1. K

   kache@yacineMTB · Feb 3

   you can outsource your thinking
   but you cannot outsource your understanding

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2. You should try contra dancing

   A popular icebreaker in San Francisco these days is “How would you spend your life if AGI meant nobody needed to work?” For me, I think a surprisingly big part of the answer is a dorky-sounding kind of folk dance called contra dancing.

   It is a fun question to answer. I wonder if the answer for me is in the next couple of links.

3. My year of timelessness:

   Once I committed to my writing, life lurched forward and started moving again. I regained the ability to arrive on time. I learned how to excuse myself from conversations. I came up with a posting schedule and created a process for my essays. I still can’t estimate time very well, but there are tools to help: calendars, timers, reminders. My days became infused with the urgency of excitement. And with the arrival of spring, my year of timelessness came to a close.

4. The Varieties of Jhanic Experience:

   A remarkable, reliable means and all-round aid to the purification of mind and consequent clear seeing is the practice of jhana, what the Buddha defined as samma samadhi, right concentration.

1. THE PEOPLE DO NOT YEARN FOR AUTOMATION:

   In fact, the polling on this is so strong, I think it’s fair to say that a lot of people hate AI, and that Gen Z in particular seems to hate AI more and more as they encounter it. There’s that NBC News poll showing AI with worse favorability than ICE and only a little bit above the war in Iran and the Democrats generally. That’s with nearly two thirds of respondents saying they used ChatGPT or Copilot in the last month. Quinnipiac just found that over half of Americans think AI will do more harm than good, while more than 80 percent of people were either very concerned or somewhat concerned about the technology. Only 35 percent of people were excited about it.

   These are not my feelings but I understand them. I worry about how this will manifest politically, in China and here. And what do the Chinese feel about AI? Maybe the next three links provide a reason to not hate AI.

2. The task is not the job:

   A job is a bundle of tasks. The real question is not whether AI can perform one component of the bundle. It is whether that component can be separated from the rest at low cost, as we discuss in a recent working paper. When that separation is cheap, the bundle is weak: AI takes a piece, the human role narrows, and labor loses share. When separation is expensive, the bundle is strong: AI helps with part of the work, but the human still sells the full service and keeps the larger share of the revenue.

   Many thought travel agents would be eliminated by online booking. As Ernie Tedeschi of Stripe Economics showed this month, travel agent employment is now more than 60% below its dot-com peak. For most of what agents used to do —searching flights, comparing hotel rates, issuing tickets— the bundle was weak. Separating the booking task from the human was cheap, and once it was cheap, the task was gone. But something else happened to the agents who stayed. They moved upmarket, charged planning fees, and joined luxury consortia that offer upgrades and personalized itineraries. In 2000, average weekly earnings at travel agencies were 87% of the private-sector average. By 2025, they had reached 99%. The surviving agents earn more per hour than they used to, precisely because the machine took the weak part and left them the strong one.

3. What will be scarce?:

   If this is right, then AI won’t just automate the commodity economy. It will trigger the emergence of something new: a post-commodity economy, where a growing share of expenditure goes toward goods and services whose value is inseparable from the human who provided them. The same economic forces that moved 40% of the American workforce off farms and into factories and offices will move workers out of automatable commodity production and into what I’ll call the relational sector. By this I mean the human-intensive, provenance-rich, sometimes artisanal part of the economy where the human aspect is part of the value of the good or service itself. The economics of scarcity won’t disappear, it’ll just relocate.

4. The Jevons Paradox and Insatiable Humans: Why AI Won't Empty the Finance Suite:

   when something becomes dramatically cheaper to use, we don't use less of it. We find a million new uses for it — because applications that were previously unthinkable become affordable.

   The intuition here is that if a company was willing to pay $100K for a software engineer, it was because the average engineer was generating more than that much in value for the company. If the same engineer can now be 10x as productive i.e. if they can now generate $1m in value for the company, would the company hire more or less software engineers? Unless you assume that there is only a fixed amount of work to be done, they would hire more. Historically that assumption has been wrong.

   This is a "paper" but reads very much like an article. Recommended.

5. Is Mythos for real? It seems so:

   As part of our continued collaboration with Anthropic, we had the opportunity to apply an early version of Claude Mythos Preview to Firefox. This week’s release of Firefox 150 includes fixes for 271 vulnerabilities identified during this initial evaluation. [...]

