CMO at Humanity Labs | Building the AI Workforce for the Human Firm | AI-native, AI-first | In the great debate, I believe that ST:TAS is canon.
New York, NY, USA
Joined June 2008
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Grad Conn retweeted
Republican voters showed up this week. A lot of them just walked into the booth and voted Democrat.
That's how the GOP lost 7 Senate seats while its own data team spent election week feeling pretty good about the numbers.
The thing they were watching has a name in campaign world. Data people call it composition, which is a fancy way of asking whether the folks voting this year look like the folks who voted for you last time. Same people turn out, you win. JD says that number kept coming back fine, and in Florida the electorate landed 9 points more Republican than Democrat, only a couple points off 2024.
The problem is that number can only see who walks in the door. Once someone's inside the booth, the model has no clue what they did. A guy who voted Trump in 2024 and voted for the Democrat on Tuesday shows up on that dashboard as a turnout win.
And there were a lot of those guys. NBC's exit poll found 7% of Trump 2024 voters went Democrat for the House, while only 2% of Harris voters crossed over the other way. In Kansas it was 10% of Trump voters, which is how Adam Hamilton became the first Kansas Democrat elected to the Senate in nearly a century.
Republicans tried to spend their way out of it too. They outspent Democrats on Senate ads $227 million to $154 million down the stretch and still lost 10 of 11 battleground states.
Anyone who's sat through a weekly business review knows this trap. I ran them at Epic, Affirm and Apollo. You track how many people log in every day, the number looks great, and nobody notices that a chunk of those logins are people on their way to cancel, because a login looks the same either way.
JD's other pollster went about it differently. He went straight to the Trump voters who had left and asked what would bring them back. End the war, deal with prices, put America first, change the relationship with Israel. Those four answers covered almost everyone, and JD says the same pollster called a 13-point generic ballot loss the day before.
He asked the people who left what it would take to get them back. That one question told him more than $227 million in ads could.
One of the things the data analysts on our side obsessed over was "composition"—whether the electorate looked close enough to 2024 for Republicans to win. And despite polls that showed a Democrat blowout, the data kept on telling us the same story: in some states turnout was merely OK, in other states it was downright amazing, and in no state was it catastrophic. There was a genuine sense of optimism on our team: our people were showing up.
So, I asked the smartest data guy I know, does that mean we're going to shock the world? "No," he told me. "We might do better than the polls suggest. But the data is telling us that a lot of Trump/Vance 2024 voters are pissed and planning to vote for the other guys. Our voters are turning out, but they may not vote for us."
Well, that looks prophetic now. Our voters did show up. In Florida, for example, the electorate was 9 points more Republican than Democrat, just a couple points worse than 2024. Undoubtedly there were places we could have done better on turnout. But the main problem is not turnout. The main problem is that many people who voted for Trump/Vance in 2024 voted for Democrats in 2026.
There will be a lot of infighting and arguing over what happened and why that is. One of the pollsters I really respect told me that our economic messaging wasn’t sharp enough down the stretch. I’m sure that’s true.
But the real reason we lost is obvious to almost everyone.
Another pollster—one of the smartest people I know in politics, told me yesterday we’d lose the generic ballot by 13 points. I felt negative going into Tuesday, but even I was shocked by this. In his polling, he saw that a lot of Trump 2024 voters were angry and planning to vote for Democrats. He asked those voters who had abandoned us what would cause them to come back on our team. The top four answers, accounting for nearly all of the responses were:
1) End the war
2) Focus on cost of living/inflation
3) Put America First
4) Change our relationship to Israel
Our voters showed up. And the above four reasons are why many of them voted for Democrats. This is according to a pollster who nailed the results. While many spent Monday attacking Rachel Campos Duffy for calling for a diplomatic resolution to the conflict, it turns out her political advice was sound. (She’s also a great person.)
In the next few months, there's going to be a lot of gaslighting. Expect to hear any number of establishment politicians say the solution to our woes is amnesty. I'm open to the idea that we should change enforcement—by focusing more on businesses that hire illegal labor, for instance. But anyone pushing amnesty is lying to you.
The reason we lost is the war. The president himself said so last night.
If you'd like to argue it was worth it, that losing the Senate for the next 6 years was worth it, then do so. Argue it was a worthwhile cost to pay. Agree or disagree, that's at least honest.
