the best example of that memo that I've ever seen. Um would you mind just like reading I don't know maybe the first paragraph or two of what you wrote because I think it's amazing. \>\> Using chat GBT is not cheating. That's a non-applicable idea from academia. I use chat GBT to write this email. You should be using it too and be proud of it. 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. From the very top, we are building a culture around AI. Not using these tools is like refusing to use the internet in 1995 because it wasn't perfect. \>\> \[music\] \>\> Will, welcome to the show. \>\> Thanks, man. Thank you. \>\> So, it's great to have you. For people who don't know you, you are the 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, like regardless of the stuff we've done, you're I think one of the most impressive examples of someone um a CEO who is like pivoting their entire organization around AI and you're sort of like leading by example. And so I'm psyched to get to talk to you. \>\> Yeah, thanks. Um yeah, maybe I could just give a little more context to that. Um I guess my my tactical title is uh is CEO, CIO, managing partner, but you know, I'm both both the owner operator of um you know, one of the one of the larger hedge funds out there. I I don't do many press. Um you know I don't typically speak at conferences. I've only done one other podcast. So this is very deliberate. \[clears throat and cough\] It's very deliberate for me. Um and and because of the relationship that that we've developed, you know, on this subject, I do feel a great sense of both purpose and conviction about \[clears throat\] where our industry is going, where our firm is going. Uh I do believe that we're already a leader in that is going to continue to be the case. So you know sometime 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, you \[clears throat\] know, up up front, you know, because I have that conviction, you know, the skills to lead us into the next uh, you know, the next phase. We'll get into that, of course. Um, and ultimately the power to to enact that. I really feel it would be irresponsible of me uh not to go after it with sort of the maximum amount of discipline and intensity I I can muster, which which is a lot. So first, you know, three main audiences here is the people at Walleye. You know, we have about 400 people. Um not big for a normal company, but uh in our corner of the world, um that's it's not a small small amount. Um you know, I'm second I'm also speaking to people that that aren't at aren't at the \[clears throat\] firm today, but may join us in the future just to understand how how serious um the firm is about AI and uh and and that ultimately starts starts with me and then others. And then third, you know, finally speaking to people in the ecosystem, whether they be companies building products that firms like us can can use um you know, or or in other ways of work together, you know, that's that's why I'm here. But it it does all start with me having, you know, as I said, an enormous sense of conviction about uh about where the world's heading. So, \>\> how did you develop that? Like what was that journey like for you? I actually don't even know this. \>\> So, I'm a I'm a bonafide nerd by background. Um you know I I was an engineer at Princeton. I went to Oxford to do a PhD in math. I started my career writing code all day for uh you know algorithmic strategies. Um so you know we as a firm you know and me personally have been using let's just call it advanced statistics not even AI for for years. A large part of what our firm does is in pure quant trading. Um, so I I've thought for for many many years about how machines increasingly can both either augment or do the jobs of of humans and finance. That that's nothing that's \[clears throat\] that's new for me. Um, you know, 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 um being curious, being interested. A huge part of this is about curiosity. Um you know I've noticed the productivity improvements that I see um using using these tools just even for from a writing perspective let alone um some of the sort of more advanced things you can do. So it's a combination of called having been in uh deeply versed in a technical background as I said bonafide nerd and then noticing what's out there and just said the sense of responsibility to you know \[clears throat\] to the people at the firm to our investors to say like look we we understand where this is going um if we ultimately get disrupted by AI that's that's on me and so let's get after that. So even two years ago like this isn't a sense of oh yeah we're going to do all these things in the future you know two years ago we started an internal AI program you know today um you know we're already doing doing a lot so it's not just a story about what's what's to come um and yeah that a lot of that does start with me I mean that a lot of times leader of organizations won't sort of say that how much actually matters um you know that in the leadership but this is one where where I I feel like I absolutely needed to lead from the front So \>\> tell me about that. Um like a little bit more concretely. Like one of the things I I appreciate about you as a communicator is you're just kind of like no Um we were talking like I don't know 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 \[laughter\] I'm a little afraid of this. Um uh so you're not you're not afraid to kind of like um put your finger on the nerve and you're also not particularly like hypy as a person. I don't think. Um, so tell me about the moment where you're like, oh, we have to take this seriously versus it's just like uh it's just like, yeah, tech people, nerds are nerds are psyched about it, but like it's something that we really need to understand. \>\> Yeah. Um, and I appreciate you saying that. That's definitely the the way I try to operate. Um, many people tell tell stories. Sometimes those stories get get hyped and for 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 something of someone you're you're not. Um, so that um that's that's been a hallmark of mine trying to \>\> I would never have done that. So I I don't know from experience that that's a problem. \>\> Yeah. \[clears throat\] No, really that's uh that's a core belief, you know, in terms of AI. Um there there have been a couple moments over the years um that have uh led us to continue to go down and and recently accelerate this journey. The first was two years ago called our most advanced internal AI project is called current. um that's led by someone who was a former analyst in one of our uh TMT you know for technology longshore stockpicking teams comes to me in March of 2023 and says look I built I' I've used these tools that are now available to um you know make myself way more efficient eventually trying to replace um what I was doing as an analyst and I was pretty skeptical at first because that's that's not typical that someone would just go out and do that. \>\> This is with GBT3. \>\> Yeah. Yeah. This is like two years ago and it was early but the point was just sat down gave me a demo and I was like wow like 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 \[clears throat\] um the tools that are available it's like this is absolutely where we're going and so that's when we started you know an effort to say okay for fundamental investing absolutely there should be agents that are um ultimately helping with with with analysis and and ultimately to provide provide mean to what's going on. So people talk about that now, but that was that was two years ago. That was a real moment for me. Um and then more recently this year um you know said I I I listen to a lot of podcasts but consume a lot of information and and I was listening to one actually with uh with Chris Saka who's a very entertaining individual um sort of talking about with frankly a bit of hyperbole but entertaining hyperbole um just about you know where we're going and I was like you know what that's that's so true um what these machines can do now is incredible um and it does take a little bit of magic ination, but in some ways it's it's