6. I can never talk to an AI anonymously again:

   But soon, the entire debate over internet anonymity will be as anachronistic as an iPod Touch. That’s because Claude Opus 4.7 is here, and last week, I discovered it could identify me from text I had never published, text from when I was in high school, text from genres I have never publicly written in. And if it can identify me, soon, it will be able to identify many of you.

7. Why are you like this: Freaky.

8. This will be me.

   AH

   Awni Hannun@awnihannun · Apr 24

   Adopting Claude speak in my regular life, episode 1:
   
   Partner: Did you do the dishes tonight?
   Me: Yes they're done.
   Partner: Why are they still dirty?
   Me: You're right to push back. I didn't actually do them.

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After last week, did you not expect mean reversion?

1. Sites Unseen: What Travel Is Like for Those Who Can’t See:

   Amar Latif, a British entrepreneur, founded Traveleyes in 2004 to address the lack of accessible travel options for blind and visually impaired people. After losing most of his sight by age 18 because of retinitis pigmentosa, Mr. Latif struggled to travel independently. Mainstream tour companies often rejected him, insisting he bring a caregiver and excluding him from more adventurous activities like hiking and skiing. Those exclusions pushed him to create something of his own: a company that would allow blind travelers to explore the world without relying on friends or family. “Friends and family switch off,” he told me. “They’re not as eager to describe things.”

   Traveleyes runs on a simple but radical model: It pairs blind and sighted travelers as equal companions. Sighted participants assist with navigation and describe visual details — in exchange for a discounted trip — while blind travelers bring a fresh perspective that often deepens the experience for both. The company promises “a truly multisensory travel experience,” with itineraries designed to engage all five senses.

   Loved the ending.

2. What happens when you don't die on time?:

   Bit by bit, she emptied her bucket list — and, not insignificantly, her bank account — and now, at 34, is left to wonder: “What next?” She wasn’t supposed to be here now. She’d prepared for that final trip. And now it’s on hold for … well, no one knows for how long.

   These days, the questions she finds herself circling are unexpectedly ordinary. Should she look for a job? Should she consider dating? They’re the kinds of decisions that assume time — not just months, but years — suddenly a strange constraint when trying to plan a future. She had already organized her life around an ending. Now she’s expected instead to plan for something open-ended.

3. The Hidden "Hand Farms" of India: Fueling the AI Robot Revolution with Human Motion:

   Dubbed "hand movement farms" or data capture labs, these unassuming facilities employ hundreds of workers who strap cameras to their foreheads and spend hours meticulously folding towels, stacking boxes, and manipulating everyday objects. This isn't performance art or a quirky TikTok trend; it's the backbone of training humanoid robots to mimic human dexterity.

4. AM

   Anish Moonka@anishmoonka · Apr 17

   Before it took off, the bird ate parts of its own liver, kidneys, and gut. That was the only way to be light enough to fly. Then it flew 8,425 miles from Alaska to Australia, in 11 days, without eating, drinking, or landing once.
   
   The bird is called B6. It's a bar-tailed godwit, four months old, weighing about as much as a can of beans. In October 2022, scientists at the US Geological Survey tracked its flight from Alaska all the way to Tasmania. The trip took 11 days and 1 hour. It is still the longest non-stop flight of any animal on Earth.
   
   For two weeks before takeoff, godwits eat until they almost double in weight. Fat ends up being 55% of their body, more than any bird ever measured. Then they shrink their own insides. About a quarter of their liver, kidneys, stomach, and intestines gets broken down and reused for fuel, making room for the extra fat and cutting weight. Their heart and wing muscles grow bigger at the same time.
   
   They never drink along the way. The water they need comes out of burning fat, the same reaction their muscles use for energy. They also never really sleep. B6 flapped its wings for 264 straight hours, cruising around 35 miles per hour with help from storm tailwinds. By the time it landed, it had lost almost half its body weight. The shrunken organs grew back over the following weeks.
   
   Scientists still cannot explain the navigation. B6 had never made this flight before. Adult godwits leave Alaska weeks earlier, so young birds fly alone with nobody to follow. How a four-month-old bird finds its way across 8,425 miles of open ocean to a place it has never seen is still an open question.
   
   About 100,000 bar-tailed godwits leave Alaska every fall. Most of them land in New Zealand or Australia 10 or 11 days later, having eaten parts of themselves to get there.

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An (almost) AI free post - have I unlocked a new achievement?

