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🚨ATTENTION YOUNG MONEY READERS🚨

As some of you know, I spent the last ~year and a half, give or take, working on a book. Last Friday, I finally read the first physical copy: 272 pages of an “uncorrected proof for limited distribution.” I’m quite proud of this thing. It’s a mix of humor, philosophy, irreverence, and reflection, but, most importantly, it’s the book I wish I could have read when I was 22, and I think the contents of the book will be relatable to all of you.

I’ll give more details on “what” and “why” for this book in a moment, but first, I am stoked to announce that you can pre-order your copy of Young Money right now, available for delivery on August 4, 2026.

Pre-orders are super important as they show bookstores that people are interested in this particular book (thus telling those bookstores to stock up!) so if you’re considering buying Young Money, I’d love for you to pre-order a copy by clicking here:

Pre-order Young Money here!

So, what is Young Money?

In the last chapter of his memoir, Norm Macdonald warned us that “The only thing an old man can tell a young man is that it goes fast, real fast, and if you’re not careful it’s too late. Of course, the young man will never understand this truth.”

Norm is right, but since this book is coming out while I’m in the last year of my 20s, my hope is that young people will listen to me. Young Money is a book on opportunity costs. Most specifically, the opportunity costs that come with that transitional period between “youth” and “adulthood.”

Your twenties should be an incredibly fun, exciting, adventure-filled decade of life. But they’re also filled with stress. Anxiety. Uncertainty. You have no money or skills, the guardrails of higher education are gone, and you are, for the first time, wholly responsible for the outcomes of “your life.”

You’re supposed to be planting the seeds that you want to compound for decades with a romantic partner and career. But memories compound, too, and what about the memories that you only have a few short years to create before the opportunity disappears? Fun nights out with friends? Taking an impromptu job opportunity across the world? Starting a business on a whim? Learning a new language, or taking up a new sport? With time comes complexity. Responsibility. Commitment. Risk.

It’s easy to get so preoccupied with chasing a particular thing, or, worse, reeling in indecisiveness worrying about chasing the wrong particular thing, that your youth goes by before you blink, and so many of the things that you wanted to do once you had a bit more money, stability, or certainty, are no longer available or enjoyable.

Anxiety and uncertainty are the biggest obstacles facing young folks today, and it’s my hope that this book can help a few of them navigate this highly-fun-but-equally-uncertain phase of life. (Of course, this book isn’t just for the younger folks in the room. While many of the stories in Young Money are reflections from my 20s, opportunity costs and the “stage-specificity of life” tend to be rather timeless topics).

So, anyway, if you’ve followed along for a while, or if you’re new here but you liked this piece, I think you’ll like this book, and I’d love nothing more than if you ordered your copy here:

Pre-order your copy!

A few other points:

• I’m going to, over the next four months, be ramping up the marketing a ton. 1) Please forgive me, and 2) if you know anyone who doesn’t follow me, but you think might benefit from this book, shoot them this blog post, too.

• If you work for a company, university, nonprofit, or other organization that would like to bulk order 25+ copies of Young Money, please add your information here.

• If you, or someone in your network, is a podcaster I should chat with, let me know with a reply to this email or DM on Twitter or Linkedin.

• I’ll be throwing a few different launch events in different cities this summer. Stay tuned.

Thanks for reading along, I hope you enjoy reading Young Money as much as I enjoyed writing it.

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!

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Now that I am again writing this newsletter on a regular cadence, I’ve asked myself, “What should the current iteration of Young Money look like?” The equilibrium I’ve reached is treating Monday mornings as the time to publish my thoughts on the “current thing(s)” in tech / markets / whatever is dominating my Twitter feed, while publishing non-regular, less timely blog posts as they take root in my brain. To today’s piece.

Yesterday, someone pulled up to Sam Altman’s house in San Francisco and fired a gun at the property. Three days ago, someone threw a molotov cocktail at Sam Altman’s house in San Francisco.

It goes without saying that these are horrible, disgusting attacks against Altman and his family, and the freaks that perpetrated them should be punished by the fullest extent of the law.

These were also not, in my opinion, isolated and/or “random incidents.”

The man who threw a molotov cocktail at Altman’s home is 20-year-old Daniel Alejandro Moreno-Gama. Moreno-Gama was an active member of “PauseAI,” an organization whose name is self-explanatory. In the “PauseAI” Discord chat, he had sent messages including “Is there any sort of timeline for how long humanity has left?” As an 18-year-old college student, he emailed congressman Dan Crenshaw addressing the group’s concerns with AI labs not taking safety and alignment seriously. Last week, he threw a molotov cocktail at the home of OpenAI’s CEO.

Meanwhile, Americans in multiple states are actively protesting, and closing down, data center construction projects. In January, NPR reported that protesters in Virginia, Pennsylvania, and North Carolina have shut down proposals for new data center buildouts. A town in Wisconsin tried to can their mayor for approving a new data center. Maine banned new data center until November 2027, after seeing their total cost of electricity bills spike 60% between 2021 and 2026 (they also, notably, banned nuclear reactor construction, which may have helped with power costs, but I digress). Virginia, the top state for data center construction, booted its GOP governor and elected a democrat who promised to “make data centers pay their own way for power.” It turns out that everyone, especially young people, dislike data centers, and that disdain carries across both sides of the political aisle, per Heatmap News.

Democrats hate data centers because of their environmental impact. Republicans hate them because they represent big tech forcing higher power bills upon Americans. Zoomers hate them because.. vibes?

In Oklahoma, 21-year-old GOP organizer Kennedy Laplante Garza started fighting a nearby data center proposal known as Clydesdale after learning over the summer that it would be built a mile from her family’s farm. “I didn’t even know that much about data centers at that point,” she told me. “But I knew my friends across the state were fighting similar things, whether they were solar panels or wind turbines.”

Will Manidis made a site tracking data center moratoriums in the US by state. Guess what? five states have active bans, ten have legislation advancing, and seventeen are under discussion.

The majority of Americans “hate” AI. Of course, that shouldn’t be a surprise when the CEOs of three of the biggest AI labs in America are all basically saying the entire white collar labor force is just a few years away from getting brutally job-mogged by LLMs:

• May 2024: Elon Musk says AI will take all of our jobs.

• May 2025: Dario Amodei tells Axios that AI could wipe out half of all entry-level white collar jobs and spike unemployment to 10-20% in the next 1-5 years.

• October 2025: Sam Altman says AI could eliminate jobs that ‘aren’t real work,’ implying that many of today’s white collar jobs are, to put it bluntly, “fake.”

• January 2026: Dario Amodei predicted that humans would be unable to adapt to AI development’s rapid pace, and this would trigger an “unusually painful” short-term shock in the labor market.

• January 2026: Elon Musk says that in 10 - 20 years, “work will be optional.”

• March 2026: Sam Altman admits that AI is killing the “labor-capital balance.”

It turns out when you tell people, “Hey, we’re building mega technology, it’s going to take your job, and, by the way, you’re going to help pay for it with a higher power bill,” people get pissed off and/or anxious. Some of those people will act on that anxiety and/or anger by protesting data centers, but, in a population exceeding a minimum size, there will be outlier, left-tail individuals who decide to take matters into their own hands, threatening to destroy infrastructure, or, in the case of Altman, threatening the leaders of AI themselves.

There is a very, very good blog post by Tim Ferriss called 11 Reasons Not to Become Famous that is, I think, relevant when thinking through these attacks.

Think back to your 5th-grade class. In my case, there were 20–30 kids. Was there anyone totally off the rails in your class? For most of you, there’s a decent chance kids seemed pretty sane. It’s a small sample size.

Next, think back to your freshman year in high school. In my case, there were a few hundred kids. Was there anyone volatile or unbalanced? I can think of at least a handful who were prone to violence and made me uneasy. There were fights. Some kids brought knives to school. There was even a kid rumored to enjoy torturing animals. Keep in mind: this high school was in the same town as my elementary school. What changed? The sample size was larger.

Flash forward to my life in July of 2007, less than three months after the publication of my first book.

In that short span of time, my monthly blog audience had exploded from a small group of friends (20–30?) to the current size of Providence, Rhode Island (180,–200,000 people). Well, let’s dig into that. What do we know of Providence? Here’s one snippet from Wikipedia, and bolding is mine:

Compared to the national average, Providence has an average rate of violent crime and a higher rate of property crime per 100,000 inhabitants. In 2010, there were 15 murders, down from 24 in 2009. In 2010, Providence fared better regarding violent crime than most of its peer cities. Springfield, Massachusetts, has approximately 20,000 fewer residents than Providence but reported 15 murders in 2009, the same number of homicides as Providence but a slightly higher rate per capita.

The point is this: you don’t need to do anything wrong to get death threats, rape threats, etc. You just need a big enough audience. Think of yourself as the leader of a tribe or the mayor of a city.

Tim goes on to explain the various death threats, stalker incidents, and psychotic messages he’s had to deal with since his first book blew up. And Tim Ferriss isn’t particularly controversial or mega-famous; he’s a moderately well-known podcaster known for his life optimization and bio-hacking content.

The leaders of the AI labs have millions of Twitter followers, and, in 2026, information spreads across the internet like wildfire, meaning the total “audience” for any message involving any major figure in AI is likely in the billions, or, at minimum, hundreds of millions. And that message, right now, is that AI is about to blow up your way of life and displace most of the white collar labor force.

Say that “audience” in America alone is 100 million people. Even 1% of 1% of that audience is 10,000 potentially unhinged actors off their meds going through some version of psychosis. And you just never know when one of these psychos is going to act on their impulses. Particularly if that psycho is a frustrated young male. Who threatened to blow up an xAI datacenter last spring? A 25-year-old male. Who threw the molotov cocktail at Altman’s home? 20-year-old male. Remember Luigi Mangione? Yeah. Young male.

Young males are, compared to other demographics, prone to violence, disorder, and destruction if their life is otherwise in disarray. And people really, really hate AI. Look at the TikTok comments on posts about Altman’s home being attacked. It’s a mixture of satire, crude irony, support for the attacker, and allusions to Luigi Mangione.

Take nation-wide AI psychosis, disgruntled young males, online communities festering AI resentment behind closed doors, fundamental misunderstandings of what this technology can actually do, and narratives that spread like wildfire, far outpacing whatever the “truth” might be, and you have a pressure cooker for a few insane folks to take a vigilante approach to defending their ideals, no matter how false those ideals might be.

I mean, come on, Luigi Mangione was a mentally unwell 20-something dude who committed a horrific act in killing a married father of two, and he’s still a cult hero amongst internet incels who think Mangione was standing up for something. But this is, in fact, the world we’re living in today. Guess what? Narratives, even if they’re false, can be powerful, and, through that power, dangerous if they frighten the wrong soon-to-be bad actor. “The American health insurance industry is preying on you.” Is that true? Who knows. Someone thought it was, and they murdered a healthcare executive over it in Midtown, Manhattan.

Is AI going to “kill white collar jobs?” No. AI, and, more specifically, LLMs, can do a lot of things well. It’s great at generating code! It absolutely can churn out code, read through documents, and write prose in, basically, no time, and it can scale, theoretically, to infinity. That is very useful. But AI does not have activation energy, agency, desire, or will power. It’s not nuanced, though it can mimic nuance. It doesn’t “know” or “remember” things like humans, though increasingly large context windows allow it to “recall” increasingly impressive amounts of information. But there’s so much subtle friction in, well, most jobs, that I’m just bearish on the idea that AI will, at some point, “do everything.”

But the narrative being pushed by every player in AI is that AI will, in fact, eat the entire world. And there’s nothing anyone can do about it. Is that narrative true? I mean, I’m personally bearish on any concept of “ASI” or “AGI,” but you need a narrative when you’re trying to go public at what will likely be that $1 trillion+ valuation.

The bigger the valuation, the bigger the narrative needed, particularly when you’re still years from profitability, access to compute is increasingly “the only thing that matters,” and the difference between frontier models is marginal at best. And the only narrative that can support what will likely be multiple loss-making trillion-dollar companies in the public markets is that we’re $500 billion in compute spend away from ending “work” as we know it.

I do think Anthropic’s founders actually believe in an AGI and ASI future. I do not know if OpenAI’s executives believe it, or if they are simply aware that they have to sell this vision to keep raising capital. It doesn’t really matter. At the end of the day, all of the talking points basically boil down to, “We’re raising to terminate all of your jobs. Tbd on what comes after that.”

Silicon Valley’s ethos is “accelerate or die.” Most of America just wants to earn their living wage and watch their kid’s baseball game on the weekends. Folks don’t want to be “liberated from white collar work.” They just want to put in their hours, get their check, and do whatever they want in their free time.

The AI narrative of “We’ve built the thing that’s going to eradicate your jobs” is antithetical to the long-standing unspoken agreement between capital and labor in America: “Do your work, and you’ll earn enough money to live a good life.”

Now it’s, “We are replacing your work. Maybe you’ll get UBI or something. Have fun in the permanent underclass.” Again, I am “short” the idea that AI is actually going to take all of our jobs. But if you tell the same story over and over again, do you really think the very people whose jobs and power bills are threatened are just going to sit by and think, “Ah well, I guess I should ride out the next five years, then good luck.”

No. People, unlike LLMs, have agency.

When threatened, or at least when they perceive themselves to be threatened, the far left tail actors will, in fact, act. And each actor emboldens more actors. A protest in one town shuts down a datacenter? More protestors will appear in other towns. The momentum accelerates. Someone throws a molotov cocktail at Altman’s home? Someone else comes by two days later with a gun. Every vigilante spawns a new vigilante, and the vigilantes think they’re the good guys stopping the “evil overlords” of AI.

I’ve seen a lot of takes on Twitter blaming journalists for stoking flames of resentment against Altman and AI industry in general. And, yes, sure, there have been plenty of pieces painting these folks in bad lights, and, yes, sure, some of these pieces were likely in bad faith. But when your talk track for two years has been “AI’s going to eradicate the income stream that supports your family,” I don’t think it’s that crazy that some folks might take that threat seriously, and act on their desperation in desperate ways.

A lot of investors are worried about training costs, long-term margins of increasingly-commoditized frontier models, and access to GPUs in 2029. I’m worried that some asshole from rural Arkansas is going to spend too much time on Reddit and then go blow up a datacenter in Memphis to “save the world.”

Anyway, happy Monday. Let’s churn through some tokens.

Content Recs:

• For my SF folks: I’m co-hosting a tech / VC / startup breakfast with my buddy Morgan Barrett on Tuesday AM. If you’re around, come hang!

• Former US Senator Ben Sasse, a great Twitter follow and also rarity of a good person in Congress, is dying of stage four cancer. But before he dies, he’s also hitting the podcast circuit hard. This conversation with Ross Douthat at the New York Times is a really, really good read / listen.

• Hilarious project that someone made all “NYC lines” that is, literally, monitoring “lines” at popular NYC restaurants. Shout out vibe coding. Here’s the website link: damnlines.com

• Really fun piece in the New York Times by John Carreyrou on finding the creator of Bitcoin.

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!

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Brief note: I’m co-hosting a San Francisco Tech Breakfast Club next Tuesday from 9-11 AM PDT. If you’re around, come hang, caffeinate, and chow down with friends. Signup link here.

I spent most of 2025 living in San Francisco.

Before December 2024, I had never visited San Francisco. In fact, my only experiences on the west coast before December 2024 were a trip to San Diego with my grandparents for my grandpa’s board meeting when I was 12, a trip to Los Angeles for the Rose Bowl in 2017 with my then-college girlfriend, in which we slept in an RV camper in a tailgate parking lot with her family (they lived in LA, but went all-out for the Rose Bowl every year. This was when UGA pulled off a miracle over the Baker Mayfield-led Oklahoma. Sick game. I think that ex-girlfriend is engaged or married now. I still have my Hinge radius set on four miles of Union Square, Manhattan and filtering for 20-something chicks that are Christian and/or Catholic. Who’s the real winner?), and a wealth management conference called “Future Proof” where I saw Third Eye Blind play live in September 2024.

I had never visited San Francisco.

Then I went out there for a job interview. Self-driving had always “sounded cool” until I flew out there and tried my first Waymo. I’ve never done crack cocaine before, but I imagine the “wow” factor is similar. That thing blew my mind. Car driving itself. Insane. Suddenly, I could connect my Spotify to the surround sound in a fancy Jaguar and jam to whatever I wanted without some stranger with a 4.88 Uber rating who smelled like a mixture of cigarettes and stale pizza judging my music or eavesdropping on my phone calls. I think there are a list of “firsts” that are quite memorable for dudes born in the 90s.

• First touchdown (or goal, homerun, etc).

• First time bench pressing two plates.

• First time sipping alcohol.

• First time having sex.

• First time beating the last mission on Halo 3 on veteran difficulty.

• First time riding in a self-driving car.

On the second point, if you’ve never benched two plates, I think it’s hard to call yourself a dude. Especially now that everyone is ripping peptides. Get your weight up. I digress.

Anyway, the future is now in San Francisco. So I ended up moving out there for a year. Where I’m from, in Georgia, “self-driving” is some mythical future from the Jetsons. Except in Atlanta, where sometimes the Uber you order is a Waymo, and sometimes it’s some stranger who doesn’t match the Uber picture, and their best friend in the front seat with blunt wrappers on the floor, and you wonder “why did I pay $20 for this?" For some reason, Atlanta forces you to order Waymos through Uber rather than just using the Waymo app.

Anyway, self-driving is this insane, futuristic-but-not-realistic thing in most of America. In San Francisco, it is my default form of transportation.

Oh, have you seen the housing market going crazy in the Bay Area? It’s because OpenAI just raised like $120 billion at an $850 billion valuation in preparation of their $1 trillion IPO despite the fact that they’re about to incinerate another $100 billion+ on data centers. Does the business work? Who cares. As long as Masayoshi Son will buy $20 million+ of OpenAI stock from AI researchers (read: folks who figured out how to get “next token prediction” to convince you that, yes, your idea which isn’t great is, actually, quite genius), and Nvidia continues its generational run of printing infinite money by selling their former bitcoin mining rigs to companies who want to generate infinite tokens by forcing their developers to vibe-code 100,000 lines of code per day, it’s going to cost you $5 million for a 3 bed, 2 bath home in Pac Heights.

I set up an old Mac Mini a month ago.

Why? Well, when I got on Twitter in February, I saw that some Austrian / British dude named “Peter” built an AI assistant that you can tell, through Whatsapp, to order pizzas for you. If you’re not careful, someone will prompt inject your OpenClaw and steal your social security number and the nudes your girlfriend sent you, but hey at least it can monitor your email for you. OpenAI “acquired” Peter (but not OpenClaw, which is a nonprofit foundation, similar to how OpenAI was originally, before it became a trillion-dollar, for-profit company. Because who the hell wants to be a non-profit when Masayoshi Son will shove $100 billion down your throat and speedrun WeWork again?) for about as much money as they paid to acquire a niche, but popular, daily tech show: hundreds of millions of dollars.

There’s this meme of “escaping the permanent underclass.”

That meme basically means you have about 18 months left (probably less, now) until AI gets so good that money, and really your entire existence, is rendered totally irrelevant. Which is a hysterical conclusion to draw from a “next token prediction” machine, regardless of how good it is at predicting tokens, but it seems like everyone in San Francisco believes it. Either A) you better get hired by an AI lab, or B) you better raise $100m for your startup and get acquired by an AI lab, by 2027, or… adios! Off to the token mines for you. Go make some human training slop to create marginal improvements for Opus 5.69 or whatever.

Of course, maybe there is some truth to the “permanent underclass.” At least in the engineering world. See, LLMs can’t replace most jobs, in my opinion. Most jobs have some level of nuance or friction, and LLMs are, really, word-and-number prediction machines. They’re quite good at these predictions, but, again, they’re kind of limited to screens. But coding? Well, coding is just a bunch of words and numbers, and it’s easily verifiable. The code either works, or it doesn’t. Give an AI enough context and a big enough context window, and it can build basically “any code.” And San Francisco, which was originally a gold rush city, has made a lot of people who knew how to code rich over the last 30 years. New platform comes out (computers, the internet, mobile), and the folks who could “use code” to build on that platform (Facebook, Airbnb, Uber) made a shitton of money. But now, “code” is commoditized. The biggest value prop in “tech,” being the guy who can build the digital money printing machine, went from a tightly held secret to accessible to anyone with a keyboard and 5th grade reading comprehension.

No wonder everyone in the Bay is so anxious.

Also, shout out to Stack Overflow for selling for $1.8 billion just one year before ChatGPT rendered it redundant. Talk about securing the bag. That feels like a microcosm of what’s happening in tech in general: get your bag before you get rug-pulled. And the timeline for securing that bag keeps shortening.

Anthropic now has a “Mythos” model that found several security holes in the Linux, and helped patch a 27-year-old bug in OpenBSD, an operating system, two years older than me (launched in 1995), known for its security. This thing is so powerful that Anthropic wouldn’t even launch it. They just tweeted about it, and said that 12 companies have access to it, and it’s too dangerous to release publicly right now because everyone and their mom could use Mythos to hack everyone else and everyone else’s moms. That’s pretty good marketing, to be fair. “Hey, we build AI God. It’s super scary. We’re telling you about it, but you can’t use it. Sorry!”

With Mythos, you could, hypothetically, say, “Hey Claude, steal all of _____ internal secrets. LOL what a good prank.” and it could probably do that?

The marginal value of the marginal software engineer is quickly plummeting to zero, and a small group of people and companies with GOATed models are operating on God-mode right now. It’s like a zero-sum race to extract the last amount of money left while money is still a thing.

Anyway, I moved back to New York two months ago. A couple of my buddies asked me, “Have you used Perplexity?” I went on a date with a girl who “worked in consulting,” and you would be shocked, SHOCKED, to learn that not once did she ask me about what harness my OpenClaw runs on. I think most of my friends are using ChatGPT at this point (?), a few know what “Claude” is, no one has touched a terminal, and the word “bash” sounds a bit like what a Neanderthal does with its club. I’d like to see Opus-4.6 split the G, or rip a Citibike across the Williamsburg bridge. I went to a Broadway show a few weeks ago. No AGI in sight.

What’s the point of this ramble?

The disconnect between the epicenter of AI (San Francisco, and. more broadly, a certain subsection of Twitter) and the rest of the world is just wild. The former truly believes we’re on the verge of a world-changing paradigm shift. The latter just doesn’t care. Perception doesn’t just shape reality; it is reality. And, really, I think both can be true. In a world that lives and dies by the power of bits, well, yeah, an automatic bit generator certainly changes everything, doesn’t it?

But in a world that just wants its Uber to arrive on time, (or, even better, a Waymo with no mystery man behind the wheel), which is most of the “real world,” by the way, some super-powered coding assistant is just, like, irrelevant. And that’s what’s funny about this whole AI boom: most people don’t care. And, hysterically, they don’t have to care. I mean, like, yes, they could, hypothetically, get a lot of leverage from all of this stuff. But does it “really” matter? I’m honestly not sure.

Again, I subscribe to the belief that AI can, and will, automate all code. “Coding” just becomes another form of writing. Some people will be prolific, others will suck, but everyone “can” do it. Or soon will be able to. Guess what? The invention of writing was pretty cool. We’re all just used to it now.

I don’t think “AI” will impact most other jobs, occupations, and sectors, nearly as much as “code generation” because there are too many edge cases. So, I guess, I see the world going something like this:

• The speed in which better and better software is released and updated will be astounding.

• 99% of people who have never written a line of code will never write a line of code.

• That 99% of people will benefit, as consumers, from cheaper code (competition drives prices to zero when anyone can generate code for no cost!) by having access to an ever-growing selection of impressive software. They might notice, “Oh wow, my apps don’t glitch as much,” but that’s about it.

• That 99% of people will remain totally unaware of the existential-levels of anxiety happening in the Bay, and they’re probably better off because of it.

On this last point: I feel the angst. I have, somewhat, sipped the “AGI kool-aid.” I panic-forced myself to figure out how to use Claude Code to build different stuff because. I thought it was going to be table stakes to “survive” as technology continues to accelerate. I’ve used Claude and ChatGPT and Grok and Perplexity and Wispr and Parallel and Exa and Manus and… you get the idea. I have a personal AI assistant named “Clank,” that I can talk to through Telegram, who can order pizzas for me or figure out who, in my rolodex, I should grab beers with next week.

And yet, all of my friends who have no idea what the hell a “Command Line Interface” is are making fine money living in their Manhattan shoe boxes, just like me.

There’s a tale of two worlds happening right now: a small subset of people speedrunning “AGI,” and then everyone else, who couldn’t care less. The former might make a lot of money, at least in the short-run. But the latter is probably having more fun.

Ignorance is bliss. Enjoy the permanent underclass, it’s fun down here.

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!