kind of like you can see the end point more easily than you can see the steps to to get there. I was using this analogy recently is a little bit uh well, I'll just tell it to you, but I really did did use this one. So, my favorite movie growing up was The Sword and the Stone um made in the 60s 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 \[clears throat\] he can see \[snorts\] um you know glimpses of the future uh but he doesn't see the steps in between and that's kind of how I felt like here like it's it's impossible for me \[clears throat\] not to believe that in five years firms that do what we do won't be heavily heavily um you know integrated with best of breed AI technology across the firm not just for investment for non-investment purposes. And I say that, you know, in in our industry because it's one of, if not the most clear associations between, you know, information and ultimately money, right? The the value of of having an edge from an information standpoint um is huge. And so that's why finance is is really going to pick up and actually use these tools and say, okay, what applications actually give me an information advantage? So that's very clearly where we're going. Um but the steps to get there can be a bit hazier. And so actually it was after this podcast I said with with Chris Saka that I wrote I wrote the team this is how we ultimately met you \[clears throat\] is like we're going to train mandatorily every single person at the firm doesn't \[clears throat\] doesn't matter what department you how technical or not technical you are you're going to have a base case level proficiency in AI tools and as part of this actually does come from a sense of responsibility like people are anxious about what are all these things going to mean what is that how does that impact my job what skills do I need to have and uh you know me saying to the firm \[clears throat\] of like okay we are going to be a place that is going to be leading that 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 accessible to everyone um so that was when we just started doing a lot more um \[clears throat\] not just building call it tools using advanced AI and as I said we've been doing that in our quant business for for 10 years um and not just building \[clears throat\] essentially digital analyst replace the work of of humans in in longer stockpicking. But then over the past really this year, I've said to everyone across the firm, you know, even in accounting, finance, compliance, legal, like yes, you should be using either chat GBT or Brock or some LLM to assist in in anything that you're you're doing that's analysis or writing. Um, you know, we record pretty much every bit of information that, um, you know, flows through the firm. You know, a huge part of this is actually having a proper data strategy. Um, and then also just \[clears throat\] having the culture of, yeah, we're uh we don't really know all the answers to this, but let's just start talking about let's make it accessible. So, so simple things like having weekly emails where there's leaderboards of, you know, who's using these tools the most. Um, actually, you know, I send the entire firm an email and said, "Hey, if you you suggest a tool that um ultimately we end up pushing out across the firm, you know, just like there's incentive systems for employee referrals, we'll we'll do something similar here here too." you know we have weekly meetups um informal weekly meetups internally just to talk about AI be it be it prompts um or other use cases I mean the your your one of your previous guests talked about the sort of the social nature of AI and and how hard it is just to even discover best use cases which is couldn't agree with more um but just even internally trying to make it a bit more social bit more accessible and you know I'm involved in in all of this and in fact I'm sort of the chief a evangelist Um, and a huge part of that is just my own personal curiosity, but you can already see it working. You know, people are doing things that they weren't they weren't asked to do. It's it's so cool and the productivity coming from that like it's real. This isn't just paper. So, so yeah, we're um we're definitely going down this path. Um, one of the things I think you've been so effective at doing is basically like you can think of companies, companies even, you know, 10 people, but 400 people bigger than that. Like they're almost the bigger they get, the more kind of hard to steer they are. The like, you know, maybe a a startup is like a canoe and like a 400 person company is like a cruise ship and a 10,000 person company is like a battle battle cruiser or whatever. And um I think you've been you've done a really incredible job of like pointing the cruise ship um really quickly and that's something that's happening a lot now. Like it's becoming a meme that um CEOs are like writing basically like the where AI first memo. \>\> Yeah. \>\> And I think you have like the best you have the best example of that memo that I've ever seen. Um would you mind just like reading I don't know maybe the first paragraph or two of what you wrote because I think it's amazing. \>\> Yeah. Yeah. Yeah, I can read that and and on that point of as I said there there is \[clears throat\] it's words are words are cheap particularly in a word world world of AI you can create great world words very very easily you know to your point around um you know be being a bit of a cruise missile um you know I do think that's an advantage of ultimately governance you know I'm I'm the owner operator so I I don't worry about getting fired I believe on I worry about doing what I think think is right and I very much believe this is right and so we can just go and do some of these things and large organizations just um just can't operate that way. So as I said a huge sense of responsibility because we can act that way um to uh to do it. So yeah I I can read uh read a couple couple sentences. Here we go. Um so yeah so this is an email that I wrote um to the firm um and the the entire firm and it's the subject is AI at Walleye a challenge to all of us. It says I use chat GBT to write this email. You should be using it too and be proud of it. Uh, 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. You know, Walleye is 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 Chat GBT 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% 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 ChattBT 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 talk a bit about some of the things we're doing recently that I just mentioned and then ended, you know, that this is the beginning. The edge is real and we will not fall behind. What's lead? \>\> I love that. Like what was the um you hit on a couple things there that that I really love. Like one is this the sort of um is this \[clears throat\] cheating question that um a lot of people have. Like I have that too. Um not from it's like it's just like an internalized sense of like oh my god this might be too easy. And when something's too easy you're like am I cheating? Um and and and and also sort of like addressing this um this fear that I think a lot of people have which is like am I going to be replaced? And I think the way that you're talking about it is very like actually this is now part of your this is 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. \>\> Yeah. Yeah. So I have very strong views on on both of these. you know, as I've gone on in my career, you know, my my role has changed and I believe that for all the effective leaders that as they go on, they they they should evolve as well. You know, I I love the Jim Collins quote, you know, build build a clock, don't be a timekeeper. Um, 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 or long memos that used to take me hours that maybe I could do that in a half hour or less. Um and that to some extent people have this insecurity that oh if I didn't put my blood, sweat, \[cough\] and tears into it um that somehow it's not it's not real. But at the end of the day, you know, results are what matter. Um, I think having I spent a lot of time as as an