1. Slop Watch: GLP-1 Edition:

   We did find some Reddit comments, though, warning other netizens to steer clear of MEDVi, claiming serious allegations of possible HIPPA violations, shady billing practices, and even damaged vials of seemingly bogus drugs causing physical harm.

   AI is making the web weirder and muddier than ever. And though MEDVi promises that “sometimes you have to see it to believe it,” in our burgeoning AI-powered web, that’s no longer the case.

   MEDVi, sadly, is the same company from last week's NYT's article about a one-person, $1.8bn company. It is disappointing to see NYT fall for their hype despite this article being published almost a year ago.

   This, yet again, also raises the question of just how credulous and naive am I being when it comes to the AI Hype cycle. Keep that in mind with rest of this week's coverage.

2. Project Glasswing:

   Today we’re announcing Project Glasswing1, a new initiative that brings together Amazon Web Services, Anthropic, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorganChase, the Linux Foundation, Microsoft, NVIDIA, and Palo Alto Networks in an effort to secure the world’s most critical software.

   We formed Project Glasswing because of capabilities we’ve observed in a new frontier model trained by Anthropic that we believe could reshape cybersecurity. Claude Mythos2 Preview is a general-purpose, unreleased frontier model that reveals a stark fact: AI models have reached a level of coding capability where they can surpass all but the most skilled humans at finding and exploiting software vulnerabilities.

   Mythos Preview has already found thousands of high-severity vulnerabilities, including some in every major operating system and web browser. Given the rate of AI progress, it will not be long before such capabilities proliferate, potentially beyond actors who are committed to deploying them safely. The fallout—for economies, public safety, and national security—could be severe. Project Glasswing is an urgent attempt to put these capabilities to work for defensive purposes.

   Since Anthropic (along with OpenAI) is trying to IPO this year, it is tempting to dismiss this as hype, especially in context of the previous link. However, there are many signals that end credibility to their claims.

   First, there is the large list of credible partners above including their competitor in the LLM space, Google. Second, was the news that Treasury Secretary Scott Bessent and Chairman of the Federal Reserve summoned CEOs of major Financial Services firms to warn them about the risks posed by this model. Third is the long list of credible tech people endorsing the abilities of this model.

   With this level of publicity, if this was hype, we will find out soon enough but the evidence so far suggests it is likely real.

   In which case, this is a huge step change in the abilities of LLMs. I expect this will also bring AI centerstage in national and global political discourse. This is a model with major national security implications because the NSA / Mossad types can use one vulnerability in operating systems to compromise personal devices of their targets. Imagine what they could do with "thousands of high-severity vulnerabilities".

   This also raises important questions like what if China had developed a model with such abilities first or what if Anthropic hadn't realized the power of this model and released it to public or who gets to decide who gets access to a model like this, a private company or government?

   The other question I am thinking about is how do leaders of China, Russia react to this news knowing that NSA / CIA have access to such a system?

   There is a lot of excellent coverage of Mythos and related stuff, if you want to read more.

3. Banksy, Satoshi & The Unmasking Impulse

   First Banksy and then Satoshi. Something about their unmasking is not sitting right with me. I am bothered by it. I am annoyed by it. And even more annoyed with myself because as a former journalist I should understand, but I don’t. I am referring to Reuters’s meticulous investigation and unmasking of Banksy, and John Carreyrou’s in-depth report labeling Adam Back as Satoshi, the creator of Bitcoin.

   Both investigations are technically impressive. Both raised the same question I keep turning over: what exactly was accomplished here, and for whom?

4. We Are on the Cusp of a Revolution in Rare Disease Treatment

   When KJ Muldoon was born in the summer of 2024, his parents were told he had a disease so rare, it strikes about one in 1.3 million newborns. His condition, a severe deficiency of an enzyme known as CPS1, left his tiny body unable to properly break down protein, flooding his blood with toxins that could cause brain damage or death. A liver transplant could correct the problem, but KJ was too young and too fragile to undergo one. With each passing day, the risk of irreversible neurological damage grew.

   What happened next may become the most important medical story of the decade. In just six months, a team at Children’s Hospital of Philadelphia and Penn Medicine designed a personalized therapy that could correct the single misspelled letter in KJ’s DNA using a gene editing technology known as CRISPR. To get the therapy inside KJ’s cells, doctors relied on the same kind of mRNA technology that powered the Covid-19 vaccines. He received his first dose at 6 months old. One year later, KJ is walking, talking and thriving at home with his family.