But everyone knows why we lost. And any honest conversation about where we go from here must start there.
I remain hopeful about our country. To the people who are pissed off and want to say, “I told you so”: you’re right, you did tell us so. Take that energy into electing Republicans who share your worldview. To the people who are just pissed at the results, you should be. Let’s take that anger and get back to the work of saving our country.
I’ve been making this mistake with my Time Machine over and over again and it’s really a giant pain in the ass. One of these times I’m going to mess up so big that my suit will run out of oxygen before I can catch up with the planet!
If you built a time machine and went back just one minute, you'd die in outer space.
Earth wouldn't be there anymore. It would be about 22,000 km away, almost two whole planets down the road, because the ground under your feet is flying through the universe at around 830,000 mph and your time machine didn't come with a steering wheel.
And we actually know that speed pretty precisely, which still kind of blows my mind. The Big Bang left behind a faint glow of microwave light that fills every corner of the sky. It reads 2.725 degrees above absolute zero, almost exactly the same everywhere you look. The patch of sky we're heading toward runs about a tenth of a percent warmer, and the patch behind us runs cooler by the same amount. Same reason your windshield gets hit with more rain than your back window when you're driving through a storm.
Back in 1977, a Berkeley team led by George Smoot bolted a microwave detector into a U-2 spy plane, flew it 20 km up, and measured that warm side well enough to clock our speed. NASA's COBE satellite nailed it down later. Relative to that glow, the Sun is doing about 370 km every second.
This is where time travel gets really messy.
Galileo figured out back in 1632 that you can't feel steady motion. Below deck on a smooth ship, a dropped ball falls straight down whether you're docked or sailing. Einstein built relativity on top of that idea, so "where you were a minute ago" only means something once you decide what you're measuring from.
Measure from the Sun and Earth moves about 1,800 km a minute, so a one-minute jump puts you somewhere between 1,800 km up in space and 1,800 km underground, depending on which side of the planet you started on. Measure from the center of the galaxy, which is what the counter in this animation tracks at 21,200 AU in 455 years, and you're about 13,000 km off. Measure from the Big Bang's glow and you're at 22,000.
Every time travel movie skips this. Doc Brown's DeLorean shows up on the same street in Hill Valley because the movie quietly decided Earth is the one thing in the universe standing still.
If you want the most honest answer to "where was I," that ancient glow is the best one anyone's got, since it's the only thing spread evenly across the entire universe. Nothing about using it breaks Einstein, either. Physics works the same at any steady speed.
And 370 is us going slow. The whole Milky Way drifts through that glow at about 550 km/s, and right now the Sun's lap around the galaxy points mostly the opposite way, so it cancels out a big chunk of it. In about 115 million years, halfway around the lap, the two line up and our speed roughly doubles to somewhere near 780 km/s.
So get your time machine's math wrong by 34 seconds and you'd be floating directly in Earth's path, with the whole planet coming at you at 830,000 mph.
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Grad Conn retweeted
Here’s a story for you. We started filming without owning the title and had to do alternates.
Taft Broadcasting owned the title Ghostbusters as part of their half-hour sitcom starring Larry Storch and Forrest Tucker (F-Troop) and a gorilla chasing ghosts. I had never heard of it. They didn’t have proton packs or Bill Murray. Columbia paid $500,000 to buy the name, but they really should have paid Dean Martin, from whom I first heard the term.
In the film Scared Stiff (1953), he and Jerry Lewis (check out his acrobatic stair descent) are in an old haunted castle, and Lizabeth Scott asks Dean: “Who are you guys?” And Dean answers: “You’ve heard of Trustbusters and Gangbusters, we’re Ghostbusters!”
For my research writing the first movie, I watched every single ‘ghost’ comedy ever made. Bowery Boys, Hope and Crosby, Abbot and Costello, Martin and Lewis all did such films.
Happy Halloween 2026.
Grad Conn retweeted
My Grok Bot now decides what I post every morning to get over 100k impressions per post
here's everything it does:
1. Scout.
it reads the 18 accounts I learn from and keeps only original posts that cleared 5,000 views. anything past 10k gets a star. replies don't count.
2. Pattern miner.
it doesn't copy posts. it pulls what keeps showing up in the winners: cold opens, numbered stacks, named tools, soft calls to action.
3. Draft writer.
patterns go in, ready English drafts come out, each with a short video tip. same energy that already traveled, none of the original wording.
4. Weather check.
every day it also scans ~20 fresh AI posts from the last 48 hours outside my list. my watchlist is school. outsiders are the weather.
5. Noon digest.
everything lands before noon: the hits, the patterns, the drafts. I open it with coffee instead of scrolling for an hour.
6. The board.
one screen with my X Score, a daily target and a DONE / NOT DONE chip on every hit. I see what's left at a glance.
the result: I ship 1-2 posts a day without guessing. and the formats it chases are the same kind that took one of my posts to 5M views per month.
it never posts for me. I pick the draft, fix it in my voice, hit publish.
it's free. the repo, the live board and the Grok Bot template are in the article below
Readers added context they thought people might want to know
Recent posts by this account have 10k-36k views, not over 100k impressions. The described system is an experimental manual tool per its repo and docs; the public board is a static demo with placeholders.
github.com/monkeyteamvip/…
monkeyteamvip.github.io/kiosa-board/
x.com/thegreatest_sv…
x.com/thegreatest_sv…
x.com/thegreatest_sv…
Grad Conn retweeted
This is perhaps one of the great ironies of our time: China is increasingly shaping the future of AI, yet very few people in the West have the faintest idea how its key thinkers see it - its philosophers, sociologists or ethicists.
As is too often the case, we - much like the frog in the well - assume our own AI debate covers every possible view, when much of it springs from the same cultural soil, built on assumptions about what defines us that we don’t even know we’re making.
Take for instance the assumption that intelligence is a key part of what makes us human. It’s so intuitively obvious to us that we literally named our species after it - Homo sapiens (Latin for "wise man").
If you think about it, just this assumption explains a large share of the anxiety: if intelligence is what makes us human, then artificial intelligence - or super intelligence - threatens the very thing that makes us us: we’re about to compete with artificial or super “us”. No wonder this feels existential.
But China has a tradition of thought as old as ours, if not older, and every bit as rich and sophisticated, which never placed intelligence at the core of what makes us human, and so meets the thinking machine from a completely different starting point.
Have you, for instance, ever heard of Zhao Tingyang? Probably not, and yet he may be the most original thinker on AI you’ve never read. He’s one of China’s most prominent philosophers, at the Chinese Academy of Social Sciences. While Silicon Valley spends billions trying to make AI share our values, he for one argues that doing so “may very well be a suicidal mistake”.
Sounds pretty important to hear him out, don’t you think?
Or take Liu Yongmou, a philosopher of technology at Renmin University in Beijing. His thinking is almost the opposite of ours. Where we fear machines that become more and more like us, he says that “humanity’s biggest problem is the machinization of humans, not the humanization of machines.”
You could even go back to antiquity, when, in many ways, we started asking questions about AI.
Did you know, for instance, that Aristotle, in the Politics, imagined a world where “the shuttle would weave and the plectrum touch the lyre without a hand to guide them”, and wondered about the social order consequences of this (mostly whether slaves would still be needed)?
There are Chinese equivalents to this. For instance, in the Zhuangzi, a foundational Taoist classic, you’ll find a similar thought experiment, with a completely different worry attached. An old gardener is watering his vegetables by hand, hauling water out of a well jar by jar. A visitor shows him a labor-saving device, and the gardener turns it down for the reason that whoever uses machines ends up with 机心 (jīxīn), a “machine-heart” - a mind that schemes, calculates and loses its simplicity. “It is not that I do not know [the machine],” he says, “but I should be ashamed to use it.”
Two labor-saving machines, two very different questions: where Aristotle wondered what automation would do to the social order, the Zhuangzi wondered what it would do to us, on the inside. Which, you’ll notice, is exactly Liu Yongmou’s worry, more than two thousand years earlier.
In fact, as we’ll see, 心 (xīn), the heart, is a motif that runs deep through the Chinese AI debate. It appears both in the fear, from Zhuangzi to Liu Yongmou, that machines could give us a “machine-heart” and its mirror image: the ambition to give machines a heart of their own. Zhu Songchun, who heads the Beijing Institute for General Artificial Intelligence, wants “to set a heart for machines” (为机器立心, wèi jīqì lì xīn).
“Heart” in the Chinese sense, that is, which differs totally from the Valentine's Day fluff we’ve reduced it to. 心 (xīn) means heart and mind at once: it’s where we feel but also where we think, tell right from wrong and care for others.
And, crucially, it’s in the heart that the quality Confucianism sees as the very definition of a human being takes root: 仁 (rén). We need two words to translate it, “benevolence” and “humaneness”, but in Chinese they’re one and the same: to be benevolent is to be human. It’s not about intelligence.
This is the entire point of my new article: to step out of our well for a moment and peer over the edge of China's.
What you’ll find there will, I think, surprise you, with questions you’d never thought to ask: from Zhao Tingyang warning that AI’s bad consequences can at least be fought, but that “humanity may die of all the good things AI creates”, to whether the fear that AI will make us “useless” rests on the false premise that a person is worth what they’re useful for.
A premise that a 2,300-year-old Taoist tree, which survived precisely because it was useless, demolished long ago. Could our predicted uselessness turn out, much like that tree’s, to be our saving grace?
Chinese thinkers’ answers to these questions are, I think, among the most interesting anyone has given to the defining question of our time. Whether or not you agree with them, they’re the intellectual backdrop of a country shaping much of AI, and with it our future: you might as well know what they think.
Enjoy the read here: arnaudbertrand.substack.com/…
We live in whatever era is the era that is past and beyond the thinking of science fiction authors…
After six years in stealth, Atomic Machines is out. Our mission: on-demand, universal command of matter. First beachhead: the Matter Compiler, an AI-native manufacturing system that builds working micro-machines from code alone. No per-product tooling. No process development. Different code, different machine.
Grad Conn retweeted
Rita Moreno performed “Fever” with Animal on The Muppet Show (1976) — a comedic performance that earned her an Emmy Award.
Grad Conn retweeted
The most insane paid ads program in Silicon Valley, behind Wispr Flow's $0 to $2B run
1/ "10 really good creators can get you to $50M a year"
-> The model: brands recruit creators to film their ads and pay them a percent of the ad spend
2/ A year ago Wispr Flow stopped organic UGC completely and put everything into paid
-> 500 to 700 new UGC ads a month now, aiming for 1,000
3/ They took the paid ads playbook of killer ecom brands
-> SF finally figured out what the best DTC brands have been doing for years
4/ Their view: organic only works with real talent on the team, while paid works for anyone who can ship enough different ads
-> You don't need a genius to win on paid, you need lots of ads that each look and sound different and a system that keeps them coming
5/ Ecom brands pay creators a cut of each sale. SaaS brands pay a cut of the ad spend, since a software sale can take weeks to close
6/ Wispr pays 7% of ad spend, uncapped, paid out every 7 days
7/ New creators get a guaranteed minimum, which is how Wispr signed good ones before it had a track record
-> $1,000 for 20 to 25 videos a month. A creator who earns $500 in commissions gets the other $500, and once they earn more than $1,000 on their own the guarantee stops
8/ Each creator works on one customer segment
-> A customer no ad was speaking to, a format nobody could shoot, a country with nothing running. One creator per gap
9/ No two videos are allowed to look alike
-> Meta's Andromeda clusters videos that are 50 to 60% similar and suppresses them, so 1,000 talking heads get treated as one ad
10/ They recruit on Instagram with keyword search
-> Search "UGC creator", "tech", "SaaS", mine the followers and comments of every good creator, send 100 to 200 DMs in a week
11/ 50 creators accepted out of 5,000+ applications
-> $220k paid out so far, top creator makes $12k a month
12/ Creators get $100 for referring someone at their level or above
-> No beginners on the team
13/ They scaled 5 creators, then 10, then 20, then 40, and stopped at 40 to 60
-> The whole climb from 5 to 50 took four months
14/ Creators are run like a sales team
-> 30-minute onboarding each, a weekly call with the media buyer, 1:1s, creator coaches
15/ Creators see the ad account
-> Every Thursday the media buyer walks them through what's working, which customers to target next and what to test
16/ One media buyer runs all of it: 50 creators, 700 ads a month
17/ The same creator ads run on Meta, AppLovin and TikTok
18/ The group stays small on purpose
-> $100k paid to 20 creators looks better to creators than $200k paid to 1,000
19/ Creators see which ad is winning and start making their own version of it. Wispr stops this and pushes them to film something new instead
-> Meta treats the copy as the same ad as the original, so the copy never gets shown
20/ Why other creator programs fail: brands accept everyone who applies, nobody coaches the creators, and creators join without understanding they only get paid when their ads perform
21/ Meta charges more every year for the same amount of reach, and that cost is out of Wispr's hands. The one thing they control is how good and how different their ads are, so that's where the money goes
-> Last quarter Meta showed 14% more ads than the quarter before and still raised the price of each one by 12%
22/ The guy who built it joined Wispr Flow at 19, before the product existed, with a 2.5 GPA
-> 25 months later: $280M Series B at a $2B valuation
So, I finally saw GOOD WILL HUNTING (I know, I've been busy) and it struck me that this Robin Williams' speech is oddly appropriate in the Age of AI: There's a human sensory experience that writing just can't quite capture, and it's special: youtu.be/8GY3sO47YYo?si=QMQx… via @YouTube
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There's always money in solving the everyday.
there are so many everyday demos that could make ai, personal agents, & agents in general feel insanely powerful to normal ppl & yet ai companies keep choosing things like booking flights, planning travel, or god forbid planning a god damn wedding.
these are not everyday problems. they’re relatively rare events & worse for a lot of ppl they’re actually part of the joys of life. the best demo should make someone feel pain they already are familiar with disappearing. almost every company gets this wrong. they optimize for spectacle instead of relief which is fine in some cases but it doesn’t last.
one of my favorite historical examples is a product called head on.
the ad showed someone with a headache, then showed them applying the product directly to their forehead while repeating:
“head on. apply directly to the forehead.”
beautifully simple. you instantly understood the product, the problem, & the value. ai companies should be doing the same thing.
show me the annoying thing i deal with every single day then make it disappear. it’s not sexy, i guarantee it will work. when jobs demo’ed the iphone he picked universal simple problems that the iphone did better than anything else on the fucking planet.
anyway, thanks for coming to my ted talk.
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Maslow's hierarchy of agent needs ... I like the idea, I might phrase it as an agent autonomy hierarchy. But generally, excellent progress here.
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AI-driven inflation. Now THIS is an interesting unintended consequence!
🦔The Blue Cross Blue Shield Association says insurers paid out nearly $1 billion more than usual from AI-assisted hospital documentation in 2024-2025. Hospitals use AI to scan records and find secondary diagnoses that human reviewers missed. More diagnoses means higher reimbursements. But treatment levels haven't gone up.
BCBSA's SVP of data science said AI is "identifying more billable conditions, not sicker patients." Insurers now deploy their own AI to deny those same claims. Patients pay for both through higher premiums.
My Take
This might be the most American healthcare story I've ever read. Hospitals bought AI to find more things to bill for. Insurers bought AI to deny those bills. The technology cost money on each end and the tab went straight to patients through higher premiums. A billion dollars moved and no one got any healthier. The only thing that changed was the size of the invoices.
Two sides of a trillion-dollar industry found a new tool to fight over the same pool of money and the person in the hospital bed pays for all of it. Premiums go up, denials go up, and the AI vendors collect from everyone. If you want to know who AI works for, stop reading the press releases and look at where the money goes. In healthcare it went straight into the billing department.
Hedgie🤗
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Grad Conn retweeted
🦔The Blue Cross Blue Shield Association says insurers paid out nearly $1 billion more than usual from AI-assisted hospital documentation in 2024-2025. Hospitals use AI to scan records and find secondary diagnoses that human reviewers missed. More diagnoses means higher reimbursements. But treatment levels haven't gone up.
BCBSA's SVP of data science said AI is "identifying more billable conditions, not sicker patients." Insurers now deploy their own AI to deny those same claims. Patients pay for both through higher premiums.
My Take
This might be the most American healthcare story I've ever read. Hospitals bought AI to find more things to bill for. Insurers bought AI to deny those bills. The technology cost money on each end and the tab went straight to patients through higher premiums. A billion dollars moved and no one got any healthier. The only thing that changed was the size of the invoices.
Two sides of a trillion-dollar industry found a new tool to fight over the same pool of money and the person in the hospital bed pays for all of it. Premiums go up, denials go up, and the AI vendors collect from everyone. If you want to know who AI works for, stop reading the press releases and look at where the money goes. In healthcare it went straight into the billing department.
Hedgie🤗