athlete and I still do um a bunch of stupid stuff in the gym as my hobby. Um, and at the end of the day, either you pick up the 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 like oh my god it is ruining school um which in the call it 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 p.m. So you can actually spend time thinking about next \[clears throat\] level tasks, higher level contexts, be a bit creative. Um, and ultimately think of yourself, even if you're an individual and you don't manage any human, um, you're still going to be managing employees. A lot of those employees are just going to be AI robots. And that's a skill in of in and of itself. So just I the reason I wrote that to the entire firm is just making people feel comfortable and not kind of embarrassed where it's like cuz what I was seeing before is people were you know using chat GBT or another similar product to create an email and they were trying to like dust it up. It's like oh I don't want to be seen as doing that. Like that's just stupid. Um you should be doing that and if you weren't like why did you waste three hours writing this thing? Um so again \[clears throat\] very very strong uh feelings about that. At the same time you're you're commenting around this anxiety of you know what is my job going to be? Um you know when spreadsheets came out or email came out you name it like yeah you have to learn how to use these these tools and I see this all the time. You know very deliberately we hire people or we say are at an inflection point of their their career. um typically mid-career where they um you know know enough um to be dangerous um the competencies there but the hunger is still there and the the ability to be dynamic to learn new skills is also also still there that matters a lot and I don't think there's any different um you know if you're just use an example if you're a long short stock picker and you can't use Excel to create a company model like you're totally obsolete and in future years you're going to 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 um you to give you access to the tools to give you operating leverage, then you're also going to be obsolete. And so, you know, that phrase is what I use a lot is just this this concept of operating leverage and not not being afraid of that. But yes, absolutely. I see that all the time and it goes back to like my earlier comments around feeling a sense of responsibility um to put people in a position to say like don't be afraid of this stuff. Um, embrace it. And another thing that I was seeing, Dan, um, a lot of these tools aren't they're not perfect. Um, I mean, none of them are actually perfect. Um, they all have their flaws. They all do stupid things. Um, but the direction of travel is very, very positive. And so, I wanted to set a culture and environment where instead of people being like, oh, it didn't do exactly what I wanted, so I'm just going to ignore it until it's perfect. It's kind of going the opposite way of being like, yeah, let's have, you know, a demo with a third of the company joining, which is real. That's how many people join. And uh if if that demo screws up, who cares? Like I I basically had one last week that um the demo gods were against me. But that's totally fine. And and having people accept that and embrace that and be like, "Yeah, this some of the stuff isn't perfect, but you can see where it's going. Um as opposed to just almost using that imperfection as an excuse, excuse to ignore it." So all those things combined into one. Um there's there's no other person besides me. And I think this is true of all leaders of the organization. You have to lead from the front. You know, no one no one can set that tone um besides besides a leader. And once that tone has been been set, it's it's kind of incredible how how much you can unlock people to be like, "Yeah, have at it." And it's okay. Um setting setting that tone and flipping it outside be sort of, you know, you you need to be afraid or a lot of people are afraid not to or to make a mistake. um kind of need need to be more afraid to getting getting left behind. \>\> And what have you seen like for someone who's watching this and um maybe is in finance or maybe is just running another company with a lot of people and is thinking about okay like but really uh what what productivity gains has it actually unlocked for you? Like concretely what are a couple things that have been useful for you or for the fund? So there's a couple things and you have to um you know put this into into categories of what's what's recent and what's not. So as I mentioned you know we we do run a big quantitative trading business. You know as a as a multist strategy firm we want many different strategies but quantitative equity training is a big part of what we do. Um those models have used you know nonlinear statistics um AI or some of the underlying models and AI for for years. More recently with the advent of large language models coming about the ability to process you know unstructured data of course and incorporate that into signals which historically was called sentiment analysis you know the ability to do that at scale has gone up dramatically so that's one improvement just in a pure money-making standpoint \>\> and you're doing that like you're using language models to do sentiment analysis. \>\> Yes. Yes, we absolutely are doing that and have been doing that for years and frankly all worldclass quant firms are doing that but it's hard um that's why you know quant trading is one of the things that that definitely benefits scale um some of the things that are \[snorts\] called more recent or are newer and I I do believe that the explosion that we've seen um it empowers the less and less call technical people um the technical side where really you just have to be creative um so so sometimes we're doing like you \[snorts\] 75% of the firm um you know is an active called chat GBT or chatgbt like user um you know every single week like actually almost every single day that's pretty cool \[snorts\] about a third \[cough and clears throat\] um of the firm you know use AI coding tools such as wind surf um that's sort of very real are as I said an internal product um for fundamental longer stock pickers you know that's that's also a big part of our business um every single team uses this tool. It's called current. Uh it spikes dramatically, you know, during \[clears throat\] user spikes matically during earnings. Um we have people that that come here um from our competitors and tell us that this is, you know, it's both way better. Um but but really an essential part of their of their job. And I 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 provide meeting um and real analysis as opposed to just summarization. Um but yeah, you know, you kind of can't go through earnings period now as a launch first stock picker without some of these tools if you're going to be competitive because um you know, one one of your competitors like someone here is going to be able to process all of them in real time and then have a machine go and basically impute things that humans can't do as fast. So um how do we actually measure that? Of course, \[snorts\] um having benchmarks like that's kind of nonsense in a real real company. Uh but just sort of seeing the the level of uh level of adoption. Um just seeing people suggesting products like okay \[clears throat\] we want a um we we talked about last week on our one of our meetups to have a product that can do um summarization via podcast to make it more accessible to pe people that want to listen to to something. And then that day um we had you know five different products in beta and then the next day was pushed out across across the firm. So you know some of these sort of cultural elements of just having actually set up a process where we can both incorporate thirdparty products and and and build some of them ourselves. Um you know that that's pretty cool and I don't know how much smarter \[clears throat\] more efficient that's that's making people. Uh I certainly can speak from for personal experience. Um, a big part of running an organization