   Worth a read, the key question being how does the FDA regulate individualized treatments when the current paradigm is to rely on RCTs with thousands of subjects.

5. The Jump Rope Queen of Beverly Hills

   Ms. Judis currently holds the Guinness World Record for oldest competitive rope skipper. She also thrives on having an audience: If she doesn’t share a workout, she said, it’s like it never happened.

   82!

6. I Trained for the Paris Marathon Using ChatGPT:

   Twelve months ago, I signed up for the Paris Marathon. Within six months, I knew I’d be in trouble without a trainer. So, living in the San Francisco Bay Area — the home of artificial intelligence — I decided to build one myself.

7. Singing a Vote of Thanks:

   We should all do this sort of thing more often. 🙂

8. AI, Unemployment and Work:

   Imagine I told you that AI was going to create a 40% unemployment rate. Sounds bad, right? Catastrophic even. Now imagine I told you that AI was going to create a 3-day working week. Sounds great, right? Wonderful even. Yet to a first approximation these are the same thing. 60% of people employed and 40% unemployed is the same number of working hours as 100% employed at 60% of the hours.

A lighter edition this week as the family traveled for Spring Break. Normal service should resume next week.

1. How A.I. Helped One Man (and His Brother) Build a $1.8 Billion Company:

   His start-up, Medvi, a telehealth provider of GLP-1 weight-loss drugs, got 300 customers in its first month. In its second month, it gained 1,000 more. In 2025, Medvi’s first full year in business, the company generated $401 million in sales.

   Mr. Gallagher then hired his only employee, his younger brother, Elliot. This year, they are on track to do $1.8 billion in sales.

   A $1.8 billion company with just two employees? In the age of A.I., it’s increasingly possible.

2. How should you change your life decisions if we are being watched by alien drone probes?: His take?

   The most plausible decision however is to slightly lower your level of ambition.

   I thought the correct response was the opposite. Think of it along the lines of immigration - one very common path for an ambitious person from India / China / Africa is to immigrate to the West. Do big things there or learn and go back to do big things at home. An advanced alien world opens up a whole new frontier. But here's a much better answer:

   I, like most people, used to think that UFOs were ridiculous and in the same category as Bigfoot and the Loch Ness monster. Nutcases believed in them because they wanted it to be true, to feel special, and to enjoy confirmation bias.

   Now I feel that I owe the UFO nuts an apology. I’m not claiming they’ve been definitively proven right, but evidence has come out that they don’t belong in the same category as other conspiracy theorists.

   This means I was globally miscalibrated. My model of the world was too narrow, so I should broadly update to be more open-minded about crazier things.

   A lot more at the link.

1. China and the Future of Science

   The Chinese party-state is fundamentally a set of goal-oriented institutions. This is not unique to China—it is in fact a distinguishing feature of all Leninist systems. I sometimes think of Leninist systems as a little bit like that bus in the movie Speed. Who here has seen it? For those who haven’t, here is basic gist of that film: an extortionist attaches a bomb to the speedometer of a bus. If the bus ever slows below 50 miles per hour, everyone blows up. So it is with your average communist system. Either it hurtles towards some clearly defined goal or things start to fall apart.

2. SS

   Stefan Schubert@StefanFSchubert · Mar 28

   While social media is polarising, evidence suggests AI may nudge people towards the centre.
   
   This holds true of all studied models. Grok is more right-leaning than other models, but also has depolarising effects.
   
   By @jburnmurdoch.

   

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3. I Saw Something New in San Francisco (NYT):

   Behind this drive is an experience of A.I. that many casual users have not yet had. An A.I. without deep knowledge of you is an upgrade, perhaps, over Google search. An A.I. with deep knowledge of you feels like something else entirely. I have heard people talk about their A.I.s in terms that bring to mind the daemons from Philip Pullman’s “His Dark Materials” trilogy: They become companions that know you deeply, that you feel safe telling things you’d never tell another person, that become a separate self that nevertheless feels like a part of your own self. That this sounds strange and disquieting does not mean it is not happening.

4. The Big Here Quiz:

   Here are 30 questions to elevate your awareness of the greater place in which you live:

   1. Point north.
   2. What time is sunset today?
   3. Trace the water you drink from rainfall to your tap. Where does your water come from?
   4. When you flush, where do the solids go? What happens to the waste water?
   5. How many feet (meters) above sea level are you right now? How about your home?
   6. What spring wildflower is consistently among the first to bloom here?

