2026-06-13 00:14:13
Friends,
For several years, I’ve wanted to launch a weekly intelligence briefing. While there are exceptional private intelligence groups covering the financial markets and geopolitics, and many great tech publications, I nevertheless found myself wanting something a little different from what I was able to find.
Something that delivered an elegant, insightful analysis of the hidden shifts and fresh opportunities bubbling up in our industry. Something high-signal, low-fluff, and with, perhaps, a dash of wit. Something that provides a little greater situational awareness in thirty minutes or less.
But doing it right would require taste and craft, as well as real time. For an intelligence product to succeed, it must find fresh angles on known stories and the non-obvious ones just bubbling beneath the surface. That takes scrounging and scouring.
Earlier this year, we were able to unlock both. Most important was convincing one of my favorite writers, an old hand at this kind of work, to jump aboard and lead the charge. By leveraging frontier models, we’ve been able to build an extensive signal-gathering apparatus that would not have been possible to conduct without a very large team, spanning news, industry outlets, social media, academic research, government and regulatory filings, code repositories, model-adoption aggregators, fundraising data, prediction markets, website monitoring, open-source intelligence sources, and talent flows. We also monitor a select group we refer to as “super signalers” across various verticals, selected by us, who we believe are frequently ahead of the curve. Not all of these approaches are bearing fruit yet, but we expect them to improve as we build and fine-tune. Already, we’ve seen the benefits of a process that searches so expansively. Not only does it surface tidbits a human might have missed, but it spots echoes or juxtapositions that are revealed only with capacious context.
However, the story selection and writing are done by us, the humans. The system hunts ceaselessly, bringing up a furious exhaust of data, noise, and signal, all in one. It is up to the human to think, judge, analyze, and write.
Generalist Intelligence is the result of this marriage, a weekly intelligence briefing designed for tech’s most discerning professionals. It will arrive Friday mornings. Our hope is that it opens you up to perspectives you hadn’t considered and offers a look at fresh pockets of the future you might have missed. I’ve been reading internal versions of this as we tuned the format over the past couple of months, and have found myself looking forward to it every week.
We’re in the very early stages of getting this right, and there’s a long way to go. We’d love to know what you think, especially what you’d like to see more of, as it comes up. Our goal is for this to become the highest signal-to-noise newsletter you receive each week, and one worth setting aside the time for.
Now, onto the briefing.
— Mario
With SpaceX blasting into the public markets and Anthropic and OpenAI straightening their ties to follow suit, the bajillion-dollar question is, obviously: are they worth it? Anyone claiming to know the answer very likely has a bridge to sell you. Nevertheless, we can’t stop thinking about it.
SpaceX feels like a special case. Public markets are being asked to price in total interstellar domination at IPO, with a good trillion of the $1.77 trillion price tag – at which the loss-making company would trade at over 90x last year’s revenue – based on a series of highly speculative goals including repeat business on Mars, data centers in orbit, and making a key contribution to the development of AI. On the other hand, it’s Elon. So, you know.
What’s really got our chins wagging at Generalist Towers this week is a more existential question. Anthropic and OpenAI haven’t filed public prospectuses, but they look likely to be priced as though they are in, effectively, a two-horse race for control of the future (ok, maybe Google too). Some of us think that’s right – that it’s only a matter of time before one of the model labs cracks recursive self-improvement, and then it’s a short hop to AGI and either Sam or Dario as World King.
But a couple of things have landed in the past week that have got us thinking seriously about the other side. So we thought it would be fun to take the contrarian stance, and make the bear case for AI.
AI, huh, what is it good for?
LLMs are incredibly good at coding. At the end of last week, Anthropic dropped an essay titled When AI builds itself, in which the Claude-maker claimed that more than 80% of the code it merges into its codebase was written by Claude, and that its engineers were shipping “8x as much code per quarter” compared to their relatively flat productivity between 2021 and 2025. (When I asked Claude about this, it raised an eyebrow at the figures, pointing out they were “self-reported by a company currently raising money on exactly this story.”) And to be fair, rather gallantly, the good folks at Anthropic point out that the 8x figure is likely an overstatement as it measures “quantity over quality.” But the direction is clear: Claude is incredible at writing code. Presumably, this is translating into giant gains for all?
