I have massive respect for Viking One of the few hedge funds that actually runs a disciplined portfolio Everyone in a bull market forgets what happens when the tide turns, see 2022 below Serious question, if you are an LP, which of the below do you prefer? 1) Viking: actually provides lower vol 2) Whale Rock: smart levered beta 3) Coatue: somewhere in between

Juan Soto goes BACK-TO-BACK with Bo Bichette! (via @AppleTV)

I loved this episode between @patrick_oshag and Alex Sacerdote. Probably one of my favorite investing podcasts of all time. For my way of thinking and investing, this was an A 💯. As I was nearing the end of the episode, I thought to myself "Alex has mapped out the entire global tech stack and ecosystem and uses that map as his guide to the future.” As soon as I was thinking of that, Patrick said that Alex has "built a research machine to understand the world through the lens of companies.” I think it's the same thought, just different way of saying it. Alex also gives a nice shout-out to @shaunmmaguire who was talking to Alex about the opportunities in hardware three years ago. Here are some of the quotes I am filing away… “Anytime you have a new compute paradigm, there is a new [tech] stack, and that creates new winners and losers on the old stack.” “We have this infrastructure layer S-curve, which we think is like 10% penetrated, and by the way, we think it’s still one of the best ways to play Ai.” “Sundar said its 10 basis points of the knowledge workers in the world [currently using Ai coding tools].” “We think the enterprise application Ai market is less than 1% penetrated. We talk about S-curves, but we call this an L-curve.” “We’re at 10 basis points of people really using Ai and we’re already sold out of compute…there’s not enough compute in the world. So, Anthropic has half of what they need right now.” “We do 2,000 to 3,000 face-to-face meetings with management teams each year, and about 10% to 15% of those are with privates.” “We have an investing framework of (1) S-curves, (2) competitive advantage, and then (3) underappreciated earnings power…when you get the right part of the S-curve you get exponential unit growth if you have a very strong business model (which in tech there are so many of those for so many different types of moats), your earnings don’t grow linearly, they grow exponentially, and that is the last piece…invest when there is underappreciated long-term earnings power, and very often the earnings can grow from $1 to $10 or 50 cents to $20, and it happens way more than you think, and it allows you to buy some of the best companies in the world for extremely low P/Es. When we were buying Nvidia in 2023, we were paying 4x earnings. When we bought Tesla in 2019 for the car S-curve, we were paying 5x earnings. When we were owning Apple, we were paying 4x earnings. When we bought Amazon for AWS we were getting it for free.” [Fascinating about how the bottom part of the S, before the exponential growth phase, can last 10 years]: “Smartphones were out ten years before the iPhone. The Internet was out 20 years before Netscape…Tesla went public 15 years before 2019 when it went vertical.” “Andy Grove says when you have strategic inflection points you can’t trust the data. Strategic inflection points are about intuition, anecdotal evidence.” “BTW, it’s OK to be late. It’s OK to miss the first one, two, three years in a lot of cases because if the top of the S-curve is half a trillion, the growth can go on for a long time. It’s OK to miss the first 100%.” “I started at Fidelity and Peter Lynch loved to mentor young kids, so I got some time with him, and he said “whiteout the chart. It’s all about the future.” “First we look at the S-curve and then we do an exhaustive study of everyone with exposure in that area and try and find the one with a very powerful competitive advantage.” “Warren Buffett didn’t like tech because he couldn’t predict the future. But the S-curve is our map for looking into the future.” “We sold almost all of our application software…entering this year we were actually net short [SaaS].” “You can imagine a world where in one, two, four, five years you could have a brand-new AI native company going after each one of these very strong [SaaS] incumbents.” “In software there is the Rule of 40…for chip investing we have a new Rule of 40: what percent of your sales are AI and what is your market share in that category (say 30% and 30%, you’d be 60%...that’s a great place to look because you’ve got exposure and you’ve got a strong market position). The problem with software is their AI is 1%-2% of sales and it’s a long way to go.” “AI could make some of these software platforms more important because what’s the first thing you do with Claude??? You plug it into Slack.” “The workloads in AI are growing 10x every year. And it is pushing every single aspect of hardware to the physical limits of what it can do. So not only are you creating tremendous unit growth, but we are experiencing the de-commoditization of the hardware industry. I met with Shaun Maguire like three years ago and he said I wish I could come back and be a hardware hedge fund because all the companies are public, and they all have powerful IP…and we’re in this renaissance of chips so not only do you have tremendous unit growth but it’s requiring tremendous innovation across every aspect of the server and so…” “We need you for the next four years designing this road map with us.” “No one has paid attention to hardware and chips at all. So, we’ve got all these newbies coming into it.” “One thing that bothers me is there is a lot of negativity in the general population about AI. And there is a lot of negativity in some aspects of the government…But I do think that the genie is out of the bottle. Another risk is that if AI slows down in its improvements…then the open-source models will catch up and then it could be a race to the bottom and it wouldn’t be good for the stocks, probably…it could be good for the chip companies because chip companies don’t care who wins.” “We’re meeting with as many companies as humanly possible…the [scuttlebutt] system we use is right out of Common Stocks and Uncommon Profits by Phil Fisher.” “Phil Fisher said get to know ten or fifteen like-minded people [investors] around the country and share ideas…you share ideas and it’s important that it’s a two-way street. I call it the tripod when I like something, and then my analyst like it, and then somebody who I really respect also likes it. Those three legs of the stool can really help the conviction.” “We think there is a huge structural underweight of the largest tech companies in the world…[partly because] there is a belief that there is no alpha in large caps]…[investors worry there is not alpha in big companies] but we realized this is just a product of the digital economy in that in tech the leader usually grows bigger and wins and develops very high market share quickly and there is great competitive advantages, and they are also selling around the globe so this is going to lead to massive profit pools and massive market caps…And most endowments are betting against this because they are completely underweight this…I think there is tremendous alpha in the largest cap because with a small cap it takes just one person to figure out it’s good and move it up. But it takes 100 diversified PMs to realize Google is not a loser, it’s a winner, and can we figure that out before 95% of those generalist PMs?…and we’ve been able to do it and we like our odds on that. Disclosure: I am an investor in and the portfolio manager of the Bastion Industrial and Infrastructure portfolio, which owns shares of Nvidia, Alphabet, and Amazon. I personally own shares of Apple and Tesla.