Word of The Day: TESCREAL

Meaning: A neologism and a acronym, it stands for Transhumanism, Extropianism, Singularitarianism, (modern) Cosmism, Rationalists (the internet community, not to be confused with other uses of the term), Effective Altruism, and Longtermism.

Gebru and Torres argue that these ideologies should be treated as an "interconnected and overlapping" group with shared origins. They claim these constitute a movement that allows its proponents to use the threat of human extinction to justify expensive or detrimental projects and consider it pervasive in social and academic circles in Silicon Valley centered on artificial intelligence. As such, the acronym is sometimes used to criticize a perceived belief system associated with Big Tech.

A regular reader of the blog pointed this word out to me, as a message that blind cheerleading for big-tech was something for me to guard against. The link last week to the story about the Sydney Data Engineer developing a vaccine for his dogs cancer was the trigger for sharing this.

Its advice well received, since that story did trigger some red-flags at the back of my mind but I over-rode those signals with little thought as I continue to be very excited by the developments in AI space. However that is no reason to throw caution and skepticism to the wind. The story has held up so far but I continue to watch with interest.

Links

1. The H1B Fees:

   CO

   Connor O’Brien@cojobrien · Mar 12

   85 people have paid the $100,000 H-1B fee so far, totaling $8.5 million in revenue. But fee revenue from H-1B apps abroad is down $28 million.
   
   So the fee — justified by a paper claiming the revenue-maximizing fee was >$100,000! — appears to have lost the government $20 million.

   

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2. Agents over Bubbles

   Microsoft is admitting, at least for now, that delivering a truly compelling agentic product that enterprises are willing to pay for means abandoning their stated goal of being model agnostic; that, by extension, raises the possibility that models are not and will not be commodities, because agents require more than models.

   Food for thought as my framework so far was that models will become commodities but the recent developments are pointing away from that direction. There is a lot more of interest in this article.

3. Why Fraud Is The Boring Problem:

   Michael Smith used AI to create music, and then used AI to create bots to get the “plays” and took the smartest technology companies, including Spotify and Amazon, who should know better, for about $8 million. He is going to jail for his crimes. It is easy to dismiss this as one-and-done fraud. It is anything but. It is an early warning of how AI will disrupt the systems that power our digital society: how culture gets discovered, how commerce gets directed, and how conversations get shaped.

   Will AI break all recommendation algorithms, from YouTube to Tik Tok?

4. The Last Quiet Thing:

   Nothing you own is finished. Everything exists in a state of permanent incompletion, permanently needing. Your phone needs updates, needs charging, needs storage cleared, needs passwords rotated.

   Your apps need permissions reviewed, terms accepted, preferences re-configured after every update.

   Your subscriptions need evaluating, need renewing, need canceling, need justifying to yourself every month when the charge appears. The purchase isn't the end of anything. It's the first day of a relationship you didn't agree to, with no clean way out.

   You live in a house full of dependents.

5. More guides and ideas for how to use LLMs.

The first two stories this week are mindblowing. Huge if true, as they say.

1. Australian Tech Founder Uses ChatGPT and AlphaFold to Design Dog Cancer Vaccine — Tumours Shrink by 75%. Originally seen here and video here:

   A Sydney data engineer with no background in biology has used ChatGPT and AlphaFold to design what researchers are calling the world's first personalised mRNA cancer vaccine for a dog, and the results have stunned the scientists who helped make it.

2. A Fly Has Been Uploaded:

   In 2024, the entire neuronal diagram of the fruit-fly brain–some 140,000 neurons and 50 million connections–was mapped. Later research showed that the map could be used to predict behavior. Now, Eon Systems a firm with some of the scientists involved in the fruit-fly research and with the goal of uploading a human brain has announced that they uploaded the fruit fly brain to a digital environment.

   The digital fly appears to behave in the digital environment in reasonably fly like ways–this is not a simulation, the fly’s “sensors” are being activated by the digital environment and the neurons are responding.

