Partner @LightspeedVP - fintech, stable coins, vertical AI. Capital markets junky - recovering MBS trader. Dad & Pittsburgh Sports Fan

New York & San Francisco
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Justin M. Overdorff retweeted
Damn they move quick
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“AI is going to take the old business models of ads and subscriptions and just annihilate them. Something will replace it, and I think there’s a good likelihood it’s going to be built on stablecoins.” - @eastdakota Was incredibly prescient of Matthew Prince (@cloudflare) with @benmilne (@bralexyz) at @averystableconf in March of this year. Can't wait to tell you what @ay_o @kerrykellogg and I are working on for next year!
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😂
At some point you have to ask how serious these types of asks are: 1. You see them all the time 2. They sound grandiose (price insensitive) 3. Very opaque counterparty info sharing Then you: 1. Make intros, which are blown on account of them either not knowing what they want, not being serious, or not actually being blanketly price insensitive as they claim. 2. Get caught up in some four-to-six guy deep broker chain of guys who are all rushing to find the colo space or supply tranches under the auspices of some very real “buyer” If it were an educated buyer, with serious interest, and not price discerning, the g1 — the guy one-hop away from them, that they talk to should conduct the affairs in order and pocket the spread. But for whatever reason it’s constantly not that. Either the g1 doesn’t have the juice and is looking for a gN that does or (more likely) the g1 doesn’t actually have a captive counterparty (buyer) and is competing against n other g1’s and *their* whisper networks. Too many non-circs, too many mndas, too few captive counterparties. Welcome to the age of deal making, you should see parallels to the Gilded Age and if you don’t, you haven’t been doing your homework. Please get in touch if you are also a student of history. Always looking for shrewd folks that can spot rhyming patterns across time.
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Blackwell Ultra (B300) GPU rental prices up 17 consecutive days to a new all-time high, according to Compute Desk's index of verified transactions from U.S. neoclouds.
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Joe is asking a good question, but if you look a little closer, things are responding in a relatively rational manner. The front end of the yield curve is staying rather fixed. This means the market is suggesting that the Fed will hike and hold even as systemic risk is increasing (neoclouds). The net impact of that is to decrease growth and inflation expectations further out the curve, which causes forward rates like 5y5y to rally. Moreover: tighter fiscal conditions, relative to risk factors, increases the value of volatility and convexity, which would cause forward rates again to be supported. This is exactly what we are seeing. There are of course flows to go alongside this: if people have hedged the duration exposure of their core weave holdings, then a sale of such holdings would cause a backend rally. BC
We've had two hot inflation prints in a row, and yet rates have been sliding. The entire market is all about the AI trade, and the recent jitters about Anthropic's revenue numbers matter way more than some random government datapoint right now.
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Least surprising and very much expected outcome. This is the Plaid v JPM fight all over again but probably bigger surface area of risk
JPMorgan Chase blocks outside AI agents like Muse, Instinct from directly accessing accounts cnbc.com/2026/10/13/jpmorgan…
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Justin M. Overdorff retweeted
There are a legion of posters now putting out AI quant trading models. Most are crap. Here’s a quote from this post: “Betting Against Beta, a classic from every textbook: minus 7.78% a year while the market rose 14.86%. A corpse.” Of course I can’t find how it’s constructed or what period he’s referring to (or what paper he claims to base this design on). Welp… There is no period starting from today and looking back any decent amount of time that has BAB significantly down (available on our website). It’s been flattish in the USA for a bit but still good global ex USA. Its long-term record is still great. The chief challenge to BAB comes from Robert Novy-Marx where he says it’s empirically subsumed by the profitablity. This is an interesting debate (we still prefer a portfolio of both, partially as the economic story for BAB is better than the one for profitability). Again, economics not just AI. Economics with AI can be super powerful. AI w/o economics, or any understanding of the literature, in a “small data” problem like investing *at all by high frequencies) is a recipe for silliness. Like the post below. I suspect what has happened here is a mistake I’ve pointed out in other papers. The BAB factor needs a hedge ratio. You short less than you long as the shorts are (this is the point) much higher beta. If you do it dollar neutral you are running a very short the market position, and not doing the BAB factor as anyone serious has learned in the large literature. Thus in a bull market you wrongly think it stinks. Or they just did it all wrong in some other way. They don’t explain a lot. This is why AI in the hands of people who don’t know economics, haven’t read the literature, etc., is handing a nuclear weapon to those who should only have a butter knife if they pass a test and get a license. And it’s why I think these people are suppliers not consumers of alpha for the foreseeable future. One day that may change. Hopefully whoever takes over for me at AQR in my coming dotage (not for a while!) can deal with that. Oh, and “corpse.” Rude as well as wrong. Cool graphics though.