One agentic workflow now does 1,000 hours of hedge fund analyst work. Aakarsh Ramchandi founded the data team @ Third Point, built screening engines @ FactSet, & now builds agentic research tools @ RavenPack. "There's gonna be a full convergence of quant and qual. Most discretionary analysts I know are somewhere in their Claude journey — and the quants are going the other way around." We cover: - Year one at Third Point: onboarding 100 data sets with a team of 4 — & why they kept point-in-time copies of every vendor feed to catch panels that silently changed overnight - The Dan Loeb pitch story — a 45-page deck, six weeks of work, he stops at page 26, asks one question, & the whole thesis breaks - "Kind but not nice" — the zero-politics office where everyone gets corrected by elite people daily - Why analysts don't want your forecast — they want facts in Excel, red-green-blue, formatted their way - Hedging a concentrated activist book with alt-data short baskets built from a 400-500 factor model - Why Nvidia broke the Barra model — & building custom semiconductor factors instead - The agentic earnings preview: 8-9 step workflows, 35M tokens per run, ~1,000 hours of analyst work encoded - Self-improving loops — agents reviewing their own last 10 traces & patching their mistakes - The WorldQuant hackathon: 7,000 quants turning unstructured text into 35M unique time series Highlights: (00:00) Intro (01:38) Founding Third Point's data team in 2017 (03:55) Six months building point-in-time data infrastructure (06:20) How an event-driven fund actually uses alt data (12:40) Team structure & the original forward deployed engineer (17:10) Nobody wants your forecast — just give it to them in Excel (19:35) Measuring signals: direction, point estimates & confidence intervals (24:05) Working with Dan Loeb — the elite bullshit detector (26:05) The page-26 "Why?" story (28:55) 5AM Saturdays & discipline that compounds (32:05) Kind but not nice: the zero-politics office (33:55) How an activist creates alpha by re-running the business (43:10) Hedging the book with alt-data short baskets (50:40) Why Nvidia broke standard factor models (56:25) From search to RAG to agents (1:04:20) Opus 4.5 changes the game: 70% → 90% accuracy (1:11:00) Anatomy of an agentic earnings preview — 35M tokens per run (1:17:20) Ambient agents: the always-on Jarvis (1:19:40) Self-improving loops & encoded judgment (1:20:20) Finance in 10 years: the full convergence of quant & qual

🇺🇸🧊 Gio Reyna trivela. Perfect angle

🍹 How to smuggle tequila into a World Cup game in Mexico. Genius.

Pals chatting. One pal was hungry

Elon Musk is a real-life Bond villain ft.trib.al/zAOuVKk

lots of good commentary on this intvw, I have very little to add except highlighting this one clip re: lollapalooza effects on modeling px/vol/margins translating qualitative input to quantitative output putting aside the bull/bear debate or the man in question -- generally if dan loeb says someone is "one of the smartest and savviest investors he's ever met" u can prob disregard the peanut gallery -- this is the right way to think about a business transformation/narrative shift u can basically follow his logic line item by line item, or from top-down to bottoms-up: -what is mkt share / has it changed / what is industry growth rate -what is unit growth % -what is ASP growth % -what's the new GM% profile -then flow that onto a fixed cost base/degrees of op leverage this framework is always behind any story where EPS goes from 20 cents to like 20 dollars I dont think u see variant views of this magnitude outside of tech....the same dynamic/flow-thru exists re: px/vols/profitability, but just much lower delta vs street ests (thinking consumer industrials) and then last, the way he frames visibility duration of supranormal growth, is how you'd think about the multiple/disc rate in a DCF. combine it all and u get the "lollapalooza effect" in action.

Opinion: SpaceX IPO makes Elon Musk the first trillionaire. Here’s how to properly hate him theglobeandmail.com/business…