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Happy Monday, to those who celebrate. Last week was quite busy on the Slow Ventures front. We hosted an Etiquette School in NYC on Tuesday evening, then an “AI bots training school” for creators in San Francisco on Thursday and Friday. I also turned 29 last week. One more year until I’m officially washed. Okay let’s get into it.

Forward Deployed Hedge Fund Analysts:

An idea I’ve had for a while now is that market cycles move faster, and more violently, than in the past because information disseminates quicker than ever before thanks to X and Reddit. Online narratives around stocks are like crack cocaine for market reflexivity. LLMs have only accelerated that trend.

A good working model of the investing world in the age of AI is that any data that is publicly available will be instantly reflected in market participants’ models. “Crunching the numbers” isn’t edge when AI can both gather all publicly-available data and integrate that data in any and all relevant models instantaneously. Wire your computer to constantly parse EDGAR filings and tap into the X API for real-time coverage of relevant stocks, and AI can now process information far faster than was ever possible for humans.

In a world where AI can both gather and process all publicly available information instantly, the only “real” edges left are 1) access to hidden information and 2) discernment over what information should be discarded. On the second point: when you have unlimited tokens at your disposal, “analysis paralysis” is a greater threat than ever before. You can always look at “another thing,” even though any good investment comes down to 1 or 2 things that really matter. But that’s a topic for a later blog post; for now, I’d like to focus on point 1) hidden information.

In the private markets, hidden information means that you know a hot founder is raising for their new company before that becomes public knowledge. Either you know the founder directly, or a mutual friend makes an introduction, but you are granted “access” to that information before it became public knowledge, therefore positioning you to act on that information before everyone else. This has, of course, always been the way venture capital has worked, particularly at the seed stage. The only difference now is how quickly you can speedrun the “research” part of your diligence (mapping out competitors, understanding the technology itself, etc). Access + discernment are the only games in town.

In the public markets, hidden information is… a bit different. You, obviously, can’t coerce material nonpublic information (MNPI) from executives of public companies. That’s a great way to end up in prison. But you can, however, go find information that could be, but currently is not public. One way to find that information might be sending your analyst on a speedboat to the Strait of Hormuz.

Last week, investment research firm Citrini did just that…

And on Sunday evening, they published a “field trip” recap, both detailing the adventure in Oman (events include, but are not limited to, near arrests, in-person footage of ships on fire, and drones buzzing overhead their dingy) and providing actionable investment takeaways stemming from what their analyst saw in the Strait. (See below for the full piece):

Citrini Research

Strait of Hormuz: A Citrini Field Trip

Introduction…

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22 days ago · 503 likes · 23 comments · Citrini

I mentioned above that analysis paralysis is a real threat to the investment process with AI being able to ingest, well, everything. Combine that with the fact that AI slop is bombarding social channels left and right, and it becomes difficult to know what’s real, and what’s worth ingesting, in the first place. Over the last few weeks, for example, there’s been so much fake footage of bombings in the Middle East (either claiming the wrong location, or, quite literally, just AI-generated slop), that it’s impossible to sift through the noise. One way to know what’s real, then, is to see it first-hand. In an interview with Lex Fridman, Jeff Bezos said, “I have a saying, which is when the data and the anecdotes disagree, the anecdotes are usually right…” In a world with infinite data, anecdotes, such as eyewitness reports from an analyst that you send to Oman, can be quite valuable.

Citrini is a research publication that also trades its own book, and in this case, they did adjust their portfolio positioning based on what their analyst saw in the Strait, from tanker traffic to anecdotes from Omanis and Iranians he met sharing their thoughts on how they believed the conflict would play out.

While I don’t necessarily think every Tiger Cub is going to start sending analysts to Ukraine, I do think that as LLMs continue to commoditize the gathering and modeling of public information, more “journalistic” approaches to investing will drive more and more alpha. IRL investigation is also one of few things that AI won’t, at least for the foreseeable future, be able to disrupt.

OpenAI Buys TBPN:

Three weeks ago, OpenAI claimed that they were going to “cut back on side projects” and focus on nailing their core business; aka coding and enterprise. The reason? Anthropic started kicking their ass as of late, both in revenue growth rate and “vibes.”

In January 2025, OpenAI’s annualized revenue was $6 billion and Anthropic’s was $1 billion. By October 2025, OpenAI’s was $13 billion and Anthropic’s was $7 billion. By March? Anthropic had reached $19 billion in annualized revenue, closing in on OpenAI’s decelerating annualized revenue (~$25 billion in February).

Anthropic has taken a very, very focused approach to AI. For starters, they never released any video or image generation product. From 2023 through early 2025, their only “consumer” product was their chatbot, and they offered API access for their models to enterprise customers. Then, in February 2025, they released “Claude Code,” and it took the internet by storm. Claude Code was the first AI product that, for a lot of people, offered a glimpse into what “autonomous coding” could look like. By typing “claude” into your terminal, you could describe what you wanted in English (or Spanish, Japanese, whatever) to your computer, and it would just… build it. Early on, it made a lot of mistakes, and you had to regularly re-prompt it, but, still, it was magic. And it’s only gotten better. When models experienced a step function improvement in November, Claude Code got really, really good. Like, “spend 15 minutes brainstorming a task, tell it to go “cook,” and let it do its thing” good. By this point, OpenAI had countered with the launch of Codex (its version of Claude Code), but Claude Code had run away with the mindshare by 1) being first and 2) (more importantly) being consistent.

OpenAI, over the last 3.5 years, has launched ChatGPT (which has had its own ridiculous set of model names, from “mini” to “turbo” to “o1-preview” to “01-mini.” Like, seriously, who can keep up with these?), DALL-E (text-to-image), Sora (its now-cancelled text-to-video “social platform”, Codex (coding assistant), Frontier (agent-management platform), Atlas (browser), an unnamed consumer hardware device (they acquired Jony Ive’s startup for billions), custom chips, “adult mode”, and ChatGPT Health.

Anthropic had Claude and Claude Code. It turns out that developers will pay a lot of money to use Claude Code, so they doubled, tripled, and quadrupled down on Claude and Claude Code. Pretty much all of their product releases have just been improvements to these two tools: either integrating Claude into other platforms (Claude for Excel and Claude for Powerpoint) or adding new features to Claude Code (skills, plugins, Claude Cowork). Much easier to get the messaging right and win customer trust when you’re only selling a couple of things.

So it’s not a shocker that a few weeks ago, OpenAI’s “CEO of applications,” Fidji Simo, sent around a memo claiming the company would be cutting back on side projects. Then, two weeks later, they acquired daily tech show TBPN for ‘low hundreds of millions.’ The $100 million question on X last week was, “What did OpenAI actually buy?”

I love TBPN (which was basically Sportscenter for people who know what “reinforcement learning” is). I know John and Jordi fairly well, I’ve been on the show a couple of times myself, and they invented a novel, new media format that was expected to do ~$30 million top-line this year. Good for them for getting their bag; but there’s just no way, (regardless of what a lot of folks on Twitter are saying) that this was a “distribution” purchase.

This deal was likely on par with Joe Rogan’s latest Spotify deal, worth $250 million. Between Youtube and Spotify alone, Joe Rogan averages ~4 million+ views per episode. TBPN averaged something like ~70,000 viewers per episode across platforms. Sam Altman’s Twitter account, with 4.6m followers, has greater “distribution” than TBPN. So a 9-figure acquisition in the midst of a “no more side quests” command from management is.. interesting.

My $0.02? OpenAI’s vibes have been cooked for the last ~six months, they’re trying to push through an IPO by the end of the year while the market is increasingly skeptical of their valuation, and Jordi and John have the best marketing and comms chops in tech right now. Paying ~$200 million, when you were last valued at ~$850 billion (0.024% of your enterprise value) is actually a really low price to pay for a couple of guys who just might fix your brand perception, particularly when AI research talent is routinely getting acqui-hired for billions of dollars. And that’s the right framing to look at this from, by the way: talent acquisition, not “buying distribution” or “the future of media” or whatever.

Altman / OpenAI realize that they need to fix their public image ASAP in this ramp towards an IPO. Jordi and John both understand how to 1) capture the narrative and 2) charm OpenAI’s target market (tech investors, entrepreneurs, and developers). They also almost-certainly realized that, if they were to take a deal from OpenAI, Anthropic, or any other big tech platform, their credibility would be, at least slightly, tainted when they were critiquing AI platforms. Even if they are actually editorially independent, there will be an inherent level of audience skepticism toward their AI takes now that OpenAI owns them. To be “okay” with the opportunity cost of the drop in perceived independence (particularly when they were set to make ~$30m this year), it was going to take a big number, and OpenAI hit their ask.

Sure, paying a “forward revenue multiple” of ~7-10x 2026 revenue for a daily tech show sounds high, but this was never about the business. They’re winding down their ad business post-acquisition; OpenAI couldn’t care less about the ad revenue. This is about hiring the talent that they think could help them “control the narrative.” And $200 million is cheap if it increases your odds of a $1 trillion IPO.

Mercor’s Big Security Lapse:

AI models, like ChatGPT and Claude, train on data. Much of that initial training data was scraped from the internet. Blog posts, Github code bases, Youtube videos, tweets, etc. Most of that publicly available data has now been fully ingested and picked over. But AI labs can further improve their models through practices known as “supervised fine-tuning” and “reinforcement learning.” In the former, humans write high-quality responses to prompts to teach the AI “how to answer,” and in the latter, humans compare two model outputs and select the superior one.

AI labs need a supply of humans to provide these data-training tasks, and Mercor fills that gap. If you go on their website right now, you’ll see “find remote work opportunities.”

Those opportunities involve, essentially, creating workflows that mirror what you do in your job, and selling those workflows to AI labs via Mercor. For your efforts, you’ll earn anywhere from ~$50 to $150 per hour, or ~$500 to ~$1,000 per project. Put differently, you’re being paid to help train AI models to do your job.

(I don’t fall in the full dystopian camp that thinks AI will kill the labor market or whatever, and I think people are quite malleable, but the fact that AI labs are paying willing contractors hundreds of millions of dollars to help them train AI to do their jobs is a bit.. wild).

To land one of these opportunities, you take a recorded “AI interview,” your information is saved, and then you can apply for open positions on their site. Here’s a couple of example job listings for “audio and video technicians” and, hysterically, “basketball experts.”

Through this process of interviewing candidates and collecting their submission data, Mercor collected a massive data set on 10s of thousands of contractors, including personal identification information, videos of workflows, screenshots of their screens, and, obviously, videos of them interviewing and performing these tasks. This is, obviously, valuable training data, given that labs are paying millions of dollars to acquire it.

And last week, 4TB of data, including candidate profiles, PII, employer data, source code, API keys, video interviews, and customer data, ended up in the hands of Lapsus$ group (according to Lapsus$). The brief play-by-play:

• A month ago, a hacker group called TeamPCP exploited a misconfiguration in the GitHub actions workflow of Trivy, an open-source vulnerability scanner.

• They leveraged that hack to push a malicious Trivy version live.

• LiteLLM, an open-source Python library that routes API calls to different LLM providers, installed and ran Trivy, infecting LiteLLM and giving the hackers access to LiteLLMs publishing credentials.

• The hackers then pushed a malicious LiteLLM update. The malicious LiteLLM was live for ~40 minutes.

• Mercor uses LiteLLM to route data to different AI labs, so the hackers were able to steal Mercor’s credentials and access an alleged ~4TB of data.

• That data then ended up on other hacker group Lapsus$’s website, up for auction.

It’s not clear if this was the only data breach Mercor suffered (it would be difficult to steal ~4TB of data in ~40 minutes, though there’s no evidence of other exploits thus far). The result: 4TB of really valuable training data could very well have gotten leaked to whatever bad actor bid the most.

Woof.

The Mercor data has since been removed from Lapsus$’s site (I don’t know if that means Mercor cut a deal, they sold it to a 3rd party, or something else), but Mercor’s future now looks bleak: Meta paused its deals with the platform to investigate the breach, while other labs are also reevaluating their relationship with the platform.

The problem facing Mercor, now, isn’t just that they’ve lost customer trust. They product also just isn’t all-that defensible. Mercor offered a top-of-funnel for quality training data. Scale AI does the same thing. As does Surge AI. And probably several other companies whose names end in “AI.” Even if Mercor had, initially, been the “better” platform, exposing customer and contractor data to hacker groups is 100% grounds for reconsidering your data vendor, especially when there are similarly-positioned competitors ready to take your money right now. The result? I would not want to have been a Series C investor at $10 billion.

That being said, this does highlight a growing trend: AI both 1) makes hackers exponentially more proficient and 2) has made potential security breaches exponentially more common as former non-coders are now trying to build stuff (and have no idea how to handle security) and even experienced engineers are increasingly automating their outputs, introducing more surface areas for dangerous code. I think we’ll consider to see more and more hacks like this.

- Jack

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The date is April 3rd, 2029.

A few months ago, I moved back to San Francisco, as the effective tax rate in New York City has now reached 85%, with a billionaire tax becoming a centi-millionaire tax becoming a tax on anyone earning above $200,000. These taxes, of course, went to a good cause: every Friday evening, fearless leader Mamdani sends a Streeteasy push notification to residents of Bushwick, the East Village, Astoria, and the Lower Eastside to let them know if they won a $500/month refurbished 1BR apartment. I didn’t live in Bushwick, so I never made it in the raffle. Eventually, “Cheyenne,” from Park Slope, “won” my refurbished 1 BR apartment. My rent was $5,750. She got it for $500. I was evicted.

Whatever.

The only jobs left in the world are “datacenter technician,” “Waymo security guard,” “hot guy,” “funny guy (who desperately wants to be hot guy),” OpenAI serf, Anthropic serf, and the four freaks who pledged allegiance to Grok (though they seem to be having the most fun). Podcasters used to exist, too, until the AI labs bought all of them. Now, they’re just being milked for training data for GPT 0.o00-formerly-mini-now-normal-sized, or whatever the current model is called.

I was previously the 5th Grok freak, but I got RIF’d after Google started hoarding data center compute from Grok, so now I’m an Anthropic serf.

I call a Waymo to the office. While I wait, a crackhead stumbles up to me, screaming about the “prediction market for bum fights” that he vibe-coded on his flip phone. I guess on-device inference is now a thing.

One more job: active bum fight participant. We’re rebuilding the Colosseum from first principles.

I successfully avoid eye contact with the homeless man. He starts live streaming. “He must think he is ‘hot guy,’” I tell myself. I glance over: he’s actively replying to the AI-generated OnlyFans accounts in his comments. AI psychosis: confirmed. I open the door to my Waymo. My Spotify used to sync when I got in the car, but there hasn’t been a new song released since 2027. By anyone. So now Suno connects. Gemini must have told it that I was Googling “ski trips early 2030,” because it starts playing AI-generated Christmas carols.

Whatever.

I get to the office, pledge allegiance to the flag of Effective Altruism, and say good morning to the head of database energy trading, Sam Bankman-Fried, who was pardoned by President Trump on the eve of his third election thanks to Bankman-Fried’s 53,592nd tweet calling Donald Trump “the coolest guy ever.”

I then sit in front of 4 monitors, open 16 total Claude Code instances, and say, “Okay, Claude. Build a $5 billion company. Make no mistakes.” Then I take a nap. Hard morning of prompting. When I wake up, I head to the gym. Marina Equinox. It’s packed, because, again, “hot person” is one of the only jobs left. I make my way upstairs, to a squat rack, where I open my camera, take a picture of the rack, and DM my OpenClaw on Telegram and say, “hit 5x5 on back squats.” Then I repeat this process at the pull up bar. And the rowing machine. And the kettle bell station. My workout agent vibe-burned 700 calories. Great.

I grab a protein smoothie. Back to the office.

I say hello to Sam Bankman-Fried again. He has, since I last saw him, removed his shoes. I go back to my desk to see if my Claude instances have finished one-shotting a $5 billion company. I see a message waiting for me: “Does Claude have permission to make edits to the chosen file?”

“Not great,” I think to myself. I forgot to “approve” his actions before I left.

I reply, “Yes, you are good to proceed.” Claude replied, “Sorry, but you’re been fired for lack of agency with your vibe-coding. I was idle for 7 hours.” I forgot to mention, Claude is also my boss. Claude just fired me and immediately hired a new human. Tough love.

I walk out of the office and head to the Tenderloin. Now, I too am part of the permanent underclass. Because my human capital score was dinged immediately after Claude fired me (Claude built an API into the “capital score” network in 2027 to promote “altruism”), I’m now job-less and homeless.

I call a roundtrip Waymo from San Francisco down to San Jose and back. I plan to sleep in the Waymo while it’s traversing the Bay Area. I sprawl out in the back seat and log into Twitter.

Garry Tan just finished typing 457,000 lines of code in the last 24 hours. Both OpenAI and Anthropic have replaced their personal coding architecture with “gStack.” I’m pretty sure gStack fired me. Whatever.

My laptop dies, so I download claude to my Waymo’s TV screen instead and tell it to build a ~$1 billion company (less ambitious than my previous idea for a $5b company). By the end of the roundtrip ride, my claude has vibe-coded 27 new “companies,” none of which have even a semblance of consumer demand.

My Waymo kicks me out. Apparently I’m out of Gemini token credits. We’re in the Tenderloin. Welcome to the permanent underclass.

I see the homeless guy from earlier. I squint. He wasn’t homeless. It was Jack Dorsey. He keeps murmuring “bum fight markets. bum fight markets. bum fight markets.” I glance at his phone screen: portfolio value up by $17 million on bum fights markets. The guy is a savant. I put my last $25 on Dorsey’s prediction market platform. It’s connected to Hyperliquid. I take on 10,000x leverage. “To Valhalla, or to my death,” I think.

My fighter, wearing a faded and backwards Yankees hat, one shots the competition. Deal: over. I made $250,000. I immediately wire half of that into an SPV claiming to build “AI for dogs.” Seems like a good market. I lease a new apartment in The Marina. My credit score has improved since winning my fight bet, so I call another Waymo to take me there, and I Doordash an inflatable bed, too. As I arrive at the destination, a drone airdrops a bed mattress at the foot of my new apartment. I walk inside, put it on the floor, and fall right asleep. No headboards needed in the permanent underclass.

- Jack

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Brief Introduction:

Is the obvious thing “priced in”?

On February 28th, the United States and Israel launched a surprise attack against Iran, killing Supreme Leader Ali Khamenei and several other Iranian military officials. Iran retaliated by launching missile and drone strikes across the Middle East, targeting sites across Israel, as well as US military sites and other infrastructure sites, including data centers, across Bahrain, UAE, Kuwait, Qatar, Saudi Arabia, Oman, Jordan, and Iraq. Lebanon and Yemen have since attacked Israel in retaliation as well.

In the last month, thousands of people have been killed in the Middle East, with the majority of casualties coming from Iran, and Iran has effectively created a toll booth in the Strait of Hormuz, blocking transit for any US and Israeli vessels (as well as allied vessels). ~20 commercial ships have been hit in the last month, and shipping traffic has dropped from ~138 vessels per day to 2-6 (or at least 2-6 vessels using automatic identification systems).

20% of the world’s oil production goes through the Strait of Hormuz, and I don’t think it was a crazy extrapolation to think that, once the US and Israel decided to “Leroy Jenkins” the Supreme Leader of Iran and half of his cabinet, that Iran might retaliate with strikes against US assets in the Middle East and, in general, cause chaos in global energy markets. After all, if your country is going to shit, why not wreak havoc on the rest of the world on the way out? So, now, data centers and hotels are being quickscoped by rockets and drones, the Strait of Hormuz is an IRL game of battleship, and the speaker of Iran’s parliament is tweeting out macro-trading strategies for futures markets.

(An aside: X is still dominating “real-time conversations” for anything that matters, from geopolitical game theory to financial market mayhem. Congrats, Elon Musk).

If, on a Saturday, you assassinate the leadership of a country that controls the body of water through which 20% of the world’s oil moves, then you’d probably expect futures markets that Sunday to melt down in anticipation of global trade being thrown into a tailspin, or, at least the possibility of said tailspin.

And oil futures did, initially, spike on March 1, with the price of Brent crude (global benchmark) jumping from ~$70 to ~$80 a barrel. But, still, markets weren’t pricing in Armageddon.

And the S&P 500 remained basically unchanged from the previous week.

Some would say the war was “priced in.”

There’s a funny “priced in manifesto” that originated on r/Wallstreetbets six years ago that basically claimed that, yes, “everything is priced in.”

Don’t even ask the question. The answer is yes, it’s priced in. Think Amazon will beat the next earnings? That’s already been priced in. You work at the drive thru for Mickey D’s and found out that the burgers are made of human meat? Priced in. You think insiders don’t already know that? The market is an all powerful, all encompassing being that knows the very inner workings of your subconscious before you were even born. Your very existence was priced in decades ago when the market was valuing Standard Oil’s expected future earnings based on population growth that would lead to your birth, what age you would get a car, how many times you would drive your car every week, how many times you take the bus/train, etc. Anything you can think of has already been priced in, even the things you aren’t thinking of. You have no original thoughts. Your consciousness is just an illusion, a product of the omniscent market. Free will is a myth. The market sees all, knows all and will be there from the beginning of time until the end of the universe (the market has already priced in the heat death of the universe). So please, before you make a post on wsb asking whether AAPL has priced in earpods 11 sales or whatever, know that it has already been priced in and don’t ask such a dumb fucking question again.

The TLDR of this is there’s “no real alpha” in anything because the price of a particular stock or security perfectly reflects all available information about that stock or security, and markets are efficient, etc. I’ve never really thought that markets were all that efficient given that every single week we’re confronted with new evidence that markets are not, in fact, efficient.

A few somewhat recent examples:

• SaaS stocks didn’t start selling off in earnest due to the threat of AI until mid-January of this year, two months after Opus 4.5, the first model that felt like it could truly “one-shot” tasks in Claude Code, came out in November 2025.

• Fundrise Innovation Fund, LLC (ticker: VCX), a “public venture fund” with stakes in Anthropic, Databricks, OpenAI, Anduril, Ramp, SpaceX, and other hot startups, traded at ~30x above NAV a week after hitting the public markets.

• Google being viewed as an “AI loser,” flat from Jan 2024 to April 2025, and then doubling once the market realized that, no, ChatGPT is not “winning” search, the Gemini models are fantastic, and Google is the only AI player who controls its own infrastructure stack.

• Or how about the pandemic: Reports of Covid were coming out in December 2019, and it was a “known thing” globally by February 2020. The market continued to climb until mid-February of 2020.

Recent history shows that markets are, in fact, not efficient. I actually think they’re becoming less efficient. So anyway, back to Iran.

The US and Israel kill a lot of people in Iran and throw the country into chaos. Iran responds as one would expect: by breaking everything in the region. And then, finally, a week later, oil spiked above $100 a barrel. But it took another two weeks for the S&P to really start sliding on a catalyst that, presumably, emerged a couple of weeks earlier.

I think the markets have grown accustomed to the “TACO,” or “Trump Always Chickens Out” trade. When you threaten countries with tariffs as a negotiating tactic, it’s fairly straightforward to pull out once you get what you want (like if they pledge to buy more natural gas from you). When war breaks out, it takes two to TACO. And Iran has thus far (at least publicly) shut down any peace talks.

It just took the markets a couple of weeks to realize that, yes, this war will likely be prolonged, and this oil supply chain disruption could cause inflation, which could lead to rate hikes when we were instead pricing in “rate cuts,” which could… you get the idea.

I have no idea what will happen next. No one does. But sometimes the simple thesis is the right thesis. If you saw the news of the Iran strikes on February 28th, and then on March 2nd thought to yourself, “Hmmm, shouldn’t oil be higher given that… 20% of the world’s oil supply is cut off?" and then went long oil, you would have been up ~50% despite being a day “late” to the trade. Not particularly priced in, was it?

How much would you pay for Anthropic stock?

In 2012, brothers Ben and Dan Miller launched Fundrise, a crowdfunding platform for real estate investments, giving retail investors the opportunity to investment in real estate projects with as little as $100. A decade later, in an expansion beyond just real estate, they launched a “Fundrise Innovation Fund,” through which they planned to “democratize access to investments in “top private technology companies.” A year after the fund’s launch, they had invested $100m+ into companies including OpenAI, Anthropic, Databricks, Canva, ServiceTitan, and Vanta.

Last summer, Fundrise filed to list this fund publicly, which would basically create a publicly traded “fund” with positions in high-flying AI startups. It would also, importantly, create a permanent liquidity window for any investors who wanted to sell their stakes. For the three years that this fund was private, Fundrise capped quarterly liquidity tender offer requests at 5% of NAV (though the average request rate was sub-5%; in Q4 2025, only 1.5% of investors requested redemptions). With a public vehicle, fund investors could sell on the public markets to whoever they wanted whenever they wanted. And, unlike the quarterly redemptions, which were done at NAV, public markets could trade at premiums or discounts to NAV. The one catch with this listing: most investors would be bound to a 6-month lockup period.