3. Some more AI tutorials. So many tutorials, so little time.

4. BO

   Brooks Otterlake@i_zzzzzz · Mar 13

   Japanese society is so civilized that the fires simply drive themselves to the fire station

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Savitha Shan, an undergrad double major here in economics and information systems, who was murdered over the weekend by an Islamist terrorist who started randomly shooting people on Sixth Street, apparently angry about the war in Iran. Two other innocents were also killed. - Scott Aaronson

So senseless. And the 180 schoolgirls Minab, Iran. Did any of them know it was their time? Did they get to live a full life? Will I? It's one thing to know this and another to feel it in your bones. But the worst is when you start feeling it and your self-preservation instinct kicks in - allowing the feelings to only go in so deep and no more. RIP.

Links

1. The Brand Age: Worth reading the whole thing just for this sentence but there's a lot more and it ends in a very different place from where it starts.

   This is an instance of what I call the comb-over effect: when a series of individually small changes takes you from something that's a little bit off to something that's freakishly wrong.

2. The Hidden Advantage of Being Over 50 in the Age of AI: Hope & cope?

   The leaders who win this era won’t just be 22‑year‑olds building AI‑native startups. They’ll also be experienced operators who integrate AI quietly and intelligently into systems they already understand. If you’re over 50 and feeling behind, you might actually be early. Because when the tools get easier, experience becomes more powerful—not less. And this time, that experience may finally be the competitive edge.

3. BC

   Brett Caughran@FundamentEdge · Mar 6

   I'll provide a little more specificity on this, and snippets of an example.
   
   For many months people have been talking about a "Cursor moment" in finance, where workflow changes so dramatically that you hit the steep part of an adoption curve. I've been highly skeptical of that, for a few reasons.
   
   But the most fundamental reason is the LLM technology just wasn't there. The foundation models simply did not have enough power to interact with Excel spreadsheets in any sort of usable way (despite splashy demos...). Even if you solve the (very hairy) data challenges, 2025-era LLMs just didn't have the power to interact with spreadsheets.
   
   So we could sit and talk about a lot of ideas and concepts on how AI could augment institutional investment research. But it was just that, a concept.
   
   I have a series of tests I run on new AI models that are capability tests for hedge fund style research workflows. And the easiest is just uploading an existing Excel file to see if the LLM can understand what's going on. If LLMs can't sufficiently read and understand an Excel model, the full stack of AI Excel workflows is just not possible (in my opinion). And a waste of time to try to explore.
   
   This didn't work to any sort of impressive degree (Opus 4.6 could do it, but not do it well). Until yesterday, with GPT-5.4 Thinking.
   
   Suddenly, I can now get something that is not only modestly useful, but I think will immediately become part of my investment process workflow.
   
   I call it "PM Review", or a structured evaluation and push back on a model. I have participated in literally hundreds of these as both analyst and PM. Effectively the analyst builds a model, sends it to the PM, and they walk through it together. The wise, experienced-scarred PM will rip the model apart, push back, and help steer the model to a usable outcome.
   
   A great PM will be able to hone in on the two or three key variables that matter and identify aggressive or conservative assumptions. An analyst may be pitching a stock where the core quantitative input is supported by flawed logic. And the PM's job is to try and identify that flawed logic. This workflow, to me, is a key differentiator between good and not good PMs.
   
   However this workflow isn't just for PMs; it's for analysts who are trying to evaluate their own work, peer analysts who want to do thoughtful push-back on ideas the team may participate in, our director of research teams who are looking to efficiently evaluate the idea underwriting process. Or PMs for the first cut if they're looking at lots of ideas.
   
   The intriguing aspect of augmenting this process with AI is it scales incredibly. And it can run autonomously. Across 300 models I could have a swarm of agents doing automated due diligence on the key drivers, updating those models, feeding those results back to me, and flagging which of my covered ideas have earnings revision potential. This workflow is the "Cursor moment" for public equity research, in my opinion. I'm not saying we're there by any means as data accuracy and the structures required to incorporate internal data are still in progress. But we just took a step forward in the technological capability.
   
   I tested this out in GPT-5.4. And while it's not perfect this is the first time I've received anything that's useful back in this test.
   
   I'll walk you through a couple of steps to do this on your own.
   
   Step 1: brain dump into Claude. I don't know if there's any logic to it or just my own habit but if I'm executing in Chat GPT, I'll meta prompt and Claude and vice versa. I'm not sure where you meta prompt matters all that much for the types of workflows I do but it CERTAINLY matters if you meta prompt vs. raw prompt so don't skip this step.
   
   Step 2: take that prompt output, turn it into Markdown, and put that as custom instructions in a GPT project. This is just a workflow efficiency because then I now have a GPT project that I can upload any model into.
   