Well, no.
A new study of more than 100,000 GitHub developers found that Claude Code allowed coders to create or edit almost 300% more files. But that uplift was halved to 150% by the time they got to submitting pieces of work for review, and that in turn shrunk a further 5x by the time it got to shipping. In other words, coders using the latest agentic AI tools released just 30% more software, compared to those raw-dogging it. The researchers attribute that remaining 30% to what they call “strong complementarities” between the agents and the coders, meaning the agent very much needs the coder. They also noted that while there was a marked uptick in new apps being made this way, there was “no increase” in overall demand. This doesn’t mean agents are bad at code, but it does mean they might not be nearly as good as you thought at the thing they’re best at.
So what happens to the model makers?
2026-06-04 23:23:05
“I chose cultural anthropology, since it offered the greatest opportunity to write high-minded balderdash.” — Kurt Vonnegut.
2026-06-02 20:04:31
“Warfare is always just adapting to whatever the other side is doing. And the person that wins is whoever adapts faster. And at this point in time, American aerospace is uniquely poorly suited to do that.” —Bryon Hargis, Co-Founder & CEO of Castelion
Listen or watch now on
YouTube, Spotify, or Apple Podcasts
Bryon Hargis is the co-founder and CEO of Castelion, a defense startup building low-cost hypersonic missiles designed to be manufactured at scale. Before founding Castelion, Bryon spent more than a decade at Johns Hopkins Applied Physics Laboratory and nearly six years at SpaceX, where he worked on national security space programs and saw firsthand how iterative engineering and manufacturing speed could reshape aerospace. Castelion’s first missile, Blackbeard, is slated for integration on the Navy’s F/A-18 Super Hornet in roughly a year.
In our conversation, we explore:
Why Bryon believes building missiles is paradoxically essential to maintaining peace
The game theory behind warfare and why tit-for-tat strategies require credible middle-ground responses
How China’s 2021 hypersonic test revealed not just a capability gap but a manufacturing and cost advantage
Why traditional aerospace processes—optimized for low risk and high cost—can’t compete with rapid iteration
What Bryon learned in his first week at SpaceX (after 12 years in traditional aerospace)
Why building a carrier-based, air-launched hypersonic missile as a first product was the hard but right choice
How focusing on manufacturability and cost over maximum capability can produce more effective deterrence
Why the person who adapts faster in warfare always wins, and how that shapes Castelion’s philosophy
.tech domains: An identity for builders at their core.
Ahrefs Brand Radar: Find your brand in AI results.
Persona: Trusted identity verification for any use case.
(00:00) Intro
(04:01) Why America needs hypersonic missiles
(07:13) China’s edge in hypersonics
(12:05) The missing middle ground in deterrence
(18:05) Preventing warhead ambiguity
(19:40) How hypersonics differ from ballistic missiles
(25:05) The economics of defensive vs. offensive systems
(28:21) How SpaceX differs from traditional aerospace
(37:40) Why Bryon chose to build in defense over space
(42:42) Key factors that drove Castelion’s success
(48:28) Designing Blackbeard, Castelion’s first hypersonic missile
(1:01:06) The importance of lower costs and quicker manufacturing
(1:10:04) Book recommendations
LinkedIn: https://www.linkedin.com/in/hargsb
Carrying the Fire: An Astronaut’s Journeys: https://www.amazon.com/Carrying-Fire-Astronauts-Michael-Collins/dp/0374531943
Skunk Works: A Personal Memoir of My Years at Lockheed: https://www.amazon.com/Skunk-Works-Personal-Memoir-Lockheed/dp/0316743003
The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers―Straight Talk on the Challenges of Entrepreneurship: https://www.amazon.com/Hard-Thing-About-Things-Building/dp/0062273205
Gravitation: https://www.amazon.com/Gravitation-Charles-W-Misner/dp/0691177791
“Surely You’re Joking, Mr. Feynman!”: Adventures of a Curious Character: https://www.amazon.com/Surely-Youre-Joking-Mr-Feynman/dp/0393355624
Perfectly Reasonable Deviations from the Beaten Track: https://www.amazon.com/Perfectly-Reasonable-Deviations-Beaten-Track/dp/0465023711
Kip Thorne: https://en.wikipedia.org/wiki/Kip_Thorne
Richard Feynman: https://en.wikipedia.org/wiki/Richard_Feynman
Castelion: https://www.castelion.com
Chinese hypersonic weapon fired a missile over South China Sea: https://www.ft.com/content/a127f6de-f7b1-459e-b7ae-c14ed6a9198c?syn-25a6b1a6=1
Prisoner’s dilemma: https://en.wikipedia.org/wiki/Prisoner%27s_dilemma
Planet Labs: https://www.planet.com
Falcon 9: https://www.spacex.com/vehicles/falcon-9
Veritasium: https://www.youtube.com/@veritasium
3Blue1Brown: https://www.youtube.com/@3blue1brown
Making Mistakes with Greg: https://www.youtube.com/@makingmistakeswithgreg
Super Fast Matt: https://www.youtube.com/@SuperfastMatt
This game theory problem will change the way you see the world: https://www.youtube.com/watch?v=mScpHTIi-kM
I’d love it if you’d subscribe and share the show. Your support makes all the difference as we try to bring more curious minds into the conversation.
Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].
2026-05-19 20:01:48
"China can do it because the labor is cheap. That's not true anymore. They are incredible at automating things and automating them in a way that makes them cost competitive." —Davide Asnaghi
Listen or watch now on
YouTube, Spotify, or Apple Podcasts
Davide Asnaghi is the co-founder and CEO of Diode, a Brooklyn-based startup using AI to design and manufacture circuit boards in the United States.
Before Diode, Davide worked on Apple’s Special Projects Group and spent time in Hong Kong and Shenzhen studying Asia’s electronics manufacturing ecosystem. That experience convinced him that PCB design, despite powering everything from smartphones and satellites to medical devices and autonomous systems, remained one of the most overlooked layers of the tech stack.
Since its founding just two years ago, Diode has landed Physical Intelligence and Saronic as customers and partnered with Anthropic to help Claude become a better electrical engineer. The company’s ultimate ambition: to make hardware as nimble as software.
In our conversation, we explore:
Why the West outsourced PCB manufacturing to Asia in the 2000s and why bringing it back matters for American competitiveness
What Shenzhen’s manufacturing culture does better than Silicon Valley (and what the U.S. can learn from it)
How Diode’s models can one-shot much of schematic design and compress hardware timelines from months to weeks
The three-week YC pivot that transformed Diode from a design validation tool into a full-stack manufacturer
Why circuit boards are the “forgotten middle child” between silicon and software
How Diode partners with Anthropic to make LLMs better electrical engineers
What it takes to build a hardware company in 2025—and why the talent bar must stay incredibly high
How Italian, American, and Chinese cultures shaped Davide’s approach to entrepreneurship and manufacturing
.tech domains: An identity for builders at their core.
Guru: The AI source of truth for work.
Brex: The intelligent finance platform.
(00:00) Intro
(04:15) Why Davide calls himself a copper merchant
(05:53) Diode’s mission to rebuild PCB manufacturing in the U.S.