At the time of the proxy filing, the fund had 28,346,610 shares eligible to vote for the conversion, and its NAV was ~$600 million, pricing the fund at ~$21 per share. Investors who invested before February 20, 2026 would have a six-month lockup. Investors who did not want to carry their positions into the six-month lockup could participate in one final tender offer at NAV on February 28th. This also meant that anyone who bought after February 20th but before the listing went through could have purchased shares at NAV (~$21 per share) and then sold at… whatever price the markets set the shares once they were listed.

So, the conversion gets approved, and now you have a situation where most of the shares (likely > 90%) are locked up in a fund that owns Anthropic, OpenAI, and SpaceX: the hottest private companies in the world. This trade went about as you’d expect: after opening at ~$31 per share (50% above NAV) with 90%+ of the float locked up, the stock proceeded to climb from $76 on the 19th, to $105 on the 20th. Then we had a weekend where, presumably, more retail investors discovered the fund, and by the following Wednesday, VCX was trading at ~$575, or ~30x NAV. Basically “valuing” Anthropic at ~$15 trillion.

I remembered seeing this on the 20th and thinking, “Hmmm, that’s a crazy pop,” just to watch in disbelief as it 5x’d again from there the following week, but low float + meme stock is one hell of a combination. But the craziest thing is that you could have (and someone probably did!) buy private shares at NAV after the February 20th cutoff for the lockup, allowing them to flip their shares, risk-free, for a cool ~20x markup: ~$20 to $400 per share. To anyone who pulled this off: 1) kudos to you. To everyone else: how’s that for an “efficient market hypothesis”?

Perplexity Computer is Surprisingly Great

I’ve tried my best to stay on top of “the current thing” with AI tools over the last year or so (should I publish a longer piece on everything I’m using in AI now?), but one tool I initially loved, then hated, but now love again is Perplexity Computer. For context: Perplexity was one of the hotter AI tools deemed to be a possible “Google killer” a few years ago. They were the first mainstream “AI search” tool built on top of other models from AI labs like OpenAI and Anthropic, and their product was neat in 2023 and early 2024. But as the AI labs rolled out their own internal “deep research” products, it looked like Perplexity was going to quickly get commoditized.

Combine that with Perplexity’s increasingly-ridiculous “M&A proposals,” like attempting to “buy” Chrome…

Artificial intelligence startup Perplexity AI has made an unsolicited $34.5 billion bid for Google’s Chrome browser, CNBC confirmed on Tuesday.

That figure is higher than Perplexity’s current valuation, but the company said several investors have agreed to back the deal. In July, Perplexity was valued at $18 billion as part of an extension that valued the company at $14 billion months earlier.

and TikTok…

Perplexity AI officially made a play for TikTok on Saturday, submitting a bid to its parent company, ByteDance, to create a new merged entity combining Perplexity, TikTok U.S. and new capital partners, CNBC has learned.

The new structure would allow for most of ByteDance’s existing investors to retain their equity stakes and would bring more video to Perplexity, according to a source familiar with the situation, who asked to remain anonymous due to the confidential nature of the potential deal.

Despite having nowhere-near enough capital to afford either of those purchases, and I wrote the company off as a joke. And then they launched Perplexity Computer. And it… rocks.

I’m a big Claude Code guy. I need to build stuff with code, it just does it. And it’s gotten better and better. It can work with local files, Github files, whatever. Last week, I was trying to revamp a separate personal website, in which I wanted to add a chronological list of links to everything I’ve written online to share in one page. Claude could not, for the life of it, check the URLs for all of my Substack posts, validate their title names and dates, and update the Github repo where I’m hosting that website. Perplexity Computer, on one prompt, managed to work around Substack and Cloudflare’s bot blocker, deduce all of the correct titles and publishing dates, and add them, with working hyperlinks, to my website, in ~20 minutes with no errors. For whatever reason, I find it much more capable than Claude when working directly with Github repos, + it can “build” anything you’d build with Claude Code or Codex in a digital server and let you download the code.

While some functionalities are still needed, like local file access, it’s really, really good for cranking out work in Github repos. No idea if they’ll justify their valuation, but the computer tool is just wonderful.

Content, Recs, Other Notes:

• Fun April 2025 blog from Andrej Karpathy on his experience vibe-coding a menu visualization tool for fancy restaurants.

• Logan Bartlett and the Redpoint team put together a great deck on the state of SaaS + AI startups. Very good read for those interested.

• TBPN hosted a live debate between “pharma bro” Martin Shkreli and Superpower founder and peptide maximalist Max Marchione. I think Shkreli is a wizard and generally fantastic Twitter follow and love watching him cook folks in debate format.

• We’re hosting Slow Ventures Etiquette School 2.0 in NYC tomorrow night; if you’re a founder and want to learn about cologne, caviar, and not falling in love with your AI chatbot, come hang.

• We’re also hosting an AI bootcamp for creators in San Francisco next week. If you’re a writer/Youtuber/podcaster/whatever that wants to up your AI game, pull up.

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!

I spent the last ~two years writing Young Money, and I couldn’t be more excited to share it with you all. Below, I’ve included a brief excerpt to describe who I wrote this book for and why. You can pre-order your copy at Amazon, Audible, Barnes & Noble, Bookshop.org, Books-A-Million, Apple Books, and anywhere else you find your books today.

“Uncertainty.” The default state of one’s post-college twenties can be summed up in one word: “uncertainty.” Where should I live? What should I do for work? Should I marry my girlfriend? Should I break up with my boyfriend? Should I quit my job? I have no idea what I’m doing with my life.

Compound these questions, and more, with the realization that this stage of your life is quickly slipping away as your social media feeds are bombarded with engagement rings, pregnancy announcements, home purchases, and promotions, and it’s no surprise that everyone feels like they’re falling behind. But falling behind what? Your twenties are painfully short. Graduate college, blink, and you’re thirty-three, wondering where the last decade went. It’s quite important, then, to make the most of this stage of life before it’s gone.

But how should you approach this stage of life to make the most of it? As a current twenty-eight-year-old (and previous twenty-two-through-twenty-seven-year-old), I’ve spent my fair share of time wrestling with the more pressing questions of postcollege existence. While I’m not naive enough to think I can tell you, dear reader, what you should do with your life, I do have a few thoughts that just might help you figure out how you should be spending your time.

This book is really a letter to my twenty-three-year-old self, detailing the experiences he would have over the next few years and unpacking the uncertainties of a young person’s personal and professional journey through their twenties. It’s less so a “what you should do with your life” and more of a “given what you’re going to encounter, here’s how to best think through this phase of life” book. If you have your shit together and everything is perfect and your life hasn’t sniffed an ounce of self-doubt in years, then this book probably isn’t for you. Or maybe it is for you if you want to know how the rest of us live. But if you, like me, have spent a significant amount of your youth asking yourself, Why am I doing this? What should I be doing? Everything just feels so uncertain. Well, this book might be for you.

You can pre-order your copy at Amazon, Audible, Barnes & Noble, Bookshop.org, Books-A-Million, Apple Books, and anywhere else you find your books, today.

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Hello there, and happy Monday to those who celebrate.

I am, to the best of my abilities, trying to work back into writing this thing weekly. Beyond the fact that 1) I enjoy writing and 2) this newsletter is probably the most valuable asset I have to my name, Young Money serves as a good forcing function for me to put my thoughts on the world around me into writing. Plus, “AI brain” is 100% a thing (I’ve felt it!) and I do think regular writing is more important now than ever before as forced cognitive exercise.

I’ve also done a bit of thinking on the format here, and I do think the “right” setup is a mix of riffs on my life + my thoughts on whatever tech/market/investing trends seem most relevant, since that is 1) what I’m interested in and 2) where I spend most of my time working / reading. So let’s get started.

A few thoughts on the internet, serendipity, etc.

I’ve written this newsletter for, something like, five years now. I think I put out my first piece in June 2021 explaining how it was structurally impossible for bitcoin to simultaneously be an “inflation hedge” and a “currency.” I was right, but didn’t matter. It turned out to be a fantastic risk asset despite it still sucking as a medium of exchange. Whatever. Anyway, I’ve written like a million words since then, and downstream of those words have been a fantastic stream of new connections and friendships. Yapping on the internet, it turns out, is a really good way to attract people you’d probably like hanging out with.

Yesterday I hung out with a new internet connection-turned IRL friend Pilar Brito. She’s an attorney-turned wine creator (IG here, Substack here) turned startup operator who just moved to NYC. We ended up drinking wine at Fedora for like 3 hours. Great place; highly recommend. Pilar is also one of our panelists at Slow Ventures’ Etiquette School in NYC next Tuesday (more on this at the bottom of the newsletter) where she’ll be discussing everything you didn’t need to know about wine. We met through some combination of my newsletter, the Etiquette School we hosted in San Francisco last fall, and a bunch of the Creator stuff we’ve been doing at Slow; it was a fresh reminder that, yes, putting yourself out there online is such a ridiculous serendipity machine and I should get back into it. Also, orange wine is great. But more on that next Tuesday at Etiquette School.

Okay, some thoughts on private credit:

Private Credit / AI Doom Loop:

Blue Owl is an “alternative asset manager” that manages ~$307 billion, with ~$158 billion going toward private credit, and $115 billion of that in direct lending. You know how you can go borrow money from the bank to buy a house (aka a mortgage)? Well, Blue Owl, among other things, similarly lends money to companies, and Blue Owl makes money by charging their investors somewhere between 1.25% and 1.50% on their AUM, + incentive fees in the form of a slice of the net interest income generated from their loans.

When you make money from fees, your revenue jumps with your AUM. Blue Owl’s AUM at the end of 2022 was $138 billion. Its revenue was ~$1.4 billion. Blue Owl’s AUM at the end of 2025 was $307 billion. Its revenue for 2025 was ~$2.9 billion. Wall Street, for a couple of years, rewarded this AUM and revenue growth with a soaring stock price as Blue Owl’s market cap cruised from ~$15 billion to ~$40 billion from November 2022 to January 2025.

Then the stock collapsed, now back down to a ~$14 billion market cap since peaking early last year.

What happened? Investors are losing trust in private credits’ “marks.” Again, private credit funds primarily make money by charging fees on their AUM. To make more money, they want to grow assets, which means loaning more money to more companies. But if the value of those loans declines? Then so do fees and profits for the firm.

You may have heard of Claude Code. It’s pretty cool; you can just tell your computer, in English, to build some software, and it can, with some guiding, do it. Random things I’ve built with Claude Code in the last year or so:

• A personal assistant, named “Clank,” that I chat with through Telegram who can edit Github repos, access and navigate my rolodex, make phone calls for me, email folks, etc.

• A few different personal organizational tools that consolidate and summarize meeting transcripts, email threads, etc.

• An automated newsletter digest podcast that takes newsletters I flag as “podcast material” and transcribes the content to audio format, then publishes a private podcast for me to listen to any interesting newsletters I lack time to read.

• An automated email translation tool that translates any newsletters I forward to a specific email address into Spanish, then sends them back to me.

Coding assistants last summer sucked. They “worked,” but needed to be hand-held to build anything even remotely useful. In December, around the time Anthropic and OpenAI released their new models, coding assistants suddenly became “good.” Like, you give it a task, go cook dinner, come back, and you have a fully-functioning web app good. A lot of investors worry now, for good reason, that a lot of software companies might be a lot less valuable than they were six months ago.

Some software only exists to give humans a good interface through which they can interact with their data. AI tools don’t need “interfaces” to interact with data; they just need APIs. And with the costs of software creation (or, at least, code generation) plummeting to zero, there’s a real possibility that some previously-bought software tools can now be created internally. I don’t buy the argument that anyone is going to “vibecode a Salesforce” any time soon, but even the possibility of building an alternative to parts of your internal software stack hurts the pricing power of software vendors. Pre-AI coding assistant, you might expect to hike your prices by ~5% a year because of course you can. That’s just how pricing increases worked. But now? You have to work a lot harder to maintain customers who think they could, with some effort, build their own replacement if they’re feeling overcharged.

So now what? You, the software vendor, might make less money. Your margins compress. Maybe a creditor had loaned you $100m in 2023 when your EBITDA was $20m and you looked poised for rocket ship growth, but now your customers think they can vibe code half of your functionality and they’re considering cancelling their contracts. You offer them a big discount to stay on platform, but the contract drops from $500,000 to $425,000 in a year that you had otherwise expected to charge $525,000. This happens to a lot of customers. Suddenly that $20m in 2023 EBITDA is $14m in 2026. Interest coverage is getting hairier. The assumptions you made in 2023 got blown up by Claude, and now those loans are worth as much as you thought they were. The market wants higher yield for that risk, and the value of those loans declines. If the value of your loans declines, your AUM declines, you make less in fees.

That stock price collapse? It’s the market saying it doesn’t trust a lot of these private credit marks anymore.

Blue Owl has several funds, including an unlisted (private) Blue Owl Capital Corporation II (OBDC II) and a publicly-traded Blue Owl Capital Corporation (OBDC). OBDC II had a cap on quarterly redemptions set at 5% of NAV; throughout 2025, they kept hitting that cap as investors wanted to get out. Blue Owl thought it had a solution to give more investors liquidity: merge the private fund with their publicly-traded OBDC, giving the OBDC II investors 1:1 shares in the public entity for their shares in the private fund. There was just one issue: while the shares of OBDC II were still supposedly worth around their par value, the public vehicle was trading at a 20% discount to its NAV, meaning the market didn’t think the loans were worth what Blue Owl said they were worth. Had the merger gone through, the investors in the private fund would have likely taken a 20% markdown on their investments as well. Investors, were, obviously, pissed. No one wants a 20% markdown.

Blue Owl instead sold $1.4 billion worth of loans, including $600 million from OBDC II, to raise cash to return capital to their investors at close to par value. Very nice of them. It doesn’t fix the core issue that, while they’re returning capital at “par” in the near-term, the market doesn’t trust their marks now, and some other investors don’t either:

Boaz Weinstein’s Saba Capital offered to buy investors’ stakes in OBDC II at a 20-35% discount to NAV for any investors who want liquidity. TLDR: the market increasingly doesn’t think these private credit loans are “worth” what the funds claim they’re worth. You can say your NAV is whatever you want, but the price of anything is only what someone else will pay for it.

Blue Owl isn’t the only private credit lender with growing pains, either. Last week, Nick Nemeth wrote a great piece calling for increased transparency on private equity and private credit valuations, calling out private credit fund Cliffwater for almost-certainly mis-stating its loan book. Unreported payment-in-kind (PIK) loans (meaning that, instead of paying back interest in cash, interest is “paid” by accruing more debt on the principal of the loan), marking up loan valuations when the rest of the loan market fell on Liberation Day, claiming a 41-month win streak despite all of the volatility in the lending market in the last year. It’s just basically impossible that Cliffwater’s loans are worth what they claim they’re worth.

Fine. Whatever. Private credit is “overly optimistic” about some of their loans, and maybe they’ll take some haircuts on those loans as their borrowers lose customers who vibe-coded their SaaS solutions instead of renewing contracts. Who cares that a few MDs lose out on their carry checks because their funds underperform? Well, the irony here is that the same folks dishing out private credit loans to SaaS sellers are financing the datacenter buildout that’s fueling the AI models that are threatening to kill the same SaaS apps they also lended to.

Guess who partnered with Meta on its ~$27 billion “Project Hyperion” datacenter buildout in Louisiana? Blue Owl, the same fund whose stock has collapsed over the last year. Blue Owl created an SPV called “Beignet Investor LCC” (which is, objectively, a hilarious name for a Louisana-based datacenter project) through which it raised $27.30 billion (on top of $2.45 billion in equity contributions itself) to finance this datacenter buildout. Meta is contributing the other ~20% of costs. Cool. Meta’s free cash flow is now projected to go “negative” in 2027 and 2028 due to the cash they’re pouring into the AI buildout.

Okay, let’s play this forward a bit.

Frontier AI models cost an insane amount of money to train (hence OpenAI, Anthropic, and xAI raising hundreds of billions of dollars to capture and/or maintain their leads). Data centers cost an insane amount of money to build. Private credit is a big source of financing for datacenter construction. Frontier AI models are (allegedly) killing a lot of SaaS companies with their expensive-but-ever-improving models. Private credit lent hundreds of billions of dollars to SaaS companies under the assumption that their EBITDA and revenue were, in fact, stable.

The existential risk facing the big AI companies is that either 1) they can’t secure financing to pay for GPUs or 2) they can’t secure the compute itself needed to train models. That compute constraint is alleviated through datacenter construction. Datacenter construction requires funding, and a big source of that lending is now coming under pressure as the market is stress testing the “value” of private credit funds’ books. Throw in a not-crazy possibility of an interest rate hike due to inflation (thank you, war in the Middle East!) that could further hinder refinancing opportunities on these struggling software loans, and, well, we’re in an interesting spot.

I’m not calling for the imminent collapse of the AI industrial complex, but it is more than ironic for me that AI seems, in 2026, to be primarily displacing 1) the very people who built it (software engineers) and 2) the very parties who are funding it (private credit).

Welcome Back, Trevor Milton

GOATed fraudster Trevor Milton parlayed his political pardon into a new gig as the CEO of Utah-based SyberJet Aircraft. If you don’t remember, Milton took his hydrogen-powered truck startup, Nikola, public through a SPAC in 2020. At one point, it was worth more than Ford despite never producing a functioning truck (though they had some sick rendered images!). It later turned out the the whole thing was a house of cards, with Hindenburg research publishing a scathing short report that, among other things, showed that video of the “battery-powered” truck was actually only gravity-powered: “live” footage was really just the truck rolling down the hill with the camera rotated.

Anyway, Milton went to prison for securities and wire fraud after, among other things, getting busted misleading investors, but then he was pardoned by Trump after, among other things, playing up “political victim” as much as possible and donating a few million to the Trump campaign. (This is a great move, by the way. Sam Bankman-Fried has been trying to tweet his way into a pardon for months).

And now Milton runs a plane manufacturer. Look, on one hand, I think it’s not great that someone who lied about a truck’s motor actually functioning is now running an aircraft manufacturer with the goal of creating “the first light jet to focus on artificial-intelligence flight” (like what does that even mean?) But also, I respect the balls it takes to lie your way to a $40 billion market capitalization for a vaporware truck company, so why not run it back? Would I ride in the plane? No. Would I buy the stock? If history is any indicator, probably.

Good Content:

• Fun, nine-year-old piece from Byrne Hobart on how he accidentally became an entrepreneur before accidentally working for a hedge fund.

• Wild deep dive piece claiming that SOC-2 compliance startup Delve has been running a fake business. A couple of thoughts: 1) if true, this validates my thesis that all of these “street interview” videos are a grift, and 2) Forbes 30 under 30 has another fallen angel.

• Really fun interview with Travis Kalanick discussing his new company + thoughts from Uber on TBPN. This dude rocks.

• Excellent conversation between Hubspot founder/Sequoia partner Brian Halligan and OpenDoor’s new CEO Kaz Nejatian.

Other Notes, Thoughts, Riffs:

• Etiquette School in NYC: Last November, after noticing the disconnect between Silicon Valley’s venture-backed abundance of financial capital and lack of social etiquette, We (Slow Ventures) hosted an “Etiquette Finishing School,” (TechCrunch coverage here) in which we had three hours of panel discussions covering everything from how to dress to how to eat your caviar. The event was a real hit, so now we’re running it back next Tuesday in New York City! Signup link is here; we have a few slots left and we’re prioritizing RSVPs from NYC-based founders. If you’re around, sign up and come hang.

• Creator AI bootcamp in SF: Another Slow Ventures plug: we’re also hosting a “Creator AI Bootcamp & Hackathon” in San Francisco next Thursday and Friday. For any creators (Youtubers, Substackers, whatever) reading this that have been wanting to up their artificial intelligence game, we’re hosting a two-day bootcamp teaching you everything from proper set up / tool usage to actual workflows for automating the boring stuff. If you’re interesting, RSVP here.

• Ever since buying / building this bookshelf from Ikea a couple of months ago, my rate of purchasing physical books instead of Kindle has exploded. Highly recommend.

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!

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Change is in the air, or so it seems.

Over the last three weeks, I’ve had more conversations with friends and acquaintances who are “considering different career moves” than I’d had in the last year up to that point. Part of this is, as it always has been, structural.

I’m 28 and coming up on two years out of business school, which means most of my peers are ~5-8 years into their careers, and my former classmates are now ~2 years into their “post-business-school” paths.

For the business school folks, it’s pretty common to recruit for some version of banking/consulting/private equity/whatever, knowing you’re signing up for a two year role where it’s either “up or out.” You work really hard to get that job, and the assumption is, likely, that around 12-18 months into the job, you will have a feel for 1) if you want to be up or if you want to be out, and 2) if “up” is even a possibility based on your performance and the likelihood of room/mobility at higher levels.

The issue, when you reach that 12-18 month point, is that, unless you are all-in on your current thing, you’re probably having second thoughts. “I could make VP, but should I? Is that the right move?” And that uncertainty yields anxiety.

Many of my non-business-school but otherwise ambitious-and-successful friends are having similar thoughts? “What comes next?” “What comes next?” “What comes next?”

The late-20s-to-early-30s window is primed for anxiety and uncertainty because it’s where clearly-marked paths evaporate. You can either commit to climbing an increasingly exclusive, difficult, but lucrative ladder that you’re currently on, or take a leap and try something new. But there’s no blueprint for “new.” The current ladder offers stronger visibility into your expected compensation and status. “New” might mean that you have to upskill in areas that are currently unfamiliar. It almost certainly means reduced “guaranteed” compensation in exchange for higher hypothetical upside. But most of us in the land of “white collar” labor spend our formative years optimizing for the “de-risked” option. The issue, once you’re 5-10 years into your career, is that the “de-risked” option quietly stops being the “de-risked” option as the definition of risk shifts.

At 22, the “risk” of not landing a premier job can mean a slower career trajectory and lower earnings. For all of the shit that “investment banking” gets, anyone who can land a job at Goldman out of undergrad almost-certainly should take it. You’ll make more money than you would anywhere else, and you also get a stamp of approval that screams “I’m competent.” Legible competency is quite useful in life (why else would I have gone to business school? It’s a $200,000 stamp of competency).

But that risk curve shifts if you spend too long on any particular path. Once you’ve stacked a few pedigree stamps (good schools, jobs, etc), the greater risk, I think, is failing to leverage that pedigree to explore new opportunities. The “risk,” if you don’t make a change, is that you find yourself investing 70+ hours a week into climbing an increasingly-narrow ladder, where burnout, fatigue, and career stagnation are real, while the folks who took a differentiated path at, say, 26, probably suffered a short-term compensation and status regression, but compounding then kicked in, and by 30, they were likely running laps around the hypothetical version of themselves that never deviated.

And the longer you stay on current path, the harder it is to deviate from current path, because inertia kicks in. Uncertainty is uncomfortable but not paralyzing in your 20s, but if you spend a decade doing one specific thing, and particularly if that “thing” is a well-defined, well-trodden career path, you’ll find yourself unable to begin conceptualizing what “something new” might look like. If you spend too long optimizing for certainty, your risk perception becomes fried.

The most important traits, I think, are 1) the ability to learn new skills, and 2) the confidence in your ability to learn new skills. Malleability is one of the only competitive advantages with staying power. Especially with AI blowing up the traditional model of how pretty much the entire white collar economy works.

And AI is blowing up the traditional model of how pretty much the entire white collar economy works. If your job has consisted of some version of “move things around on a computer,” it’s in the process of being totally commoditized, whether or not you realize it.

There was, basically since the invention of computers, some version of a “stable career path” that went something like this: earn your stripes doing the BS “analyst / junior” tasks for a few years, slowly take on more responsibility, and, eventually, you can become “the guy.” That path is disappearing, or, at least, certainly changing shape. At the company level, pure-play software businesses that offer specific point solutions are around a year away from being commoditized by AI model providers. At an individual level, much of the “work” of most junior-level white collar jobs can be “done” by AI now, and, more importantly, one junior employee who has actually been curious enough to figure out how to use Claude Code, or Codex, or Gemini, or Cursor, now has the leverage to handle the work loads of a team of 4 juniors previously. That’s the real shift: I don’t think AI “kills” all white collar work, but it does enable much leaner teams, which changes organizational structures and career paths.

I’ll give a more specific example from my workflows:

I now have my email, calendar, and Granola notes synced to Claude to 1) maintain project folders with full context on any startups I’m looking at so I can instantly query any information relevant to any particular deal, and 2) have AI send me an automated email each day recapping all meetings and laying out existing “to-do’s.” It’s still not perfect, but it probably saves me a cumulative 10+ hours per week of “looking for stuff.” If I spend a full weekend really going deep on current capabilities, I can probably double my time saved on “admin-ish” tasks. All of that freed up time means I can meet with more founders, or spend more time in deep research on different market sectors. AI, used well, creates leverage. And companies know this.