is communication. My communication is is dramatically and which a lot in a lot of cases written and that's dramatically more efficient now than a lot of us when I wasn't using these tools and I think it's probably true for literally every single person in our firm. \>\> What does that actually look like for you? Like when you're using it to communicate, what are you doing? \>\> I think best when I write out my thoughts. Um, I I tell people that uh my education is very expensive, so I better be able to write. um or else what the hell is all that for? Um and uh so historically, you know, I I really would write um to convey what I'm thinking, where the firm is going, why and uh I just believe that leaders should be able to to really communicate. And I I believe in the power of high quality pros and it's actually one of the things in general before LLM came about that it was pretty pressing that younger people just were terrible, terrible writers. Um, so for me, when \[clears throat\] I want to, you know, write an email, um, as an example, write write a memo, I do it in bullet point form. I I I type out here's what I'm thinking, here's why, you know, I work on my prompts. Um, and, uh, maybe I'll give a bunch of context of, hey, you know, here's all the stuff that I've written on a similar subject. Um, and I want you to give something in my my own voice. And uh that can be, you know, no exaggeration, like a a 15-minute process that would have taken me four or five hours historically. That's why I have such, you know, almost religious views on this stuff, cuz um it's it's uh it's pretty wild. Um so that so that's one example of where I'm using that personally. Um you know, another thing that we do and yes, there are always the the questions on what can or can't be recorded. um kind of going back to the governance element where I can say this is what I believe this is the right thing we're to do so internally with with a few exceptions we really record you know 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 every um everything \[clears throat\] they say for for months and months at a time you extend that forward without sounding too much like a nut job I think people are going to have essentially recording devices implanted you know in bodies that record everything. So just getting comfortable with the fact of yeah like all this data is going to get get captured. So we're trying to do a bunch of that internally um and then \[clears throat\] of just being able to go back and 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 where you can then you know put a straw into and get it out. So, you know, a big part of my job overseeing the, you know, the the risk of the firm, the the chief investment officer title, uh, you know, every single morning, me and my my risk team sort of like in the in the control center of of running this this giant process. um you know we have our risk calls and and those are all recorded and uh we we can go back and \[clears throat\] say hey you know what were we talking about at this time and continually have \[snorts\] LLMs that are that are processing those transcripts and and helping helping us to both remember and and provide insights and ultimately be a bit a bit predictive um which has been hugely helpful just just in that exercise which is you know we haven't sort of talked about where I think this is going and the and the power of all this and I mean like we're I I do believe that we're um that we're a leader. Um I don't want to say we're we're the leader because because I I definitely don't know what other firms are doing, but um I certainly think that we're a bit more advanced in our thinking of how to use these tools, but we're just scratching the surface of what what is possible once you actually start connecting all \[clears throat\] bits of of information within the walls of the firm. And this is not just um you know not just Wall-E, not just hedge funds, really any company and saying, "Hey, let's actually put all of our our data together into effectively a collective and then that that information can get process." We're we're totally just scratching the surface there, but we're certainly working towards that. \>\> Everyone's talking about how AI is changing how we work. For anyone working in sales, you felt it. The whole job is changing under your feet. But one thing isn't changing. The win. The deal that finally closes. The moment the hard work pays off. Maybe you've got a gong in your office or a confetti machine or something else. We don't judge. Every team has its rituals. That's the moment Adio is built for. It's the agendic CRM that runs the work behind every win. It turns every customer signal into context you need to move at unmatched speed and scale. With revenue agents and automations that build pipeline, advance deals, and grow accounts around the clock. You'll get all the context and velocity you need to scale any go to market motion. so your team can raise the ceiling on what's possible. Start with Adio today and just focus on the win from here. Go to adio.comy and get 15% off your first year. That's atio.com/every. \>\> I want to go back to something you said earlier about writing as thinking and using language models to turn like a you know four or five hour task into a 15-inute task. \>\> Yeah. What is your like one of the things I worry about for example is um maybe I'm not thinking it through as clearly if um the language model has like written a bunch of stuff that it's coming from my bullet points but I haven't like really gone through every single thing and been like I I stand behind that. \>\> Yeah, sure. I think you have to separate this out in terms of you know thinking through the concepts versus the linguistic syntax. What I was noting at least personally, and I do think a lot of people do this, is what when they're writing, they're they're trying to be both consistent to some extent clever and to some extent uh 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 preposition and and everyone here at the firm knows that. Um but but you don't so you don't have to spend as much time again I think on the the important um but not as powerful tasks of of writing like a lot of it is just sort of stitching stitching these pieces to together the tying your shoes part. So the princip the the elements of writing you know what are the concepts that I'm looking to to convey that's what I spend my time on now. So, so what I found with these tools is really trying to be clear like this is the concept that I want you to get across um and this is how and then yes it will suggest you know string of words that that convey that and particularly with the way the recent models are architected it's has everything that I've I've written so it can do it to some extent in my own voice but I just don't have to spend as much time like frankly trying to be clever and that's what a lot of writers do they they try to say a lot of relatively straightforward concepts in in a clever Um, I just don't think we need to waste time on that anymore. \>\> I would never never do that. Um, as a writer, um, I'm curious, uh, like, but let's 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 \[snorts\] like let's accept, for example, like if someone's going to publish something on every that sounds like it's AI written, I don't that that's just out for different reasons. But like if I get an internal report that looks like it's written by CHBT and I did this actually last week cuz \[clears throat\] everyone internally is using these tools all the time. Um it's not that I care that the voice sounds like CHBT. It's that I 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. Um so how do you like deal with that? Look, these tools don't negate the necessity to think. Um, \[snorts and laughter\] and I say that all the time. If anything, they they should just give you more time to think. Like, if you say, "Okay, you have an hour to complete this task." And it used to be historically, I don't know, 50 60 50% of that time it was just going to be mechanically typing out. Um, and now I don't know 5% of the time doing that. So, you have more time