(07:58) What success looks like
(09:00) Growing up in northern Italy and spending a year in Minnesota
(13:14) Why Italy produces fewer venture-backed founders
(15:30) Why Hong Kong accelerated Davide’s learning
(19:09) Silicon Valley vs. Shenzhen
(22:05) What Davide learned in Apple’s Special Projects Team
(24:11) Why Davide left Apple after two years
(26:54) Meeting his co-founder, Lenny
(29:32) How Davide uncovered the need for better PCB design and manufacturing
(33:23) PCB manufacturing in Asia, and Diode’s approach
(41:29) The YC pivot that changed Diode’s business
(44:39) Inside Diode’s customer journey
(48:10) Where the value is in electronics manufacturing, and Davide’s AGI thesis
(51:30) What separates a working board from a great one
(55:32) Where Diode fits in the electronics stack
(59:55) Diode’s early near-death moment and long-term vision
(1:02:30) Diode’s exceptionally high bar for hiring
(1:04:48) Where Davide gets his best ideas
(1:07:00) Final meditations
LinkedIn: https://www.linkedin.com/in/d-asnaghi
X: https://x.com/davideasnaghi
GitHub: https://hexdae.github.io
Breakneck: China’s Quest to Engineer the Future: https://www.amazon.com/Breakneck-Chinas-Quest-Engineer-Future/dp/1324106034
Chip War: The Fight for the World’s Most Critical Technology: https://www.amazon.com/Chip-War-Worlds-Critical-Technology/dp/1982172002
Alex Wong on LinkedIn: https://www.linkedin.com/in/alex-wong-6b8930205
Lenny Khazan on LinkedIn: https://www.linkedin.com/in/lennykhazan
Brendan Eich’s website: https://brendaneich.com
Diode: https://www.diode.computer
Arduino: https://www.arduino.cc
Bending Spoons: https://www.bendingspoons.com
Fortell (formerly Chromatic): https://www.fortell.com
Butterfly Network: https://www.butterflynetwork.com
Foxconn: https://www.foxconn.com
JLCPCB: https://jlcpcb.com
Anthropic: https://www.anthropic.com
Quilter: https://www.quilter.ai
KiCad: https://www.kicad.org
Cadence: https://www.cadence.com
Stripe: https://stripe.com
Dogpatch: https://en.wikipedia.org/wiki/Dogpatch,_San_Francisco
I’d love it if you’d subscribe and share the show. Your support makes all the difference as we try to bring more curious minds into the conversation.
Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].
2026-05-05 20:03:43
“AI is going to be the age of the polymath. If you have the ability to think about different systems and how they might work together, you’re going to be able to come up with outcomes that were previously impossible because those disciplines didn’t work well together.” — Cyan Banister, Co-Founder of Long Journey Ventures
Listen or watch now on
YouTube, Spotify, or Apple Podcasts
Cyan Banister has built one of the most distinctive early-stage track records of the last fifteen years, with early bets on companies like Uber, SpaceX, DeepMind, Niantic, and Postmates. Today, she is co-founder and general partner at Long Journey Ventures, where she backs what she calls “magical weirdos.” Banister describes herself as a professional daydreamer, running constant thought experiments and paying close attention to signals others ignore. In this episode, she explains how that mindset translates into investing, and why many of her best opportunities have come from observation, curiosity, and a willingness to look in unlikely places.
In our conversation, we explore:
Cyan’s philosophy of treating life as a series of experiments
The strange, profound experiences that led her to question and ultimately move beyond her atheism
How scanning Wi-Fi networks in a Four Seasons café led her to Flock Safety, last valued at $8.4 billion
Long Journey Ventures’ “Biz, Tizz, and Rizz” framework for identifying exceptional founders and why the trifecta is rare
How AI will enable the age of the polymath
Why she believes brain-computer interfaces are closer than most people think
Why she says Pokémon Go was “the closest we ever came to world peace”
Why she lives part-time in a retirement community and her vision for a more connected future
.tech domains: An identity for builders at their core.
Brex: The intelligent finance platform.
Persona: Trusted identity verification for any use case.
(00:00) Intro
(03:51) Never playing the game you appear to be playing
(07:18) Practicing childlike wonder as a daily discipline
(10:08) Questioning belief after her stroke
(13:30) Cyan’s metaphysical experiments
(23:24) Non-local consciousness and creativity