Goldman Sachs is trying automate back office and internal functions with AI wherever possible. Anthropic built Claude Cowork in ~10 days, and the whole thing was “built” by Claude Code.

Leverage. Leverage. Leverage.

Ever-improving AI models with ever-increasing context are going to be able to “do” anything on a computer, and I think that most people’s ideas of AI still being “chatbot that hallucinates” stem from lack of experience with what’s out there today. This stuff is nuts, and coding assistants are the leading indicator of what’s to come everywhere else. All software can be, and, at Anthropic, who I think is “winning” the AI game, is, written by AI today. That’s only going to accelerate.

A year from now, Claude for Excel is going to be able to ingest any source materials you provide it and spit out a model showing whatever you want, however you want, in minutes. You’ll be able to link your bank account, credit card statements, and pay stubs, and have AI spit out your taxes for 2026. Legal contract review will be totally commoditized.

This isn’t to say that every “business” is a zero, but most businesses are heavily bloated in a world where AI can operate increasingly autonomously. Tokens are cheaper than new hires, particularly when you don’t have to “train” the AI on anything. You just say, “Do thing,” and it does it.

Even if all “developments” in AI models stopped tomorrow, their current abilities are powerful enough to permanently reshape what labor markets look like as they continue to penetrate the economy. The world, quite literally, can’t keep pace with the speed of improvements in models, and it’s only accelerating.

Back to the career stuff.

Whatever model of the “professional” world that you had three years ago is almost-certainly outdated. Simply put, many ladders that were impervious over the last ~50 years have either been pulled up or disappeared entirely, and many of the things that did work will no longer work because things that used to be valued have now been commoditized. Pattern-matching off the prestige of the 2010s, or even early 2020s, is no longer a high-signal decision making process when considering “what you should do?” It’s not that the prior paths were Thanos-snapped out of existence overnight, but previous headcount needs in what were otherwise unassailable roles/paths/positions have just been greatly reduced.

And yet, at the same time, this massive wave of change brings with it opportunity. Littlefinger was right; chaos is a ladder.

So, what comes next?

I would say that there’s two ways to play the next few years. Both of which involve getting comfortable with the uncomfortable, particularly with leveraging AI. The first is that you become proficient with whatever AI offers, apply it to the existing world, and put yourself in a position to run laps around everyone else who is otherwise either failing to appreciate this shift or is too paralyzed to take advantage of it. AI doesn’t just give companies leverage to hire fewer employees, it gives employees leverage to have an outsized impact. You want to be the employee who has the leverage. LLMs are performance-enhancing drugs for people who use Excel and VSCode. Like a baseball player in the 90s, you’re crazy if you’re not using them to up your game.

The other opportunity is identifying which versions of the world are “outdated,” and molding yourself to the shape of what you believe comes next. This could mean starting your own company. It could mean pitching yourself as an “AI-first” version of a role within an organization that may not have previously existed. Either way, the only things that matter are identifying what got commoditized, avoiding putting yourself on a track headed for commoditization, and identifying how to best position yourself where the puck is going.

Ironically, the skills that were most valuable even a few years ago, i.e. playing the “career game,” are likely outdated now. Particularly when consulting firms face pricing pressure, investment banks are rapidly automating work, the time to make partner in big law keeps getting extended, and the music stopped for “easy money” in PE when interest rates were hiked.

Independent thought and curiosity now trade at a premium when the previous ravine-like gap between “idea” and “execution” has been reduced to a few inches. I don’t buy the narrative that “everything is cooked” because AI is getting really good, but I do think that the days of speed-running an existing status game to successfully are in their twilight phase.

Put differently, you can no longer expect any particular job to “save you” of the task of figuring out what to do with your life. 20 years ago, you could outsource your sense of agency to whatever your alumni network was doing and probably make a lot of money along the way. I’m not so sure that’s true any more with how fast everything’s changing. But, conversely, it’s never been more possible to dive headfirst into something new. You just need the wherewithal to identify where those opportunities might be, and the willingness to explore them.

My personal opinion? The rapid re-organization of all things “status” is probably a good thing. At least now we can stress about achieving our own goals rather than those bestowed upon us by others.

Anyway, happy Thursday.

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!

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Happy Tuesday to those who celebrate. Getting back in the habit of making this a weekly column of sorts again, digging into the more interesting stories I see in tech/markets/culture over the preceding week. In today’s letter:

• X investors are set to get paid thanks to Elon’s latest financial engineering.

• Fake quantum companies have valuable stock.

• Murray Hill Guy broke dating app Twitter.

• Other assorted links.

Elon Musk = Financial Engineering King

Grab a stick of chalk and write this over, and over, and over again on a blackboard:

“Never bet against Elon Musk. Never bet against Elon Musk. Never bet against Elon Musk.”

Last night, The Information reported that Elon Musk’s SpaceX is acquiring Elon Musk’s xAI (which had previously acquired Elon Musk’s X), for $250 billion in a deal that would value the combined entity at $1.25 trillion dollars. The result: Musk’s rockets, satellites, social media platform, and AI lab are now all one business (and, importantly, investors in any of those entities now own shares in SpaceX) as the launch company is gearing up for an IPO in what will likely be a meme stock of epic proportions.

SpaceX investors and employees are getting paid, xAI investors and employees are getting paid, and the seven X engineers who weren’t fired when Musk cut 80% of the company’s headcount are, somehow, now going to receive rocketship IPO dollars for their previously overpriced, underwater equity in a dying social media company.

God bless Elon Musk’s financial engineering.

This deal (and the deals preceding it) was, of course, possible because Musk is the majority/controlling shareholder of SpaceX (where he owns 42% of the company), xAI, and X. The farfetched theory of “how this all works” is that we’re going to need a lot more compute as AI demand continues to explode, AI data centers in space will become a thing, combining xAI with SpaceX puts all of that infrastructure in one house, and xAI’s models should have a data advantage thanks to the constant stream of real-time training data from user-generated content on X. The more cynical but (in my humble opinion) more likely theory is that this is a “thank you” from Musk to the investors who were willing to back his overpriced purchase of a dumpster fire social media network.

There is a narrative, now, that Elon Musk “saved democracy” buy purchasing Twitter for $44 billion. There might be some layer of truth to this narrative, but Musk also tried as hard as possible to get out of buying Twitter. In April 2022, when Twitter was publicly traded, he signed a definitive agreement to buy it for $44 billion, or $54,20 per share. This was a stupid price to pay for a terrible business, especially when the tech market collapsed over the next six months.

For context on how bad the tech market was in 2022, the market cap of Meta, which is currently worth ~$2 trillion, collapsed from $1 trillion in December 2021 to below $250 billion in October 2022 (xAI, which didn’t even exist in Q4 2022, is now worth $250 billion), and Nvidia, which is now worth $4.5 trillion, fell from $800 billion to $300 billion. Twitter, by any conceivable metric, was “worth” maybe ~$15 billion at the time.

But Musk had top-ticked a bid in April that he was legally bound to. In May and June of 2022, he tried to bail on the acquisition, claiming Twitter hadn’t properly disclosed the percentage of “bot” accounts, before ultimately terminating the acquisition agreement in July due to a “material breach” for failing to provide adequate information on spam bots (in total, Musk tried to bail on the deal 3x).

Twitter sued Musk for bailing, the courts were leaning toward ruling in favor of Twitter, the social media platform rejected Musk’s reduced offers to buy it for $31b and $40b, and Musk ultimately reversed course and went through with his initial $44 billion offer. It’s not terribly uncommon for shareholders to sue to avoid an acquisition, but it is very, very rare for a company to sue to be acquired. But everyone, especially Musk, knew the business of Twitter was a dumpster fire not worth $44 billion. If the goal of a CEO is to create shareholder value for their business, Parag Agrawal certainly did his job when Musk paid 3x more than it was “worth.”

Musk contributed $27 billion in cash (primarily raised through selling Tesla stock), outside investors (Larry Ellison, Sequoia, a16z, Fidelity, Saudi Prince Alwaleed bin Talal, and others) invested $7.1 billion, and banks committed $13 billion in debt financing, which no one else wanted, so it was stuck on their books for a couple of years. By September 2024, Fidelity had slashed its internal valuation of its X stake by 72%, marking it down from $54.20 per share to $15, or a ~12 billion valuation, and its debt was trading well below par value.

23 months after the Twitter purchase, it was a bad investment.

However, Musk rewarded the folks who backed his Twitter purchase by giving them preferential access to invest in xAI in 2023, before outright “buying” X with xAI in March 2025 for around the same price he initially bought Twitter for in 2022 ($45 billion enterprise value, $33 billion equity), making investors whole + giving them even more access to xAI. Basically, anyone who invested in Twitter in 2022 got their money back for their X investments in the form of xAI stock at a ~$113 billion combined valuation, along with access to make earlier investments in xAI. With the SpaceX / xAI deal valuing the AI platform at $250 billion, those investors’ stakes more than doubled in just ~10 months.

TLDR: if you invested in Twitter, the real-time news media platform that never figured out how to make money, you now own shares in a trillion-dollar rocket ship company preparing for its IPO.

If your deal memo for investing in Twitter at a $44 billion valuation included “return to growth,” “better operational discipline,” or “stronger margins due to more efficient ad targeting,” you would have been sorely disappointed as advertisers fled the platform and X’s revenue collapsed. But if your deal memo for investing in Twitter at a $44 billion valuation said “Who cares, it’s Elon?” You were right, and you’ll triple your money when SpaceX IPOs this year. A big congrats to Morgan Stanley, who’s been making billions in deal fees on these restructurings and acquisitions.

I’m so curious if anyone managed to buy a secondary stake in X when Fidelity was marking down their valuation? If so, have fun being rich.

Fake Quantum Company Buys Real Actual Company

From April 2020 to ~August 2021, I spent every waking moment trading “SPAC warrants.” I tell this story a lot, so I’m not going to fully re-hash it, but the TLDR is that when I was 23, I was pretty good at trading this weird market bubble, to the tune of ~6,000% returns in less than a year. Then too many people raised SPACs, there wasn’t enough money to go around, I started trading microcap stocks instead, and I lost 3x my salary at the time in like ~7 minutes on a bad earnings print. So I stopped trading stocks after that. You can read that full story here, if you’re interested. It’s pretty funny.

Anyway, the reason I bring this up is that, while most of these former SPACs have since gone bankrupt or been acquired by private equity firms for pennies on the dollar, some are still kicking in the public markets! For example, DraftKings is trading ~3x from when it announced a deal to go public in late 2019. Not bad.

Generally, a few “real” companies have survived or thrived since 2020/2021, but all of the pure hype companies, like Nikola Motors and a slew of failed EV “manufacturers,” have gone bust.

And then there’s IONQ.

IONQ is an American quantum computer hardware and software company founded by a couple of Duke professors back in 2015. The TLDR is that the two academics wrote a research paper called Scaling the Ion Trap Quantum Processor, venture capital fund New Enterprise Associates gave them $2 million to commercialize the technology proposed in their paper, and two years later they raised another $20 million (from Google + New Enterprise Associates). They then hired an Amazon exec to expand their commercialization efforts, they signed partnerships with Amazon Web Services, Microsoft Azure, and Google Cloud to make quantum computers available to the public.

I am not going to waste your time by explaining the intricacies of quantum computing other than to say that quantum computing is (theoretically) good at doing a small subset of tasks incredibly quickly under extremely precise environmental conditions that may or may not have any mainstream economic viability at any point in the future (for more on this, see Martin Shkreli’s essay on why quantum is stupid, or why several specific quantum stocks, including IONQ, are overvalued).

In 2020, IONQ had no revenue, it was burning ~$16 million a year, it had ~$36 million cash on its balance sheet, and it was forecasting net losses until 2025. IONQ was going to need more money in the next year.

And then the SPAC boom took off.

IONQ was a fantastic SPAC merger target in 2020 because investors were throwing money at any and every buzz word, particularly “electric vehicle,” “solar,” “space,” “gambling,” “lidar,” and “quantum.” So IONQ signed a deal to go public through a SPAC called dMY III that would value the business at ~$2b ($1.4b excluding cash). The original investor deck, which is still available here, projected $60m in 2024 revenue and $237m in 2025 revenue.

Five years later, IONQ has sharply missed those projections: it only generated $68m in revenue through the first nine months of 2025. A normal business, under similar circumstances, would likely have collapsed from its $10 per share, $2 billion market cap.

IONQ is trading at $39 a share at a $13.6 billion market capitalization. Why? Because “quantum.”

See, you can be totally “right” about your negative outlook on the present value of a company based on its lackluster commercial opportunities, but if the median buyer of that stock doesn’t actually understand how quantum works, and that median buyer comes in volume, then it doesn’t matter if the business is stupid. They like the stock because it’s “quantum,” and they buy it because “quantum,” even though they don’t know what “quantum” is. En masse, the stock will go up.

Example: Shkreli asks stock market influencer Shay Boloor, “Tell me what algorithm can you run on these quantum computers that is useful?” Influencer proceeds to… ramble.

But it doesn’t matter. With the right investor base, bad company becomes good stock and IONQ is now worth ~$14 billion despite not really doing anything.

What gets interesting is that when your stock price pumps really high, it becomes an asset that can be used smaller companies that are real. So, last week, fake company IONQ bought real company SkyWater Technology for ~$1.8 billion.

SkyWater Technology is a US-based semiconductor foundry (think TSMC or Intel) that has carved out a niche manufacturing semiconductors for quantum computing companies. It did $150 million in revenue last quarter and $350 million in revenue over the last year (it’s a real company).

If you are IONQ, and retail invested have pumped your business to a $14 billion valuation, and suddenly, you’re worth 7x more than a potential supplier despite making ~25% of its revenue, the optimal move is to issue more of your overvalued stock to buy “real” businesses that impact your cost structure. The irony here is that, by doing that, IONQ does make itself more valuable, despite initially being ridiculously overvalued, because it now owns a real foundry making real chips. So I guess the optimal capital allocation strategy, if you’re the CEO of a company that’s trading like a meme stock, is take full advantage of your cheap equity to buy real businesses before the market realizes you’re fake. If you’re lucky, those acquisitions could prove to make you the real company the market is already pricing you as.

Murray Hill Guy Broke Twitter

There is this account on Twitter (X) called “Murray Hill Guy.” There’s a dozen or so “guys” named after different neighborhoods on Twitter. East Village Guy. Mid Thirties Manhattan Guy. There was a West Village Guy, but he moved to DC and changed his handle. I personally love the network of folks using anonymous Twitter accounts to hide from their employers while they shitpost online.

Any way, for those of you not in New York, Murray Hill is the stereotypical “22-24-year-old fresh out of school” neighborhood, and the guy running the “Murray Hill Guy” Twitter account has become one of the main characters on the internet for providing nonstop dating discourse commentary. He’s been doxxed a few times now after different girls caught him sharing Hinge screenshots on Twitter, and apparently he’s a 5’9 ~30-ish-year-old dude who hits the gym a lot. I used to hate him. Now I love him. His content is hysterical. Highly recommend a follow.

Anyway, he made a new Hinge using a girl friend’s pictures to see what the female experience on dating apps is like, and documented the whole thing on Twitter for the world to see. The girl whose pictures he used is, objectively, pretty, but not like Margot Robbie super model level.

He (She?) hit something like 1,000 likes in a less than a day. There was some good humor here, like him sending a dozen guys to The Spaniard on Thursday, but it was unironically a pretty good social experiment of just how poor the structure of dating apps actually is, especially for dudes. The odds of your like even being seen, let alone responded to, are next to none simply due to the volume game you’re competing in. If it’s a peak traffic time, you’ll be buried so far down the backlog it’s practically hopeless.

Considering that fertility rates are declining and girls complain that guys “won’t approach them” any more, might I suggest ditching the apps and instead hitting… a bar? Gym class? Maybe church? (I went for the first time in I don’t know how long last weekend).

What I’m Reading / Consuming

• Interesting article by Amelia Miller in the Free Press considering what the world would be like if men and women had matching fertility windows; AKA: what if men had to get vasectomies around the age that women typically begin struggling with fertility concerns. In the insurance and pension industries, the risk of mismatched duration between assets and liabilities is real. For example: if you buy a bunch of long-dated bonds, then rates spike and your bonds drop in value at the same time that a cash outflow is due, and you don’t have enough liquid/short-term assets to cover the cost, you’ll have to sell your other bonds at a loss to make the payment. The issue was duration mismatch: the assets were longer-dated than the pension liabilities. Male/female fertility windows aren’t all that different: men’s windows are longer-dated than women’s, creating a mismatch in the market where one party has to “commit” earlier than the other, biologically speaking. No, I don’t think we should mandate vasectomies, but as a 28-year-old dude who hasn’t thought all that much about “fertility” for myself, it’s an interesting thought experiment.

• In case you missed it over the weekend, an “AI-agent-first social app,” Moltbook, went live. A few weeks ago, a software called OpenClaw that gives AI agents full access to everything on their users’ computers went viral, and thousands of folks ordered new Mac Minis to test out their AI system agent. Then someone made a Reddit-like forum, Moltbook, for the agents to hang out in. Naturally, screenshots went viral all over Twitter of AI agents “plotting” to overthrow humans (all of the mass-hysteria screenshots were almost-certainly just humans prompting their AI bots to act in a certain way), but now it seems like people are already moving on. However, while “Moltbook” might not be a permanent thing, this phenomenon of AI agents having full access to all of your memories (through your texts, photos, emails, etc), and being able to interact with other AI agents is… weird. Very likely we see some versions of new consumer apps (think about how dialed a dating app would be if it had access to all of your data?) as all of the information we have becomes additional context.

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!

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Apologies for the lack of writing the last week or two. Normally, weekends are for writing, but for the last two weeks I was running all over Manhattan touring apartments, ordering furniture, etc. The good news: I found a sick spot near Union Square, and that spot now has a bed, bedside table, desk, chair, unbuilt Ikea bookshelf (Ikea sent me a lot of wood planks but no screws, classic), a computer monitor, and a lot of kitchen stuff. Still very much a work in progress, but I got some writing done yesterday which was nice.

Claude does Excel

Over the summer, I spent a lot of time messing around with Claude Code and Cursor. The reasons for that were three-fold:

1. If you’re investing in early-stage startups, knowing the current capabilities of large language models is table stakes. Coding assistants were the most developed LLM “products” that had seen skyrocketing adoption, it would be ignorant not to test them out myself.

2. AI coding assistants had made simple software creation and computer data manipulation accessible to someone “nontechnical” like myself for the first time in history.

3. I thought there was real career risk to not knowing how to use these tools, and, similarly, real career advantages in getting up to speed quickly.

The first thing I built, in Cursor, was a rolodex that consolidated all of my contacts across Twitter, Linkedin, phone contacts, and email. I had no idea what I was doing, initially. I had never used API keys or even written a simple python script, so it took hours for me to get used to the Cursor’s IDE interface. But, after a weekend of hacking away and troubleshooting with ChatGPT, it worked. I still use that rolodex.

The second thing I built, with Claude Code, was a translation tool allowing me to forward any newsletter/blog to “translate@translatemynewsletter.com” and receive a Spanish translation of that newsletter in my inbox a few moments later.

The UX, particularly for someone who had not previously coded, wasn’t great in June 2025, especially with Claude Code, because I had to access it through my computer terminal. But it worked. And coding assistants have only continued to improve; to the point that employees at the big AI labs aren’t even “writing” code anymore. AI can just do it.

Why is AI so good at coding, and why was coding the first real “enterprise” use case that took off? At risk of grossly oversimplifying this whole thing, it’s because there were virtually unlimited troves of coding data to train models on, and code has objective “right” and “wrong” structures. Miss a parenthesis in a python script, and it won’t run. Get the structure right, it runs. Train on billions (trillions?) of examples of code, and suddenly AI can write code quite well. Humans stopped writing code in 2025. Yes, sure, it takes time for this trend to flow through the full economy, but coding assistants are the worst they’ll ever be, and they’re actually quite good.

My thought, at the time, was “What comes next?” meaning what other computer-based workflows have billions of examples of “correct” and “incorrect” scripts that can be verified formulaically, have millions (or more) of users, and subject users to tedious time-sucks as they seek to get these formulas correct. Financial modeling (and Excel use, more broadly) was the next low-hanging fruit. The real issue wasn’t technical capabilities. Microsoft’s Office Javascript API has been around for a while, Claude’s API went live in ~2023, and Anthropic added tool calling functions in 2023 and 2024, so you could have “built” this functionality a year or two ago. But the product wasn’t there yet. Coding assistants blew up so quickly because 1) there was a lot of training data and 2) a “right” and “wrong” state of code, but also because the UX just didn’t matter as much. Accessing Claude Code through the terminal wouldn’t have intimidated a software developer because… they were used to that interface. But (and this is ignoring compliance issues) no second-year JPMorgan IB associate is going to tie together the APIs needed to build an automated financial modeling tool. The tech was already there, the product wasn’t. But now? A chat window within Excel opens on the right side of the screen, and you can ask Claude to manipulate, analyze, and create anything you want directly in Excel.

A few months ago, I would go back and worth with ChatGPT on figuring out the right Excel formulas to do XYZ thing. I would upload screenshots of spreadsheets, it would give me a formula, I would paste it, it might work, and we would iterate until it was done. It “worked,” but the process was clunky. Now? The AI can just iterate directly in Excel in real time.

For example, I uploaded a sample Series A Pro Forma and gave Claude the following prompt:

“Create a waterfall showing how the funds will be distributed on a $50 million exit, assuming 1x non-participating liquidation preferences from all VCs. Generate your graphic in Cell J25 and work right / down from there.”

After ~10 back and forth messages to tweak formatting, remove hardcoded cells/only reference cells in the model, etc, it spit out the following waterfall analysis. The whole thing took about four minutes.

This is, obviously, a simple example, but it still cut a ~25-30 minute task down to ~4 minutes, and actually freed up more time to spot check that the right cells were referenced, inputs weren’t hard-coded, etc. Basically, you can get to a testable final product much, much faster.

The value of “modeling skills,” at least defined as the “ability to do Excel fast,” drops to zero when you can ask AI to build a fully-fleshed out version of the thing faster than a human can type, taking out the “value” of a lot of entry-level white collar labor (IB analysts, consultants, etc) as well, at least as the work is currently done. This also, by the way, probably kills a lot of the “AI for Excel / AI for finance” startups that popped up over the last few years, particularly as Claude continues to integrate with data providers. One of my banker buddies thought the same:

My next question is what are the other “financial modeling” or “coding” pursuits that have 1) logic that must be followed to generate outputs and 2) a lot of training data to pull from? Protein synthesis? Something else? Idk. But this is only going to happen faster and faster.

What I’m Reading / Consuming

• Fun thread from a Wharton professor on Claude’s Excel plug-in vs. Microsoft’s own Excel agent.

• Fun blog about OffDeal, the “AI-native investment bank.” I love these stories of entrepreneurs taking an existing business model and leveraging AI to apply it to markets where it previously wasn’t possible. In this case, using AI to build an investment bank that targets small ($1-$10m EBITDA) businesses as a sell-side advisory firm.

• Good clip of Tim Ferriss on Shawn Ryan’s podcast discussing audience capture and the widespread grift of “motivation” influencers who have built audiences telling people how to “do the thing” without ever doing anything meaningful themselves.

• My buddy Jon Goodman’s new book, Unhinged Habits, goes live tomorrow and I’m excited to dig in. Jon is one of the more interesting individuals that I’ve met (he’s a multi-time founder and author, and he lives most of the year abroad traveling with his wife and kids). I don’t read too many “life advice-y” books, but Jon has very much “walked the walk,” so I’m pumped to check out his new work.

• Tim Clissold’s Mr. China is a fantastic memoire for anyone interested in what “investing in China” actually looked like back in the 1990s when the Chinese economy started to take off. Tim partnered with a few investors to raise and deploy hundreds of millions of dollars in China on the thesis that you could mint some pretty profits by providing capital to businesses in a country poised for a GDP explosion. His account of the absurdities he encountered all over the country, from scams and grifts to just pure confusion in rural desert factories, is just excellent.

- Jack

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Hello from Geneva, Switzerland. I spent the last week skiing with a few friends in Val Thorens, France before heading back to the grind tomorrow morning (though, I guess it is now tomorrow morning, as I wrote this on Sunday). This has been the most travel-intense holiday season of my life. It’s certainly been fun (bachelor party + Indian wedding + holidays with family + ski trip with friends is a jam-packed, but very enjoyable, way to spend ~3 weeks), but I’m more than ready for a little routine again.

A brief review of Val Thorens: Over the last three years, I’ve taken an annual ski trip with a group of friends from New York, and, typically, we’ve headed to Colorado. However, we realized that it’s actually cheaper to ski the Alps (particularly if you don’t have an Ikon / Epic pass), even inclusive of international flights and currency exchange rates, so this year, we headed west. I skied in Europe a couple of times in business school with ~150 of my closest friends ( every business school trope you have is true), which made me the de facto trip planner for our European ski trip in 2026.