Ken Griffin, who runs Citadel, just admitted that the most expensive skill of his quants, the one he paid them millions for, now costs nothing And for the first time in history, that skill belongs not just to a hedge fund, but to anyone with access to AI A fund's entire quant team runs one cycle: come up with a strategy, turn it into code, test it on history, deploy it to the market Every step used to cost separate people and years of training. Now AI does the whole cycle You describe an idea in words, it writes the strategy itself, runs it on years of real data, and if it's alive, deploys it straight to a broker But the speed isn't the point. The point is what the retail trader doesn't understand You take a strategy with a beautiful chart and you believe it. But a beautiful chart is no proof Run enough versions and a profitable curve will appear even on random numbers. One just got lucky, and you decided you found gold Funds don't trust any curve until they test it on data the strategy has never seen. There the fit falls apart, and a real edge survives I ran two of the most-cited quant papers through this cycle Time Series Momentum on Bitcoin: +1,537%. Alive Betting Against Beta, a classic from every textbook: minus 7.78% a year while the market rose 14.86%. A corpse One still prints money, the other died long ago. And trading blind, you'd never know which is which until it took your deposit If you want to run your own idea through the same test, it takes minutes here (free trial after signing up): join.horizon.trade/qwinsiiii The entire hedge fund is six steps. AI already ate four of them. Which ones, I broke down in the article below
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The NFL is $24B annual rev biz and generates the largest $s of bets of the big 4 pro leagues (NFL, MLB, NBA, NHL) in the US (some data reports that NFL betting handles exceed all other U.S. sports combined). I'd expect the other leagues to follow, but this is a heavy voice jumping in the convo.
NFL tells Supreme Court prediction markets are gambling and should be regulated by the states cnbc.com/2026/10/08/nfl-tell…
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Ok, now do Intuit $INTU next
This guy re-created all the adobe apps with opus-5.5, ported them to rust, and opensourced them something really cool is happening
Community note
These projects are partial open-source Rust reimplementations of Adobe apps (built rapidly with AI agents), not complete recreations; their READMEs and roadmaps document many missing features and features still in development. github.com/storytold/phot… github.com/storytold/vect… github.com/storytold/vect… github.com/storytold/film… github.com/storytold/film… github.com/storytold/ligh… getartcraft.com
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My eyes were wet from start to finish. I thought of being little in a big world & watching my son's first tries at this mad game. ESPN's Open to the NHL season is beautiful. I didn't expect to cry today-this is stunning. There's nothing like this sport. We at ESPN love the sport as you do. ❤️ Enjoy.
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Fascinating. Chief Economist at Apollo: agents could cause a bank run by sweeping household cash into accounts paying 3-5% instead of the 0.1% national average, causing banks to lose a large share of their cheap deposits.