(27:22) Investing with extreme openness to signals
(29:05) The importance of timing in investing
(32:26) Meeting Travis Kalanick
(34:19) Finding Flock Safety through a chance encounter
(38:23) The summer of Pokémon Go (what worked and what didn’t)
(39:55) Human nature and what makes something “stick”
(42:15) Brain-computer interfaces and AI’s accelerating effect
(52:53) “Biz, Tiz, Riz:” her framework for evaluating founders
(59:20) Why Cyan lives in a retirement community part-time
(1:03:50) A unique way of finding books that speak to you
(1:08:44) Final meditations
LinkedIn: https://www.linkedin.com/in/cyanb
Newsletter: https://uglyduckling.substack.com
Website: https://cyanbanister.com
Harry Potter and the Philosopher’s Stone: https://www.amazon.com/Harry-Potter-Philosophers-Stone-Rowling/dp/0747532745
Impro: Improvisation and the Theatre: https://www.amazon.com/Impro-Improvisation-Theatre-Keith-Johnstone/dp/0878301178
The Diamond Age: https://www.amazon.com/Diamond-Age-Neal-Stephenson/dp/0553573314
Snow Crash: https://www.amazon.com/Snow-Crash-Neal-Stephenson/dp/0553380958
My Life and Loves: https://www.amazon.com/My-Life-Loves-Frank-Harris/dp/9358712538
Milton Friedman’s books on Amazon: https://www.amazon.com/Books-Milton-Friedman/s?rh=n%3A283155%2Cp_27%3AMilton%2BFriedman
The Razor’s Edge: https://www.amazon.com/Razors-Edge-W-Somerset-Maugham/dp/1400034205
Kurt Vonnegut: https://en.wikipedia.org/wiki/Kurt_Vonnegut
Aldous Huxley: https://en.wikipedia.org/wiki/Aldous_Huxley
J.K. Rowling’s website: https://www.jkrowling.com
Neal Stephenson’s website: https://www.nealstephenson.com
Travis Kalanick on X: https://x.com/travisk
Ryan Graves: https://en.wikipedia.org/wiki/Ryan_Graves_(businessman)
Keith Rabois on LinkedIn: https://www.linkedin.com/in/keith
Garrett Langley on LinkedIn: https://www.linkedin.com/in/glangley
John Luttig on LinkedIn: https://www.linkedin.com/in/luttig
John Hanke on X: https://x.com/johnhanke
Paul Stamets website: https://paulstamets.com
Keith Corso on LinkedIn: https://www.linkedin.com/in/keith-corso
Brendan Eich on LinkedIn: https://www.linkedin.com/in/brendaneich
Arielle Zuckerberg on LinkedIn: https://www.linkedin.com/in/ariellezuckerberg
Josh Browder on X: https://x.com/Joshuabrowder
Aleister Crowley: https://en.wikipedia.org/wiki/Aleister_Crowley
George Gurdjieff: https://en.wikipedia.org/wiki/George_Gurdjieff
P.D. Ouspensky: https://en.wikipedia.org/wiki/P._D._Ouspensky
The Telepathy Tapes: https://thetelepathytapes.com
The Intuitive Hour: Awaken Your Inner Voice: https://open.spotify.com/show/3Ws7WZsFuQuwgl6uiPMJq3
Spellers: https://www.imdb.com/title/tt27558471
Animal Telepathy & Consciousness: https://thetelepathytapes.com/podcast/the-telepathy-tapes-s2-e5
Brain-computer interface: https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface
Saturday Night Live: https://en.wikipedia.org/wiki/Saturday_Night_Live
Modern Meditations: Keith Rabois: https://www.generalist.com/p/modern-meditations-keith-rabois
Y Combinator: https://www.ycombinator.com
Pokémon Go: https://www.pokemongo.com
Ingress: https://ingress.com
Monopoly Go: https://www.monopolygo.com
Pikmin Bloom: https://pikminbloom.com
Niantic: https://nianticlabs.com
Niantic Spatial: https://www.nianticspatial.com
This Beanie Is Designed to Read Your Thoughts: https://www.wired.com/story/this-beanie-is-designed-to-read-your-thoughts
CTRL-Labs: https://dsvw8jmuo45j8.cloudfront.net
Fungi Perfecti: https://fungi.com/pages/bees?srsltid=AfmBOoqnjt2xKnfY7H3bW_yLaUuVrvoogzsa8mt5BHEqN_iWze0WQEkx
Etsy: https://www.etsy.com
Busright: https://www.busright.com
Rizz & Tizz (and a Little Biz): Our Framework for Magical Weirdness: https://www.longjourney.vc/news/founderrizzandtizz
Crusoe: https://www.crusoe.ai
Mafia: https://mafia.gg
B Street Books: https://www.bstreetbooks.com
The Restaurant With No (Visible) Workers: https://www.npr.org/sections/alltechconsidered/2015/08/31/436377616/the-restaurant-with-no-visible-workers
“The Magic Glasses” by Frank Harris: https://hermetic.com/crowley/equinox/i/i/eqi01007
Kabbalah: https://en.wikipedia.org/wiki/Kabbalah
The Razor’s Edge (1946 film): https://en.wikipedia.org/wiki/The_Razor%27s_Edge_(1946_film)
The Razor’s Edge (1984 film): https://en.wikipedia.org/wiki/The_Razor%27s_Edge_(1984_film)
I’d love it if you’d subscribe and share the show. Your support makes all the difference as we try to bring more curious minds into the conversation.