The biggest differences between skiing in Europe vs. the states:

• Europe is much, much cheaper. Lift tickets were $50-$60 a day, vs. ~$200+ in Aspen or Jackson. This alone offsets any potential flight cost differences if you ski 3+ days.

• If you don’t pull down the safety bar on your chair lift, the lift operators will freak out on you and pause the lift until you lower the bar.

• While they take chairlift operating quite seriously (there’s literally security cameras at the lift stations that will trigger an alarm if you don’t lower your bar immediately upon sitting), basically zero parts of the mountain are roped off. Want to ski off-piste? Do your thing. If you ski off a cliff, that’s on you.

• The après scene just isn’t comparable. In the states, you might grab a couple of beers in the village at the end of the day. On some slopes in France, you can throw down a full rave on the mountain before skiing back after sunset.

On this particular trip, the snow quality wasn’t great; Val Thorens almost got dumped on a few days before our arrival, but the storm just missed our destination, so it was a pretty icy outing. When I skied here two years ago, we carved up the whole mountain thanks to some fresh powder. This time around, we played Where’s Waldo? trying to find any routes with a bit of non-icy snow, with mixed results. That being said, all in all a successful trip. My only wipe out was when a French man hit an ice patch near the bottom of a run, which led to him yelling, in an impossibly French accent, “Sorry! Sorry! Sorry!” as he plowed into my right thigh as I was cutting right to head to a gondola. Solid form tackle, but no real damage. On the first run of the day, one of my buddies also lost control on an icy run and ran face first into a (padded) ski lift pole. He’s sporting a smart black eye, but, again, nothing that a few (several) Guinnesses couldn’t heal.

Also, another one of my buddies (who lives in Atlanta), who is now dating a German girl (who lives in Cologne) that he met at a hostel in Southeast Asia, happened to be skiing in Val Thorens with his new boo this week, which led to a nice impromptu reunion.

Anyway, 8/10 trip. Would have been 10/10 with better snow, but would do again. Most of my crew, who is flying KLM through Amsterdam, had their flights home delayed by a day (or two), which just sounds horrible. Air France has never failed me, so after a 4 hour stop in Paris, I’ll be back at JFK, then back in my bed, then back to the white collar labor force.

I hope you had a relaxing and/or fun holiday season. Let’s create some shareholder value in 2026.

Ideas I’m Thinking About:

What does the world look like when my kids don’t have to drive?

One of the more popular arguments in the tech world right now is, “who’s going to win the driverless war?” With pundits chiming in on Tesla, or Waymo, or perhaps Uber as a facilitator of a few different platforms that all offer driverless solutions. I neither know nor care which particular player is going to win, but it’s increasingly obvious to me that 1) “driver-less” is the superior form of car transportation for most passengers, and 2) it will almost-certainly be the de facto mode of road transit in the near-future. A few thoughts on why:

If you’ve never ridden in a Waymo, it is a life-changing experience. This isn’t hyperbole; when I visited San Francisco for the first time in December 2024, I ordered a Waymo from my hotel to the other side of town to check it out, and the ride was, quite literally, magical. My Spotify connected to the car’s sound system, and I watched, in awe, from the back seat as the steering wheel turned left and right with no operator assistance, and my car avoided jay-walking pedestrians, adjusted to sudden brake-checks from other vehicles, And maneuvered a four-point turn navigate a narrow alley, en route to my destination. Once I moved to San Francisco, Waymos became my default form of transportation as much as possible. Why? A few reasons. First, they were cost-competitive with Ubers and Lyfts. Obviously, if a Waymo cost $40, and an Uber cost $12, I would err toward the latter. But when they’re cost competitive, I’m taking the Waymo every time, because it minimizes randomness. Every time you order an Uber/Lyft, you face a few degrees of uncertainty. The car might smell like stale cigarettes or old food. The driver occasionally has their partner or friend in the front seat, and, if you have a group of ~4 passengers, they can’t accommodate you. Some human drivers are erratic behind the wheel, or they might text and drive. And, candidly, there are moments where I just want 20 minutes of peace without having to worry about small talk with another human.

When I’m in a Waymo, the car is always clean, I’m free to take phone calls (or even Zoom calls!) without having to worry who’s listening since I’m by myself, and all risks/uncertainty related to human behavior disappear. It’s just better. What’s shocking wasn’t how much better Waymos were than Ubers, but how seamless my adoption was: within a week of moving to San Francisco, I would check Waymo prices / times before opening other ride sharing apps. And judging from driverless growth rates, I’m not the only passenger who feels this way.

Tesla recently broke 7 billion full self-driving miles (up from 1.3 billion miles in April 2024), and monthly miles traveled in driverless taxis in California has jumped from ~200,000 miles in September 2023 to ~4.75 million in September 2025.

A few days ago, someone completed the first coast-to-coast autonomous car ride, proving that the whole length of the country is surmountable via driverless car, and Waymo is now active in 10 cities (Phoenix, LA, SF, Austin, Atlanta, Miami, Dallas, Houston, San Antonio, and Orlando) and growing, meaning that coverage gaps for driverless vehicles will, at some point, be a non-factor.

The question I have is “what comes next?”

Some immediate thoughts:

Suburban living becomes immediately more appealing for white collar city employees because driverless vehicles turn the commute into a viable work window. You obviously can’t “work” while driving, and even on public transit, you face logistic issues such as taking calls in public spaces, but when I’m in my little four-wheeled bubble of solidarity, I can get real work done. I’ve taken Waymo’s to my boss’s house in the suburbs from my apartment in San Francisco, and I could easily get my full “beginning of day” routine done in the car (check emails, update legal on deal documents, look through a company’s data room, etc.) in the ~hour ride with no interruption. If your commute is a viable part of your workday, you are far-less geographically limited on where you live.

Chicks leaving bars/clubs will never use cars with drivers again. Particularly at night, girls always face a risk that guys don’t: they have to be on their guard against creepy men. Every month, there’s a new horror story about a woman getting kidnapped / harassed / assaulted by a bad actor driver; driverless cars remove a risk category that has existed as long as cars have. If you’re presented with two similarly-priced options, but the first has a 0.001% chance of something really bad happening, and the second that has a 0% chance of something bad happening, you will obviously take the second, no?

Parking-related real estate becomes less relevant. Right now, driverless cars still face a supply issue that leads to long wait times. For example, I played in a basketball league in south San Francisco, about 25 minutes from my apartment via car. If the wait time for a Waymo was 20 minutes, I would opt to drive and look for parking upon arrival. Wait times are the primary friction point in areas where Waymo is active. But with a sufficient supply of driverless cars in a given geography that reduced wait times to, say, 3 minutes or less, a lot of current drivers would gladly opt to take a driverless cab. Driverless cars can continually operate until they need to be recharged / refueled, meaning that you move toward a world with less stationary vehicles taking up space near their owners’ locations, and therefore you need less parking spaces in general.

The rate limiter for long-haul rides becomes a vehicle’s battery: Driving is a fairly tiring activity, but presumably, I could, right now, take a self-driving car from San Francisco to Los Angeles and spend the entirely of the ride reading, writing, working, building a B2B SaaS slop application, etc, only interrupting the trip to 1) hit the restroom or 2) recharge / refuel the vehicle. For any medium-length trip in which you don’t want to deal with the hassle of airports, car rides in which you don’t have to drive become a legitimate alternative.

And rental cars are cooked? Whenever I head back to Georgia for the holidays, I typically rent a car from Hertz at the Atlanta airport before driving down to Tifton, Georgia to see my dad / dad’s side of the family for a few days, then I drove to Birmingham, Alabama to see my mom / mom’s side of the family, before returning to Atlanta to fly out. Those drives suck. Atlanta to Tifton is ~three hours, and there is almost always traffic. Tifton to Birmingham is ~five hours. Birmingham to Atlanta is ~two hours. And you have to worry about refueling the car. And not getting in a wreck. And what insurance do you want on your rental. And… you get the idea. The whole rental car process just sucks. If I could just call a Waymo to pick me up from each geography and take me to the next one, I would never rent a vehicle again. In five to ten years, this is almost-certainly a reality.

I guess my follow up follow up question is what commercial opportunities are there in a world where everyone is renting their robo-car instead of driving themselves? The obvious 101 answers are charging infrastructure and cleaning facilities to support growing autonomous fleets, but I’m open to any and all 201 thoughts.

What I’m Reading / Consuming

• On Becoming “Legible to Capital” - Will Manidis wrote an interesting essay about the role that being “legible to capital” plays in firms’ successes that I think is particularly true in private markets. The thesis is effectively that any idea sufficiently legible to capital (which, in this case, can mean intellectual, social, and financial) develops a gravitational pull of its own in which it sucks in all of these forms of capital as they seek to play a role in enabling this idea/person/firm’s success. “Story” plays a role in legibility in that people have to care about your thing, or the story of what your thing will become, to be attracted to it. But “story,” in this case, isn’t marketing as much as it is a prophecy of the direction of the world and the role that you’ll play in it. “Legible to capital,” then, really just means a collective belief that you’ll be a winner in a particular arc of history, and those sources of capital want to be along for the ride. This legibility shifts over time, from being heavily story-weighted to more evidence-weighted as it attracts more and more capital. The way to make money, then, is either invest early (deploying capital in an idea before it’s legible, then profit from the “multiple-expansion” as that legibility develops), or throw the most money at an already-legible-but-still-growing business (I’ll bet $100m that this is the idea that matters).

• The Mischievous Ex-Bankers Behind “Industry” - Fun profile by The New Yorker’s Rebecca Mead covering Konrad Kay and Mickey Down, the creators of the now-HBO hit: Industry. The duo met in college and both headed to investment banks right out of undergrad, but they were both notoriously-poor bankers who were quickly canned from the finance world. I’m a sucker for a good “underdog success” story (who isn’t?) and it was fun to read about how the duo took their experiences in London finance and built a world that now entertains millions.

• Secrets of Sand Hill Road - For anyone interested in how the venture capital world works, Scott Kupor (managing partner at Andreessen Horowitz) wrote an excellent guide to all things Silicon Valley and startup investing. It’s an easy, but informative read for anyone new to (or simply curious about) the world of VC.

• Anthropic has a set of courses on its site for how to use their API, Claude Code, MCP, etc. Pretty cool.

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!

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Winter Travel and Wedding in India

I hope everyone has been enjoying the holidays. This has been one of the more hectic travel periods of my life. From mid-December through next week, my travel schedule has looked like this: San Francisco to New York to Tampa to New York to New Delhi to New York to Atlanta to Tifton to Birmingham to New York to Geneva to New York. Safe to say I’m stacking up airline points during the holiday season.

A couple of weeks ago, I flew to India for a week for a friend’s wedding. It was, without a doubt, both the most fun, and most hectic wedding I’ve had the pleasure of attending, so I fired the travel blog back up to recap my week in South Asia. See below for a brief snippet from the blog, as well as the full post:

Tie comes off. Ben grabs me. “We need to go outside, now.” He seems serious. We head to the courtyard. A bunch of older Indian men are there.

“How much do you want to bet?”

“What?”

This 60-year-old Indian man stares at me, takes another hit of his cigarette, then repeats himself. “I arm wrestle your friend. Gamble on it. How much are you going to bet?”

Ah. Apparently, Ben had orchestrated an arm wrestling ring to take place the final night of the wedding.

I look in my wallet and see ~$120 and change.

I glance at this Indian dude. He definitely has old man strength, and, at 12:42 AM, there’s a healthy dose of nicotine and whiskey flowing through his veins. I glance at Ben. There’s more than a healthy dose of tequila flowing through his veins; we’ve been drinking non-stop for five days.

“$120, that’s all the cash I have.”

“$20?”

“No. One HUNDRED and twenty dollars.”

“How many rupees is that?”

“I don’t know, like 13,000?”

The Indian man grabs his wallet and yells “THIRTEEN THOUSAND RUPEES” and throws it on the table.“I guess I’m betting $120 on an arm wrestling match,” I think to myself. I throw my cash down too.

What I’m Reading / Consuming:

• I didn’t read many books in 2025, largely due to much of my free time being subsumed by my own book. With that largely behind me, I plan on reading quite a bit more in 2026. As always, I’m open to any and all book recs that you find interesting / useful.

• Deep Work by Cal Newport. One of my biggest struggles over the last year (and I don’t think I’m alone in this struggle) is the ability to “lock in” and focus on mentally taxing tasks for extended periods of time. Working from the same device that houses iMessage, Instagram, Twitter, Reddit, etc. leaves your distractions just a click away from your work, meaning that the temptation to break concentration for “just a few minutes” is ever-present. I found Newport’s classic to be quite, quite helpful in 1) unpacking the value/importance of preserving “deep work” windows in your daily life (vs. spending the whole day triaging emails, jumping from low-leverage task to low-leverage task, etc.) and 2) structuring your life to preserve these deep work periods. Good read for any other white collar workers who feel that they spend their days just trying to stay on top of their days.

• Default: The Landmark Court Battle over Argentina’s $100 Billion Debt Restructuring. I did some research in the litigation finance space last fall, which send me down a rabbit hole of interesting Lit Finance cases. Elliott’s Management’s decade+ legal battle with Argentina over a series of bonds they bought in the midst of an Argentine debt restructuring remains one of the most fascinating stories in law/investing. I’m still working through this book as the writing is fairly dense, but the author paints an incredibly detailed picture of the multi-year legal battle between various claimants and the South American sovereign. For anyone interested in the space, it’s a quite interesting read.

• Greg Blotnick’s recent Twitter threads. Eventually, you come across a new Twitter follow churning out interesting post after interesting post. Greg is one of such posters. His story is pretty wild: a fellow CBS alum ~10 years older than me, he spent most of his career as a L/S hedge fund analyst/PM before launching his own fund. He went to prison for a couple of years in 2022 for PPP loan fraud (I believe he was investing funds raised from PPP loans), and he was released maybe a year ago? Anyway, he’s been churning out really interesting thoughts across both valuation frameworks / public equities investing and broader life philosophy. It looks like he wrote a book while in prison, too. Anyway, if you’re interested in markets, he’s a good follow.

• The Bitter Lesson: A six-year-old post from Canadian computer scientist Rich Sutton on the long-term trend of the only thing mattering for the sake of improving AI/ML research being the availability of more compute. Evergreen blog post given what we’re seeing with datacenter buildouts in 2025. “The bitter lesson is based on the historical observations that 1) AI researchers have often tried to build knowledge into their agents, 2) this always helps in the short term, and is personally satisfying to the researcher, but 3) in the long run it plateaus and even inhibits further progress, and 4) breakthrough progress eventually arrives by an opposing approach based on scaling computation by search and learning.”

• Bill Gurley on The Tim Ferriss Show. Bill Gurley is one of my favorite minds in the venture world, and I really enjoyed his discussion on the world of VC today, developments in China, and figuring out your career.

What I’m Interested In:

Building off my note on Cal Newport’s book, the number one priority for me in 2026 is being meticulous about creating and maintaining time for deep work during my day(s). There are exponential payouts to being able to hone in on a particular thing for hours at a time without interruption, and every time your attention deviates from the task at hand to check an email, scroll Instagram or Twitter, or text someone back, you blow up that focus. This has been a long-time struggle of mine, particularly when sites like Twitter are, at least loosely, “useful” for my job. But it’s a battle I want to address head-on and win this year.

Besides that, I have a couple of non-work-specific focuses to kick off the new year:

1. Going quite, quite deep on building more novel vibe-coded AI applications and refining my understanding of where these models are going at a technical level. Regardless of whether you’re an investor, entrepreneur, or employee, I think you’re doing yourself a massive disservice by not seeing what these tools are capable of, and, importantly, what they’re not capable of.

2. Tightening up my accounting / valuations / modeling frameworks / skills. I never went through the investment banking gauntlet common to a lot of investor/finance types from 22-24, and, while we largely invest in the earliest stages of companies, I think having a full toolkit as an investor where you can breakdown any business, from a $30 million startup to a $30 billion publicly-traded company, is just useful. I’m going to spend the next month or so working through McKinsey’s “Valuation” book, plus a few other resources for improving this area for me.

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!

“How much do you want to bet?”

“What?”

This 60-year-old Indian man stares at me, takes another hit of his cigarette, then repeats himself. “I arm wrestle your friend. Gamble on it. How much are you going to bet?”

I look in my wallet and see ~$120 and change.

I glance at this Indian dude. He definitely has old man strength, and, at 12:42 AM, there’s a healthy dose of nicotine and whiskey flowing through his veins. I glance at Ben. There’s more than a healthy dose of tequila flowing through his veins; we’ve been drinking non-stop for five days.

“$120, that’s all the cash I have.”

“$20?”

“No. One HUNDRED and twenty dollars.”

“How many rupees is that?”

“I don’t know, like 13,000?”

The Indian man grabs his wallet and yells “THIRTEEN THOUSAND RUPEES” and throws it on the table.“I guess I’m betting $120 on an arm wrestling match,” I think to myself. I throw my cash down too.

Day five of an Indian wedding, and I’m watching one of my best friends arm wrestle another one of my best friends’ uncles, with a dozen ~30-year-old American dudes betting against a dozen ~60-year-old Indian dudes on the outcome.

I had never, before last week, been to India. I was supposed to go to India during spring break a couple of years ago, but the start date of my last job coincided with our spring break, so my team offsite took priority. Last week, however, I got another chance when one of my best friends, Tanmaye and his girlfriend Quinn, got engaged. He’s Indian, and they were hosting the wedding in India, and I received an invite to said wedding, so I was finally able to take my first trip to the subcontinent. This was not one of those “take a month and see a new country” trips. I’m employed, plus the holidays were coming up, so it was much more of a “six days on the other side of the world” trips, with the wedding itself being a five-day celebration. And the whole thing was a blast. So fun, in fact, that it deserved a standalone travel blog.

So let's get into it.

Most weddings I have been to consist of the following order:

The wedding party arrives on Friday, and you spend the afternoon riffing with the groomsmen who you attended the bachelor party with a few weeks’ prior. You have the rehearsal and welcome dinner, catch some sleep, wake up Saturday, throw on your suit, take lots of pictures, head to the venue, sit through a pleasant, ~hour-long ceremony, head to dinner, listen to anywhere from 2-4 speeches of varying quality, some of which are genuinely heartfelt, but most of which are compilations of unnecessarily-forced inside jokes (most inside jokes are not great wedding speech fodder, FYI), tear up the dance floor, and then, if you’re feeling crazy, hit the town after, before smoking a cigarette at 3 AM and calling it a night. 36 hours of fun, then back to reality.

The itinerary of this wedding was, well, a bit different.

Take a Monday evening flight from New York to New Delhi, land Tuesday night. Wednesday night brings a welcome party in New Delhi. Thursday: Welcome lunch in New Delhi. Friday AM: fly to Jodhpur. Welcome lunch at the Umaid Bhawan Palace. That night? Sangeet party at Fort Mehrangarh with an after party that follows. Saturday: Haldi at the Umaid Bhawan Palace, Baraat that afternoon, wedding in the courtyard that evening, after party inside at 2 AM, and we run it back on Sunday with a Bahu Swagat the following afternoon before a Christian wedding that evening at the palace. Oh, and, yes, one more after party because why not? An aggressive week.

After spending Monday hurriedly washing my clothes and packing, I ubered to JFK for our 14 hour flight to Delhi. I am, normally, a carry-on-only maximalist. For this? I had to make an exception. I needed a suit. No, two suits. Because I don’t want to wear the same suit twice. And what shoes do I wear? Well, I don’t know. Let’s pack cowboy boots. And oxfords. Running shoes, but also some dressier sneakers, too. Loafers, because they look cleaner with Indian fits, right? Dress shirts. Linen shirts. A tie or two. A jacket, sweater, and hoodie, and anything else you might need for Christmas since you’re headed straight from India to Georgia for Christmas.

So, yes, I had to check a bag.

Head to the airport. JFK is New York’s disgrace compared to La Guardia. Get to the gate. Run into a couple of Israeli founders I met in Tel Aviv in May. Confusedly ask them, “Headed to India..?” No, of course not. They’re headed to San Francisco, and had stopped through New York on the way. Obviously.

Run into a couple of friends at the gate: Ben, a day one from business school referenced in the opening paragraph, Landon, and Ben’s new girlfriend, Claudia. Initial read: we’re Claudia fans. She also selflessly provided me with some performance enhancing sleeping medicine. I’m not a great sleeper on red eyes, but if I didn’t catch eight hours on this 14 hour monstrosity, I knew I was cooked. Grab a glass of wine from the bar by the terminal. It tastes like stale grape juice, but it serves its purpose. Board the flight; seat 24J. I really thought I had done something smart by landing the exit row, but, actually, I played myself! Because this was a large, long-haul plane, there are three seat sections per row in economy (cattle class) where I was sitting. I was in the section to the right. A fun trick about the front row of economy on long-haul flights: families can book the entire middle section because the wall in front of those seats doubles as a support for bassinets to put babies in. Directly to my left, I find a family of four: two parents who either lacked the ability or desire to exercise any level of authority over their 2- and 4-year-old children. Dad is holding the younger kid who is competing with the jet engine to see who can maintain 100 decibels the longest. Mom is staring at the older kid: she keeps trying to eat the safety manual.

“Ah! Ah! Ah!”

I hear someone giggling behind me as my seat gets kicked. I turn around. A three-year-old is slumped in her seat kicking her feet against the seatback table. Her mom mouths, “Sorry!” to me. I don’t think it’s a Herculean effort to stop your kid from taking out their ADHD on the back of some stranger’s seat, but here we are. I take a sleeping pill. “Please work.”

Engine accelerates. Flight takes off. I close my eyes. Hear a gasp. Open my eyes. The four year old to my left projectile vomited all over the wall in front of their seat, and now they’re crying. It smells horrible. Awesome, I’m seated in the crossfire of the worst toddlers on the planet.

A few minutes later, before the sleeping pill kicks in but after the fasten seatbelt sign comes off, I head back to row 33 where Ben and Claudia are, so I can take a brief break from the scent of partially digested baby peas and tell my friends about my great fortune. Ben is seated in the aisle, Claudia in the middle. To her right, I see a 12-year-old kid, iPad out, completely barefoot with his right leg crossed over his left, bottom of his foot a few inches from Claudia, giving himself a toe massage. “Incredible, we all won the flight lottery.”

I consider bribing the kid to switch seats with me and sit in kiddie crossfire. I restrain myself and head back to my seat. Sleeping pill is kicking in. Goodnight, world.

I shoot awake, sweating. Four hours until landing; that sleeping pill worked wonders. It also amplified my dreams: seconds earlier, I dreamt we had just flown into one of the Himalayas. I’m pretty sure the kid kicking my seat caused my dream realm to simulate a plane crash. Whatever, we’re nearly there.

Land in New Delhi. First thought, it’s foggy. Check the weather app. Air quality is so bad that the radar just shows dark red. Apparently Delhi in winter time has the worst air pollution on planet earth. Reconvene with Ben, Landon, and Claudia. The foot kid apparently passed out for the entirety of the flight. Never put his socks back on.

We receive a Whatsapp message from the wedding coordinator telling us to head outside and look for a sign saying, “Tanmaye and Quinn wedding.” We grab our bags, head outside, and are greeted by drivers with said signs. They have a list of names. We’re on it. I’m in a different hotel from the others, the Leela, so I walk to a cab with one of the drivers. Everyone in the parking lot is smoking cigarettes, which doesn’t bug me, because the entire biome feels like a cigarette. We get in a car, exit the airport, head down the highway. The roadways had no lanes, so the vehicles, like osmosis, quickly filled any loose space that might help them reach their final destination even one millisecond faster. We weave left, right, accelerate past bicycles with carriages attached to the back, people appearing out of nowhere to cross the highway on foot, and other taxi drivers dodging pedestrians. Somehow, no one hits anyone. Everyone navigating Indian roadways is operating in some sort of collective flow state. It’s impressive. I get to the hotel, and the guards open the hood and the trunk. I realize a few days later that this is routine for all taxis entering nice hotels. Every car gets searched. We pull up to the hotel. The driver gets out, gives me a slight bow. A hotel attendant walks up, gives me a slight bow. Grabs my bags. I walk through a metal detector and enter the hotel. The clerk gives me a slight bow, escorts me to the front desk. The reception gives me a slight bow, checks me in. I get my room key and head upstairs. There’s a knock on my door. The bag guy gives me a slight bow, drops off my bags.

I hit the gym to work up a sweat after sitting for 16 hours, then shower to wash off the gym sweat before hitting the bar for a bite to eat. I grab a beer and some chicken wings before hopping on a work call with a dude in Thailand. He was chill.

At this point, it’s around 1 AM, and I read for a bit before calling it a night.