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What’s funny about these reservation sniping apps is that every restaurateur I talked to for this piece was like “these are the exact people I don’t want in my restaurants.” cnn.com/2026/09/23/tech/ai-a…
For months, I've been snagging tables at some of NYC's hottest restaurants like Don Angie and Semma, impressing my wife and friends. But I wasn't suddenly well-connected. I was using an invite-only new app called Spot 👀 My interview with its founders: upstartsmedia.com/p/inside-t…
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SCREAMING! The only thing missing here is the lender should have been Countrywide / NewCentury / WaMu Otherwise 🧑‍🍳💋
Belongs in a museum
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Today we launch Margins, a financial infra and analytics suite that feeds your and your agents’ day to day. Margins is the first fully-reconciled data layer built for consumer brands. It connects to all your data sources, including Shopify, Amazon, Payments processors, Meta, 3PL, EDI, billing, and bank transactions. Connect Claude and chat with your data, build your own dashboards and workflows, or use our sleek, designed ones built off our experience working with thousands of brands. 🎉 To celebrate the launch, we’re giving away free forever, unlimited access to the FULL Margins product for the first 200 brands to sign up, no matter your size from starter to 9 figures. No trial. No sales call. No stripped-down version. RT+ comment “MARGINS” and I’ll send you your personal link. The story 👇👇
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We grew from ~0 to $500M ARR, adding $250M last year alone while being EBITDA profitable. 1,300-word post on every growth tactic that worked for us: 1. What got us from 0-$400M ARR in the US works in every country. 2. Retention and Monetisation Hacks. 3. Localization > Translation. 4. Experiment with $1M internal seed checks. 5. Pivoting to only AI content production unlocked 100% ARR growth. Pocket FM is like Netflix for audio-only dramas, with our own pool of one-person studios. 1. Acquisition Playbook for 0-$10M ARR in any country in 6 months We run a 90 sec video trailer of an audio drama as an Ad and ask users to download the app if they're interested in the rest of the story. Our core insight after spending >$100M on acquisition is: If the clickthrough rate (CTR) for an ad goes from 2% to 2.25%, our customer acquisition cost (CAC) decreases by ~ 30%. We remodelled our system around this insight and built an AI-first 2.25% CTR ad manufacturing machine that works in every country. For every new country, we take our hit shows -> use LLMs to extract and most intriguing moments -> Write a 5-min script combining all the best parts. The first 60 seconds has to have a hook every 5 seconds and needs to end with a crazy cliffhanger to force a download mid-scroll. If a marketing video is not hitting our benchmarks (2.5% CTR and 55% 3-second through-play), a creative director gets involved to change the hook or cliffhanger to get the numbers there. AI lets us make 1,000 Ads per show, and in total we do ~17.5k Ads per month. When a business creating scales from 1k to 10k Ads, the normal thing is for CAC to skyrocket. But with what I just shared, we 7-8x'd our User Acquisition budget without increasing our CAC materially. It took us 8 months to figure this out, but then the timeline from 0-$10M in every country got shorter and shorter: US revenue grew to $25M in 19 months. (US is now 78% of total) Germany to 21M in 11 months. France to $10M in 3 months. 2. Retention and Monetisation Hacks. We knew we wanted to create an audio entertainment platform, but there was no standard format. For the first 2-3 years, we tried 10 different formats before landing on the winner. After we got it right with audio drama (8-12min chapters, written for mobile fiction, serialized, episodes have strong hooks and end on cliffhangers), avg daily streaming time went from ~25mins to 150+. Audio drama made us realize that Pocket FM was creating a whole new medium. There was no playbook for anything that we were doing. Everything had to be thought & built from scratch. This is what we did for each major bullet: - Monetization: Users have some free daily minutes to listen; then it's pay per episode. We also added the option for users to unlock episodes by watching ads, which is doing extremely well. Ads scaled from zero to a ~$90M run rate in 12 months. - Engagement & production: You don't become obsessed with an app you open once a week. To have users engage daily, we make the next episode free every day. Also helps them build the habit. - Discovery. Huge problem because people consuming Pocket FM enter the app, tap the show, and lock the screen. We fixed it by doing "playlists" of episodes. Once users's free minutes on a show are done, we ask users if they want to pay. If they say no, we play a new show, one where they haven't used their free mins. And we stitch episodes of different shows together that way, creating natural discovery. 