to think just in a fix fixed amount of time. So, you should you should really think. you should you should read, you should proofread and say like does this make sense to me? Is this what I'm trying to convey? And so I can definitely tell as well when something is written by a machine. Um sometimes that's just the way that the the text appears like the the bolds like clearly a human didn't go and bolded in exactly this way but but that's fine. Um but it's not enough. It's not sufficient. Um 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 like, okay, why are you doing this? Um, why does this make sense? Uh, and you didn't waste your time doing something that wasn't nec necessary, but at the same time, you didn't just outsource all of your brain to a machine. And sort of there's that optimal point on the curve \[clears throat\] that we're trying to to get to. Um, and that's again why I don't I don't think people should be totally totally afraid of using these tools because by themselves I I don't think they're sufficient. I think that, you know, it's like having a you a very powerful jet jet engine, excuse me. And you use that analogy to with me as well. Like a jet engine won't fly by itself. You still got to hook it up to the plane. And there's a hell lot of things that matter when it comes to aerodynamics and um, you know, that 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 very powerful ways. Um but but you need to be a part of the process for sure. \>\> I want to talk about that the thing you brought up next which is sort of this data lake idea of like sort of recording everything. You've been calling it the Borg as a Star Trek fan. Um, so like where like you're recording all the meetings now, which I think is awesome. And you said it's already helping like in your for example in your risk calls you can tell like uh how you made a decision like can you give us a concrete case where having all those recordings has actually been helpful. \>\> So yeah, the Borg which which gone from Star Trek um and uh I'm kind of sad now that when I say the word Borg um even some real nerdy people don't even know. It means I'm getting a little bit older. Um, and the the collective, which is, you know, get get all the information together. That's that's at least our our spirit animal, our our spirit guide for for the future. It is this 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 like 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. Um so the most salient example of where we've done a miniature example of this goes back to set our internal product current which uh you know it takes analyst notes all you know information is coming in from from brokers and these PDFs that get emailed around all the time um \[clears throat\] earnings transcripts uh really any bit of information that's that's germanine to to a stock um that's that's our our most advanced call it or example and that as I that really is real like all of our all of our PMs view this as as an indispensable tool that saves them a ton of times particularly when information flow is is very fast. Um \[snorts\] again quantifying that \[clears throat\] exactly you know there there's no perfect metric a lot of it is is definitely subjective but I can see the internal use case numbers and I can also see like firms all external firms know that we're that we've built this and and are doing it and over 50 of them have asked like hey can we can we be a beta user of current and we'll give you feedback to help make the product better which we which we've done in some cases. Um, and it just also makes sense, right? That a huge part of the job of a human is synthesizing information. Um, and until recently, like when it comes to reading documents, like machines couldn't do that very well, reading documents or listening to to voice essentially other text forms. Uh, but now machines can and now the surfacing the second order, the third order effects of that again, not just summarization. Um, \[clears throat\] that's what machines are are starting to do. That's I said that's our main use case. And so this the broader idea of the the Borg I look at what we've done to just help you know our long short stock pickers and say that same concept should be able to help every single department at the firm. um that's you know generating text um as a simple example um through emails through through Slack messages through you know live live calls \[clears throat\] live conversations uh and then ultimately the the ultimate goal is to tie that back to numerical data whether that be market data uh internal data accounting data you \[clears throat\] name it so the the applications as I said do take time to to imagine to design \[clears throat\] 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 of the firm of any firm and then linking them together um like that that will happen. It's just a matter of um how to get there that I think everyone is still trying to to figure out. \>\> I know that you're a student of history. Do you have any historical periods or examples that you're turning to to kind of help you navigate what's going on right now and and this transition that you're going through? \>\> I'm a student of history. Um I do love \>\> \[snorts\] \>\> um you basically the period between the Civil War and uh World War I is is a time when I think uh the whole world changed dramatically. Um, and then part of that is that my my office looks out on a train station built by one of the robber barons. So I do think about it all \[clears throat and snorts\] the time. Um, so it's certainly not the only period of history, but um, you know, definitely a time period where things changed dramatically. Um, I'm I'm not a VC. Um, thank God because I think most of them don't know what they're doing. But uh certainly this idea that when you look at a you know an exponential curve you know humans sort of knows hits up against that don't realize how how fast things can change. Um so there there are periods of time like how how fast the the railroads got connected um or or didn't um how fast you transenic cables and what that actually meant. Um you know that as I said the period between civil war and and World War I just huge huge amounts of change um and people within their own lifetimes sort of went from having relevant skills to to obsolete skills. Um that is going to happen faster this go around. And when I said I thank God I'm not a VC because they hear a lot of people investor types prognating about the prognicating 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 principal arguments of yeah things are going to change dramatically. you know, corporations, collections of humans, um, let's just say companies in the future, uh, that want to operate in a world-class manner at scale are still going to need many, many thousands or more of employees, but, uh, few of those employees are going to be humans. Um, a lot more of them are going to be to be machines. And so you've certainly seen that level of disruption in other other areas that just happen a little bit faster this time. Um but at the same time I'm of an optimist in general. Um I think that's very important with uh for leaders actually to have an optimistic tone. I don't think the world is is going to end because all of a sudden people are going to have their jobs disrupted by AI that they need to adapt. Um it's sort of having a level of realism around that of that's 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 going to be competitive. And we are at the the tip of the spear from a competition standpoint just given the nature of what of the industry and what what our types of firms actually do. But I think it's going to be true across a a bunch of wider swath of population where yeah, you got to be trained to be to be efficient and um at some point that if you don't, that's your choice and that just is what it is. \>\> Yeah, I think that period of history is so is actually is actually really relevant and coincidentally I've been I told you this already, but I'm sort of in my cowboy era. Um and I've been like reading a lot of cowboy stuff and um \>\> you watch the Netflix thing on on