Production and marketing by penname.co. For inquiries about sponsoring the podcast, email [email protected].
2026-04-23 21:41:25
Friends,
Sometime, about three months ago, I had a realization. It may sound obvious to many of you, and absurd to others.
It is this: the Claude models released in December (and improved upon since) have driven the greatest personal capability leap in my lifetime.
The iPhone changed the way I accessed information and navigated the world. Social networks altered how I communicated and fraternized. Any number of apps and programs improved my workflows, smoothed opportunities, and accelerated my thinking. Doubtless, dozens of quieter improvements have changed the texture of my life without me realizing it — superior medicines and more efficient machines.
But as a single, discrete jump, nothing else comes close. Before Opus 4.5 — Claude’s winter upgrade — I had opened my computer’s terminal on a handful of occasions, mostly by accident. The last time I’d actually tried to use it had been a 2015 continuing education course at General Assembly that I’d bungled through with the grace of a macaque running a printing press.
Today, I spend more than 70% of my working hours in the terminal. I build software, construct systems, and conduct sprawling research assignments. Agents parse hundreds of articles, looking for tidbits aligned with my interests or writing goals, and prepare reports in my preferred style. Others streamline administrative duties, find bugs, polish edges, and ship the next feature I have in my mind.
The result is a system that increasingly feels not just like an extra employee, but closer to 20.
One of the challenges of running a business like The Generalist is that you cannot play just one role. I may get the greatest pleasure from sitting in front of an empty screen and beginning to write, but there are bills to be paid, scheduling to do, dashboards to survey, growth strategies to deploy, sponsors to consider, and emails to send. Every day is a battle between deep work and the realities of running a business. It is an unavoidable fact that every hour spent on these things is one I cannot spend on the parts I enjoy most and where I feel I have the greatest advantage.
Even outside these especially mundane tasks, there are thousands of little irritations and distractions. Try to conduct detailed research on a person or topic, and count the moments of friction. How many paywalls will you hit for publications you already purchase? How many pop-up ads or cookie advisories? What purposefully distracting news carousel will spin across the bottom of your article? What video will stuff itself in from the side? If you want to study someone’s background on LinkedIn or Twitter, how many red notifications will raise themselves like welts? How many DMs call for your attention? What new product announcement screams for you from the feed? How many greedy fingers try to grab your focus in the simple act of trying to travel from A to B, from intent to information?
The modern internet has become an attention casino, and we have grown accustomed to working in the middle of it, averting our eyes from clanking slots and spinning wheels. But what if your workspace could feel more like a quiet desk in a well-lit library? What if you could dispatch 20 virtual employees to wade through the morass of the modern web for you and deliver the results? What if you could cut back on the logistics and wrangling and give yourself the time to focus on the one thing you do not want AI to do for you? What if you could double the time you spent in deep work?
Over the past few months, I have been using Claude Code to explore these questions for myself. The result is a full-stack knowledge management system spanning multiple software products, internal systems, and a local model. (I have built several other things, but this is the crispest distillation.) It is not perfect, nor will it be for everyone. Showing these systems to friends and family over the past months, I’ve found that it often helps people better understand what is now possible with these models, and how you might use them to your benefit.
When I’ve caught up with these people days or weeks later, I’ve often found they’ve undergone a similar transformation, from dabbler to devotee. While there’s undoubtedly a risk in outsourcing too much, including the act of thinking itself, so far I haven’t found this to be true for myself or others. Rather, people seem to be having an extremely fun time, building systems that take away drudgery and interfaces explicitly shaped for how their minds work. It’s incredible how much easier and more pleasant it is to navigate an app that intuitively works the way your brain does, rather than one constructed for the general population.
If you’re curious about these tools, I would recommend setting yourself the goal of building the smallest possible thing you can think of. You’ll quickly find your ambitions grow as your comfort sitting in front of a terminal does.
With that, here’s a look at my system and how it’s changed my workflow.