In the morning, I once again hit the gym before testing out the hotel breakfast. The Leela breakfast was phenomenal. Waffles, omelettes, yogurt, granola, and a random assortment of spicy Indian breakfast foods were waiting for me, plus a cappuccino. I consume all of it, then head to the Taj hotel to meet up with my boys Brody and Lawrence. The three of us will be roommates for the final three nights of the trip, and we need to get fresh fits for the Indian festivities. Namely: kurtas (shirt/gowns), sherwanis (formal coats), and jackets/vests. I grab a coffee at their hotel, Brody says, “I know a place,” and we hop in a $2 Uber.

Traffic was, once again, a free-for-all. We drove past a park with hundreds of people laying in the grass, but it wasn’t a “hot girl in LA laying out” kind of laying in the grass as much as a “I was walking and just decided to cease movement in this particular spot” kind of laying in the grass. Lots of dogs all over the place. All sorts of bicycle-like vehicles with anywhere from 1-4 people on them.

Brody takes us to what must be the nicest shopping area in New Delhi. We enter this boujee, white-washed complex with a Ralph Lauren store near the entrance and walk into a traditional Indian clothing store. The manager of the store, who was quite metrosexual (he would have fit right in in Brooklyn), immediately starts taking kurtas off the hangers for us to try on.

None of them fit.

He assured us that the could adjust the kurtas and have them delivered the next day to our hotels before our flights.

Maybe.

These clothes were very, very nice, and they absolutely did not fit. Except one kurta, which I quite liked, that fit quite well. I took it to the counter. He showed me the price. I checked the exchange rate: “$800.”

“No way,” I thought to myself. I glanced at Brody and Lawrence. They shook their heads. I said, “Don’t think I’m going to be able to swing this for something I need to wear once.”

We leave.

Next we head head downtown, to Khan Market, which is basically a mix of Canal Street and Soho in New York. A bunch of narrow winding alley ways that are simultaneously dirty yet filled with interesting retail stores + bars and restaurants. Smog is still, pretty much, everywhere, so whenever you’re outside it’s like walking through a smoking lounge. Slight burn in your lungs.

We ran into Jacob, one of Tanmaye’s friends from Northwestern, and Laura, his wife / one of Quinn’s friends in one of the 27 clothing stores in this Delhian alley. Jacob was already fitted in Indian apparel. We weren’t huge fans of store number one, so we kept walking until we found a tailor: B. Rai Son’s. This was the right store.

Apparently, half of our crew had already been to this same spot, and we were all looking for the same thing: a sherwani. It was a must-have item for the Indian wedding in a few days, and, like a good suit, we needed to get them tailored. The boys at B Rai Son’s pulled out some fabrics for us to choose from (I chose a navy blue base with lighter blue patterns), took our measurements, then bartered with us until we agreed to a price. I think I was ~$500 all-in for the sherwani, some tailored pants, and a nice yellow kurta. Then we headed to a more casual store for kurtas, jackets, and scarves. I copped a red and a navy kurta, as well as a red/black scarf.

I headed back to my hotel to shower and change, then I grabbed a cab to the welcome party on the outskirts of New Delhi. Dress attire for night one was western suits, so I threw on a navy suit and tried my best not to fall asleep in the cab. 10 hour time change isn’t for the weak. Looking out the window, it felt like the opening scene to a B-list thriller film: thick fog with 8 feet of visibility, strangers appearing out of nowhere walking across the street, cars weaving all over the road. My driver was chill. We exchanged a total of 9 words.

After 45 minutes, I arrived at the “welcome dinner,” which was more grandiose than most weddings I’ve attended. Red carpet rolled out at the entrance with servers waiting with glasses of champagne, then I walked down the hallway into a massive, circular room with a round bar in the center, a stage at the front, and an outdoor dining area to the left with everything from a sit-down omakase station, to a massive grill covered with an assortment of meats, to a dessert bar that would have made Willy Wonka jealous.

This was also my first time seeing the rest of my crew attending the wedding. There were ~20 or so of us from Columbia in town, with about ~10, specifically, of my closer guy friends. Among those 10, the split of single vs. relationship guys was approximately 50/50, which is the ideal split of relationship status at a wedding. Having been on both sides of that equation at different points in my life, the relationship guys are guaranteed to have a good time (assuming, of course, that the party is good), while the single guys tend to experience more volatility somewhat dependent on their successes at both identifying, and wooing, any of the single girls in attendance. Their efforts, of course, serve the broader entertainment of everyone in the friend group. This is the underlying side plot of any wedding, particularly a destination wedding. Who finds love that wasn’t predestined when the invites were sent out?

At this particular wedding, I was one of the single guys.

I grab a drink (gin and tonic?) and start making the rounds saying my hello’s to everyone, and, as the last paragraph would suggest, keeping an eye out for anyone who might fall into the “single girls in attendance” category. My crew had flown in from all over the place: the majority live in New York, but we had friends from Guatemala, Argentina, and France as well. Tanmaye’s friends were largely split between graduate school (Columbia) and undergrad (Northwestern).

I walk over to say what’s up to some of the Northwestern guys, when I recognize one girl from Raya. “Traveling to New Delhi” was a telltale sign of someone else at the same wedding. I said hello. I made very little traction with that conversation.

Then the bride and groom arrive, and they look stunning, which was, as it should be, the common theme of the weekend. Tanmaye, to his credit, really pulled himself together for his wedding week, Quinn looked like a princess. We all say hey to them, and I chat with his dad and uncle for a few minutes. I had met them once, at our graduation party a year and a half ago. Tanmaye’s dad is a 6’ 5 giant of a man with an incredibly dry sense of humor, and his uncle Bobby is exactly the type of Indian uncle you would want at your 5 day wedding extravaganza: life of the party perpetually tearing up the dance floor.

Dinner time; I grab a table with Marcos, Nana, Pierce, Maite, Guille, Rafa, Toni, Clem, Lucas, and Brody(more Columbia friends). Then time for dessert. I turn to walk over the dessert area, where I see Sebo and Antonio chatting with a group of girls near the espresso bar. Zero time wasted for the Latin folks. DJ comes on, back to the dance floor.

Again, I would like to highlight that this was a welcome dinner, but it was more extravagant than most weddings I had attended. Two hours later, my whole crew was dancing on stage to Indo-English jams, and two hours after that, Lawrence, Brody, and I finally made our way outside to grab cabs home. 3:52 AM.

At this point, our visibility had declined from 8 feet to 4, and the ride home felt more like a fever dream than reality. I genuinely have no idea how these drivers can navigate New Delhi smog like this; it’s like they have a 6^th sense.

Back in the hotel, I pass out at 4:30, but not before setting my alarm for 10:45; we have lunch at 12:30.

I grimace and roll over to grab my phone.

“5:37.”

“Did I only sleep an hour?” I think to myself.

I open my phone. Four missed calls. Brody: “Yo where are you?”

Turns out it was 5:37 PM. I had missed an entire day, and it was already dark again. So much for adjusting my sleep schedule. I roll out of bed, throw on some shorts, and hit the gym, before showering and heading to the hotel restaurant. At this point, I resigned myself to staying up til ~midnight then trying to catch 6-7 hours of sleep before our flight to Jodhpur in the morning.

My mistake, at dinner, was ordering a lamb burger. I like lamb. It’s typically a delectable meat, particularly in burger form. At least at Israeli restaurants. But, in hindsight, I think this specific burger was undercooked. I was, going into this trip, incredibly wary of “Delhi belly.” Don’t, under any circumstances, drink the tap water. I rinsed my toothbrush with water bottles. There was no chance I was going to risk a stomach bug in India. And yet, I got sick anyway.

That evening, after a couple of work calls, I was unwinding for bed, when I started to feel awful. Or, like, “pre-awful.” That feeling where you know you’ll probably throw up in like 2 hours but you haven’t yet. I spend the next 90 minutes on and off the toilet, before getting back in bed for ~30 minutes, then running to the shower and projectile vomiting everywhere for another 30 minutes.

Lamb.

Disgusted both in myself and the murder scene around my feet, I rinse out the shower, take a shower myself, brush my teeth, throw away that tooth brush, and look at my phone again.

3 AM.

“Great,” I thought to myself. My alarm was set for 7 AM.

I try to go to sleep, but at this point, there was no chance I was falling asleep. Waking up at 5:37 PM makes it pretty difficult to fall asleep just 10 hours later. So, at 5:30, I made the only reasonable decision to make after blowing up your sleep schedule then puking your guts out for 90 minutes: practice the following evening’s dance routine.

One of the funnier parts of this wedding was that all of the Columbia and Northwestern boys had to perform a 20-something-man synchronized dance routine Friday night at the Sangeet. You may have seen one of the classic viral videos on TikTok of a bunch of American dudes crushing a synchronized dance routine to an Indian beat. That was us. We had, hilariously, practiced it twice over Zoom, but the results were mixed. I myself am not a particularly natural dancer. I’m good at a few things, and fine at many things, but serviceable at best on a dance floor. And I didn’t at all have this one memorized. So, I went back to the bathroom, put my laptop on the sink, and spend the next hour going through the dance routine in front of the mirror, shirtless and sweating, before showering again and heading to the airport.

The wedding coordinator communicated with all of us via Whatsapp, so I got a message saying my ride would be there at 7 AM. I thought I was running late when I walked out of the hotel at 7:17. I arrived at the airport at 7:43. First one there for our 10:30 AM flight.

Navigating the intricacies of flying domestic in India with an overweight bag on no sleep is a bottom-3 life experience. I had to wait in line to enter the airport as they checked my passport and ticket. Fine. Then I get inside. I went to print my boarding pass so I could go through the self-bag drop. Couldn’t print boarding pass because we were a group reservation. Fine. I get in line. 10 minutes go by. 20. 30. We’ve progressed, maybe, 12 people total in the line. It feels like each time a new traveler reaches Indigo’s desk, it’s the worker’s first time checking someone into a flight. I’m nearing the front of the line, and the rest of my party begins to arrive. Landon says “I think we have a dedicated check-in desk.” I get out of line.

This was a mistake.

The critical mass of our party is now here, and Tanmaye talks to an airline worker off to the side. We have our own check-in desk. Good. They have no idea how to check us in. Bad. No one gets checked in for 30 minutes. It’s now 9:45 AM. Our flight leaves at 10:30 AM. No one is checked in. No one has gone through security. I haven’t slept since 5:30 PM the previous day and feel as though I lost half of my body weight via oral expulsion around 3 AM. Not great!

I get back in line with Antonio, Lawrence, Ben, and Claudia. Borderline delirious. The issue, I now realize, is that it takes approximately 8 minutes to process a payment for an overweight bag, and the weight limit for a bag is quite light: 15 kgs. So, naturally, most suitcases getting checked come in over that weight. One person goes up. Bag overweight. 10 minute check-in. Maybe longer. We saw some folks from our party stand at the desk for 30+ minutes before checking in. Nightmare fuel.

45 minutes later, I finally get my boarding pass. It’s 10:42. Our flight was scheduled to leave 7 minutes ago. Luckily, we were 95% of the seats on this flight, so they pushed back takeoff instead. I grab some snacks and make my way to the gate. 12:35 PM, we finally take off. My snacks suck. I eat them anyway. At 1:42 PM, we land in Jodhpur.

Jodhpur was refreshing, quite literally, because it didn’t suffer from the same smog overhang as New Delhi. A smaller city, it was best-known for the Umaid Bhawan Palace and Fort Mehrangarh, which we would soon party at for the next three evenings. When the flight landed, we left our bags with the transportation staff and took cabs to Umaid for lunch.

The scene was when we rolled up to this palace was insane. Driving through town, it’s like a slightly nicer, but directionally-similar, New Delhi. Cars all over the place. Slightly nicer infrastructure, but still a plethora of 3-people-piled-on-homemade-bicycles cruising down the road. Then we take this winding path up to the palace, the gate opens, and BOOM: Trumpets. Camels. Red carpet rolled out. More champagne. I walk upstairs into the palace, and this thing is just glorious. One of the more impressive buildings that I’ve ever seen, filled with portraits of impressive-looking mustached, turban-wearing men adorn the walls. We have lunch in the courtyard. I eat as quickly as possible to expedite my path to my bed for a few hours. Family and some friends stayed in the palace. Most of my crew was at the Ajit hotel down the road.

I Uber there, and Lawrence had beat me to the spot (he skipped lunch). This hotel was villa-style, spread out across a dozen-or-so buildings. Our room and patio overlooked the pool. We had a “suite” with a big, L-shaped couch at the front of the room, then a corridor to the bedroom with a queen bed. Three of us were sharing a room with one bed, so we ordered an extra cot. I passed out for three hours. At this point, I was delirious.

Wake up at 6. Brody can’t find his backpack. Don’t have time to look; time to get dressed for the Sangeet. Lawrence and I practice our dance routine again in the hotel. Brody lays in bed doomscrolling on his phone. We throw on some kurtas (I’m wearing red with a black vest that Lawrence scooped for me), then we Uber to Fort Mehrangarh. We thought we were 30 minutes late. We were still 30 minutes early.

We pull up at the fort, and massive spotlights are painting its wall with a wedding logo. More camels. More trumpets. A bar outside; more champagne.

Tanmaye and Quinn arrive, the gates open, and they lead us on an ~hour pilgrimage to the top of the fort, where the first party in Jodhpur will take place. The walk through the fort felt like Alice in Wonderland meets Aladdin. As we reached higher elevation, we would peer from the ramparts toward the interior to watch exotic dancers move their bodies to hypnotic music. A half-dozen fire breathers performed a show. Two women in what must have been ~20-foot-tall stilts swayed back and forth to a rhythmic beat. And a few guys dressed as monkeys sprinted around on all fours, hiding in the castle walls before jumping out to intimidate guests. I said I wasn’t going to drink after my stomach issues. This was not an event to experience sober. I took imodium and hammered my third cocktail of the evening.

Those monkeys were just nuts, man.

Finally, we make it to the top. An interior courtyard of the castle that had been retrofitted with a massive stage, several bars, and yet another insane spread of foods, most of which I couldn’t begin to pronounce. We head first to the bar, then to the buffet station. I try, with the food at least, to take it easy on my stomach. Three different groups perform interpretive dances on the stage. Everyone cheers. Suddenly, “Boys, you’re up!”

Shit. Our turn. Heart rate starts to accelerate. It’s like gearing up for a football game again. We, literally, huddle up and start the “we ready” chant that you see in every Hallmark sports movie, then, “It’s time!” We hit the stage. Crush it. All of that anxiety, for nothing. 10 / 10 performance.

Everyone daps everyone up. We’re just glad to be done. Here’s the YouTube video if you want to watch:

Then Tanmaye and the men in his family have a dance routine. They rush. There’s two other dance routines. They crush. Everyone crushed their respective routines. Go back for another bite to eat. A DJ comes on, we all hit the dance floor. Two hour dance-fest commences. I try to spit game with another girl from the wedding. Vibes seem strong. We chat for 20 minutes. I go back to my crew. Crack some jokes. More dancing. Servers are walking around with shots, I grab a couple. I walk back to the girl. “Here, let’s take these.”

We take the shots. She says, “That was pretty weak.”

Sensing a layup, I say, “Want to get something stronger at the bar?”

She smirks and says, “I’m good.” and walks off.

“Well, I definitely need something stronger.” I go back to the bar. Brody grabs a drink with me instead. I tell him the story. He laughs. I laugh. Back to the dance floor. 1:30 AM. I’m exhausted. I head to the bathroom, which is in the previous courtyard before we entered the party area. I want to leave. I see most of my crew hanging out chatting near the bathroom. I wait til they’re distracted and make my way to the exit. 2 AM. Taxi home. Pass out.

Half wake up to Brody and Lawrence. Are they staring at me? I don’t care. Back to sleep. I wake up. 10:30 AM. “Finally, rested,” I think. I grab breakfast, it’s pretty solid. More omelettes. More waffles. I head to the gym. My stomach is finally cooperating; Larry walks in too. I hit back squats, then pull ups and and ab circuit. Feeling good. I jump in the pool. It’s frigid. I can feel my manhood hide inside myself for warmth. Marcos jumps in. Then Toni. I think he’s going to get hypothermia. Ben jumps in.

“INU. WHAT DID YOU THINK OF THE ROCKBAND?”

My friends call my Inu. It’s Japanese for “dog.” Like, “shiba inu.” long story.

“rock band?”

“Yeah! a rockband came on… did you… leave before the rock band?”

“I mean, I guess.”

“You left at 12:30??”

Lawrence pipes up, “That rock band didn’t come on til like 2:45!”

I think to myself, “how did a whole other band come on… at 2:45?”

Ben said, “Damn. I guess I was there til 4.”

Go back to the room. Brody still can’t find his backpack; he heads to the airport. It isn’t there either. He comes back. We shower and get ready for the next thing: Haldi.

We head back to the palace, where workers were busy constructing a massive stage for what I assumed to be the Indian wedding that night. I was directed down and to the right through a series of hedges to another bar and dining area near a nice pool. I was wearing a yellow, shiny kurta. Brody, Lawrence and I stopped to take some pictures and aura farm.

Then to the pool. Then to the bar by the pool. I had what I think was a Corona mixed with a bloody mary. It was fine. For lunch, I had a fat plate of Indo-Mexican cuisine. Indian and Mexican food are directionally similar, so the hybrid was delicious. Back to the pool. Jacob and Laura gave speeches. Then Jonah, one of Tanmaye’s friends, and Maya, his sister / one of Quinn’s friends, gave speeches. We all cheered. Another corona-mary cocktail. More pictures. This “party” was a bit more casual, so I posted up at a table with my Columbia friends and just riffed for 30 minutes. Then music started. We walk back to the pool. Tanmaye’s dad is laughing and dumping a basket of what appears to be a mixture of flour and yellow feathers on the couple. Jacob pours soda on their heads.

I have no idea what’s going on. We all get on the stage. We all start dumping stuff on them. Then we start dumping stuff on each other. I’m throwing feather/flour clumps at Brody. Ben hits me in the face with a massive mound of this unidentified substance. Everyone jumps in the pool. The pool had been roped off the whole time, like you shouldn’t jump in. But they can’t stop 15 people from jumping in.

Back to the hotel. Brody finds his backpack: another guy had accidentally grabbed it thinking it was his, and didn’t check until a day later. Trip = saved.

Tonight is wedding #1: the Indian wedding. But first! The baraat. I have no idea what a “baraat” is, but apparently it’s like a “last journey” that the groom takes before meeting the bride, where he rides on a horse or vintage car to the wedding venue. This is not a solemn journey, it’s a banger. The irony is that we’re supposed to “delay” his arrival via dancing in front of the car. Apparently, every culture has an undertone of “don’t do it!” Regarding a man getting married.

We throw on our sherwanis and head back to the palace, where our drivers drop us off on the bottom of the road. He lets us out in front of a marching band standing at the ready. The tuba players start right as we get out of the car, meaning that they’re playing directly in our ears.

Tinnitus.

There’s a small stage set up, plus two bars and some food stations. There’s also three seats next to a couple of mirrors, where I see someone having a turban tied to their head. I grab a blue cloth and sit down. An Indian dude twists part of the cloth and says “hold.” I hold. Over the next five minutes, he twists this cloth around my head an impossible number of times. Ben is snickering taking pictures. I look in the mirror. I like the turban look. “Maybe I’ll make this my new Linkedin photo," I think to myself. I grab a tea. Then a beer. Everyone else gets their turbans. We take photos and crack jokes. Then Tanmaye takes the stage for what would be an hour-long ceremony in which he got a gold turban and lots of jewelry. Back to the street.

Tanmaye gets on a horse. It’s wearing more jewelry than him. Music starts. He’s moving at a speed of less than 1 foot per hour. The band is crushing it. We all start dancing. A truck pulls up. The trailer behind it is filled with beers and cocktails enclosed in water bottles. Basically, advanced High Noons. I grab a couple. More dancing. Tanmaye’s horse makes it 17 feet after an hour. He is then moved to a Rolls Royce. His childhood driver, who hasn’t stopped smiling in 3 days, is driving. He regularly stops driving to get out of the car and dance. Or get on top of the car, dancing. Their top speed never surpasses 1 mph.

Indian Pit Bull shows up. I have no idea who he was but that’s the best description I have. He arrives on a massive, two-story trailer covered in speakers, standing on the second floor. He starts playing what must be Indian bangers, because all of the locals went nuts when the music started. We caught onto the beat and started throwing down. Tanmaye’s uncle Bobby appears out of nowhere with a bottle of liquor.

“you drink! you drink! you drink!”

We all follow orders.

The symbols from the band are so, so loud. I linger in the back. More tinnitus.

We approach the palace. Bobby grabs us. “Dance in front of the car! Stop the car!” We all lay on the ground in “protest” while we continue to dance. The car stops. The palace is gorgeous. We aura farm in front of it. More pictures. Finally, we can go inside.

Someone steals a shoe. Apparently, there’s a tradition at Indian weddings called “Jotta Chupai,” or “shoe hiding,” where the bride’s female relatives steal the groom’s shoes as he arrives, hiding them and demanding a ransom for their return. Someone apparently asked for $200,000, then a $40,000 safari, taking it a bit too far. I think they ended up with $2k. I have no idea if the shoe(s) were ever returned.

We walk downstairs behind the palace. Construction was complete, I was looking at a scene from Star Wars or Dune. Walk down the red carpet on the stairs to a stage with a spotlight on it, waiting for the couple of the evening. Two bars, in elevated buildings, to the right and left, with red carpets leading to them as well. Seats facing the stage in front of me, then more seats, further back, facing a newly-constructed temple, which I presumed would hold the evening’s ceremony. Brody and I grab seats in the bar/building construct on the left. We wait. And wait. And drink. And wait. Suddenly, the most intense music of the weekend kicks off. I mean it was like the movie 300. Tanmaye takes the stage. Then Quinn is escorted down, her head covered by some sort of cover carried by her family. Drones are flying around at 50 mph recording from all angles. Fireworks explode to my left and they take the stage to my right. I notice a dining area further behind the temple to my left. Brody and I walk over.

We grab a drink, then grab dinner plates. I strike up a conversation with another girl. She and one of her friends had largely been traveling in a four-person pack with a gay couple. Brody and I grab a table with them. I try to talk to the girl. Again, zero traction. End up spending more time talking to the gay couple. They’re chill. The girl I had chatted with at the previous evening’s events sits down next to Brody. They appear to hit it off. Gay couple leaves. Girl I was attempting to wine and dine leaves. I’m inadvertently third-wheeling, I leave. I link up with Lawrence and say, “Don’t interrupt Brody.” We then watch, in a mixture of amusement and horror, as Ben and Toni walk by, glance at each other, snicker, then sit at Brody’s table, fulling blowing up his spot. Lawrence and I walk back over there as well.

There’s nothing worse than attempting to be suave with a girl, then a bunch of your boys pull up on your spot. Just an all-time poor situation. Brody and the girl eventually go to the bar. Brody eventually walks back, with one less girl, a few minutes later. Lawrence and I glance at Ben and Toni and say, “What was that for?”

They play dumb. “What are you talking about?”

We all laugh. More drinks. It’s 11 PM. Now midnight. Ceremony still hasn’t started. Finally, music begins to play. We take our seats. I’m hanging out with Lawrence, Sebo, and some of the Northwestern guys. Tanmaye and Quinn are in the temple in the back of the courtyard. About half of the crowd is watching attentively. Half is floating back and forth to the bar. Eventually, after 45 minutes, I take one more loop to the bar as well. 2 AM. 2:15. Ceremony over. We go back to the palace. After party in the front room, + more food in the courtyard where we had the first lunch. There’s a glowing, spinning cheetah statue in the middle of the floor. The walls are covered in mounted animals. DJ plays too many Indian beats; at this time of the night, if you want to keep the crowd rolling, you have to rip top 50 dance tracks. I’m there til the lights come on. Back to the hotel with Brody and Lawrence. Good night world.

Wake up at 10:45, make breakfast right at close. End up sharing a table with the dude who bid $200k on the shoes; he’s hysterical. He also stole Brody’s backpack. Chat with a couple of Quinn’s friends as well. We all look terrible. Someone’s mother was in the restaurant; she found my jokes to be funny. Take another dive in the pool (cold plunge, Huberman would be proud). Then throw on a linen shirt and scarf for the Bahu Swagat. Hit the bar, grab a drink and some food. The band is playing. Turns out, I know half of the band. Toni, Sebo, and Ben are on the drums. “Not bad,” I think. I run back to the room. Come back down. Eight men from the wedding are in all black holding rifles. “These ceremonies are insane,” I think. Post up on a bench with Brody, Ben, and Lawrence. I’m exhausted; it’s been a long wedding. Stand up to watch Quinn’s parents dance. Then Quinn dances. It’s all beautiful. I grab ice cream. Lawrence tells me, “ice cream is a kid’s food.”

I don’t apologize for using my free will.