wider and the cowboy war. \>\> No. Should I? Yeah, it's really good. It's really good. \>\> It's It just came out. \>\> Yeah. \>\> Okay, I'll check that out. I just finished Deadwood, which I was telling you about. \>\> Yeah, Deadwood's good. I never watched like any TV, but uh this one came out and I also love sort of the old old west. It was a it's a good story. \>\> Do you know why the why cowboys disappeared? I just learned this and it's it was a really interesting fact. \>\> You tell me. I have a hypothesis, but you go first. \>\> Um barbed wire. Yeah, I was going to say the broader con well in the that documentary the cowboy war. What basically the answer was civilization kind of came in. You had the railroads come in which brought a lot of people and then \>\> yeah eventually barb wire and you couldn't steal cows. I mean the cowboys were a gang in Arizona in the 1870s and 1880s stealing you know cows especially \>\> I didn't know that. Oh yeah, like the cow. So it it's fascinating, but the the cowboy war and Wyatt Herp, which is this, you know, historical figure of of legend, you know, gets in a this huge fight like the movie Tombstone, which is kind of historically accurate, but not really. Um, it was sort of the wider posi versus the cowboy, two words, posi. And uh it was this big it ended up being this big deal like that's the gunfight at the OK Corral because it stirred up all this \[clears throat\] sort of north you know north versus south sentiment 20 years after the civil war but the broader historical context there is people sort of wanting to bring about change because tombstone where um you know OK Corral was and where was was a silver mine so it brought in all these um you know people from across the country both north and south but there was this huge tension between those wanting to modernize and those wanting to get stuck in the ways of of the past. So yeah, it it it's it's that period of time is um I find it fascinating too because you had 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. 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 like 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 it's at odds with that frontier spirit. So there's that there's that always that tension between structure and creativity and and I think that there's something very similar there about technology \>\> so many levels man I mean that's even true with sort of at least historically of the you know why does VC investing exist you know why is it that you go and read about the story of you know you pick any company you know from Nvidia on down where they're like I can't do this at a big company \[clears throat\] so I'm going to go and push the frontier uh in a world in which I'm less constrained you know there's no barb wire and I'm going to go and build and then at some point you know those those companies become successful they become institutionalized and then someone does that again and so that's not a geographic frontier but but a technology frontier um and as I mentioned earlier like I feel a sense of responsibility because we can kind of do both and they're just not the only companies that can say that if we want to push the frontier but with resources um and you know those ultimately are I think Think the businesses that when you look at any technology transition are are able you know not just to adapt but but to thrive of uh you know having that mentality but not being you know not using \[clears throat\] singleaction rifles when other people have machine guns. \>\> How do you think about how the past informs the future? And and I'm I'm asking this both from like a kind of I don't know late 1860s to now perspective but also from a from an investing perspective. Um, and and and and I think this 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 reliance to some degree on the idea that certain things that happened before are going to happen again. And and part of the investing, part of being good at it is knowing which which one's going to happen again and which one's not. Um, do you do you agree with that characterization? And how do you how do you think about when to when to \[snorts\] rely on past patterns to help you understand the future? \>\> I don't think human nature's changed in 10,000 years. Um, you know, and maybe it's evolved a little bit, but you go back and my my son who's eight is really into uh to Egypt right now. Um, I love Roman history because I took Latin and I'm said I'm a real nerd so I know a lot about Rome. \[snorts\] 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 a famous example like you the old always wants to or that the new always wants to replace the old. You know, the the son wants to outdo the father. These these are timeless. You know, when Alexander the Great was, you know, conquering Persia, Das, the king of Persia, sends him a note and he's like, "Hey, how about we have a truce?" And he responds like, "I'm coming for you." And so \[laughter\] this concept of uh um yeah no that's a good story right but this concept of the new wanting to you know replace the old and this continuous evolution you know you find it in nature you know everyone sort of knows the analogy of a a forest fire burns the trees so the new new brush can can grow like this this this concept renewal is always going to be there it's in human nature it's it's nature I think it's just a a pattern that we're going to to see and it's the same case here. Like there's going to be um a group of people, a group of firms, collection of individuals that are going to look what's happening and and embrace that. And then there's going to be groups of people that are going to hold on to the past and um there, you know, there there's going to be conflict to varying degrees because of that. That that hasn't changed a lot. So when it comes to investing when we look for patterns uh you know quant quant investing um of course is built on this concept that there are patterns um in history in stock \[clears throat\] prices and information that was predictive um and and there's a structure to that data even if that structure is so complex that humans can't \[clears throat\] understand it. And in worldclass quantum investing, you know, we we've moved past what humans can understand, you know, many decades ago. People forget how long and well the book on renaissance came out, but um you know, some people still don't realize that the quant investing is has been going full war since at least the early 90s. Um and so absolutely that whole class of strategies and which is a huge part of the markets today um is built on this concept that historical patterns um do repeat themselves. Um when most people think about investing they think about sort of human-driven intuition in investing. Uh I also believe that's timeless. It's just timeless on a 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 of large numbers situations where a machine \[clears throat\] hasn't exactly seen all the priors the precursors that would lead it to make an informed decision but a human can be better at dealing in the fuzzy mess. Um and so all these tools that that we're building can be built \[snorts and clears throat\] um to enable that human um to you know to make a prediction more more accurately. Um yeah there there's there's patterns that come with history. It's you know history doesn't repeat itself. It it rhymes. Like that's absolutely true for for humans. Um \[clears throat\] so I guess summing all that up um just saying oh this is the way things happened in the past um is silly that because they never repeat themselves exactly. You have to sort of more go to the you know the the underlying mechanics um particularly around human nature. I think I think human nature is um is a constant is is stationary across time if you just look at it in the right right way where orthogonalize all the other crap that's that's happening. Hm. Well, we we'll have to we'll have to debate whether human nature is static or not because I I'll I'll take the opposite on that one. But I have a I have a uh another direction I want to take this, which is um uh I didn't realize now you're now I'm nerding out like I didn't realize that uh 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. \>\> Um, well, there's there's so many different flavors of quant investing. You know, there's um but yeah, generally speaking, the higher sharp ratio or the more consistent strategies that you get that aren't pure arbitrage. It's not just based on speed. Um, you know, it's just like why does an LLM do what it's going to do? People kind of understand that, but but not really. there are all these nonlinear relationships. Um, a lot of those techniques have been used on structured data um in these models for years. I mean, you go back and read the \[clears throat\] book about when the guys from IBM came over to to Renaissance, what what they were doing, they're they're doing speech recognition, like a lot of that sort of pattern pattern matching and sort of predicting what what comes next. Um, \[clears throat\] yeah, for a human to actually sit down and like walk me through all the different layers of the neural network and why did a machine do what it's going to do? But no, the dimensionality of that problem just it's way past what a human mind can can understand. Um so I'd say generally speaking worldclass \[snorts\] quant models um while the the signals you know what goes into them of saying you know this is something that I ultimately this feature um makes sense how those features get and which I do think is important um and that again there's various different ways in which firms go about this um generally speaking we want to understand at least some rationale \[clears throat\] to our features even if there are many thousands of them but how those ultimately combined uh and understanding nonlinear relationships from that that's that's very complex and and that's totally fine. So, \>\> it's it's interesting that you brought up intuition um a little bit earlier as a something something sort of separate from the more algorithmic and it a uh helpful addition to the more algorithmic quant decision-m because I actually think of um I think of neural networks and intuition, human intuition as being analogous and 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. that you're working on a very highdimensional basis with 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 over many many, you know, experiences. And I think neural networks are the same way. \>\> I do think intuition is very important uh for building a process. Uh and really, you know, another term that you could say is analogous to intuition is is is first principles. Um, and there's a very famous guy that uses first principles all the time. Um, but I I very much believe that is actually sort of understand and it's really a math term, right? If if you can understand some of the core concepts, the first principles in math, then you can take any test and and get 100%. So, I was a math guy. I like thinking from first principles. Um, and I think it's the same way. But when you interface that with machines, \[clears throat\] um, what machines can really help you to do is say, I might actually help you come up with something intuitive. Um, but you wouldn't necessarily come up with yourself. Kind kind of like having a coach where you they could watch you doing a movement or lifting a weight and like, "Hey, did you actually realize that these things are are connected?" So, I don't I don't think they're antagonistic, but \[clears throat\] it it's 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. Do you think that first principles and this is a leading question because I I have a opinion on this but like do you think that first principles in this like I don't think that first principles in the math sense are the same thing as first principles in the like let's say decision-m sense um in in in the sense that when you when you use the word first principles in a math sense um once you adopt them you can just like work out all of the implications of those principles without like you said you can take the test and you know you can just figure out what all the answers are. But first principles in a kind of a decision-m sense like um they're not at the bare level of like uh you know a axioms in math. They're they're already like many layers up above and can be filled in in many different ways. \>\> The real world the difference is in a in a mathematical model and and math is just a model for the way that things operate. And within a model you have rules. And so um there's real objectivity to to what are the rules. Sometimes those rules can be very complicated but there's an underlying structure. Um in organic systems that that sometimes there's structure, sometimes there there isn't. So I agree with you when it comes to decision-m um that's why that the word subjectivity exists. What could be first principles to one person might be totally opposite of someone else's first principles. They both call them ground truth and axioms whatever it is. So there is an element of subjectivity in the real world. You know when it comes to decision- making and what what I believe and what I believe really good decision makers try to do is is understand their own decision-m process both to um discover what what's led to good decisions and what you know what are areas in which their decision- making has been subpar. So in some ways you can kind of apply it more to your own closed system. But to say there's a universal truth around how decisions are get get made like yeah that that that kind of falls down at some point because people might just totally be schooled and first principles that are so different that they would lead them to uh make completely different decisions. \>\> What are those for you? Like what are the as you've as you've learned to improve your decisions over time? What are the things that you've learned um to to take as as good reliable first principles and what are some of the ones that you've thrown out? \>\> At the top of the list would be the power of incentives when you're dealing \[snorts\] with humans. Uh and not in a negative sense like everyone is is greedy. Um although you know a lot of times that that does drive behavior. Um but actually understanding the right incentive decision for why an individual or group of individuals is doing something and and trying to align that as much as possible whether you're running a company or making an investment. Um that's extremely powerful is just to say like are the are the vectors or the are the incentive vectors all pointing in in the same dimension. Um so that's a big one. Uh you know you mentioned earlier like I I hate fluff. I hate um sometimes it gets me into trouble and uh but I I just I wish that people would be more that way whether that's an axiom or rule but whenever I sense that my antenna go up and uh you know that that's sort of a a negative sign and really just trying to be intellectually honest and uh so not not trying to reduce everything into a into a math problem but a lot of times there there is structure that you can pull out of a a situation it might just require require hard work so \[clears throat\] you you can't manage what you can't measure. So, so try to measure a lot of things and and you know, personally I I try to do that. I I uh you know, evaluate myself. I I keep a journal, you know, every single day with AI now, by the way, which is great for efficient. Highly recommend everyone do that. Um you know, every every single workout that I do \[snorts\] for years, I've uh I track, you know, I have I have a log and there's a lot of numbers in that just to to see these trends, you know, evolve across time. Um, and again, none of these are are perfect, but I feel like people because it's hard. Um, a lot of people just don't do things like that. Um, and I actually on a go forward basis, I think that's one of the things that's so exciting about this world of of really data and making meaning out of data is it's going to be so much easier to do that. Um, and a lot of it's going to around are you are you collecting right right data to to help you with that. So yeah, you know, the biggest first principles I said power \[clears throat\] of incentives and uh and intellectual