   Step 3: run the prompt. I purposely jacked up my DraftKings model a little bit (and it's a work in progress anyway so do not take any of these estimates as anything I believe).
   
   But it produced an exceptionally helpful:
   1) Executive Summary
   2) Business understanding (explaining how a dollar flows through P&L)
   3) Model Evaluation, providing an assessment and sanity check of all of the key inputs
   4) Model audit, looking for input consistency, formula integrity, and broken references
   5) A road map for incremental due diligence
   6) The highest value IR questions
   
   I encourage you to check it out for yourself.
   
   Will link to the six-page output in the replies.

   

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4. C

   Chapin@Chapinc · Mar 1

   You want me to be physically present at a meeting in the office? Like the Ayatollah?

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5. I wouldn't stand there.

   

I have been following the AI revolution almost since the day ChatGPT launched in Nov 2022. That this was a transformational technology has also been clear to me for almost as long. I even sensed the "vibe shift" in early Jan.

But so far I didn't really "feel the AGI". Last week I did.

AGI stands for Artificial General Intelligence. Here's how Claude defines it:

An AI system capable of performing any intellectual task that a human can — reasoning, learning, and adapting across domains without being specifically programmed for each one." - Claude Sonnet 4.6

It is also worth knowing the related concept of ASI, Artificial Superintelligence.

An AI that surpasses the cognitive abilities of all humans combined across every domain, including scientific reasoning, social intelligence, and creative problem-solving."

Last week we finally signed up for Claude Code at work and I started playing with it.

Claude Code works via the CLI (command line interface) or the terminal - the black screen with white text used by all the movie nerds. It can be a little intimidating if you are not a programmer but really once you set up Claude Code, it works just like the chat window.

It is so much more powerful though. It can manipulate files on your computer and run the code it writes. This means it is not restricted to recommendations or single steps any more. It can generate an entire plan of action and execute and implement the thing by itself. It can be more than a little freaky when you see the output of a particularly complex task.

Let me share a couple of examples that blew my mind.

At work we have a database that stores our financial projections for a company we cover. The investment team can use custom functions in excel to then download this data. This is useful to create reports for analysis - say comparing 5 companies across a few metrics. There are different functions for different types of data and the IT team has created an excel file with about 20 sheets listing the syntax for each function, the list of values that can go in each function etc.

I pointed Claude Code to this help file and asked it to create a "skill" for itself that would allow it to create reports in excel using these formulas. I gave it the same context as the previous paragraph - maybe a little more technical but nothing a lay person wouldn't understand.

With that single command, in maybe 3-5 minutes, the skill was ready. Now when we need to create a report we can just ask Claude Code to use the skill, the data we want in the report and it creates a fully formatted excel file with the (usually) correct formulas. Tasks that would take me or my team members 20-60 minutes, automated permanently. Using English sentences, no technical knowledge.

Second example. We wanted to perform some statistical analysis on 20 year historical performance of 600 stocks to identify specific episodes / time periods and then dig deeper into specific episodes to understand their fundamental causes.

An analyst spent probably 5-6 hours to download the data in excel, process it so we could start identifying the qualifying episodes / time periods in different markets. At this point we were somewhat stumped about how to isolate the relevant episodes from this vast data. Probably a trivial problem for a data scientist but not for us.

In the past, we would have spent probably another 5-10 hours trying to either eyeball the data using charts or some other way to get our answer. Over the last couple of years, we would have asked Claude or ChatGPT to suggest a better way.

But since we had Claude Code, I pointed it to the existing file, with all its messy sheets and structure and explained what we were trying to do and asked it to identify the episodes. It whirred away for about 20 min, an occasional question here or a permission there and then it spat out a report.

But the report didn't just have the episodes identified. It also identified potential causes for each episode (based on web searches presumably), linked patterns across multiple episodes, gave charts and commentary that helped us understand the relevance of each episode, limitations of the analysis, suggested next steps etc.

Now we have all seen more than enough AI slop to not be impressed by the sheer volume of content these tools can spit out. But we spent a few hours verifying the numbers and conclusions. So far it all checks out. You have to take my word for it, but man, this was not slop. If a junior associate had put this out I would be proud of them. There were parts that I would have been proud to create and, of course, large parts that we simply couldn't have created at all.

And those were not the only thing Claude Code did last week that blew my mind.

So, let it be noted on this 8th of March, 2026, I felt the AGI last week. I may even have felt the ASI.