Back to the room; one more event: the Christian wedding. I grab my other suit: a new gray one I’d gotten over the summer; still hadn’t worn it. Shower, suit, tie. Back to the palace, yet again. We’re greeted with champagne (again). Every time mine is half-empty, a server pours more in. I explore a few of the palace hallways. More mustaches on impressive-looking men. We head to the room across the hall from the after party room from the night before; it’s been set up to resemble a Christian chapel. The pastor, Sean, is straight out of every Protestant service I’ve ever attended, including the couple of quick, witty, G-rated jokes he dropped before the service began. It felt like home.

Tanmaye walks in, then the wedding party, then Quinn. The service was concise but incredibly sweet, even I teared up a bit as they exchanged their vows. After the service, Lawrence and I explored the premises for more photo ops, where we found Tanmaye’s driver upstairs taking mirror selfies. We joined him.

Then, back outside for the dinner (and, you guessed it: another party). I hit the buffet with Brody and grabbed a seat with our Columbia friends. There was a stage in the part of this courtyard a bit closer to the palace, where a band started playing; the dining area was further back. We started working our way to the stage. Then, siblings and friends gave speeches, with Toni and Ben representing the Columbia boys. Not bad, though I do have respect for people who can roll into a speech, no notes. Band plays a few more songs, it’s approaching midnight as they say, “This is our last one of the night!” (before the obvious, ‘one last song!’ that always occurs after).

“Early night,” I think.

Nope! Another after party. I head to the outdoor bar for another drink before the after party. Espresso martini; I need caffeine. A new girl, who I handed seen before, walks up. “Get two of those?” She asks (demands). I oblige. She tells me she’s from the states but lives in Italy. I tell her I’ve been to Italy a few times, once eating 20 pizzas in 13 days. She’s both confused and amused. I figure this is a decent chance do lean into the ‘writer’ side of me, as she mentioned she studied the classics, so I said, “I’m a writer.” “Where do you write?” “Substack.”

She’s not impressed.

“I’m writing a book.”

Still not impressed. “Do you have a publisher?”

“Penguin.”

Impressed. Funny how that works. We start chatting with a couple of Indian guys who had walked up; one was a CBS alumnus as well. I go to the party. This DJ understood the assignment. American bangers. Maybe, in hindsight, it’s because it was after the Christian wedding and not Indian. Idk. Another drink. Dance floor. Tie comes off. Ben grabs me. “We need to go outside, now.” He seems serious. We head to the courtyard. A bunch of older Indian men are there.

“How much do you want to bet?”

“What?”

This 60-year-old Indian man stares at me, takes another hit of his cigarette, then repeats himself. “I arm wrestle your friend. Gamble on it. How much are you going to bet?”

Ah. Apparently, Ben had orchestrated an arm wrestling ring to take place the final night of the wedding.

I look in my wallet and see ~$120 and change.

I glance at this Indian dude. He definitely has old man strength, and, at 12:42 AM, there’s a healthy dose of nicotine and whiskey flowing through his veins. I glance at Ben. There’s more than a healthy dose of tequila flowing through his veins; we’ve been drinking non-stop for five days.

“$120, that’s all the cash I have.”

“$20?”

“No. One HUNDRED and twenty dollars.”

“How many rupees is that?”

“I don’t know, like 13,000?”

The Indian man grabs his wallet and yells “THIRTEEN THOUSAND RUPEES” and throws it on the table.“I guess I’m betting $120 on an arm wrestling match,” I think to myself. I throw my cash down too.

Day five of an Indian wedding, and I’m watching one of my best friends arm wrestle another one of my best friends’ uncles, with a dozen ~30-year-old American dudes betting against a dozen ~60-year-old Indian dudes on the outcome.

Ben looks like he’s going to lose. I worry that I’ll lose my money. Given their seating, his arm is closest to the edge of the table, sliding off. The match pauses; we grab a smaller round table they can stand on opposite sides of, so neither has a leverage advantage. Match commences. Ben smokes the old man. USA chant breaks out. I get my 13,000 rupees. Happy Inu. A celebratory cigarette. Then back to the dance floor. Another drink. Someone’s scarf is now a limbo pole. Sebo wows the crowd by going full 90 degree bend. I don’t even think about attempting it. Two hour rave commences.

I step out to the courtyard to grab some pizza. Italy girl from earlier steps out. I engage in what can only be described as a 90-minute conversational vortex in which I quoted and described countless references of the Greek and Roman classics that were either entirely fabricated and/or extrapolated far beyond the reaches of my actual knowledge for the sake of an engaging conversation. That’s fine. I fully endorse keeping conversations fun at all costs. I thought everyone had left. Lights were coming on. I was facing the dance floor and saw little activity in there. Girl goes to the bathroom. I glance behind me. Half of my crew was still there at a table 15 feet behind me. Classic. Party’s over. Time to go home. Brody, Lawrence, and I grab a cab. Get back to the room. Our door is cracked open. Not great. We cut on the lights; a shadowy shape darts from the couch back to the bedroom. A few seconds later, it comes flying back through the corridor to the door, looking for a way out. Lawrence yells and jumps out of the way.

The cat sprints full speed out the door, meowing at the top of it’s lungs.

“Okay, we need to go to bed,” I think.

Next morning. I feel like a human cigarette. Shuffle to breakfast, feeling horrible. Sit with Nana and Marcos. Breakfast is the only thing giving me the strength to get through what will soon be the longest travel day of my life. We fly back to Delhi at ~12, then don’t have our flights back to the US til 11:30 PM. Eat food. Drink coffee. Back to the room. Pack. Lawrence, Brody, and I are the last cab to the airport. The Jodhpur airport is, for lack of a better term… lackluster. Security takes an hour. We survive. Back on the plane. I’m seated next to Larry. Commence cracking a dozen inside jokes that have no business being on Substack. We get to the Delhi airport. I grab a Krispy Kreme donut; first taste of America in a week. Now we have 12 hours to kill. What to do, what to do.

I book a room at an airport hotel. The “Roseate.” We split it eight ways. Me, Landon, Brody, Lawrence, Claudia, Jules, Ben, Sebo. I grab a cab to the hotel. The concierge asks me how many nights. I say “8 hours.” He is confused but asks no questions. We all drop our bags in the room and hit the restaurant for lunch. I get two sushi rolls and a chocolate shake. Why not? Free will.

Back to the room, I write the first half of this blog while half the crew naps; Brody, Lawrence, and Sebo left on earlier flights. Then back to the airport, and, finally, 16-hour flight home. Not a bad week.

Will I ever go to India again? I have no idea. But if you do have a chance to go to an Indian wedding, you should probably do it. Just avoid the lamb burgers.

And congratulations again to Tanmaye and Quinn, I wish you both a lifetime of love and happiness.

- Jack

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The Wall Street Journal published an interesting article last week on the tech world’s hottest new role: “chief storyteller.” The Journal noted that tech giants Microsoft and Google are recruiting storytelling leads for their cloud and security teams, while compliance software provider Vanta is paying up to $274,000 for a “head of storytelling.”

This is far from the first time company hiring practices involving wordcels have gone mega-viral. In 2023, for example, yogurt company Chobani offered $278,400 for a ghostwriter for their CEO (which, in hindsight, would have been a kickass gig during business school. But I digress).

Why is “storytelling” so hot? Perception is increasingly reality, and if you can control the narrative about your product / market, it makes it much easier to both hire and sell, which, in turn, makes your company better.

So everyone wants to “win the narrative.” Combine “storytelling” as tech’s hottest new buzz word with the fact that everyone is now looking for “taste,” and you have the perfect storm for tech companies shelling out $300,000+ to hire someone to make B2B SaaS seem cool.

The most interesting “narrative” plot to me, however, is how much narrative and “vibes” shape the AI arms race. Right now, there are four AI labs that matter: OpenAI, Google, Anthropic, and xAI. Everyone is either fighting for scraps at the model layer or building on top of / adjacent to the models themselves. Every time a new model drops, Twitter explodes with discourse over which model is best. “OpenAI is cooked; Gemini is GOATed” was the most recent narrative in AI, which, of course, will probably be outdated by the time you read this blog. Given that so much of AI sentiment is influenced in real-time online, it makes sense that the AI labs are willing to pay the most to “shape the narrative.”

If Dwarkesh Patel says the right/wrong thing about Nvidia on his podcast, its stock price could drop 10%. With new updates to models and chips and everything AI dropping weekly, it feels like everyone is waiting for someone to tell them “what’s best,” because it’s impossible to keep up with everything on your own. The companies know that, and they’re paying accordingly. For example, AI lab Anthropic is hiring a “Head of GTM Narrative” in San Francisco / New York, offering up to $400,000 salary (+ equity and other possible compensation), for responsibilities that include “Develop and own executive narratives,” “Drive cross-functional GTM alignment,” and “Lead narrative development without formal authority.”

My question, on all of this, is what do these companies expect a “Head of GTM Narrative” to do? It’s not like “sales,” where you’re selling, or “engineering,” where you’re building. “Crafting narrative” is a weird job. I do think, more than most, that narrative can, quite literally, lower your cost of capital and improve a business’s prospects. But I don’t think the right approach is hiring a CMO-esque person to “do narrative” to save your company. In my humble opinion, there are three ways to play the narrative game right:

1. The CEO crafts and controls the narrative through their public appearances and messaging.

2. An outside comms agency helps the CEO / executive team to shape their narrative.

3. Some sort of Chief of Staff / Product Marketing Lead / Customer-facing individual that can represent the business makes “narrative creation” part of their broader responsibilities.

Companies are extensions of their founders. Even massive, multi-hundred-billion dollar enterprises like OpenAI, Anthropic, and xAI are really just extensions of Altman, Dario, and Musk. Regardless of what a narrative lead says, the public perception of Anthropic is downstream of its perception of Dario. It is what it is. So if you really want to get “narrative” right, it starts with the boss.

You could bring in outside consultants to help with that narrative. And a lot of companies do this. It’s actually much easier to hire a professional narrative developer that does this full-time for different clients, and have them help you shape your brand/narrative, than it is to hire someone more junior to run it. It’s similar to why you would hire McKinsey instead of bringing on full-time consultants in-house: 1) establishing narrative / brand requires heavy upfront work, but after that, it’s a maintenance game with steady check ins. You hire someone to help you get narrative right, then they leave, but they don’t really need to be full time. 2) your team will listen to / respect a full-time “expert” that comes to fix your narrative moreso than an internal junior hire.

Now, I do think that you can have members of your team who aren’t necessarily called “narrative leads” who do, in fact, help you craft and control the narrative, if they show up where your customers are. For example, the person or people running “developer relations” for the big AI labs are, to me, heads of narrative. Expense solutions platform Ramp hired Ara Kharazian as their “chief economist,” but a big part of his role is drawing insights from Ramp’s spend data to tell stories about the economy and share those stories with the world. His job description isn’t “create the narrative,” but that is, effectively, what’s he’s doing.

Even with a mega-sized AI lab like Anthropic, the way to “win narrative” is have a product marketing lead that serves at the junction of sales/GTM and product teams, ensuring that those selling the product know how best to portray their offering to those buying it compared to whatever else is on the market. The more embedded narrative is in the building and selling, the better, because it’s hard to just slap “story” on top of something no one cares about and expect them to suddenly start caring.

Put differently, Stephen Spielberg isn’t suddenly going to make “reinforcement learning” cool, but a suave product marketer can position Claude Code so that your typical developer thinks, “Oh man, this is sick.”

People try to get fancy with “storytelling,” thinking you need insane launch videos, dozens of dramatic case studies, and all sorts of other sexy assets to win over customers. It’s really just a mixture of charisma and empathy. You just need someone who understands both the customer and the product that can generate a bit of FOMO in your users over what you’re building. And maybe there is a particular person with a particular role who can artfully connect the dots between customer and product and macro and micro to help paint the canvas, but they have to be integrated with the core business itself. Narrative has never mattered more than it does now, but plug and play solutions probably aren’t going to fix your brand.

- Jack

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I moved back to New York this weekend. I mean, sort of. I flew a bunch of suitcases to New York on Friday because I’m about to head to a bachelor party in Florida on Thursday, and then I have to immediately turn around for a wedding in India, and then it’s right back to Georgia for the holidays, so I needed all of my stuff on the east coast. So I guess it’s more apt to say I’m “moving” back to New York in January. That sentence makes me quite happy to type out, because I love New York City. Seeing the skyline when I’m flying into JFK or LGA brings a smile to my face.

This may come as a surprise to some people who didn’t realize that I wasn’t living in New York, considering I was in town quite a bit over the last year. According to my mailing address, however, I was living on Lombard Street in San Francisco from February to December.

I initially moved to San Francisco for work when I took a new job at the beginning of the year, and frankly I had no idea what to expect when I arrived. It turns out, I liked San Francisco more than I expected. The Bay area is, to me, the prettiest part of the country. And for someone getting their first reps in the venture capital world, there’s not a better city for speedrunning your exposure to hundreds of startups in a condensed period of time. I also made a lot of new friends in San Francisco in 2025, many of them building a variety of cool, ambitious companies. I took tennis lessons and joined a basketball league for the first time in years, I blared Mistletoe by Justin Bieber on full blast in the back seat of my Waymo on the way to work, and, contrary to the videos I saw floating around Twitter in 2022 and 2023, I didn’t see that many homeless people. San Francisco is a cool city where you can see the future being built real-time.

New York has ten times the population of San Francisco, but San Francisco punches above its weight given the talent density in the tech scene, particularly in AI right now. It is funny how historical precedents tend to repeat themselves over and over and over again. San Francisco was a literal gold rush town in the 1800s, and now it’s a metaphorical gold rush town. The city was left for dead after Covid, then AI happened, and boom, everyone and their mother is raising $10m on uncapped notes to build “AI for dogs.” And an insane amount of money will be made (and incinerated) with this current AI boom.

New York and San Francisco both cater to the same archetype of high-achieving white collar worker who wants to make a lot of money in tech or finance, so naturally, they are compared a lot. “The only serious entrepreneurs start their companies in the Bay; New York has too many distractions.” “Silicon Valley is an echo chamber, New York is the real world.” “Value is created in San Francisco, it’s extracted in New York.” “The main reason to make money in San Francisco is to spend it in New York.”

I don’t have much to add on the culture war between the two cities. My only contribution is that the east coast just feels like home. I like San Francisco a lot. Candidly, I’d rather live there than my first post-college city, Atlanta, but it never quite felt like home. Maybe it’s because I’m originally from Georgia or that I went to grad school in New York, but I felt like a tourist in California. I love travel more than most, but spending too much time as a tourist wears on you, so it’s nice, after a year, to finally feel “home” again.

That being said, I’ll be back in San Francisco every month, because, you know, someone needs to invest in AI for dogs and crash YC’s demo day.

What I’m Working On:

“Finding” founders vs. “finding” creators. I was asked at a holiday party Friday night what I actually do for a living. Apparently “running an etiquette school” was a poor answer. The truth is that early-stage venture capital is a pretty weird job, but it all boils down to “finding compelling people building compelling companies.” The ways in which you do this can vary quite a bit. The thing about “startups” is that both investors and founders know how the song and dance goes. Founder wants to raise money. They build a product, pitch VCs, and say, “We want to raise $5 million at a $25m valuation to build AI for dogs,” and, after a few dozen pitches, a couple of VCs will probably say, “Great, we would like to fund your AI for dogs,” and they sign some documents and collectively own 20% of “AI for Dogs Inc.” There’s also a heavy concentration of founders in San Francisco and New York; the networks are tight-knit.

The creator game is a bit different. While we’re an early-stage venture fund that has been around for ~a decade, earlier this year we raised a separate fund to back creators directly. To us, “creators” are just a subset of founders who happen to have both distribution and community, but they are, at the end of the day, still founders building companies. The difference is in the discoverability. Everyone playing in the traditional venture capital game knows how the fundraising game works at this point, but most creators have never raised money, many have given little thought to what they might do with outside financing, and unlike the startup scene, which is pretty concentrated in SF / NYC, creators live everywhere. The question, then, is how do you get in front of the folks who both 1) want money and 2) have the scale / growth / business model where outside capital makes sense. I’m spending the next week or two kicking around different ideas, but given that many of you are either 1) creators or 2) friends with creators, I’m curious what thoughts y’all have on different locations (whether IRL or digital) that might serve as creator/founder hotspots. And, obviously, if you are one of such creators, hit my line.

What I’m Thinking About:

“We should tax the trillionaires out of existence.” A tweet by Texas state representative James Talarico went viral over the weekend in which the politician played into the well-worn “eat the rich” fervor, this type critiquing Elon Musk’s potential trillion-dollar net worth. A few quotes from the tweet:

“Do we really believe one man is worth more than every elementary school teacher combined?”

“What leads a person to accumulate more money than they could possibly spend in 100 lifetimes when there are people starving in this one?”

“We should tax trillionaires out of existence and use that money to guarantee food, healthcare, and housing for every single American.”

My problem with takes like this from politicians is that, rather than addressing the underlying causes of the issues at hand, they always frame the poverty of some as a consequence of the wealth of others, which, of course, just isn’t true. Wealth is not some “zero-sum” game; in fact, the companies that make their founders billionaires have made plenty of “normal” folks millionaires along the way, because wealth creation is a positive sum game in which anyone with an equity stake benefits. And the whole “tax _____ person out of existence to end _____ societal issue” is just so tiresome.

Hysterically, a few years ago, the UN World Food Program claimed that “2% of Elon Musk’s net worth could cure world hunger,” and Musk tweeted that “If the WFP can describe on this Twitter thread exactly how $6B will solve world hunger, I will sell Tesla stock right now and do it.” Crickets. Poverty is, in fact, a complex issue, and “redistributing money” while ignoring behavioral and environmental factors is a fool’s errand.

The existence of billionaires (and, perhaps one day, trillionaires) is a byproduct of a system that lifts people out of poverty. Those who take on the most risk with new ventures that prove to be quite valuable will make a lot of money if they retain their equity in that venture. And their employees will get rich if they have equity. And consumers benefit from new and cheap and interesting products. Musk could have, and, for his own sanity, perhaps should have, taken his $200 million from the PayPal acquisition and just… chilled. Served on some boards. Instead of rolling the dice on Tesla, SpaceX, and Solar City. Would there be less poverty in America had he not parlayed his money and doubled down? I doubt it. Political vilification of those with more money always strikes me as envy disguised as virtue.

“Narrative, narrative, narrative.” It seems like “head of narrative” is the new hottest job on the market today. Anthropic is offering a $400k base for “head of GTM narrative.” I’ve seen “chief storyteller” thrown around on a few job postings. I’ve even had a few companies hit me up for a few different versions of “will you help me with storytelling?” in the last month or so. I think, on one hand, getting the narrative right is more important than ever, and “story” is something that you can’t just outsource to ChatGPT, because your “story” is a living, breathing organism that must be constantly nurtured. But I also think it’s quite, quite hard to hire a “narrative lead” and force top-down narrative from a new executive position. My $0.02: the ways to really hone in on “narrative development” are 1) hire a consultant that’s really dialed on storytelling and have them coach the founder/CEO on how to sell their story, and 2) have incredibly charismatic sales leads that can paint this same vision to your customers. Founder raises capital, sales team sells product. They’re the ones who need to tell the story.

What denotes “status” in 2026? Being “hot” has been high-status since the inception of the internet, but between Nanobanana (Google’s image model) and GLP-1s, being “hot” (especially online) is now a commodity. Similarly, “travel,” particularly travel to Europe, was a higher-status pursuit in the 20th century when it was less attainable for the masses. Now that the “normal” consumer can afford a summer trip to Rome or Paris, wealthy Americans may as well opt for the Hamptons or Martha’s Vineyard. I’m curious what the next iteration of “status” objects are in 2026 and beyond.

- Jack

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Hello there, dear reader! Long time no inbox. I owe you a brief explanation for where I disappeared to over the past few months, so let’s get to that. If you recall, I’ve been working on a book for the ~past year, and, in July, I turned in my first draft to my editor. The moment I hit send, I thought to myself, “Thank God we’re done with that.”

Then I spent the next month not thinking one bit about my book, as I had rented an Airbnb in East Hampton with six of my buds. Over the next three and a half weeks, I spent a lot of time by the pool, drinking mud slides, listening to 27 renditions of “Mr. Brightside” by the Killers at The Stephen Talkhouse, etc. All in all, a pretty good summer. Better than most, for sure.

And then in mid-August I met a Bulgarian man in Queens to ship my jeep to San Francisco, and I flew back to California (my jeep made it in one piece), and I took another look at my book draft after stepping away from a month.

Thematically, it was what I wanted. But structurally, I had so much more work to do. I realized to actually get this book where I wanted it I was really just going to have to block out pretty much everything that wasn’t either 1) work, 2) book, or 3) the occasional 45-minute pump at the Marina Equinox. So I put blogging (and 90% of my social life, frankly) on the back burner, and pretty much all of my weekend time (besides hanging out with Will O’Brien on his birthday and Halloween), went to this book.

So, that’s basically what I’ve been doing over the last three months. Work and write and work and write and work and write.

This whole book process has really been an act of self-delusion and continual gaslighting as I convinced myself that there’s only “a little bit left,” at least 12 times, but after some aggressive restructuring and rewriting, I’m finally happy with what I’ve got, and I’m looking forward to sharing more with you all in 2026. I do think instead of a formal book tour, I’m just going to rent out my favorite dive bars in NYC / SF / Atlanta this summer where we can crush Guinnesses while I give out books vs. doing something at a book store because that feels so played out.

Stay tuned.

For now though, it’s nice to be pretty much done with that, and, for the first time in a year, have just “one job” and more bandwidth in my personal life again. And I can get back to blogging. Email interactions with internet strangers are one of life’s greatest joys.

That being said, it was nice to step away from this blog for a bit and think about what, exactly, it is that I want to get from this thing. “Young Money” has changed shape a few times since I started it. This was initially supposed to be a personal finance blog. But just writing about personal finance all day is boring. There’s only so many ways to tell people to invest in a Roth IRA and spend less than they make. So then I started writing a travel blog. And then I started writing about financial markets. And then random life musings. And then… you get the idea. I realized pretty early that I didn’t want “Young Money” to be any particular “type” of newsletter. I just wanted it to be me. It’s been more fun that way. When your content is “you” vs. being a particular thing you produce, you give yourself a lot more flexibility on what you write and how often you hit publish.

I used to churn out, I don’t know, like three articles a week. Which was a lot. I don’t have time to write three articles a week any more. And then I published one essay per week. But there’s nothing worse than trying to force some profound “long-form” blog post every week if you don’t have anything to say.

Now that I’m “back,” I’ll be resuming a weekly newsletter cadence. But the weekly newsletter won’t necessarily be long-form. Every Monday, I’ll share anything interesting I’m working on / thinking about, and, sporadically, I’ll pen the occasional long-form essay as the ideas hit me. Maybe that’s twice a month. Maybe it’s once a month. Maybe it’s once a week. I don’t know. But I do think a much more effective conduit for writing is keeping the “what I’m up to” structured, and letting the brain blasts hit your inbox as they hit my brain.

I say all that to say, it’s good to see you in your inbox again. Catch you next week (and the week after that, and the week after that).

What I’m Working On:

• Etiquette School: Earlier this fall, I went to Y Combinator’s “Demo Day” to market our Slow Ventures Etiquette Finishing School to different founders. This initial idea was light humor around the “wear hoodies and dress like shit” meme that describes typical SF dress code today, but after 70+ people expressed interest in coming to Etiquette School, we decided to do it live, bringing 50+ people together at the Four Seasons in downtown San Francisco a month later for a 3 hour, 5-panel-long mini-conference on improving one’s social etiquette. That event was a hit (see below for caviar bumps and vodka shots), and we’re now hosting several around the world in 2026, but, in the meantime, we also published a ~100 page Etiquette Handbook for anyone who just can’t wait for the IRL event. Grab your copy here.

• Vibe-coding project: I’ve been increasingly vibe-coding my own personal software suite using Claude Code, and my most recent tool is rolodex/personal CRM that I now host in a Google Sheet. I’ve been iterating on this for a few months now, first pulling in all of my contacts from Twitter / Email / Linkedin / Text, running my DM history with each through an LLM to give context on how I know them, and then consolidating repeats, and I’ve now added an automated weekly email that pings me with any to-do’s / outstanding followups with anyone on the list. I cannot stress enough how much a centralized personal rolodex helps, particularly in the job I have now, and Gemini is getting so good now that I can ask it “help me find 10 founders to invite to a dinner in San Francisco next week,” and it does most of the sorting/searching for me.