honesty and uh those those would be the top for me. \>\> What goes into your journal? \>\> Well, there's three components of my of my life. um which would be um \[snorts\] you know my family um you know I have I have three kids and I've been with my wife who's pacing for for 15 years um and uh I I love being with them and that that it's not just a platitude so um my personal life and how I'm interacting with the family and I feel a huge sense of responsibility to to \[clears throat\] my family to um provide them with uh with a great life. So there's a section on that. Um there's a section on and \[clears throat\] by the way none of these are mutually exclusive. I don't believe in balance. I believe in harmony across different areas of life. Um so there's but there's a section on that. There's a section on on \[clears throat\] work of course um which you know for me at this point is is this great great big challenge. Um that's that's fun. I think sometimes people don't even use the word of fun. Um and like that's one of the things with AI like this doesn't need to be scary. This is fun as hell. Um, if you look at the right way, it's really important that people have that that view. Um, and you know, I I'm working because I um I get meaning out of it. I I enjoy it and it's it's it's different than and I feel fortunate that than most people where I can say like I I'm doing this because I I certainly want to. So, there's things on work that I talk about. And then there's things just on my my personal health that I that I talk about. Um, you know, how \[clears throat\] how I'm feeling, was it a good day or bad day? Um, how my, you know, how did my deadlifting session go in the morning? Um, stuff like that. Or, you know, I uh \[clears throat\] am a bit of a crazy person on on that subject. So, if I tried a new supplement or tried some new technique or something, I'll I'll write about that. But, I'm just trying to capture what's going on in my mind. I started doing this because, you know, I look back and uh in finance, right? We're we're dealing with time series and so we could say like, oh, on this day you made or lost money or something and stuff's happened, but \[clears throat\] um I really wanted to remember like what was I actually thinking on that day? Um and just trying to keep it all in your head, even for someone that can have a lot of uh a lot of hard drive space is is impossible. So, so getting that out of my head a bit more was uh was why I started doing that and it's been really helpful both as an exercise in itself even of of just writing it but then going back and saying like oh yeah this this is what I was thinking on that day that's it's interesting \>\> and help me understand that more like you're maybe now now you're like typing this into Chadbt you're speaking it you're writing into into a Google doc and then putting it into Chad BT \>\> I I'm trying to capture the concepts of what I felt that day so I can either speak or just write bullet points of here's what's on my in these three categories. You know, this is what's this is the date. This is what's on my mind. Each of the three categories, you know, here we go. Some days that's a lot. Some days that's that's a little. And then because I've been doing this and the machine knows my my \[clears throat\] voice. Um, you know, that that can be a one minute even 30 second exercise. Um, it's just so easy to do. And I I feel the reason most people don't journal is because historically sit down it would it would take time. But this is a perfect example of you know 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 months in the future. It's just this tiny little use case that's sort of so so powerful with with these tools and there was no way that could have happened in the in the future. So \>\> one word that you brought up a lot um in the context of work but also you just brought it up also in in the context of family that I'm curious about is the word responsibility. What does that mean to you? I I do think about this word a lot um in in the context of work work and family slightly different but but overlapping of course um you know I feel that people that either are endowed with certain skills like their clock speeds really fast um or they have a lot of resources or they have you know great networks just just generally speaking people with um that the that the world has entrusted upon them skills or capabilities um have a respons responsibility their to themselves and to their community to use that uh to to the maximum extent possible. It's like if you can you know run 100 meters in under 10 seconds and you don't it's a travesty and uh because not everyone can can do that. Um so historically I and this is you know before I met my wife and um years ago when it was really just me I' say that sense of responsibility was to myself to to try to get the most out of my my own capabilities. Um, and then as I went on in my career and felt that I was able to to do that and I was like, okay, well, you know, my my kids are are 10 and eight and two and a half and we haven't even talked about what it's \[snorts\] like to be a parent in a world of AI, but having a sense of responsibility to to have them, you know, grow up and to flourish and um, and have a relationship with them that can evolve as as they become adults, but but ultimately to to set them on a path, you know, huge huge sense \[clears throat\] of responsibility, you know, as as a parent that it's this is just amazing how much kids look to you for for guidance and then responsibility for for the firm like I um you know in our world in the investment world you know you you you have sort of two senses of responsibilities you know one is and this is by far in a way at at the top and take this very seriously is people give you money or typically in our case institutions give you money and um because of our type of hedge fund we're we're a pass through structure which is not an operational you know, nuance that gets buried in a document that that means that we have a blank check from our investors to spend money whenever we we want. \[clears throat\] There's there's only there's a very small number of firms that that that have that type of structure. Um, biggest ones would most famous ones is is Citadel, but there's really only maybe a dozen, probably less than that that are that are real. So, huge sense of responsibility for investors to do \[snorts\] what's what's right, to not abuse that privilege, and ultimately to uh we're, you know, we're we're in the money-making business. Let's just be honest about that. U but also responsibility to to our people too. And I think this is what's generic across kind of all all \[snorts\] leaders and all companies in world of AI that you know leaders have a responsibility to the people working at their their firm to prepare for what's coming next. And then I I definitely feel that and and all of it's tied together. I have a responsibility to our investors to make you know do the best job as we can for them and our responsibility to our people to be as efficient as possible. those two coming together mesh very very nicely. Um but yeah, the I think for me and I'm 40 so um I'm not that old. um uh we do do want to be doing this for a long time, but as \[clears throat\] I say, as you go go higher up as as far as responsibility, um I think that the notion of being a little bit more of a a steward and helping others accomplish um what they want to accomplish, like that's something that successful people talk a lot about and I I very much feel that and um it's very much aligned with what we talked about today in the world of AI. So, \>\> I love it. Um, well, always a pleasure. Uh, thank you so much for coming on. Um, I'm excited to have you back maybe in a year when you when we have more results on how everything has been going. Um, I always learn a lot from our chat. So, thank you. \>\> All right. You bet, man. Thank you. \>\> Oh my gosh, folks. You absolutely positively have to smash that like button and subscribe to AI and I. Why? Because this show is the epitome of awesomeness. 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