3. Localization > translation. 78% of our revenue is still concentrated in the US. Localisation is fixing this: You might write a show for a Spanish audience where language, jokes, folklore, have a certain flavor; if you merely translate the show for, say, a Norwegian audience, that color is lost and hurts the show in the Norway. Listeners would relate more if the show was written by a Norwegian. That's why, instead of translating, we localize shows to different regions. We use AI to take the spine of stories and adapt their whole cultural layer to the other country. The results: a US show that was localized for a German audience had 50% higher retention than the translated version. Localization + our user acquisition playbook led to: - $10M+ ARR in France within 3 months - $21M+ ARR in Germany within 11 months. And this expands writers' addressable market. We get messages of writers thrilled to have revenue coming from the US, India, EU, LatAm, without them doing much incremental work. 4. Experiment. We give $1M checks to new internal initiatives, and the team has 12-18 months to prove their thesis. If they prove it, we double down. This is how Pocket Saga came about, our AI video microdrama app. It's an AI video equivalent of Pocket FM. Same shows and structure, but as a vertical 2-min mobile video series. We launched it two months ago and it's at ~$15M ARR. Pocket's broader thesis is to help creators tell their stories to as many people as possible. Start with audio drama -> multiple languages or localize to diff countries -> microdrama -> more formats like movies, TV shows, and games. Best of all is that writers get revenue streams not only from countries they wouldn't have tapped into, but also from formats they wouldn't have thought possible. 5. Pivoting to only AI content production unlocked 100% ARR growth. In mid-2024, we pivoted to only AI content production. Our growth took a very direct hit. Pocket was already at $200M ARR, growing 50% YoY, and we flatlined for a whole semester. Six months later, the business exploded. After the switch, we went from ~25k hours of content produced per year to over 2.5M hours, which are also higher quality. Because AI orchestrates the writing and more data is fed into it, more blockbusters come out. Over 90 titles have $1M+ in lifetime earnings and 13 crossed $10M. Quality control is done with LLM as a judge, and LLMs are quite tough. Results are very encouraging: - 12-month revenue retention went from 44% to 76%. - In the past year, we added $250M in net new ARR. __________________________________ Pocket Entertainment (Pocket FM + Pocket Saga) has become the largest AI entertainment platform. We have the largest storytelling catalog with 770,000 titles, 550k creators, and 5.5B hours of playtime with minute by minute retention & engagement data. We are using all of this data to improve every aspect of our business. Our Bet: In the next 3 years we will be able to produce Naruto-like series for $1000. Netflix has to spend $17B to find 100 Blockbusters per year. What happens when you can produce 1M high quality shows for $1B? The streaming wars caused a $300B reallocation of market cap. The AI entertainment wars may be a $1T+ reshuffling of market cap. We are at a unique spot. Unlike other AI creator tools like Runway or Midjourney, we own both the supply and demand side of AI content. We've attracted over 550,000 writers who are producing an annualized 2.5M hours of content every year. This pairs with 137B+ minutes streamed. Because of this, growth is accelerating as we scale further. We have multiple S-curves inflecting at the same time: - AI produces better and more ads -> scale faster in new countries - ⁠Writers + AI produce more shows -> more blockbusters - ⁠Localisation -> more reach per blockbuster - ⁠Audio to video format expansion -> larger TAM -> more creators Every aspect of our business is designed to improve another, and everything is aligned so that the number of blockbusters continues to rise. If you're interested in building at the intersection of ai, tech and entertainment, DM me.
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VCs won't need to raw dog a root canal if they buy this toothbrush
Dyson introduced a $499 toothbrush that uses artificial intelligence and a built-in camera to give real-time feedback, the latest in a growing subset of gadgets that put AI and video in sometimes unconventional places bloomberg.com/news/articles/…
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Replying to @jaltma
This happens in every disruptive cycle because the aperture of uncertainty is incredibly wide. Smart people will be wrong. The smarter ones will change their minds. The smartest ones (whom I trust most) have the humility (borne from experience) to know they may be wrong, and speak in probabilities rather than declarations.
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Turns out, “Stripe for Agentic Payments” is… @stripe 🙃 Great partnerships to see @jeff_weinstein 💪🏻
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