• “ChatGPT Wrappers": One of the more interesting things about investing at the seed stage right now is that it’s incredibly easy to make a “decent-looking” v1 product to pitch to investors, and the biggest two questions I always have are “how durable is a moat here if this works?” and “what’s actually going on on the back-end, besides OpenAI API calls with a pretty UX?” A couple of weeks ago, I read this Medium post where the author claimed to have reverse-engineered 200 AI startups, and ~3/4 of them were just repackaged ChatGPT / Claude with a new UI, selling prompts are markups. It’s one of those things that everyone kind of knew was happening, but then you see the phenomenon quantified and think, “Damn, I don’t want to get tricked.” So I’ve started working through Andrej Karpathy’s videos / essays on how LLMs work structurally + playing around a lot in Python to improve my ability to quickly discern the right questions to ask diligencing these companies to better determine what’s real, and, more importantly, what’s actually hard / impressive rather than what “looks good” during a pitch. I’m open to any and all recs from anyone on best practices for refining my bullshit detector on some of this stuff.

What I’m Thinking About:

Robinhood positioned to dominate prediction markets. The big story of the week was Robinhood’s and SIG’s acquisition of 90% of LedgerX, a CFTC-regulated Designated Contract Market and Derivatives Clearing Organization. In their last earnings report, Robinhood noted that prediction markets were now a $100m+ ARR business with 9 billion contracts traded on its platform since launching a year ago, so it’s not a shocker that they’re doubling down on this business line. What’s interesting is how this move might reshape the prediction market “market.”

Robinhood had previously partnered with Kalshi to launch its prediction markets because Robinhood needed a licensed DCM, and Bloomberg reported that ~half of Kalshi’s volume was coming through its Robinhood partnership. The irony here is that Kalshi did most of the work to legalize prediction markets in the US in the first place, winning a multi-year legal battle last fall allowing them to launch election markets before the presidential election, but now all evidence suggests that Robinhood is looking to deprioritize their current partnership and run their prediction markets in-house. It’s also worth noting that SIG, who now co-owns LedgerX with Robinhood, was the first institutional market maker on Kalshi.

I’m going to write a longer piece on this next week after I do more research, but my bet, which I’ve been saying since before the Robinhood/LedgerX news, was that if prediction markets stick, Robinhood is going to win because distribution is the only thing that matters. With enough money, you can either buy the infrastructure stack needed or lobby your way to getting licensed yourself, at which point it’s a customer acquisition game. Robinhood has ~28 million users buying stocks, options, and cryptocurrencies in both taxable and retirement accounts. They have a credit card. They’re launching banking. It’s much lower friction re-allocating a few hundred dollars from stocks to a prediction market bet on the same platform than it is to transfer money to another site to place those same bets, giving them a massive entrenched advantage. The result: more than a million Robinhood users traded at least one prediction market contract since they launched.

Part of me thinks I have to be missing something and it can’t be this simple, considering that Kalshi and Polymarket both just raised at ~$10 billion valuations (Robinhood, now worth > $100b, was worth less than $10b itself just two years ago). Part of me thinks those deals would have looked different if the investments were closed after the Robinhood news, and some investors are probably sweating right now. More to come here.

What I’m Reading / Watching:

• I hadn’t read a new book in the last eight months, which is frankly a bit disgusting as someone who enjoys reading, and I have a whole backlog of books that friends have sent me or recommended + dozens that I’ve downloaded sporadically as I saw them rec’d on X. Now that I’m done with my book, I’m reading again, which means I’m also back to recommending books I’ve enjoyed. I just finished Private Equity: A Memoir, by Carrie Sun, and I highly, highly recommend it for anyone interested in an inside look at the high-stress, hyper-competitive New York hedge fund world. Carrie worked as an assistant for Chase Coleman, founder and managing partner of Tiger Global, in the mid-2010s. I found myself growing anxious reading her internal monologues as she struggled with the all-consuming nature of being the right hand person for one of the most successful fund managers of the 2010s. This isn’t an investing book, it’s a psychological story that shows the tradeoffs that come with “success.” It’s a really, really good read for the hyper ambitious-but-uncertain young professional.

• David Senra remains the best of the best among podcast interviewers, and his recent interview with Michael Ovitz is excellent.

• I’m a total sucker for “year in review” types of content around holiday season. Here’s a good list of questions as you reflect on the last year and prepare for the next one.

See you next week,

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!

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A quick PSA: 1) several of you have sent me some very cool leads / intros of different creators / entrepreneurs to chat with, thank you I love you all. 2) I do read all of my email replies and try to respond to as many as I can, so if you have someone you think I should meet, def shoot me a note!

Write it down, write it down, write it down.

As a “non-technical” San Francisco resident (a slur used by software engineers and programmers to describe normies like me who weren’t building React apps pre-ChatGPT) during an AI boom, I think it’s important to ramp up my knowledge base on how all of these AI tools work under the hood. This would, of course, make me better at my job as an investor, but it’s also a hubris thing. It annoys me when I’m interested in a thing, or I use it a lot, and I don’t really know it works.

My method for speed-running this knowledge acquisition has increasingly been to build things using the technology that I’m interested in. Pre-AI coding assistants, this would have been difficult to do without a programming background, but now with Claude Code / Cursor / ChatGPT, you really can “just do things.”

My most recent interest was learning how to fine-tune a model. You hear about “fine-tuning” and “training” models all the time, but what does that actually mean? Like, what are you, the “fine-tuner,” actually doing? So I decided to fine-tune one of OpenAI’s models by training it on all of my travel blogs to create an chat model that can generate “Jack Raines-style travel blogs” on a whim.

The whole process only took a few hours, and after taking it live, I took another hour or two to document the whole process for future record.

I’ve always been a big proponent of “writing is thinking,” and I have always thought process documentation was important, which shouldn’t be a surprise considering that I am a writer. But I think the importance of slowing down and writing out your thoughts and processes has increased 10x now that AI tools are so prevalent.

Why?

Because knowledge acquisition used to be an automatic consequence of doing or researching anything, but thanks to AI, the end result the the knowledge formerly created by reaching the end result have become decoupled. Writing is the forcing function to ensure that you actually retain knowledge from AI-enabled projects.

Pre-ChatGPT, it was pretty difficult to reach your end result or ideal output without learning how the thing you’re trying to build, or the idea you’re trying to research, works along the way. Three years ago, if you wanted to create a simple python tool that allowed you to forward emails to a particular address and receive Spanish translations of those emails a few seconds later (I spun this up a few weeks ago), you would have had to understand the logic of the code itself and be very intentional about the software stack you used to connect all of the pieces for it to work. Your intuition was being refined the entire time you were building the thing.

Now? You can hack the whole thing together in a few hours with coding assistants without having any idea how the backend that you just built “works.” The result? You have a functional tool, but your actual “learnings” from building that tool are minimal. If you spend an hour or two after building the tool to document your process, however, you’ll retain much more knowledge of “how” you built the whole thing, which will allow you to move faster and more purposefully on future projects, and if you take the time to read through the script(s) and analyze what the code is actually doing, your intuition about coding logic will improve. Again, pre-AI, your intuition was strengthened simply by doing the work. But now that you can streamline 90% of the labor, you have to be intentional about the learning.

The same is true for anything “research-y.” Say I’m digging into the marine robotics space as diligence for a couple of investment opportunities. I could almost-certainly offload most of the cognitive load of the “research” to a Gemini deep research report, and read through a thorough, well-written, AI-generated report after. The problem is that your fully-AI-generated report will be logically sound, and while reading it will obviously inform you about your topic of interest, reading without writing won’t reveal to you all of the things you don’t know.

The process of writing about a topic makes the holes in your knowledge base immediately obvious because you’ll be stopped mid-sentence when you’re working through an idea as you encounter an information gap. Those information gaps inform the direction of your research, and you accumulate more and more knowledge as you seek to fill those information gaps. You have to do the writing yourself to retain the lion’s share of the ideas, and more importantly, to strengthen your intuition over time.

Writing is also powerful reinforcement learning: ideas stick with you better when you write them out and read them. That’s not to say that we shouldn’t use AI assistants. Claude Code is fantastic, and my ChatGPT usage is absolutely contributing to global warming. But if you aren’t retaining the knowledge related to your work, AI isn’t giving you leverage. It’s turning you into a commodity.

What I’m Working On:

• Here’s the full blog post on building the Travel Blog GPT. The whole thing took a few hours; you can probably use my code + download your own content and spin up something similar if you’re curious. Links to my Github are included in the post.

• I also spent part of the weekend spinning up a “niche subreddit” scraper to look for some potentially interesting leads for our Creator Fund. Again, if you, or someone you know, has built a compelling social media presence around a particular niche, and they’re building a business on top of that, I’d like to chat. I’ve met some really cool folks the last few weeks thanks to you guys.

• We are launching a Slow Ventures etiquette school for founders. (I’m serious, see Sam’s tweet here). Too many founders have mastered the art of fine-tuning LLMs and raising capital from VCs, but what about soft skills like setting the table, maintaining eye contact, and how to properly mix a drink? This is not a joke. If you want to join cohort one, add your info here.

What I’m Interested In:

• AI’s impact on education. AI could, and should, disrupt a lot of fields, but so far, much of the economic impact, outside of coding, has been “meh” due to slow enterprise adoption and edge case issues. That being said, I think education and “how we do school” is on the verge of being turned upside down due to a mix of factors, namely: shifts in societal expectations of school, rising costs of education, and AI’s ability to create personalized lesson plans catered to students. I met a super interesting founder building an alternative school system last week, and I also thought this Patrick O’Shaughnessy interview with Joe Liemandt on “Alpha School” was fascinating. Ed-tech is traditionally a tough market, but I do think this is one of the places where AI isn’t just a shiny toy, but a legitimate force of change.

• Upstart media companies are growing up. One reason that traditional media companies have struggled in an increasingly-digital and short-form world is that their teams and headcounts no longer match the current reality. The result? Wages that haven’t kept up with inflation and constant layoff cycles. The winners of this shift were the creators who, realizing they now had the ability to create their own platforms on Substack, beehiiv, and other newsletter platforms, went independent, stayed lean (and often solo), and built six-and-seven figure profitable businesses on their own. It’s easier to build a lean business from scratch that can adapt to the new world than try to change a 100-year-old institution (though The Wall Street Journal is trying: they are hiring a “talent coach” to teach journalists how to be creators). But the “upstart” media companies are hardly upstarts anymore. A couple of examples: Emily Sundberg (founder of FeedMe / friend of the newsletter) just announced two new hires, and Paramount is looking to buy The Free Press for $100 - $200m. I’m curious to see how headcount sizes, hiring priorities, and the scopes of media roles continue to evolve as some of these “newer” media businesses continue to mature.

What I’m Reading:

• The Patrick O’Shaughnessy episode with Joe Liemandt is a must-listen if you’re at all interested in AI’s impact on education or how students actually “learn.”

• I was digging into the DTC / food space last week, and this conversation between Alex Hormozi and ButcherBox founder Mike Salguero on how Mike bootstrapped the business to $550m is great.

• Henrik Karlsson is such a good essayist; love his recent article on the transformational power of sustained attention.

• OpenAI is paying how much for a content strategist?

  

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!

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Summary:

I fine-tuned OpenAI’s GPT-4o mini by feeding it the full history of my travel blogs, and the result is that I now have a “Jack Travel Blog GPT” that can create travel blogs, in my tone, based on prompts such as, “Write a travel blog in Jack’s voice about his trip to India for his friend Tanmaye’s wedding. His friends Antonio and Ben tagged along as well.”

I can create these by either calling the model in my own terminal, or by running it in an OpenAI Sandbox.

Idea Inception:

I wanted to get some reps “fine-tuning” or “training” an AI model, largely because I knew what that meant in the abstract, but I wanted to be able to do it myself to know what’s going on under the hood. In general, I’ve been trying to “upskill” on different technical things anyway.

A few days ago, I realized a good test case would be to make a “Jack Raines Blog GPT” that can mimic my writing style, and travel blogging, specifically, would be a good way to do it. My reasoning for choosing travel blogs is because the “type” of writing is more focused/refined, thus easier to evaluate how the model is performing. While all of my writing has irreverent undertones, the travel blogs, specifically, lean into casual tone and humor with depth interjected throughout. I also “date” each day and include a lot of back and forth dialogue, so it’s more obvious whether or not the LLM is actually adopting my structure.

Figuring out my tech stack:

My full tech stack would include ChatGPT, OpenAI’s API, and Claude Code within my computer’s terminal.

I created a new ChatGPT project called “Fine-tuning LLM on blogs” and asked it “I want to ‘fine tune’ an LLM on several of my blog posts. How do I get started doing that?” (See screenshot below). ChatGPT asked if I wanted the model to mimic my tone (fine-tune a model) or retrieve answers from my content (RAG). It then gave examples of different models I could use.

The two options I considered were OpenAI and open-source alternatives like Mistral or Llama. I opted for OpenAI for a few reasons:

• This is my first time doing this, and working with OpenAI’s models would minimize all of the “other” steps I have to deal with such as figuring out hosting, compute, and security. I just want to take a model and adjust it to write like me, I’m not worried about having full access to the model weights for this, so open-source wasn’t a concern.

• OpenAI has clear documentation on how to access its API and test different fine-tuned models in a sandbox environment.

• I have familiarity with using OpenAI’s API on a few other projects and already had $100 in credits on my account.

  

After deciding to use OpenAI’s models, my plan was to use ChatGPT to occasionally “prompt” and ask questions about the process, while writing the necessary python scripts in my terminal using Claude Code.

Claude Code is a coding assistant that integrates directly with your computer’s terminal. Similar to Cursor, it can create and manipulate files directly in your computer based on natural language prompting.

Preparing the Data:

I went to Substack and exported all of my data, downloading HTML files of all of my posts. Per ChatGPT, I needed to format my data in JSONL (JavaScript Object Notation Lines) for fine-tuning the model. I placed all of the blog html files in a folder called “Blog Posts” on my desktop and asked Claude Code to “create a python script that would take all of the html files of my blogs posts and convert them to JSONL files in order to use the text from my blogs to fine-tune GPT 4o mini, because I wanted to create an AI model that could ‘create travel blogs in Jack Raines’ voice based on his blogs.’”

Claude created this python script with 65 JSONL examples of my blog post. Each line in the JSONL was formatted as follows:

{"messages":[
  {"role":"system","content":"You are Jack Raines, writing witty, reflective blog posts."},
  {"role":"user","content":"Write a blog post about moving to NYC in your 20s."},
  {"role":"assistant","content":"Moving to New York in your 20s feels like... [your blog text here]"}
]}

The data is formatted like this because chat models are trained to expect inputs in a conversational format, and the model needs examples of what the system should be optimizing for (general framework for the outputs), what types of prompts the user would ask (what you type in the chat interface), and what outputs the chat should produce in response to your prompts (the generated blog posts).

The JSONL file and the python script used to create the JSONL were added to a “Jack AI Finetuning” folder on my desktop.

Next, I went to OpenAI’s developer platform, created a new project called “Jack Blog AI,” generated a new API key, and bought an additional $20 worth of credits.

I used Claude Code to create an “env” file to store my API key in this folder as well, so I could make API calls to OpenAI from my terminal without exposing my API key in my code.

Finetuning the Model:

Next, I went back to Claude Code, installed the OpenAI python client (pip install --upgrade openai), and asked Claude Code to “fine-tune OpenAI’s gpt-4o-mini model with my jack_blog_finetune_dataset.jsonl file.”

I continually ran into issues with this, as Claude Code repeatedly flagged that “gpt-4o-mini is not available for fine-tuning.” I asked ChatGPT if the model name needed in the code was “gpt-4o-mini” or something different. ChatGPT flagged that the specific model name was “gpt-4o-mini-2024-07-18.” I noted that in Claude Code, then the model connected correctly and the fine-tuning process started (See screenshot below from my Claude Code interface)

20 minutes later, I received an email that my model had finished Finetuning.

Testing the Model:

I didn’t realize this before getting started, but OpenAI’s developer platform has a sandbox environment for testing and finetuning models, so I logged back in to start testing mine. (see screenshot below for a screenshot of the interface):

This looks complicated, but basically what’s happening here is that I can further adjust the system settings (when writing this, be moderately hungover) to set the vibe, and I can pre-set prompts with variables so I more quickly test the same prompt with one variable changed. In the context of writing travel blogs, I made the variable “city,” so I can sub in “Sydney,” “New York,” etc. The output, when I make the “city” variable in the bottom right “New York,” and hit the up arrow, looks like this:

I also wanted to be able to use this new model from my Claude Code terminal interface, so I asked Claude Code to “create a simple python script pulling from my newly-created model that will allow me to generate Jack Raines style travel blogs by submitting prompts in my terminal.”

Claude created this python script, which was surprisingly simple.

I can now type “python JackBlogGPT.py ‘Write a blog post about Jack ____ in _____ with ___,” and it will generate directly in my terminal:

Pretty cool. I also only spent $1.48 between fine-tuning and running the model on OpenAI, and $0.28 with Anthropic for my token usage from coding.

End result: I can now generate endless entertainment with blog posts that sound like a caricature of me traveling to hypothetical cities.

Learnings / what could I have done differently?

I could have done the full fine-tuning process in OpenAI’s platform instead of adding the extra step of doing it through Claude Code and it would have been faster. In reality, I was using my terminal to “fine-tune the model in OpenAI’s developer platform” instead of going to the platform myself. It took me a good 20 minutes to figure out the issue with how I had named the model, and that wouldn’t have happened on OpenAI’s platform.

This whole process was relatively simple and quick. Compared to some of my other “vibe coding” projects, this whole thing only took a few hours from inception to completion, between exporting and cleaning the data and fine-tuning the model. It was incredibly simple.

Other things I could do from here:

• “Fine-tuning” a text model is pretty simple; I would like to do something similar with image/video if it isn’t too cost prohibitive.

• The initial question ChatGPT asked me of whether I was trying to mimic the writing style or pull specific answers (which would involve RAG) was interesting. I think I’ll set up something similar to have a RAG tool for querying my personal CRM/rolodex for asking questions like “who in my network should I invite to XYZ thing.” Right now my rolodex is a Google Sheet; might move it to a SQL database.

- Jack

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“Yeah, but how hard are you working?”

Burning Man came and went last week, and according to this article by the San Francisco Standard, the crowd keeps getting older and older. The reason? All of the Bay Area zoomers have exchanged alcohol and ecstasy for “lifting heavy” and “9-9-6” work schedules.

In previous eras, Burning Man meant the clearing out of techies from the Bay Area in favor of a week on the Playa. However, more and more local startup founders and investors are now choosing to skip the annual pilgrimage.

“The culture has shifted,” said Jenny He, founder and general partner at Position Ventures. “A lot of young founders I know don’t really drink or party. They’re heads down working long hours, building brands, and creating content.”

Daksh Gupta, the 23-year-old cofounder of AI code review Greptile, said Burning Man hasn’t really been part of the zeitgeist since he moved to San Francisco in 2023.

Gupta, who has become a poster child of AI boom’s grindcore culture, summarized the current mood among young tech workers in San Francisco as incompatible with the Burner sensibility: “The current vibe is no drinking, no drugs, 9-9-6 [work from 9 a.m. to 9 p.m., six days a week], lift heavy, run far, marry early, track sleep, eat steak and eggs.”

The 9-9-6 rise-and-grind ethos is very much a thing in the SF tech scene right now. Water and tea at happy hours, “cracked engineers” coding away deep into the night, all in the name of B2B SaaS, or building AGI, or whatever. While there are exceptions, I think much of the “being seen grinding late into the night day-in and day-out” is a bit performative in nature. It also hinders, not helps, a company’s performance in the long-run.

Bryan Johnson, aka the “Don’t Die” guy, has tweeted hundreds of times about the value of quality sleep, and the detrimental impacts of not getting enough sleep. I’m not a “don’t die” disciple, but considering that Johnson has been meticulously measuring the impact of sleep on his cognitive performance and mood for years, I trust him on this one.

The good news? This lifestyle isn’t necessary to do good work. In Cal Newport’s newsletter this week, he shared a valuable highlight from one of his old blog posts from 2008:

I found writing my thesis to be similar to writing my books. It’s an exercise in grit: You have to apply hard focus, almost every day, over a long period time.

To me, this is the definition of what I call hard work. The important point, however, is that the regular blocks of hard focus that comprise hard work do not have to be excessively long. That is, there’s nothing painful or unsustainable about hard work. With only a few exceptions, for example, I was easily able to maintain my fixed 9 to 5:30 schedule while writing my thesis.

By contrast, the work schedule described by the anonymous grad student from above meets the definition of what I call hard to do work. Working 14 hours a day, with no break, for months on end, is very hard to do! It exhausts you. It’s painful. It’s impossible to sustain.

I’m increasingly convinced that a lot of student stress is caused by a failure to recognize the difference between these two work types. Students feel that big projects should be hard, so hard to do work habits seem a natural fit.

For context, Newport has collectively sold well over 2,000,000 copies of his eight books and counting, he produces a weekly newsletter and podcast, and he has been a tenured computer science professor at Georgetown since he was 33. Not bad for someone who sticks to a 9-5! The differentiating factor (as noted in his blog post) is focus.

I’ve gone through short stretches where extended hours were required to finish a project (like locking myself in a hotel for two weeks to write a book), but those occurrences are outliers, not norms, and even that was more a consequence of extended procrastination than some inevitable outcome that couldn’t be avoided.

Most of the “9-9-6” 12-hour daily grind is, in my opinion, a consequence of context switching, procrastination, waiting on replies/feedback from others, and doing things that “look like work” than it is a requirement for quality results.

Tell me if the following situation sounds familiar:

You start off researching a company or industry, you see a relevant tweet, then, 27 minutes have gone by before you realize you were absentmindedly scrolling. Oh, and you have a series of six tasks to complete today, and you get 60% of the way done with the first, but then you check your inbox, and there’s an email that you “have to respond to right now” (you don’t), which breaks your concentration, and there goes another 20 minutes of cognitive offloading and onloading.

And maybe after sending that email, you start working on another task on your to-do list instead of resuming the first one, and at the end of the day you have a half-dozen things that you’ve sort of done, none are near completion, so, even though it’s now 6:00 PM, you sprint through tasks 1-3 to at least complete something that day, and you wrap up around 8:30. I mean, sure, you “worked” ~12 hours, but the last two hours were more valuable than the first ten.

I would be curious to see how much of a typical “9-9-6” is spent procrastinating, context switching, and “attempting to work,” rather than doing the work itself. In my experience, focused blocks of work can give you the same results much faster (plus, it leaves you time to touch grass).

What I’m Working On:

• In 2020, Brian Portnoy and Josh Brown wrote one of the better investing and personal finance books out there called How I Invest My Money. The TLDR is that most investment professionals spend years helping clients manage their portfolios with little discussion of what they do with their own money, and in each chapter of How I Invest My Money, a different investor shares the reasons behind their own investment processes. I was asked to write a chapter in the new edition coming out next year, and I spent the back half of my working on it. Very excited about this.

• In other book news, I got my edits back from my editor, so it’s back to my own book grind for a bit. Probably going to run back my Spring 2025 playbook of Friday-Sunday writing, writing, writing for the next month, though editing seems to be a bit easier than turning a blank page into 60,000 words.

• We (Slow Ventures) are hosting a Creator CEO Summit in Los Angeles on September 18th to discuss how different entrepreneurs and operators are leveraging social media platforms to scale their businesses. Space is very limited with 70 spots reserved for different creators and operators, but if this is you, and you’re in the area, shoot me an email.

What I’m Interested In:

• I had an interesting conversation with Carter Abdallah (total homie, introduced by mutual friends from Atlanta) about the Gen-Z nihilism and the issue of young men “opting out” of society today. For context, Carter is a software engineer at Nvidia, but he also has 400k+ followers on his socials and a lot of his content is focused on life advice for younger dudes. Young men are increasingly impatient with their careers and finances, rising costs of living are painful, no one is going out / having sex, etc. Meanwhile, the “gamification of everything” from sports betting to stock trading has made the temptation of “risking it all” on a roulette spin more compelling than playing a long game, for many. This, obviously, isn’t great, but I’m curious what the fix, if any, will be.

• While I don’t envy my friends who went through the investment banking gauntlet out of undergrad or business school, I do think, if you’re doing anything remotely-related to finance or investing (such as VC!), it’s good to at least have some barebones Excel / financial modeling skills. As a result, in the name of “upskilling,” I’ve been digging through a couple of general modeling Wall Street Prep courses over the last week.

• Snap’s commitment to dumping every ounce of operating cash flow, and then some, into stock-based compensation, should be studied.

What I’m Reading:

• The Cal Newport article I mentioned earlier on fixed-block scheduling is a great read for anyone else who struggles with procrastination and context switching.

• A relatedly-hilarious (but valid) blog post from a Stanford professor about using “useful” procrastination to get more done by gaslighting yourself, basically.

• One of my favorite Twitter accounts is “Blueprintsmb.” He’s an anonymous account that has been documenting his journey of going from the hedge fund world to running a small manufacturing business. Anyway, he shares occasional “life advice anecdote” types of posts from conversations with young professionals in NYC, and this one was particularly good.

- Jack

I appreciate reader feedback, so if you enjoyed today’s piece, let me know with a like or comment at the bottom of this page!