There is a particular type of cognitive annoyance which one might call “thing-finding.” You have undoubtedly experienced it. It is the moment when you’re forced to stop in the middle of something and ask, “Agh, what was that thing again? That thing that person said? That thing I read? That thing I wrote? Did I save it somewhere? Is it in Google Drive? Will Finder locate it? (Nope!)”
An occupational hazard of running a media company is that there are a lot of things. There are research things and podcast things and article things and note things and PDF things and email things and interview things. And they are invariably quite hard to find. Historically, they have been spread out across my desktop, Google, Obsidian, Ulysses, The Generalist’s website, and Dropbox. In the grand scheme of the travails of the world, the callous mysteries of the universe, dark matter, and the infinite unknown, I recognize this is not a real problem. But when you are in the middle of a piece, just beginning to find that fragile rhythm that even an ambling ice cream truck can disrupt, this is among the most annoying interruptions possible.
Delphi, the all-seeing oracle, is the solution I’ve built to address this issue.
To start, I compiled every piece The Generalist has ever written, the transcripts of every podcast I have recorded, my full compendium of Obsidian notes, my Readwise highlights, a good chunk of Google Drive, and assorted files from my desktop. In total, there are more than 45,000 searchable “chunks,” with more added by the day.
The search pipeline relies on three layers, fused together: vector search via Voyage-3 embeddings, keyword search via SQLite FTS5, and a locally trained cross-encoder reranker, distilled from Cohere. I created the reranker by starting with a compact, open-source model pre-trained on Microsoft’s MS MARCO search dataset and fine-tuning it on nearly 40K query-passage pairs from our data. That taught the model what “relevant” looks like from our initial Cohere setup, and allowed Delphi to deliver high-quality results more quickly and cheaply.
If you don’t know what this means, don’t worry. It’s absolutely not necessary to get this deep into the weeds. I certainly didn’t expect to fine-tune even a tiny model of my own, but bit by bit, you start to become interested in what else you can do. The system above is, I’m sure, far from perfect, but it’s working well for me at the moment.
Now, using Delphi, I can type in a half-formed query like “remind me what philosopher Karol talked about on the podcast,” and it will recall that Karol Hausman, CEO of Physical Intelligence, shared his interest in Spinoza.
If I want to ask something that requires referencing multiple sources—for example, what CEOs have said about their hiring practices—it can handle that too, pulling in references from across my corpus.
I could have answered these questions in the past. The first one would have taken me a few minutes of pecking and tabbing; the second perhaps several hours. In all likelihood, I simply wouldn’t have bothered.
As a destination, I don’t use Delphi that often, and I still think it can be greatly improved. The UX isn’t quite as polished as I would like, and search is good, but could still be faster and smarter. But it mostly does what I want it to, and it’s reassuring to know that it’s there when I need it. As you’ll see, its power is leveraged in our other tools.
The most useful thing I have built is not visible, nor easily explicable. It is a concatenation of skills, tools, techniques, and preferences that allow me to gather information widely and thoroughly, without having to do the hunting and pecking myself.
Fundamentally, my research system operates through a collection of agents dedicated to snuffling out relevant information from particular mediums. One scans my internal corpus for existing work. Another reads relevant articles. A third seeks out podcast appearances.
Like Liam Neeson’s protagonist from Taken, each of these has been equipped with a “particular set of skills” that aid them in their quest. Jina and Firecrawl turn webpages into clean, readable text. An open-source tool searches YouTube and pulls crisp transcripts of interviews. Various scripts search for a subject’s published writing (a blog or personal webpage) or secondary media appearances. A headless browser allows agents to access articles on paywalled sites for which I have subscriptions. Instead of having to check The Financial Times, The Economist, and The New Yorker one by one, the agent can do it for you, as long as you’re logged in.
Crucially, it can do all of this in the background while you work on something else. Not only have you avoided the attention pitfalls and switching costs imposed by the modern web, but you’ve effectively hired a capable research assistant. I had always hoped The Generalist would grow large enough for it to make sense for me to hire such a person; now, I have been granted a dozen, each with a very strong grasp on what I am likely to find most relevant.
To ensure the research is conducted at a high standard, I’ve created a set of skill files for these agents to reference. These include dictums such as: