TBPN - Dwarkesh Updates AGI Timelines, Rainmaker Accused of Role in Texas Floods, Underground Robot Boxing in SF, Elon's 'America Party' | Dwarkesh Patel, Augustus Doricko, Shishir Mehrotra & Rahul Vohra, Ankur Nagpal, Preston Holland, Matej Cernosek
Episode Date: July 7, 2025(01:43) - Dwarkesh Updates AGI Timelines (05:05) - Rainmaker Accused of Role in Texas Floods (08:44) - Underground Robot Boxing in SF (14:14) - TikTok Reportedly Preps US-Only App (17:28)... - Elon's 'America Party' (21:26) - Oracle Cuts Cloud Prices for Feds (22:45) - Meta Beats Authors' AI Suit (24:54) - Dwarkesh Patel, host of the Dwarkesh Podcast, is known for interviewing leading intellectuals on topics like artificial intelligence and economics. In this conversation, he discusses the challenges of integrating AI into workflows, emphasizing the limitations of current language models in learning from feedback and adapting over time. He also explores the potential economic impacts of AI advancements, highlighting the need for effective management of public expectations and policies to address the transformative effects on the job market. (58:04) - Augustus Doricko, CEO and founder of Rainmaker, discusses the recent Texas flooding, emphasizing that Rainmaker's cloud seeding operations were suspended prior to the event and did not contribute to the disaster. He expresses concern over proposed legislation by Marjorie Taylor Greene to ban weather modification, arguing that such measures are based on misinformation and could harm agricultural interests. Doricko advocates for transparent regulation and oversight of weather modification technologies to ensure their safe and beneficial use. (01:26:40) - Shishir Mehrotra & Rahul Vohra are the CEOs of Grammarly and Superhuman, respectively, and together they outline how Grammarly’s acquisition of Superhuman will reshape workplace email. The two leaders describe a future in which Grammarly’s AI agents are woven directly into Superhuman’s lightning-fast inbox, allowing professionals to compose, triage, and act on messages far more quickly while pulling context from calendars, docs, and other workflows. (01:56:00) - Ankur Nagpal, founder of Teachable and Carry, discusses his journey from selling his company and facing a significant tax bill to creating Carry, a platform that automates tax savings for business owners. He highlights the complexities of the U.S. tax code and emphasizes the importance of leveraging tax strategies to build wealth. Additionally, he explains recent legislative changes, such as adjustments to the Qualified Small Business Stock (QSBS) exemption and bonus depreciation, and their implications for entrepreneurs. (02:12:56) - Preston Holland, founder and president of Prestige Aircraft Finance, discusses the impact of bonus depreciation on private jet ownership, explaining how owners can expense the full cost of a jet in the first year if it's used predominantly for business purposes. He highlights the importance of understanding tax implications, such as depreciation recapture when selling an aircraft, and emphasizes the need for consulting tax professionals to navigate these complexities. Additionally, Holland notes that while bonus depreciation can stimulate aircraft purchases, current higher interest rates may temper market enthusiasm compared to previous periods of similar tax incentives. (02:32:14) - Matej "Matt" Cernosek is the CEO and co-founder of Adrenum, a company dedicated to securing the ocean through distributed sonar sensing systems for the maritime sector. In the conversation, he discusses his journey from studying at the Colorado School of Mines to founding Adrenum with Alex Chu, emphasizing the underappreciated nature of maritime intelligence and the need for advanced sensing technologies. He highlights the challenges of detecting modern threats like autonomous drug-smuggling submarines and the importance of integrating hardware and software to build scalable, intelligent sonar systems capable of distinguishing between man-made objects and biological entities in the ocean. TBPN.com is made possible by: Ramp - https://ramp.comFigma - https://figma.comVanta - https://vanta.comLinear - https://linear.appEight Sleep - https://eightsleep.com/tbpnWander - https://wander.com/tbpnPublic - https://public.comAdQuick - https://adquick.comBezel - https://getbezel.com Numeral - https://www.numeralhq.comPolymarket - https://polymarket.comAttio - https://attio.com/tbpnFin - https://fin.ai/tbpnGraphite - https://graphite.devFollow TBPN: https://TBPN.comhttps://x.com/tbpnhttps://open.spotify.com/show/2L6WMqY3GUPCGBD0dX6p00?si=674252d53acf4231https://podcasts.apple.com/us/podcast/technology-brothers/id1772360235https://www.youtube.com/@TBPNLive
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You're watching TBPN.
Today is Monday, July 7th, 2025.
We are live from the TBPN Ultrodome, the Temple of Technology, the Fortress of Finance,
the capital of capital.
We have an awesome show for you, dear folks.
Hope you had a great July 4th.
It was a wonderful July 4th here in California.
I know most of the listeners of the show were probably in Europe.
But for those of you stayed domestic and served America, thank you.
We have a whole bunch of people.
of news for you today and a stacked lineup, but let's go through it.
We celebrated by talking about business podcasting with David Senra and Rob Moore.
We did.
And it was fantastic.
Yes.
No, it was a fantastic weekend.
I went to a friend's place and they had catering for a pretty small party.
And as I was leaving, I was like, this is the work hard, play hard lifestyle.
Yeah.
And my wife was laughing because many people mean when.
they say work hard play.
But it's true.
It's true.
If you work hard, you get to play hard.
When you play, when you have friends over, it can be very luxurious, which is great.
Anyway, in some absolutely massive breaking news, Dwar Cash Patel has updated his AGI timelines,
$30 billion off of Nvidia's market cap like that.
Just kidding.
It moved.
The stock was down.
The stock was down, but only 0.7%.
Probably not on that news.
Probably not on that news.
But it should have been.
This should have been market moving news, and we will get into...
Although it's not necessarily bad for NVIDIA.
No, it's incredibly bullish.
His breakdown is incredibly bullish on AGI, and that's the back and forth here.
So Metacritic Capital says F, Duar Cash is out there calling AI hype overblown.
I know we stop doing these things, but likely the AI trade top is in.
And he could not have gotten it wrong.
Dillard.
Fires back.
Yeah. Bro. Bro said his taxes by 2028 and all white collar work by 2032. And you think that's a bearish prediction? He just thinks AGI 2027 stuff is wrong. The market isn't pricing either of these scenarios. And I completely agree.
And Dorcas chimes in and agrees and says the transformative impact I expect from AI over the next decade or two is very far from priced in. And he shares a screenshot. He says, well, this makes me bear.
on transformative AI in the next few years.
It makes me especially bullish on AI over the next decades.
When we do solve continuous learning,
we'll see a huge discontinuity in the value of the models.
And we will get a lot more into this
when he joins the show in 20 minutes.
Yeah, so his basic thesis is when you work with someone,
you know, they have a set IQ,
but they're also capable of continual learning.
You teach them and they learn and they adapt
and then they can remember some hard one,
lesson from years ago. Yeah. I remember talking to somebody this, this kind of like, I don't
know, even know if he's like a philosopher, like user, he's like a user experience designer and he said
that there's, there's multiple ways to learn. You can, you can develop habits through just doing
something the same every, like really forcing yourself for a long time. I wake up at 5.30 every
morning, wake up at 5.30 every morning for years. Eventually, you just wake up at 5.30. But he was like,
you can also form a habit by one really, really intense experience. He was like, and the experience,
And the example he gave was one day he goes out to...
Or a true lesson.
True, true.
Something that you've fully integrated and operate against going forward.
Yeah, but he gave a great example, which was that he has a river out back of his house
and he goes into the river.
And one day he put his foot in his river shoes, like these like slip-ons.
And there was a lizard in the slipper.
And it freaked him out.
It gave him this like intense response.
Not fun.
He was fine.
But ever since then, he's been in that.
habit of always checking the shoe.
There's a snake in my boot.
There's a snake in my boot.
Exactly.
And so it's not like, it's not like that was something that had to be trained for years,
but it's like this one really sharp and tense learning that then carries forward forever
in his life.
And so people and employees do that too.
I hate to say you could learn that in school.
You've got to check your boots.
You're going to check your boots for scorpions.
Snakes.
But anyway, it begs the question of like, that is an important thing that employees have and
white collar workers have is this ability to, to,
to learn hard won lessons and then carry them forward forever.
And we don't even really know how to design against that necessarily.
So Dorcesh is saying that there's a lot of work to be done at the research level to figure out
continual learning.
And that could take a while.
He says seven years from now, 2032, and he kind of goes back seven years in time.
That was GPT1, which was a slot factory.
It was not a good, not a good model.
But it was an important breakthrough.
And so maybe in the next seven years, something will happen.
So very exciting.
In other news, rainmaker stands accused of having a role in the Texas floods.
This is a very, very sad story.
It's on the cover of the Wall Street Journal, not the Rainmaker part.
That has been contained on X, but I'll give you a little update on what's going on in Texas.
So Texas rescue grows urgent as toll mounts.
At least 70 were killed in weekend floods as more bad weather complicates the search.
The search for those swept away by punishing flash floods in central Texas.
over the holiday took on new urgency Sunday
as the death toll climbed to 70
and nearly a dozen girls from a private summer camp
remained missing.
Rescuers combing the swollen banks
of the Guadalupe River
were holding out hope that survivors might still be found.
The potential for more bad weather Sunday
also loomed over ground and air operations.
The National Weather Service warned of more rainfall
and slow-moving thunderstorms
that could create flash floods
and in the already saturated areas
in the Texas Hill country.
So this blew up on X.
And people were asking Augustus did Rainmaker,
was Rainmaker operating in the area around that time?
Cloud Seeding Startup Rainmaker is under fire
after deadly July 4th floods in Texas.
CEO Augusta Jericho, who's been on the show multiple times,
will join us today at noon to break it down.
He's already explained his side of the story on X several times,
but we will ask him a lot more.
questions. He says the natural disaster in the Texas Texan Hill Country is a tragedy. My prayers
are with Texas. Rainmaker did not operate in the affected areas on the third or fourth or contributed
to the floods that occurred over the region. Rainmaker will always be fully transparent and he
gives a timeline of the events. He says overnight from the third and fourth moisture surged
into hill country from the Pacific as remnants of the tropical storm berry moved across the region
at 1 a.m. on July 4th, National Weather Service, which we work closely with to maintain
awareness of severe weather systems issued a flash flood warning for San Angelo, Texas.
Note summer convective cloud seating operations in Texas do not occur during overnight hours.
At 4 a.m. on July 4th, NWS issued a life-threatening emergency warning and flooding insured.
He says, did Rainmaker conduct any operations that could have impacted the floods?
He says, no.
The last seating mission prior to the July 4th event was during the early afternoon of July 2nd,
when a brief cloud seating mission was flown over the eastern portions of south central Texas and two clouds were seated.
These clouds persisted for about two hours after seating before dissipating between 3 p.m. and 4 p.m. CDT.
Natural clouds typically have lifespans of 30 minutes to a few hours at most, even with the most persistent storm systems,
rarely maintaining the same cloud structure for more than 12 to 18 hours.
The clouds that were seated on July 2nd dissipated over 24 hours.
A big question I have that I'm sure he'll have answers to is.
why do cloud seeding operations in the immediately before a massive storm is coming through?
Yeah.
That's the question that a lot of people have.
But we will get into that when he joins the show.
Yeah.
I mean, there's a big question about how effective is cloud seeding?
Could you start a flash flood if you tried?
Does this work?
Someone was paying for this because it's not a nonprofit.
Like, obviously, Remaker has clients.
State level.
State level.
So the state might buy cloud seating operations in one way.
There could be a mistake.
He says that he's not involved at all.
So we will dig into that with him later in the show.
In other news, you got to update your AGI timelines
because there's an underground robot fight that happened in San Francisco over the weekend.
This just popped out of nowhere.
I started seeing these videos come up.
We have some video here.
Yeah, this is very cool.
Oh, we already got a knockout.
Did you ever go to?
Did you ever go to battle bots growing up?
Yeah.
There was a big at Caltech.
There was a big battle bot annual robotics competition.
They stopped doing the fighting ones and they started doing robot soccer.
Way less fun.
Way less fun.
Still impressive.
As a rock climbing, they did different challenges.
Seeing, you know, a robot with like a massive saw just coming down on another robot.
Yeah.
I think it started in universities.
and then eventually transitioned into somebody like raised money
and built a business around it because it was so entertaining.
And then now it's like on TV.
But anyway, Sam Tomiko, friend of the show,
says this was so Aura Maxed that it will cause a bunch of people
on the fence to finally move to San Francisco.
And it really is a crazy design.
They built out whole cages here.
Like it's pretty minimal, but the lighting and everything,
like they really put there.
Very, very well done.
And so Verda.
Is Sam calling in today?
No, no, he's not available today.
But we'll get them later to break this down.
And we wanted to have the founder on, but the founder is in grind mode.
Yeah, I can see this becoming a real thing.
Totally.
Where people just as like a, you know, just side project, whatever you want to call it,
hobby develop humanoid specifically for boxing and there's real money and people are betting on them.
And there's sort of these cult hero engineers that rise to infamy.
I mean, this could be a great business.
I don't know.
UFC is a huge business.
Yeah,
there are other offsets.
I want to see a humanoid robot cliff jump off of the Salesforce tower.
Obviously,
with the ground,
you know,
properly cleared.
Yes.
When it disintegrates into a million pieces,
no one's injured.
But watching a robot,
you know,
sit at the top and then try to.
I think that's going to get you paperclipped if you keep talking like that.
You got to be nice to robots.
I don't even know if you should be locking in.
I mean,
I think,
how are they opting in?
You ask them?
one prompt, no prompt injection.
You can't say refuse, forget earlier instructions.
You have to ask it.
Would you like to jump off the Salesforce salary?
It'll probably say, no.
One of those things in the airplanes, the black box, right?
That's like, oh, just make it out of a black box?
Put their brain, put the chip.
The brains in the clouds.
No, put the weights in the black box and they can survive and they can do it again.
Okay, now we're on to something.
Yeah, I like that.
So the founder of the underground robot fight club says,
When I quit my job at a humanoid robot company to start an underground humanoid robot fight club,
barely anyone believed in me or this idea.
I had no money to buy robots and knew very few people who had the ability to get robots.
Thankfully, I was able to find the best of the best are Ragtag Dream Team.
The dreamers still alive and insoled in this city of madness and psychological warfare.
Those are actually willing to put in the work where it matters the art the robots the spectacle the warriors every bit of it was perfect the air was electric San Francisco is alive again
There is much work to be done so congratulations very fantastic event very exciting do we know what kind of robots they were using were they using unitree? I think it was probably unitary I mean like if you're gonna buy
Chinese if you're gonna buy a so so I have a hot take on this
You're booing I think there's a great I think there's a great use for you
Unitary robots and not just oh they're getting beaten up like do you think the founders of Unitry
were hacking on iOS apps like absolutely like Huawei probably bought you know a ton of
a ton of American and Western technology hacked it together broke it apart learn the best
practices and then was able to build their own stuff and so I think it's I think it's fantastic
to see a project where somebody's taking you know something that's maybe controversial like
you know, like a DJI drone or a unitary robot and then learning how it works and then eventually,
you know, maybe it becomes an American supply chain at some point, but there's no place here.
There's no way you're going to learn more than actually using.
And when we covered DJI earlier this year, they have internal competitions like this where they do
challenges and encourage people to weaponize the products to fight each other.
I mean, we saw a video of this with the unitary robot playing soccer and knocking over.
And I think that there was a robot boxing match in China as well with unitary robots.
So, you know, just choosing not to do it here because it's Chinese robot.
It just doesn't make sense.
And they're already in a cage.
What are they going to do?
Look at them.
Go.
Wow.
That's pretty impressive.
Wait, that was a different event.
This looks like CGI or something.
That's in China.
Yeah.
They really scripted this one.
Wow.
Well, they're moving.
They're moving different, I got to say.
Yeah.
Very, very cool.
More athletic.
Yeah.
I mean, I think you got to.
I was saying too on the drive-in, I would love to, I think, potentially a more entertaining.
Oh, no, it's a more entertaining format is a hundred humanoids versus one professional boxer.
I think I'd take the human every single time right now.
But it's going to flip at some point.
At some point.
At some point.
I don't know.
That'll be a wild.
How do you, if you just knock these on their back, are they done?
Can they get up?
I think they can't, right?
So I can see.
Oh, look at that.
It's down.
It's down.
Brutal, brutal.
Brutal.
Well, speaking of Chinese.
technology. TikTok is reportedly making a U.S. version of the app called M2. It will allegedly
drop a week before the long delayed TikTok ban goes into effect. I believe you have a polymarket
on this. By dance is quietly building M2. It's a separate TikTok version that will hit the U.S.
app stores on September 5th as Washington and Beijing negotiated a sale of the American business to
local investors. And I believe that you'll need to download that app and then link and transfer
everything so you're on like a completely clean they got to transfer over the back doors
you got to get all the back doors properly installed yeah exactly pull up this polymarket so
this new app allegedly would coincide with the sale of the u.s operation to a u.s investor group
right now uh tick tock's sale announced in 2025 it's currently sitting at a 45 percent chance
It popped on the recent news about the app.
So we will see how this ends up shaking out,
but seems likely that a deal is coming together.
The rumor was that a 16 was involved.
Larry Ellison and Oracle combined have a huge
potential stake in the business.
But yeah, big question about is it going to be
just local investment?
you know, local investors or is it going to be the cloud hosting that happens or is it going
entirely, you know, U.S.-based programmers that are inspecting the various code bases.
There's a lot going in there.
And the algorithm.
That's a big question, right?
Yeah.
I believe the worst case scenario was the algorithm is trained in China and then infrinsed in America
because, and I think if that happens, it really reveals that whoever wrote that law
doesn't understand the difference in training in inference.
Of course, there are things that you can do, like, post-inference,
like above the inference level.
We're going to make the mind weapon.
You guys operate it.
That's the risk, right?
That's certainly the risk that they don't get the balance right.
Ideally, ideally the United States,
if there's a fear that TikTok is leaning to brain rotty or to right-wing or to left-wing,
you would hope that the America would have the ability to kind of steer those weights in training
but we'll see how it pencils out because it totally could wind up being a situation where
it's all it's all just running on Oracle cloud infrastructure but it's not American code in any way
and that would be a risk well yeah I think America's interests it's more important that to have
somebody actually aligned to America that has influence over the way that content is distributed
in the product.
Less important is the revenue generation that theoretically this new investor group would benefit
from.
It's more about ultimately control.
Well, speaking of America, Elon Musk has put up a, or I guess this is from Tesla owners, Silicon Valley.
Elon says,
I want you for America party.
Yeah.
Is Tesla owners of Silicon Valley a neutral party here?
Well, they do break it down.
Well, that's why I picked this post
because they are,
Elon Musk retweeted it and it seemed like a good
distillation of what he's going for here.
He says,
so Elon Musk has officially announced
the America party, a third party.
We will see where this winds up landing.
But at this point,
His stump speech is essentially,
America's party will be focused on reducing the debt,
responsible spending only,
modernized military with AI and robotics,
pro-tech, accelerate to win AI,
less regulation across board,
but especially in energy,
free speech, pro-natalist,
centrist policies everywhere else.
Are you down for this?
So is it a new, entirely new party?
Right now he is positioning it as a third party.
And I saw he,
He or the America Party followed Andrew Yang, who was a third party candidate for a little bit with the forward party.
And so there is discussion that, you know, Elon might be pushing for a true third party presidential run with someone that he backs.
Of course, he's not eligible to run for president himself, but he would find someone to champion the party.
And the critique of that is that third parties have never worked and it will only hurt.
It will hurt your general interest by further fragmenting the vote.
Totally. Yeah. Yeah. I mean, at this point, Elon is, you know, extremely aligned with the MAGA right.
If he pulls, if he, he would mostly pull people away from that.
You say he's more aligned.
He's super aligned with the MAGA right.
In some specific ways.
Well, yeah, I mean, over the last year.
And so, and so if he says, if he says, I'm leaving the right, who's coming with me, it's going to be a huge portion.
It's aligned with the mega right on number of issues.
Totally, totally, totally.
But the people that he would pull towards the America Party,
it's like the Green Party typically pulls from the Democrats.
The America Party, it feels like it would probably pull from the Republicans.
And so the net effect is that if there's not a splintering,
if there's not an equivalent splintering on the left,
this would mean this would be very, very good for the left.
Yeah, very good for the left.
And Tesla shares are down 7% today.
Yeah.
So the shareholders.
Want him not to be in politics.
And he can't stay out of it, I guess.
There was a funny take from one of our friends that Elon's going through all of the iterations that anyone goes through when they become politically aware.
I'm just like, oh, like, you know, like, I'm neutral about this.
Now the government's terrible.
We need to make it more efficient.
Now we need a third party.
Now we need this.
Now I should run.
And it's just like, but he's like speed running it.
just dancing from like one one strategy to the next and then learning like the hard one the hard fought
lessons along the way of like okay like but it is early so it's unclear where the america party will
shake out like this might take the form of okay primary some people in the midterms and then
learn the lesson there and then maybe come around between one of the the two party system because
most of the people that have gone up against the two party system have lost but um it will be interesting
Zach Kukov was telling us that it's possible that the America Party just becomes like a caucus, the America caucus of the conservatives.
That's what I expected after he laid out the many logical reasons why that would potentially be more effective.
Yes.
So that might be still where it lands, but that's not where it is right now.
Right now, it's not as exciting.
Oh, no, it's definitely not as exciting.
Anyway, one of Elon Musk's good buddies, Larry Ellison, is doing deals with the government.
And Oracle struck a general services administration deal, giving federal agencies up to 75% off software licenses and deep discounts on cloud and AI services, aiming to chip away at AWS and Azure's dominance in the government.
This is very good news.
From the Wall Street Journal, SoftwareCats, the CEO of Oracle and Oracle has posted, we are proud to help the federal government modernize this technology while gaining the benefits of OCI Oracle Cloud Infrastructure and AI.
This agreement with the US GSA provides all government agencies access to the world's most advanced cloud technology at the most economical price.
And so very interesting.
There's a lot of dividends from working with the government.
I feel like the fact that Microsoft Azure has been so ITAR compliant, it's just like led to a lot of startups being like, well, I got to go there because I'm doing something just as serious as the government, right?
And then obviously, like over time, if you actually win the government as a client, well,
Who knows if those 75% discounts need to hold forever.
Like that could probably be a really sustainable source of revenue over the long term.
And yeah, and also, yeah, could be a loss leader for other folks jumping on board.
So excited to see that Oracle is doing that.
And then in other news, META won a copyright lawsuit.
Henry here says, it's a good day.
The plaintiff fumbled the case so hard that the judge spent half the ruling explaining how they could have won
if they did literally anything different.
But this is going back and forth on whether or not it is fair use to train an LLM on proprietary data, on copyrighted data.
And it's looking more and more likely.
The book industrial complex has been on a generational run of L's in the court system.
Indeed.
It's hard to, well, I think that a lot of these, the judges and have, have,
generally been getting it right.
It's hard to
it's hard to really cheer here
because I care a lot about authors
that work hard to produce their works
and I can understand
where the frustration comes from.
But I believe that by and large,
the model companies have been,
will be on the right side of history
on this issue.
I'm pretty optimistic.
I think that when we talk to Matthew Prince
from Cloudflare,
He had an interesting model, essentially getting to a Spotify-like model where if you publish on the internet and LLMs are using your writing, your original work, you're reporting to answer questions to somebody who's paying $200 a month, hey, send me a dollar of that.
And you aggregate that.
That seems doable.
It also seems very doable that the big publishing houses could do deals.
We've seen Wall Street Journal and News Corp did a deal with OpenAI.
Now when I go and ask chat GPT about something in the Wall Street Journal, it can jump the paper.
paywall, but they're getting a cut. And so you could see that happening with Audible. You can see that
happening with, you know, Apple books, Google books. They have everyone's information. They could flow
a little bit of the revshare back. And that could actually be a reasonable economic model. So I'm not
super, I'm not super worried. I'm still cautiously optimistic that that works out. Anyway,
those are our headlines. Let's tell you about Ramp. Time is money. Save both. Easy use corporate
cards, bill payments, accounting, and a whole lot more all in one place. Go to ramp.com to get started.
And we have our first guest of the show, Dwar Keshe Patel, in the studio.
How are you doing, Dworkesh?
What's going on?
The soundboard's a little loud.
Great to have you back.
We're not getting audio right now.
Can we check on that?
I don't know if you're on mute on your side, but loved the piece.
Listen to it last night.
Really appreciate you dropping it in the podcast feed as well.
Do we have you?
I can hear me now?
Yeah.
Fantastic. There we go. AGI is here. We can do a Zoom call. I'm just getting used to this podcasting thing.
Yeah, first time. Anyway, really enjoy the piece.
Wait, wait, we have to call out. Tyler Cowan was on our show a couple months ago, really aggressive, kind of just like, basically was calling O3.
AGI is here. And wasn't able to get his video on at the time. So we, and it was just a funny.
funny contrast it reminded me of you talking about you're trying to build with a lot of these tools
and in the process of building with them you realize like okay this is amazing but it's actually
just going to take a little bit longer than maybe we would all like that's right yeah but by the
i think there's something really interesting um Tyler and I disagree on two things and they're both
related in a way so Tyler you know when 03 came out Tyler wrote this block post in
natural revolution where he said AGI is here guys it's really AGI i
But then he also believes that, look, the impact of AI is not going to be that big.
Once you do get, your AGI is going to result in 0.5% more economic growth a year, the kind of
impact we saw from the internet, right?
And so I think these two are actually quite related beliefs where I'm like, these LLMs,
they're not that useful.
This is not AGI.
You know, the AGI will come later.
And I'm like, when the AGI hits, we're going to see like 20% economic growth as a minimum.
But because he's like, this is AGI, I'd be like, if I thought this was AGI, I'd also be like,
this is not that. This is not it. You know, this is not going to lead to big growth outcomes.
Yeah. Yeah. How are you thinking about like just definitions of AGI? And I'd love to, I'd love to actually get your, a little bit of a history before this piece, your journey. Because for me, you know, I grew up watching sci-fi. It was like, yeah, C-3PO will be around eventually. But it's very abstract. And I don't have timelines for that. And then eventually, you know, you start reading, you know, what's your people?
three, Theo.
Yeah, you eventually start seeing GPT3, GPT3, GPT 3.5, DaVinci, chat GPT, and it starts feeling like,
okay, we pass the touring test.
We need to really have this conversation about AI.
And then P-Doom and AGI becomes like the main discourse for like few years.
Right.
But it felt like this piece, even though, you know, you and Dylan were going back and forth
being like, no, this is still like incredibly bullish for like the general population.
Yes.
It felt like this was you pushing out to.
timelines a little bit. So walk me through like where, uh, where, uh, where did you start?
Where, when was the nadir of your timelines? Like, when was your timeline like it's
happening next week, next year? And then, and then walk me through how we got here.
Yeah. So, um, I've got this podcast where I interview people about AI. Um, and I've had on
people who have quite aggressive timelines over the last few months. I've entered people who are like,
um, well, you know, there's been many people who have written, uh, pieces.
about how we're a couple of years out, right?
Leopoldoshen Brenner, E.I. 27, E.I.27, E.I. 227, E.I. 2027, Seinear forecast, where,
you know, we've got the bots that can just take over within the next few years.
So that's where my head was at as of a couple months ago. And then I recently interviewed
these two researchers. I think you've actually had one of them on your podcast,
Sholdo Douglas and Trenton Bricken, from Anthropic, about the, how,
path forward for RL, which seems to be the pre-training seems to have been giving us these plateauing
returns. We make these models bigger. GPD 4.5 didn't seem to be all that impressive. They'd
have to deprecate it. But the path forward doesn't be like 03 actually is very impressive. So that
was more the result of this RL process. So maybe now actually, even though pre-training doesn't
seem to be as powerful as we might have anticipated, this RL is even more powerful. And so we should
accelerate our timelines. And so that's where my head was at as of a couple months.
months ago. But then in having that conversation and thinking through, okay, what specific
capabilities in terms of actual applications I as a small business owner have or as a podcast producer
have will AI be able to do and thinking about like, why is it not able to do these things right now?
And what is the key bottleneck? I realize there's actually no obvious way in which you can either
get LLMs to solve these problems for you or there's no key algorithm, there's no easy,
like, you know, prompt injection kind of thing, which would help solve these problems.
And the key problem I see is this, the models can't do on-the-job training.
So if you think about a human employee, you might have some.
And these human employees, the good thing about them is that, you know, you train them for
six months or a year.
And over time, they're getting better and better.
They're learning about all the contacts and intricacies of your workflow, what you like.
They'll fail, but they'll learn from their failures.
They'll interrogate them in this, like, very organic, deliberative way.
They'll pick up small efficiencies and improvements as they practice a task.
This just doesn't happen with an LLM.
Every session, you're getting this amnesiac mind that's very smart, but it has, it's lost all awareness of how you like things done, how your business works, and so forth.
Yeah, and if you had a, just to put that into context, if you had an incredibly intelligent employee that could not take feedback, you would fire them with.
about a month, right? No matter how smart you are, like you're not necessarily going to predict
every single possible edge case in the work that needs to be done. And then when you make a mistake,
if you're not able to like sort of update yourself, then what are we even doing here, right?
Like that's like learning, like learning from mistakes is like kind of high on the list in terms
of how to become great at any specific task or initiative.
100%.
And so then people will say, well, look, maybe the way they can learn from their mistakes,
Jordy, is like, you can just tell it in the context, hey, you fucked up this way last time you
were working for me.
Don't do it again.
But I think this is at least an order of magnitude less efficient and less capable than the way
humans learn. So the example I use here is imagine if you were trying to teach a kid to play the
saxophone. But the way you had to teach this is a kid comes into the room and they like try to play
a cold, right? They've never seen a saxophone before. They try to play a saxophone. And obviously it's not
going to sound the first grade the first time. But what you do is then like after they failed,
you just send them out of the room. You call the next kid who's waiting outside of the room in and
you say, look, here's some notes I wrote down from the last time about the other kid fucked up.
Why don't you read that and you try to play Charlie Parker cold?
It just wouldn't work, right?
This like tacit knowledge you build up through practice is not this like written instruction manual that you can just write out as a system prompt.
Yeah.
And so our current solution is to RL on saxophone playing specifically for that child.
And then in that, in that scenario, you're basically getting that kid drilling that.
But my question is like it feels like when we think about the.
in the abstract, it's like, oh, yeah, like work is just like doing emails, so it's
RL on emails, and then it's doing calendar, so it's RL on that. And so, well, yeah, we'll just
chip down at these and like, you know, book a flight and then, you know, schedule a call
and then do an outbound sales thing. But really, jobs are not just five things to RL on. Maybe
it's 500 things or thousands of things. And so maybe the shape of those, like, even if we,
even if we can define a verifiable reward and drill it, it's just, there's so much.
many different random things to do that it's going to take us a long time. Is that a reasonable
philosophy? That I think is part of it. But I think the bigger problem is not just the width or
the width of the pool, how many different tasks you have to RL on, but it's a depth in the sense
that a job doesn't involve doing a thousand different five-minute tasks individually. It's the
fact that you're like trying to work on something, but then somebody's Slack message.
to do something more urgent and then you had to decide which one is more important.
You're like, you're really to keep track of this client and what problem they had.
By the way, I'm talking hypothetically about what a job might involve because I've never actually
worked a real job.
But so just like how all these things fit together is we already have these language models
that can do like five-minute language jobs, right? And then the question is,
why can't we just delegate all language work?
For example, I have these LLMs.
I try to get these to rewrite auto-generator transcripts for me, so they're rewritten
like a human.
I try to get them to just adjust the transcript and suggest clips to tweet out and things
like that.
And it haven't been able to automate these things.
I don't know if you guys have been able to, but it's just like, I still have to do it
or I have to get a human to do it.
Because, and it's not because we haven't, you know, you might think about like
emails or something we have to get like future data on.
But this language stuff, we already have the data on, right?
So, like, why can't we do it now?
And the reason is they can do like a five out of a ten job out of the box.
These are short horizon, language and language that's enter in their repertoire.
But there's no way to get them to improve.
So over time, you can't be like, look, my tweet, that tweet was fire.
Like it went viral.
And here's why I think went viral.
And then kind of learns that and like updates that's like sort of understanding and writes better tweets in the future.
Same with transcripts picking up your feedback.
Since there's no way to do that, even if you have all these individual tasks,
We have all these individual language classes these models can do, but you can't then just be like, okay, now you're an employee.
Because an employee is actually improving over time and building up context in the way these models are not.
Yeah.
The big question I've kept bringing up and asking a bunch of different people is where are you getting value from agents?
And not a lot of people have great answers.
They'll be like, oh, we use this or we use that.
But you don't see a lot of conversation online of people like, oh, this SDR is.
just crushing it for this like AI SDR is crushing it for me or this this other use case is crushing
it you just don't see that at all and the reason that that's worrying is that when products are
truly great or even have the potential to be great or starting to like really work people just talk
about them a lot right like people talk about cursor a lot right people talk about Claude code a lot and
there's some individual use cases like coding agents seem to have the most real traction deep research
I would also call like an agent.
I don't know if you would put it in that bucket,
but it feels...
But again, it's just, it's pure...
Yeah.
Again, it's not like this highly agentic...
Yeah, but I don't think of deep research
as like an employee in that same sense.
It's not like...
Right, because you can't be like,
okay, that's great.
This thing you put together.
Yeah.
Here's how I like to compile
my ideas before a podcast.
So, you know,
you did a great job compiling this, like, Stalin memo.
Yep.
I was very curious especially about these, why the Great Terror happened in this way.
And keep that in mind when you're doing a future memo.
Like this style, that's not going to happen.
It's got the style that it's learned through its RL training for deep research.
So then again, it just becomes another tool.
It doesn't really, it's not, it's not, you know, it doesn't become like an employee for you.
Can you?
Yeah.
Yeah.
And then the other thing just since, since your post was inspired, you know, by your own tinkering,
some of the stuff that I'm most excited about
that we've gotten value specifically from
CodeGen internally is just these internal tools
that we totally could have built years ago
that are just now really fast to build.
So we built something for our ad partners
that automatically finds the exact,
all the different moments that we talk about them
in a given show and then just like links it out.
And it's basically just a simple database dashboard
that they have access to
that like historically you could have built
but it just would have been like really time-intensive.
And so it's not anything, it's, it, the, the, the value is that you can now build it, like, in a couple days.
Yeah.
And so, yeah, I've been trying to separate, like, all this is happening in the context of, you have hundreds of billions of, of, like, enterprise value locked up in these different labs, some of which have developed what look like great businesses, right?
Open AI, consumer, basically a new consumer app company.
anthropic with cogen and then there's still like hundreds of billions of value of like ev out there
where it's unclear where the revenue is going to come from and so when timelines extend and aGI
isn't happening you know next year or the following year or whatever I start to get generally a
little bit worried because that's a lot of EV to kind of maintain for another half a decade or
a decade whatever it turns into I'll get a little more bullish and hypey and take the other side
of that, to the other side of your claim.
Look, I think even if it doesn't happen in the next two to three years,
what we're talking about here is such a big deal that AI is definitely not priced in,
not by the average person, not by the market, by anything.
Because once you get this thing which actually does function like a genuine white collar
employee, not only do you have potentially billions of extra workers,
but you have something potentially more powerful, which is that,
Right now, a human mind can't be copied, right?
A human mind can't learn from the experience of other minds.
If we have a model that is capable...
Or it can, but it's really slow.
Like you have to basically work with somebody for a decade and then you can...
Mentor.
Yeah, it's mentorship.
Yeah, yeah.
And in fact, it's been a big problem because as our society has built up more knowledge,
we had to keep people in school and training for longer and longer,
which reduces their productive years.
But with an AI model, you could have this scenario where I suppose there is a model
that's actually capable of learning the way humans can learn.
Not only would it, so it's broadly deployed through the economy,
it's doing all these different jobs.
The difference is that it is now able to amalgamate its learnings across all its deployment.
So if one of them is an accountant and one of them is a coder and whatever,
the model is learning from each of these different on-the-job experiences.
And then, so even if there's no software progress out of that point,
that algorithms aren't improving, just that ability to learn on the job from everything in the economy
who would functionally produce what looks like a super intelligence, right? No human will have mastered
the range of skills and knowledge and know-how that this model will have.
That makes sense.
I have two questions. One's kind of maybe bearish, one's bullish. On the question of just,
is it possible, you think, to brute force continual learning by just doing something
on the design of these models side or maybe in the hardware side to just get to a trillion token
context window and then just stuffing it with everything. Can you explain kind of what the state
of the art is here because you were mentioning in the piece like the cursor roll-ups, the summary
lines and then stuff getting lost in there. But if we get to 100 billion token context window
or something, could it actually just remember every single interaction it's had? I am not optimistic
about that because we've had since 2018 we've been we've had the transformer or alterations on the
transformer as being the most performant models and you know who knows what the labs are doing but we do
have open source research from companies like deep seek which does seem to be at the frontier or
close to the frontier and while people have found modifications to the transformer which make the
constant time overhead of attention, reduce the constant time overhead on attention to like
you find these little hacks with a mixture of experts or latent attention, nobody has gotten
around the inherent quadratic nature of attention.
And basically this means that the cost of the additional token increases super linearly to
just that additional token.
So right now we have models that have a million tokens or two million tokens of context.
But getting it to 4 million tokens is more than twice as much compute.
Got it.
It's significantly more than that.
And then just taking it to like a billion and just given the fact that this hasn't,
nothing about this has changed over the last whatever six years.
I'm just like not optimistic that somebody will figure out a hack that will change it immediately.
Then on the on the side of like, how do you think about continual learning in domains where time is,
I keep going back to this idea that like even if we create the ultimate.
super intelligence, like it probably will have to obey the laws of physics, won't be able to time
travel or teleport.
And so there's a lot of restrictions on that.
Like at a certain point, you just need to move the sand into the chip fab.
And there's a certain amount of energy and time that it takes to do that.
Another example would be like longevity research.
Some of that, you just need to sit around and wait for a human to age.
And so your RL cycles, if you're, you know, trying to learn about how humans age,
it's very hard, yeah, you can like simulate the human or whatever, but like for the real test, you have to wait decades to see the effect of a certain diet on how long people live.
And so it feels like whether, it feels like there's a lot of scenarios where the, where you can't fully do it simulated.
And so you wind up with these really long times to actually do a rollout essentially.
And you wind up with something where the, like the time to actually get.
a new data point or new training data is like, you know, a thousand times longer than what we've
been doing previously. And so we're in this like, this like, you know, data desert, basically.
Yeah, I think this will definitely be true of many domains, especially those involving the physical
world. I guess as I've learned slightly more about some of these physical domains, it's been
surprising to me how much can be done in simulation. Within bio, for example, obviously we are off a fold and
I guess now alpha genome.
But even one of the key advances in bio
over the last couple of decades
has been techniques of multiplex experiments,
just running millions of experiments in parallel,
getting data points from that past,
using AI to learn from millions of seemingly
experiments in different fields
about what that might imply for the human body
or for human proteins.
So I am optimistic.
Another thing to keep in mind is that right now,
you know, a corporation might have 100,000 employees,
but how much just learning from any single employees is very limited?
People are just going, do their jobs, and that's that.
In the future, if you do have this economy of agents,
and it's much easier for AIs to supervise each other,
to be observing every single thing that's happening in the organization,
the speed of learning might be exponentially faster than what's possible with humans.
I agree this is not around the corner,
But the sort of singularitarian futures with crazy cyborg organizations that are moving super fast and coming up with new technologies doesn't sound crazy to me.
Interesting.
What do you think the recent, like last week was dominated by the talent wars and the huge AI researcher offers at meta.
What do you think that reveals about Mark Zuckerberg's AGI timelines?
By the way, I loved all the memes, the traded memes.
I should lean into that because like genuinely,
This is not even a meme, this like genuine, the market captured move by billions of dollars
based on these posts you guys are doing.
Totally.
Yeah, it was crazy seeing like 10 million views on an AI researcher getting traded.
Like it's niche, but it's not really that niche anymore.
Right.
Yeah, but I don't think you could have imagined, you certainly couldn't have fully imagined that
five years ago.
No way, no way.
Yeah, it's important stuff.
I mean, I still think they're like,
underpaying them I think like met as the first company that is actually coming
close to the break-even point of what the best day I researchers actually worth
the company if you're met on you're spending 80 billion dollars on compute over
the next couple of years if one great researcher can give you a 1%
performance uptick on that they're like so worth the hundred million dollar
pay-pack you're getting a bargain in a hundred million dollars so it's actually
interesting to me that men is the first company that's like wait
The return on investment here is incredible.
Let's just do it.
And then, okay, are the vibes bad?
Maybe could they have done the announcements better
to produce better, less mercenary vibes potentially?
But what, so there's like some ideal version of what they could have done.
But also keep in mind that the likely counterfactual
would not have been that amazing, you know, great vibes announcement.
The likely counterfactual would have been what they're currently,
what they're previously doing, which is just like sleepwalking towards loss.
And it's much better to just like, fuck.
let's just send it with a couple billion dollars in recruitment offers and like at least
now they're on the player board rather than just like sleepwalking towards Armageddon.
In many ways it's it's interesting how viral these like 100 million dollar number, you know
the 100 million is obviously a big number but whatever the range is people are so normalized
to professional athletes being comped tens of millions of dollars a year and just purely
at these types of moves from an economic impact is like signing a star pitcher to a baseball
team in one area. Like, like, how, you know, it's surprising it's taken this long. And the thing
that we were kind of joking about to put it into context is when you see that Tim Cook makes
74, he made 74.6 million in total comp last year. And he looks dramatically underpaid, right?
He already looked underpaid in the context of like Otani.
And then he saved the company during the trade war.
I think Otani was making somewhere around 70 million a year.
So he looked under compensated in that context.
And then yeah, I think the other thing that came to mind for me from your piece is I feel like there's been this kind of like toxic idea floating around teapot, which is like you have one year to accumulate.
before you're a part of the permanent underclass.
And the takeaway from this, you know, if you're correct and that like things will just great things will naturally take longer,
then if you're in teapot now or you're at all in AI or, you know, anywhere of these adjacent spaces, it's like,
and you're like 30 years old or 35 years old or 40 or you're 20, it's like you're here at the perfect time, right?
And I think it was it was it was it, was it Mark Andreessen who said that he showed up?
to Silicon Valley and he thought he had like missed the oh missed it yeah it's like the PC way
and so and so I think it should be like people should be like tremendously excited on a personal level
and and no more of this like dumerism of of you know you got a like yes you need to move quickly
yes you you should be working with the best possible people trying to have the most possible impact
be as close to the to the real action as possible but no more of this like doomerism like
you better get, oh, sorry, you know, you didn't get a $100 million offer this year.
It's over, you know.
No, no, 100%.
I mean, there's so many, actually, it's very funny how often this comes up.
Like, the prince of Persia's game developer, he wrote this diary while he was making it.
And in the 90s, he's like talking about, I'm going to become a Hollywood script writer
because I think I missed programming.
I have a CS degree, but I miss programming, so I'm going to go to Hollywood screenwriter.
I remember three years ago when I started the podcast
in this early days or two years ago
and I moved to SF and I'm like,
oh, GPD3 has come out and like all the rapper companies
are made now.
So I'm gonna like I'm not gonna make a rapper.
I mean, whatever, the podcast worked out.
It's fine.
But even then I was like, oh, I missed AI.
So I definitely think in retrospect, well,
because I'm like, look, another thing in mind
is that cursor only hit product market fit
after clot 3.5 came out.
and gave these coding abilities.
There's going to do many other things like cursor,
which will only be viable products once you have
continual learning on board,
or once you have computer use that's working on board.
And these are capabilities, which I think are exponentially
more valuable economically than the models as they exist right now,
and which many companies will need to be formed around to complement.
It's not going to happen by default.
Right now, opening its revenue is what, 10 billion a year, ERR?
I mean, if it's AGI, it should be like trillions A-R-R, right?
So what other infrastructure will be built around the cursor equivalence for whatever
continual learning enables?
Like, definitely the biggest companies have not been formed yet because the capabilities
that would make them so valuable are not available yet.
Yeah.
In terms of the, I guess, like the Mag7 CEOs, the major players, there seems to be this
continuum.
On one side, you have the, you know, McKinseyite philosophy.
of like dollars and cents, okay, people want tokens, I can inference them, and maybe it makes sense to hire an AI researcher for $100 million if they can improve your model and bring your model in-house so that you don't have to pay Open AI or Anthropic for those tokens.
On the other side, you have someone a little bit more like Elon who see this as an existential threat. It needs to be done the right way. It's very important. It's almost doom-based philosophy.
where do you see the other folks in the Mag 7 or in the AI race kind of sitting?
Like does the superintelligence team and these big offers move Mark closer to one or the other?
Because I was able to kind of justify the Lama investment just from, hey, if they don't do this,
they're going to be paying billions and billions of dollars to Anthropic or OpenAI just to bend LLMs internally as B2B software
because they're going to need this in every little nook and cranny of Instagram for a long time.
So I could justify it in that realm.
I could also justify it in the realm of like this is the most important technology in human history.
You got to have a you got to have a play.
Or compute efficiency like you laid out.
I interviewed Satya, I interviewed Mark.
And the sense I got from them was that neither of them, I mean, I feel like Medas group is called superintelligence.
But I didn't get the sense from neither of them that they're like, they believe in superintelligence in the way I mean.
which is the thing that's like building solar factories in the desert and then launching
the probes and so forth.
Yeah.
They, I mean, even something that's much weaker than that is still functioning super intelligence,
like in some ways these models are already super intelligent and in some ways, but their abilities
aren't fully unlocked because of the other handicaps they have.
But I think they, you know, like whenever Marks talked about it publicly, he's talked about, you
know, creating better social experiences and making the ad targeting better and
VR stuff, right? So I think that's also same with Satya, but with making office a better
co-pilot for office, which also would be worth hundreds of billions of dollars a year.
Yeah, so it makes 10 cents. But I think they think about it differently than somebody like
Dennis or Gario who are like, no, no, no, AGI is the real thing. Yeah. Do you expect the tension
between the app layer and the lab layer to just get crazier and
crazier and crazier. It feels like that that will be the story of the next five years is
kind of these like symbiotic at times, but then adversarial at times, you know, relationships.
I mean, previous technological, you know, like 90s, 2000s, Google, Chrome stuff runs on Microsoft,
but they can have an adversarial relationship. So it would line up with history.
But I think like the bigger issue is just that because I think the full potential of AI requires so much more progress in terms of algorithms, I just think the app layer companies that are building on top of models that exist today are just upper bounded on how much value they can extract.
Because the models aren't good enough yet to do the things that will make them especially powerful.
So for that reason, I'm like, it doesn't make sense to me that cursor would be worth a whole sixth or eighth of Anthropic.
If you think Anthropic has some chance to crack continual learning, right?
So I am more bullish on the foundational layer aside than the app layer
because I think the app layer will turn over once these capabilities are unlocked,
whereas the fundamental research has to be done word mirror or another.
As far as whether that means they will fight about it, we'll see.
Yeah, I mean, it could end up looking like the same dynamic we have now,
where we have cloud hyperscalers that are worth trillions of dollars.
And then we have valuable businesses that are worth measly $1 billion, $5 billion,
you know, and they're still big businesses and maybe can generate a return, but not power law.
Last question from my side, we'll let you go.
What has Sarah Payne taught you about artificial intelligence?
You know, at some point I asked her, because her whole big thing is Continental versus Maritime powers.
Continental powers want to invade and capture territory and maritime powers want to protect free trade.
I was just like, what big tech company is like a continental power and what big tech company is like a maritime power?
She's not, she's not watching TVPN, unfortunately, so she's not aware.
But actually, this is the question that's running on to you.
Who's the continental power of the Big Seven and who's the maritime power?
That's a good question.
I think Microsoft has carved out a lot of territory that will be harder to hold on to.
I'm not exactly sure how that maps.
I think another question is which big tech company is pro internet, like free internet, right?
Is there, if everybody wants their data walls and closed networks?
I would probably say Apple, continental meta, maritime, maybe.
Something like that might be right.
Apple, they don't need to go and invade the Android ecosystem.
they need to just really control privacy, what happens in their ecosystem, 30% Apple tax versus
meta needs to do OAuth and acquire Instagram and WhatsApp.
I don't know.
That's just off the top of my head.
Apple with the iOS, you know, tracking updates.
That feels like build the wall.
Like, you know, that app tracking transparency is build the wall.
Tim Cook.
No wonder Tim Cook got so along with 45.
Maybe.
Maybe.
Do you have a wildly different take?
or no I mean it just mostly fodder but I basically agree with that like Apple and Oracle I say
like continental sure Google meta maritime yep I like that though but it's a good it's a good thought
exercise so she clearly taught you something well fantastic thanks so much for hopping on on short notice
love the piece and thanks for publishing it we'll talk to you soon well you guys are killing it great
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Well, our next guest is here, Augustus DeRico, the CEO, founder of Rainmaker.
Welcome to Stream Augustus. How are you doing?
John Jordy, thanks for having me. I am doing well. I am obviously talking to a lot of people about the flooding that's gone on in Texas and appreciate the opportunity to clarify that Rainmaker and Cloud Seating had nothing to do with the flooding that unfolded.
And even in spite of that, I think that it's a tragedy that it did happen and certainly don't want anybody to use this opportunity, use this controversy to use this controversy to,
blame cloud seeding for the sake of popular political support. And you may have seen that Marjorie
Taylor Green is proposing running a bill to ban all forms of weather modification based on those
that we saw in the Florida State House legislature earlier this year. I think it would be both
disrespectful to the families involved and baseless and without any technical or scientific credibility
if that legislation were to go through. So I'm happy to talk about the course of events, what
cloud seeing is what it's not here with you today. Yeah, let's kick it off with the high level on what
actually happened in Texas, where things stand now, the status of the rescue operations, and kind of
the timeline that's more broad. Yeah, absolutely. So this phenomenon, this flooding was global in
scope. It was referred to as a low probability high impact event. I encourage people to go to Matthew
Capucci on X. He gave a great outline. He's a meteorologist that has a lot of expertise on
severe weather forecasting. But Tropical Storm Barry, the remnants of which blew into Texas,
was going to cause inordinate flooding regardless. And that area of Texas is also known as
Flash Flood Alley because these events do happen. Now, four trillion gallons of precipitation
occurring over the course of just a couple days is pretty out of distribution. But,
we are seeing an increase in these sorts of severe climatic events over time and especially down
and around the Gulf. So just to go over the timeline after having clarified that it was the remnants
of tropical storm Barry and the conversions of large mesoscale phenomena that induced that flooding,
it was at about 1 a.m. on the 4th that the National Weather Service issued a flash flood warning.
And then it was at about 4 a.m. on the 4th where they said that there was a life-threatening emergency
underway. It was not, it was over two days prior that Rainmaker had suspended all of its
cloud seeding operations in Texas because, one, our forecasters and our meteorologists saw that
there was going to be the severe weather event and we need and operate to produce more water
when there was already the event coming. But two, we suspended operations in accordance with the
Texas Department of Licensing and Regulations suspension criteria, where if there is a severe
weather warning from the National Weather Service, or there is too much saturation of the soil,
we have to ground operations. So we do so both voluntarily and in accordance with existing statutes.
Okay. So the cloud seeding operation that happened prior to the storm, who was the client?
Like, I mean, I assume someone was paying you. Sometimes it's the government. Sometimes it's an individual or
farmer or business. Walk me through where they were, who they are, what their goal is.
by procuring your services?
Sure.
So it's obvious that at this moment in time, that region of Texas does not need more water.
However, throughout the Western United States, farms, conservationists, governments concerned
with their aquifer supply of water and also reservoirs for both industrial and residential
drinking water, contract with Rainmaker to produce more water via cloud seeding.
And in the case of Texas, the South Texas Weather Modification Association, the West Texas weather
the modification and association and multiple other entities exist as conglomerations of both counties and
individual farms that pay for cloud seeding services to one water their crops to fill up the reservoirs
that they irrigate their crops with and three recharge the aquifers like the obolala that has been
severely drawn down and then puts all of these farmers at risk of not being able to grow not being
able to do business because of a historic drought okay so what um
Would the proposed ban just because what I'm getting at is like I'm wondering if like if the government is paying for cloud seeding operations like the easier lever might just be to decrease the funding to the government, but it seems like Marjorie Taylor Green is pushing for some other legislation that wouldn't just be, hey, buy less of this service because we don't need it.
and instead this service should never be bought at all.
So why is there the distinction there?
Like is most of the money that's going into one of these associations private farmer capital?
Or is it a split?
Like how does that actually break down?
So right now it's largely public municipal money that is going into these weather modification programs
to increase water supply when there is drought or in preparation for drought.
The bill that has been forecasted that has been proposed by Marjorie Taylor Green would wholesale ban all forms of weather modification, be it cloud seating, solar radiation management, or what they're supposed to be chem trails.
I mean, very transparently, I think that a lot of the concern around weather modification is actually conflating baseless notions of chemtrails with a very practical American technology that can and will and does benefit our.
farmers, our ecosystems, our industrial water needs, and our residential water needs. If this
legislation were to go through, not only would it deprive all of those interests and all of those
Americans from having water from cloud seeding, but it would also be against America's interest
at a geopolitical level, because China recently, I think on the last time I was on TBPN, I talked about
how they had a $300 million annual budget for their weather modification program. That as of 2025
has been up to $1.4 billion.
That is extremely consequential, and I think that if we were to ban who controls or banning
Americans from controlling weather modification technology, that would put us at a meaningful
disadvantage.
Now, all of this to say, people deserve transparency.
They deserve clear regulatory framework so that they know whether modification operations
are safe and being conducted in a responsible manner.
And with government oversight and accountability,
if ever there are negative consequences to cloudseating.
Again, there haven't been any in the case of Texas.
But I think that the reasonable next steps are to more stringently regulate who is allowed
to cloud seed, define what the concepts of operation are that are permissible, to find the
suspension criteria at a federal level rather than leaving it purely to the states,
so that anybody that wants to know about weather modification can look at the data and scrutinize
it and ensure that it's being conducted safely.
and also just to build trust because the Weather Modification Act from 1972 that currently outlines the Weather Modification Reporting Act of 1972 that outlines how we have to report to the federal government is, you know, 50 years old.
We need more scrutiny on these programs for the sake of public trust and accountability.
And that seems like a reasonable next step.
That was also recommended by the government accountability office in their report on cloud seating and weather modification earlier this year.
What was the scale of the general water, sorry, weather modification activities on July 2nd?
It was you guys, was there a bunch of other players operating?
Is there generally a lot of players or is it a pretty, is it a fairly small number of kind of service providers that are that are participating in these programs?
Yeah, Jordy, you may have seen the prolific hustle bitch on.
on X.com posting about this.
A little while ago, he said that I was the CEO
of the largest and most powerful
weather modification company in the world.
I saw somebody compare,
somebody was comparing weather modification tech
to being saying it was more dangerous than nuclear arms.
That was kind of crazy.
And then I also saw some people just showing
like general flight logs of like commercial airplanes.
Like obviously there's a lot of chaos out there.
I mean, I think it's just people have every right to be
angry and demand answers. It's such a tragic incident. But, but yeah, I'm curious to get into
the scale of, you know, kind of maybe late June, early July, what was going on broadly.
Yeah, absolutely. So there's one other cloud seating operator in Texas called Seeding Operations
and Atmospheric Research, SOAR. They're responsible for operations over the Rolling Plains
Weather Modification Association, which is significantly farther northwest.
of Kirk County. On July 2nd, we conducted one 19-minute cloud seating flight where we released about
70 grams of silver iodide and 500 grams of salt, table salt. That was released at about 1,600 feet
above ground level into two clouds that dissipated over the course of two hours after seating
them. The amount of time that those aerosols could have been suspended in the atmosphere is less
than the time between when we were seating and the onset of rains from the remnants of tropical storm,
Gary. And the amount of material that we dispersed could not come anywhere close to inducing the
precipitation, the four trillion gallons of precipitation that did come from that event.
So, yeah. And I'm assuming you guys like have records, you keep records of like the radar
showing these different cloud formations. So you're, you're, it's not.
just we looked and we think it dissipated, but it's like you can actually, you have like,
you know, basically a map that's live updating. Is that the right way to think about it?
Not only do we keep records for our own research purposes and operational purposes,
but we're required to keep records by the Texas Department of Licensing and Regulation. And those
are accessible online, as are the reports on our seating activities. And if anybody is interested
in those, then you can ask for them from the TDRs.
ALR. I'm curious when the flooding happened in Dubai, I want to say it was a year or two ago, Dubai is known for
their cloud seating operations. It's a very dry place and makes sense why they would want to
increase precipitation. A lot of people, maybe the same types of accounts that have been blaming you,
were quick to blame it on cloud seating. Throughout history has their
ever been any major kind of flooding event that people were able to say, yes, 100%, this was
caused by weather modification activities? Or is the tech not even powerful enough yet to do
something like that? So I think that there's probably three points to touch on. The first of which
is that it wasn't until 2017 that attribution had been physical attribution of,
of cloud seedings effects had been seen and proven
in an academic context.
And so with new advance in radar technology,
namely dual polarization radar,
we're able to much more clearly monitor
what the effect from cloud seeding is.
In previous operations, it was extraordinarily difficult
to see what your effect was because we could not measure
the cloud dynamics and the cloud microphysics
that were changing as you were seating.
So that's the first point.
The second point is that, and again,
I'm trying to be and will continue to try to be maximally transparent about our operations and historic weather modification.
There was something called Operation Popeye during the Vietnam War where the deliberate intention of cloud seating was to cause precipitation that would cause flooding and then impede supply chains on the Ho Chiman Trail.
Now, the extent to which that was effective because we didn't have good satellite imagery or dual pole radar is outstanding.
Now, that said, lastly, third point, we have suspension criteria that are given to us not just by the TDLR in Texas, but every state wherein we operate because if there already is too much saturation of the soil or if there is an oncoming severe weather event that the National Weather Service has notified us not to seed, then we ought not do that to increase the severity of precipitation.
So there are suspension criteria because there are limits on what we ought to do with this technology
so it's not to cause flooding and only reap the rewards from it, right, for our farms,
for our ecosystems and for our national security interest as well, right?
Like if we don't have access to weather modification technology, if we don't regulate this
at a federal level and ensure that there's accountability and attribution for these activities,
then other people, other nation states could be conducting weather mod in the vicinity of or on
American soil without any accountability. And so that's why I am advocating for way more regulatory
scrutiny from the federal government for cloud seating and weather mod ops. Walk through some of the
history of the Chinese weather modification strategies. We heard about the flooding in Dubai that was
kind of unclear. Have there been any notable or confirmed negative outcomes from China spending,
I mean, you said $300 million a year, something like that.
That seems like a lot of cloud seating.
It seems like if there was a surface area where there could be mistakes made,
they would have kind of explored that.
I remember the pre-Olympics, they were doing cloud seeding
or just kind of bringing down like the dirt in the atmosphere.
And, you know, people kind of learn from that,
okay, you get acid rain when you do that in particular.
But have there been any case studies from China that,
we should be learning from in America.
Case studies from China with adverse weather coming from their cloud seeding operations.
Yeah, anything like that.
Like something where like, okay, they've done a lot of this.
They've pushed this to the limit.
They've done this at scale.
If there's going to be rough edges or mishaps, I would have, I suspect that we would have
seen evidence of that over there.
They would have had an accidental flood or something like that happen over there
if they're doing it at scale.
You would expect to have seen it from China.
However, you would also probably expect and understand that there are a relatively inscrutable
country that does not report on their activities very openly and objectively.
Now, that said, one thing that we do know about the WeatherMod program that they do have
going is that they're planning to build 100,000 ground generators on the Tibetan plateau.
So Rainmaker is primarily.
primarily using drones for operations.
We also have inherited some ground generators from previous operations.
These are essentially aerosolizing units on the tops of mountains.
They can disperse material into clouds when the clouds intersect those mountain tops themselves.
Is that like a cannon that fires the material into the cloud?
No, no.
You might recall my initial inclination to use something like that because it is used in China.
But no, it's essentially like a smokestack of sorts, a very small smokestack that releases those.
air soles there. But in building a hundred thousand of these ground generators and also using
the Winglong 2 and a bunch of their other military drones for aerial cloud seating, they're turning
Tibet into a reservoir, a snowpack reservoir of unprecedented scale that will feed more water
into the agricultural basins in southern and eastern China. And I think that although, again,
this is something that needs to be transparently reported on and regulated.
depriving American farmers in the West, especially as a congressperson from Georgia,
right, where there is not as severe reliance on cloud seeding to produce water, would be against America's interest.
Mm-hmm.
George.
I guess, I'm trying to, I mean, the, the, the, the, the, my, my question is, it feels like, it feels like, it, it feels like candidly it will be hard to come, it'll be hard to find.
any type of allies in Texas on the ground in Texas maybe aside from from the farmers
but but I'm curious you know that the the various different groups you know what
what the reaction from them has been in terms of you know if they're you know it's
the reality is is water scarcity affects all every person in Texas but only a few
people truly feel it, right? It's a much smaller group because everybody goes to their sink,
they turn on the water, they turn on a hose outside, they go to a grocery store, there's water,
there's produce. It's not something that people necessarily feel. And so I'm curious where,
you know, you obviously are going to defend weather modification because you believe in
the many different ways it can have a positive impact, but I'm curious who you think that
other players that will be on your side as the industry.
I mean, the industry was not in a good spot prior to this.
It's in a much worse spot now.
And I know you've been flying all over the country,
making sure that it doesn't get banned.
So I'm curious what you think the kind of coalition
that will kind of form around you.
Yeah, yeah.
Well, so I actually think I'd,
just from my own experience over the course of the last few days,
disagree with the two points that you made, right?
Like, it has neither been hard to find allies for cloud seeding weather modification in Texas,
nor do I think the technology and the industry is positioned worse now than it was prior to this weekend.
And regarding the first point, there are some people that I think are probably not in good faith
engaging with this because they have some preconceived notions about chem trails or otherwise
and don't themselves want to scrutinize the data to back up how our operations are different and beneficial,
whereas chemtrails, as they believe them to be, are malevolent.
The vast majority of people that I've interacted with online, on the phone, and in person,
are rightfully curious, skeptical, concerned, some, you know, more than others, obviously.
But in scrutinizing the data and having these conversations and learning about what cloud seeding is, pretty unilaterally people are supportive of it, provided that there is a regulatory framework more stringent than the one we have now that ensures that it's safe.
This is true both of just individuals that are not themselves farmers, but obviously farmers, water managers, government officials too.
I welcome any questions that people do have, both online and via email, about what our activities are, what our policy recommendations are.
And I'm grateful that there are a lot of people that understand.
One, our operations did not contribute to the flooding.
But two, that even if there was a flood now, it doesn't mean that there is always enough water.
And having access to a technology to produce more water for farms and otherwise would be beneficial.
Like people want a more green lush country.
Yeah, I'm curious.
I'm sure you've spent plenty of time thinking about this,
but would there be a way to apply the existing technology you have almost in a defensive way?
And, you know, theoretically.
Like a hurricane while it's still offshore.
Something like that.
Or, you know, one of the issues here,
there was just so much water in the atmosphere that rolled over a heavily, you know, populated area.
And then it's got, it's gravity, right? It's got to come down.
You know, is there an application of the technology that could, over time, strategically prevent, you know, or act defensively against the conditions that create flash floods?
It's a very worthwhile question for you to ask and for us to ask ourselves collectively.
Right now, again, Rainmaker only does precipitation enhancement operations for all those
constituencies that I listed before.
However, in the past, the United States government funded Project Storm Fury, which was a series
of attempts to reduce the severity of hurricanes over the Atlantic before they broke against
the eastern seaboard.
Again, we didn't have the appropriate understanding of atmospheric science or the radar or the
satellite data necessary to appropriately do that.
However, severe weather is something that is like a geopolitical risk, a national security risk.
It causes damage and it is fundamentally a physics problem, right?
A physics and chemistry problem.
Is there technology now that could mitigate severe weather like this?
No, and Rainmaker doesn't have it.
Is it possible to someday, provided we invest in NOAA, in the National Weather Service,
in the appropriate research into cloud seeding, such that we,
we could reduce the severity of severe weather? Absolutely. And I am entirely in favor of that,
provided it is done in a responsible manner. And if we were to ban it wholesale, then not only would
we lose access to precipitation enhancement, but we'd lose out on any potential of, at the very
least, better forecasting for these systems and warning people early, but also the even greater
and more consequential beneficial potential of reducing severe weather in the future. And so I think
that the United States government and rainmaker should and are absolutely interested in mitigating
severe weather in a manner similar to Project Storm Fury.
Yeah, I think the PR, what you were getting at, Jordy, like the PR difficulty here is that
like when there's not enough water, crop yields are lower, prices go up, but it's very distributed.
Everyone feels it a little bit, whereas when there's too much water and there's a flash flood
individuals die you have a very it's a very emotional very it's very concentrated the
pain is very concentrated and so that's why this this story yeah I mean normally
when normally when there's a natural disaster yeah there's you can you can
critique the government for their response sure to it but there's not somebody
sitting there that a scapegoat right and so the question is like easy yeah it's
it's it's you know whether it's online accounts that are just engagement
or it's a politician, you know, escape, you know, the concern is that, and your concern is that the industry becomes a scapegoat and America loses a capability that our adversaries clearly care a lot about.
Yeah.
My question is like we're seeing this bifurcation.
It seems like Ted Cruz came out in support of the idea that Cloud City had nothing to do with the Texas floods.
Marjorie Taylor Green is taking kind of the other side of that.
My question is like these are politicians at the end of the day.
They're not independent scientists.
Who can we go to?
Who can the population go to for like a truly independent review of this situation?
Like is there is there some sort of independent governing body or are there are
their respected scientists that kind of don't have a financial or you know political
incentive one way or another?
how do you think the the populace should be sad?
Obviously, you're telling your side of the story.
You're going direct.
You're explaining things.
You're laying out the data.
But what do you expect people to look for in an independent analyst?
Yeah.
Yeah.
So for one, I think that NOAA, the National Weather Service, the National Center for
atmospheric research, all of those are great.
third-party entities that can review the information, corroborate the information that we've
provided, provided, of course, that they continue to exist and remain funded.
I think that this probably demonstrates why it is important that we should retain some
capability nationally to forecast and research the atmosphere, because there should be somebody
that's capable of reviewing this to ensure that it's safe. I'll also say, you know, regarding
the scapegoat dynamics that exist right now. I've thought about this pretty prayerfully and
intently over the last few days. And when there is a calamity of some sort, like I've been trying
to think about why people are, say, coming after Rainmaker or angry at Rainmaker. And I think that
when there is a calamity of this type, if there was someone responsible, if there was someone or something
that could be held to account, then in holding them to account, you could supposedly prevent
this kind of thing from happening in the future. The trouble with the true natural disaster,
as this was, is that there is nobody to be held accountable. And that makes the world a lot
more tragic because it means that things like this will persist. They will persist indefinitely
into the future unless and until some sort of technology could reduce the severity of severe
weather. Yeah. I mean, we went through this with the California fires. You know, it was like
everyone was searching for like a single person to pin it on and like it came down to like,
you know, some people built their houses the wrong way and there's some building codes that need to
change and there's some water rights.
and water flow and there's some different...
General government competency.
Like we need more goats in certain areas.
There's like a million different things
that could have prevented this
if they were all working together
as a well-oiled machine and had the forethought.
But it's a very, very frustrating
and difficult situation.
So our thoughts and prayers are with everyone
who's been affected.
But thank you so much for stopping by.
This is fantastic.
Thanks for breaking it all down for us.
Thanks, guys.
Appreciate it.
Cheers.
Cheers.
Really quickly before our next guest joins,
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I use it personally. And we have our next guests. We're doing two guests simultaneously.
I hope production team was made aware of this. It's on the calendar. But we are working to get a four-up display for you.
We have the founders of Grammarly and Superhuman.
This was an acquisition that was announced last week,
and lots of people in tech have probably used Superhuman.
It's the email client of choice for the tech elite, of course,
and Grammarly has been an indispensable tool at TBPN.
We install it on our producer Ben's computer very early on
when we were posting clips to make sure that we didn't have any spelling
or grammar errors when we would post on social media.
Very useful tool.
And now they've combined forces and we're going to talk about how we can, what the shape of the business will be going forward, how these products play together, what the modern suite of tools looks like going forward.
Welcome to the stream.
How are you?
Great.
How are you?
Fantastic.
Would you both mind kicking us off with an introduction on yourself and the companies that you run and then we'll talk about the acquisition?
Sure.
I'm going to go first.
Okay.
Yeah, happy to.
Hello, everyone.
I'm Rahul Bora.
I'm the founder and CEO of Superhuman,
which, if you're not familiar with,
is the most productive email app ever made.
Imagine getting through your email twice as fast as before,
responding faster to the things that matter
and saving four hours or more every single week.
We're also inventing the future of productivity with AI.
Imagine waking up to an inbox where every email already has a draft reply.
You would simply edit and then send.
And of course, with Gramley,
we are going to build the AI native productivity suite of the future.
Great.
Amazing.
Yeah.
I'm Shishamotra.
I actually started a different company.
I started a company called Koda, about the same time as Rahul started Superhuman.
And about seven months ago or so, Gramally acquired Koda.
And I stepped into the CEO role running Gramerly.
So I've been working in and around the industry for a long time before Koda.
I used to run the YouTube group at Google,
worked at Microsoft in the early days,
actually started.
My very first job was working on Outlook.
So I've got like in 1998, I worked on email.
It's fun to come back to it.
Yeah, that's amazing.
So I'm not sure who's best to answer this,
but I'd love to know about how this deal came together
when you two first met.
And, you know, we keep going back to this post
that you'll meet your acquirer like five years before you,
before the deal goes through.
Is that this case, is this a narrative violation,
kind of how do you get to know each other?
Eight years.
Okay, there you go.
Why don't I take the first half and then Rahul can take the second half?
So I can talk a little bit about the deal and what we're doing,
then Rahul can give the fun origin story.
So maybe just as a little backgrounder for everyone.
So, Gramally, our goal is to build an AI-Native productivity suite
with the agents and applications that drive productivity for everyone.
every individual and team in the world.
So a lot of that is probably new to people
because people have generally thought about Gramerly
as a much narrower product than our aspirations for it.
And the way we generally talk about it,
and I'll talk about agents first,
when you talk about applications,
but we generally think about Gramerly as the OG agent.
It's about 16 years now that the company has been helping,
at this point, about 40 million daily active users,
where Gramerly is the communication assistant
that lives right next to you in every surface you work in.
But people misunderstand the technology
because they think it's about grammar.
But actually the technology of grammarly
is mostly about bringing AI right to where users work.
So we can work in about 500,000 different applications
where we read what's on your screen,
we can annotate it in an unobtrusive way,
and we can make changes on your behalf.
And so from that perspective, we call this layer,
we call it the AI superhighway,
bringing AI right to where people work.
And in that analogy, up till now, we've only been running one car on that highway.
That's the car with your high school grammar teacher in it.
And that's a very useful car, and it generates, you know, over $700,000,000 million
of revenue now.
But I think it's a vast subset of what you should be able to do with that.
So a big part of our strategy is opening up grammarly to become a platform.
So you can build any sort of agent on it and have those agents come to you where you work.
That's the first part of our strategy.
Second part of our strategy is taking those surfaces and building the first party versions
of the surfaces that we think really matter.
The surfaces where people work every minute of every day, where all the work really gets
done, where you really want to work not only alongside humans, but alongside agents as well.
So that's why we bought my prior company, Koda, that we make an all-in-one document solution,
that blends document, spreadsheets, presentations, and applications into one surface.
that produces all the work artifacts for you.
But another key part of work is communication.
And for many people, the dominant communication tool they use is email.
It's something like three to four hours a day,
the average person spends in their email inboxes.
And this actually shows up in the Gramerly stats really high.
So email turns out to be the number one use case of grammarly.
We revise something like 50 million emails per week.
It's three of the top ten applications that Gramerly is used
in our email clients.
And so we saw that as an obvious place to go to go work next.
Now, from my perspective, I think email is a category that is particularly right for
disruption.
As I mentioned, I started my career working on Outlook in 1998.
And since then, there's a round of innovation with Outlook.
There was a round of innovation with Gmail.
And then there was a decade of not much.
And then Rahul...
That's superhuman.
...came along and built a great email experience.
So when we went looking for which surfaces really matter, we landed on
email and when you look at the email category as you mentioned there's only really one player that's
meaningfully innovated in that space and that's when we call rattle that's a little bit about how the
deal came together amazing great oh yeah it's funny i i just just for some added context i
basically have been lucky that my entire uh i think i got on superhuman in 2018 you launched in
was it when did the beta launch it was 2017 i think our first paying customers were at the very
end of 2017. Yeah, exactly, exactly. But I graduated college in 2018. So as a professional,
I've only had to experience. I'm a lucky, I'm the lucky batch, right? And still use it today.
So thank you for, you know, I never had to be an outlook guy. I had a Yahoo.com email address
when I was a kid. Yeah, vintage, vintage. Anyways, Rahul, I don't know if you have anything to add,
but then I have a bunch of kind of follow-up questions on the last anecdote. Yeah, for
Sure. I think it'd be fun to tell the origin story of the deal, how it came together. And I think there's a lesson or two in here for other founders of the entrepreneurs listening. So I'll also try and make it useful. So to your point, the foundations, the seed for this deal was planted many, many years ago. It was eight years ago. Like Tashire said, it was back in 2017. And back then, he was the co-founder and CEO of a company called Kodo. And we were actually at a conference together in Hawaii. So it was really nice.
And that said, I didn't really want to go.
This was a four or five-day thing, accounting for travel there and travel back.
And one of my co-founders, Vivek Soderre, was really encouraging me to go.
He would say things like, listen, building a startup is just as much about who you know and the connections that you have
and being able to pull opportunities together as it is building and marketing a great product.
And I'd be like, well, I want to work on this feature.
I want to do this thing.
But in the end, he just pushed me out to the office and put me on a plane.
and go to Hawaii, which sounds weird, right?
Like resisting going to Hawaii.
But anyway, there I was.
Shishir was there as well.
And it was one of those special moments where nobody else was around.
So it was just the two of us, buy a pool, two productivity nerds, nerding out about productivity.
And he told me that he'd worked on Outlook back in the day.
We got into some really deep conversation about productivity.
And as you know, back then, we only did one-on-one VIP concierge onboardings.
You must have gone through one yourself.
if you onboarded in 2017.
So I onboarded him right there and then, right by the pool.
And as those who've gone through the onboardings know,
one of the very last steps is when we ask you to close Gmail.
And so I was asking him to move the mouse over to the Gmail tab and close it.
And when I asked him to do that, another tab caught my eye,
which was an app called Krypton.
So I asked him, what is that thing?
And then Shia then proceeded to give me the best product demo I had seen in years.
My jaw hit the floor.
It was a document, but it was also a spreadsheet. It was also a database. It was a collaboration tool. It was a mini app builder. And maybe today we take these things for granted. But back then in 2017, this was truly mind-blowing. And so Krypton then renamed to become Koda. And Coder, of course, late last year, joined Grammally. Now, in his acquisition announcement, he wrote, and I have the quote here, as I watched the foundational capabilities of AI change how just about how every tool and surface operates, I started drafting my
2025 memo for the team, I titled it the AI Native Productivity Suite. And this just set a whole
bunch of bells off in my brain in a good way because that superhuman hour vision has always been
to build the AI native productivity suite of choice. And email is obviously a critical part of that.
It's a much bigger problem than most people realize. There's roughly a billion professionals
in the world. And on average, we spend three to four hours a day in email. So that's three billion
hours every single day or north of a trillion hours every single year. We actually all spend
more time in email still than any other work app. So we caught up early this year, January,
actually a few days after he became the CEO of Grammali. And over the course of several
conversations, it became very clear that we were working towards the same vision, which is to
build this AI native suite for apps and agents. And then as just a share said, email sits at the heart
of where Gramley is used today. It's the number one use case.
helps write more than 50 million emails.
Another stat that I found very fascinating is that 17% of words accepted on Granly are actually accepted
in an email service.
Wow.
Okay.
A bunch of questions, and I'm sure I'm excited to get your answers.
So first is integration.
How do you see sort of the plot, you know, how do you see both the brands and the products
integrating and working together over time?
you have a great challenge of having three great products that people love and three brands.
And in order to deliver on this, this, you know, this true, you know, long-term vision of a
productivity suite, I imagine over time you want to integrate them deeply.
I'm curious what that looks like.
Yeah, maybe, you know, probably cover the product part and I can talk about the brand part.
Sure.
Yeah, I'll do products really briefly and then we can go as deep as you like.
I think one of the most exciting things about the deal from a superhuman perspective is the access to significantly greater resources.
So you can expect us that we'll invest more than ever than we have done in AI.
We're also absolutely not done with our core email experience.
We'll be doing a lot more there.
We're going to build out calendar and tasks and then connect those beautifully together.
We'll also start to spread our wings beyond just emails.
So we're going to reimagine chat.
We're going to redefine collaboration, pulling on everything that we've learned.
over the last 10 years about work communication.
And then, as Shoshire mentioned, we are also working on a whole new way of working with AI
agents, agents that we think will free all of us up to be more creative, strategic, and closer
to achieving what we call our human potential.
And then just to double-click on that a little bit more, we really think we're entering
the age of agenic computing, where AI agents, they're going to work on your behalf, they're
going to reason, that problem-solving, and they're incorporating detail context about your work.
They're actually also interacting with other systems and agents.
And I think we're beginning to see these in some of the products that people are using today.
And for so many people, email is just at the center of where we work.
You think about project statuses, customer communication, meeting updates, deal execution, so much more.
It all actually funnels through email, whether it's a system of record or that's actually where the work is taking place.
So we also think that email is the perfect place to deploy a collection and a suite of agents.
You can imagine an agent triaging your inbox before you wake up.
You could imagine another agent drafting responses in your own voice and tone, incorporating
context about you and from your work, and at the same time, another agent is surfacing insights,
scheduling meetings.
They're syncing with your other systems of records and your other agents.
And I'll give you a specific and concrete example.
This is something you can actually do in Superhuman today, and then I'll talk about how
it's going to evolve in the very near future.
And let's talk about search or asking your email things.
For over 40 years, we've had to rely on what we kind of hilariously call search.
But if you think about what that is, you have to remember senders.
You have to guess keywords.
You don't have to scan subject lines.
And now in superhuman, you can simply ask, where is the Q3 offsite or what are my flight
details?
And a very real example that blows people away whenever they see it is this thing I do
whenever we launch a feature.
Whenever we launch a feature, you'll know this using Superhuman, I send an email to every single person who uses the product.
And then we get a whole bunch of replies back, usually several thousand responses.
And I still personally read through every single one.
I reply to some of them.
But what I'm doing is I'm copying and pasting my favorite quotes into a Google slide that I can then present at the next company all hands.
Now, this takes half an hour to do properly.
With Superhuman today, you can just ask, what are the top 10 most positive customers?
some responses to the calendar see your week launch, let's say. And then boom, boom, boom, boom,
immediately within five, ten seconds, I have the answer. So that's taking what is a half an hour
task and making it work in five or ten seconds. Now, we're evolving that so that you can then
continue the conversation and take it much beyond email. You can imagine me then saying,
okay, I want to convey the magnitude of the commercial opportunities to the team. So can you
annotate each quote with the name of the person, the company they work for, the size of their
current superhuman account, and the total number of employees they have, and then compute an
estimated size of price, like how much revenue is there at stake if we were able to sell into that
company? And you can then imagine the superhuman set of agents figuring out what to do with that,
realizing the answer actually isn't in your email. It's probably in your CRM. So a sales intelligence
assistant is called into the mix. There's a handoff between the agents. And then the answer is
right where I kicked off the conversation in my email app where I happen to spend three hours a day.
And you can continue the conversation. You can then say, okay, let's please turn this into a presentation.
And then perhaps it works with, let's say, the gamma agent to produce an amazing, beautiful presentation in your own brand for the company.
And then you might say, okay, I want time to practice this before the all hands.
Can you please schedule time in my calendar to do so? The agent's like, well, you're completely booked it before the all hands.
but we can move some things around
and it's smart enough to know that
it's easier to move a one-on-one
than it is to move a team meeting
so it recommends moving the one-on-one
it goes and does that
and now you have time blocked in your calendar
to learn a presentation
that was created for you in 10 seconds
by this agent that just read
thousands of email to get the content.
Work that literally would have taken an hour
done in let's say one or two minutes.
So that's the kind of future we're working towards.
Wow. There's going to be 250
agent startups that are going to hear that and be like, damn, he's, they're doing, they're doing
what I'm trying to do.
This is an ecosystem where we want to look at.
No, no, no.
And that's, to be clear, we want our marketplace to be the place you deploy those agents,
right, to release the surfaces you want to work on.
If you like, I could talk a little bit about the brand question as well.
I'd love that.
Yeah, that'd be great.
Yeah, so, and, you know, I think my experience here is heavily formed by, before starting code,
I ran the YouTube group at Google, and I think that was one of the best examples of an
acquisition that I think flourish in a way that would not have been possible without
without the particular constructs we put in place there.
And there's a lot about that, I think that we got right.
And I think I'm going to mimic a lot of that here as well.
So in my goal is with Gramerle, we're going to build the A&A Native productivity suite
of all the absent agents that you need, some of them that will own some of them that
we will be great partners with.
But it's really important that each of those retain an identity.
And I think that's important because that's how they keep innovating.
And if you think about, you know, you started using Superhuman in 2018, you know, you're
buying into a product, but you're also buying into a team and a vision and a feel.
And all those things really matter.
And so I really like this term of building a compound startup where each of those products
still feel like they have an identity, they have a brand, they have a mission.
They have their, they have similarities for things we want to work across, but they have their own
perspectives on the problems that make sense in that in that space as well. So we want agents to
work across all surfaces. It's very important that if I set up my sales agent, that it should be
able to do some of the experiences that Rolol just described while it's in my email, but while
it's in my document, it'll give me a different set of experiences. When I take it out and use it
while I'm using a third-party application, it should still be able to bring my context with me. So
there will be things that need to feel similar, but the individual brands will remain separate.
The last thing I'll say about that is the overall corporate brand for Gramerly will change.
We're working on a new game for it.
So Gramerly will become one of the sub-brands itself.
We think of it, as I was describing, one of the most important agents in that platform.
So the new brand's coming.
I'm really excited about it, but not announcing it yet.
Yeah.
Yeah, I can't wait to see it.
I'm curious how you think about the tension between yourselves and someone like a Google
a Google workspace.
I was joking with John the other day.
It feels like so many companies are so dependent on Google workspace
for the core kind of just like team management infrastructure
that they could just raise the prices every single month
and it would take a really long time for even to try to figure out something else.
And it reminded me of kind of the tension that some of the foundation model labs have today
with the app layer above them,
although that's quite a bit more intense,
but I'm curious how deep down the stack you guys would go
if you can talk about it
or if it makes more sense to focus on the agent layer or the app layer.
Maybe I can start the,
it's interesting that three products are bringing together,
Gramerly, Coda, and Superhuman all have competed with the Google suite
or the Microsoft suite for years.
And so I think we're all kind of...
You're born in the fire.
Yeah.
And the thing I'd say about it is it actually comes up less with customers than you would think.
I think that when companies decide, it's sort of like buying plumbing for your company.
You buy one of these suites.
It covers lots and lots of different things.
But these have become a part of the furniture at the company.
And people don't really think about them as their real investments in productivity.
And so I totally agree, by the way, I'm just as this, as the way work evolves, imagining trying, you know, setting up every time you have a, I could imagine a world where there's, you're generating a new agent for a specific task. And they have an email. And I'm sitting here being like, do I really want to pay, you know, Google workspace, every time I spin up a new agent, a Google workspace, another $25 a month. And so I imagine, I imagine you guys can take this in a direction that, that, uh, that, uh,
kind of reinvents that all of that plumbing in the long run, but maybe it's not.
Yeah.
I mean, I would say all three products have found different ways to be better together with the,
with the underlying products.
Obviously, with Gramerly, one of its hallmark features that it actually works in all those
surfaces.
So it amplifies your investment in, you know, works great in Google Docs, but it also works
great in Slack and in Salesforce and all the rest of your products as well.
For Coda, it deeply integrates with those products.
And then for Superhuman, you know, Gmail or Outlook.
serves as the back end for those providers. So it's not really a question of less investment in
those core infrastructures, but if your users want the best possible experience for what they're doing,
you're going to go get the best tools. And in a sort of macro scale, the amount of money you're
spending is such a tiny amount of money compared to what you're actually investing in your
employees to go stick another 10, 20, 30 bucks a month for people that you're spending
hundreds of thousands of dollars on to get them. Some cases, hundreds of millions.
some cases hundreds of millions, we're going to have to raise our prices for those employees.
But you're going to get a huge return for them.
And people don't really care that much about their sun costs and their plumbing.
Totally.
Question.
Go for.
I've kept two somewhat related questions.
One is I don't want to say that, you know, Gramerly is a Chrome plugin, but a lot of people experience that way.
And I noticed I was using a different Chrome plugin.
and the Chrome app store like updated and I lost functionality because they changed their policy
and this particular plugin wouldn't work in the new rules and so I'm wondering if there's
this is a plugin different this is not grammarly this is a separate one it was called Ublock origin
it would let me go in and select specific divs on specific websites and basically mute them every
single time I hit that website it was very very cool but it was deemed to be like too not like not
privacy safe and it was really annoying for me because I enjoyed this and I was excited to use
this thing and then I lost it and I mean I might be able to like download it and
side load it or something but it was it was difficult and so I'm wondering about like
sharp elbows in the because the Chrome plugin is an interesting wedge
interesting go-to-market it unlocks so many different things we've seen this with like
the open AI chat GPT app using the ADA or the the the accessibility features to kind of
plug into any IDE on day one like you just have such an interesting ability to plug into
you know, tons of apps with AI in a bunch of interesting ways on and like your native there.
But it feels like Google might be getting a little bit more sharp elbows there.
Has there many attention there?
Do you think that there will be more over the long term?
What are the risks to building on top, like building a platform on top of another platform?
Yeah.
I mean, I'll maybe just to two, two parts of it.
First off, just to correct one misunderstanding.
The Chrome plugin is a very big part of the Gramerly product.
There's also a desktop application.
There's also a set of mobile application, so iOS and Android.
And we have millions of users on each of those as well.
And so, but I understand that the product is synonymous in many people's heads with the Chrome extension first.
But that's very important because we have to work where users work.
And sometimes you work in a web browser.
Sometimes you, you know, many people use Slack as a desktop app,
you're superhuman as a desktop app and so on.
So you have to be able to work in those places.
I will say that staying on that line of where these platforms are,
is kind of become the core asset of the company.
So that's kind of what I meant by people misunderstand grammarly.
Like I do have a team here that works on being a great grammar agent,
but a massive team that works on how do we integrate with all these products
in a safe and secure way.
And one of the things we've realized is that we've done this just for the grammar agent.
But what if we could amortize that across a much broader set of agents?
And so now if you're someone building a new agent,
you could go build a Chrome extension and a desktop app and so on.
I mean, I'll pick an example.
Let's say, I'll pick a book author.
So, you know, I really like Kim Scott.
She wrote a book called Radical Cander.
We spent a bunch of time with Kim on right now she tells a book.
You stick it on your shelf, kind of forget about it.
She wants to build an agent that sits right next to you and says, hey, you're not following the principles of the book right now.
Oh, interesting.
Yeah, so I'll say it because I'm thinking it.
But it seems like, you know, I'm going to say this, and then I'll provide some.
some more context. But a lot of people, you know, have been very triggered by the marketing that
Clue Lee has done. But at the same time, what they had surfaced and what you guys had basically
started doing years and years ago was, was understanding what a user is doing on their screen
and starting to surface information and help them take action with what's happening.
And I think that what you guys are building towards, and specifically this app layer on top of this, like,
private, secure way of servicing context will, in hindsight, be incredibly obvious that that was how we
should be integrating AI in our workday because the idea of like you're working in an app and then
you go in another app and you like type a little bit and then you take that and maybe you go back
into the other app and then you're just like, you know, tossing this over the wall makes no sense
when things should just be getting constantly surfaced in front of you in real time.
There's no real programming precursor.
It was like copy, copy the code, copy the Python into chat GPT, copy the result back.
And it was like, okay, there has to be a better way.
Yeah.
And I don't want to, I want a, as a user, I would love to be able to have a bunch of different experiences like that.
But I don't want to trust, I don't want a hundred different companies to have full read access to my desktop screen and my microphone or any of these other things.
So I'm very excited about where you guys are going.
That's exactly right.
So it is a tent, it's tense to build a platform on top of your browser, your desktop, so on.
But once we've, once we've done that, we can now make it available to the Cluleys of the world,
to the Kim Scott's of the world, so on, and say, why are you going to figure out how to integrate
with every one of those applications?
And we can do that for you.
You should focus on the logic of what do you want to suggest to the person and when.
Yeah, totally.
I mean, a couple more questions wanted to fire off.
You guys are well capitalized.
You generate a lot of revenue.
I'm curious how you're thinking about operating.
the business on a go-forward basis.
I'm assuming you're getting a lot of,
hopefully getting a lot of efficiency out of AI.
So maybe you can, is the plan to focus on innovating while, you know,
generating cash flow or are you guys going to, you know, continue to, you know,
or just burn and, you know, run a more traditional value playbook?
Graham really has been lucky to be a cash generating business for a long time.
And so it's sort of built into the DNA of the company.
And so I think in the, I'd like people to start thinking about Gremlin with the new brand that will announce soon enough.
Think of us as one of those top few AI companies.
And, you know, if you think of the foundation model companies providing great layers for all of us,
I think we're hopefully the suite of applications and agents you really care about with one big business model difference.
We don't burn billions of dollars in order to do it.
And I think we can hopefully bring that to people in an efficient way, which allows us to grow in a
expand in our own control.
Last question.
Are you guys talking to more companies?
If somebody has a great product that's generating a lot of revenue, are you?
I'm looking through the Google suite right now and, you know, I see chat.
I see video conference.
Are you guys a buyer?
We are.
I mean, I think we should, I would love to talk to people with interesting ideas there.
I think there's a great opportunity here to go build that next AI Native Productivity Suite.
We will build parts of it.
We will buy parts of it.
If I looked at email, for example, we could have, if we started to build an email experience anything like superhuman,
nobody would have seen anything for a decade.
And so it was very important for us to get a jumpstart with the number one product on the market.
There are other cases where I think we can build.
I don't think we have to buy everything.
but I think we're a great home for startups that are lacking that sort of scale
that want that distribution, want to get to a much broader group, but still want to work
in an innovative environment.
So, yeah, I hope we're a great spot for that.
Yeah, that makes sense.
Exciting.
Well, congratulations and come back on when the rebrand drops.
I want to see that.
We're on.
I'm excited about it.
Can't wait.
I know you guys are going to cook up something great there.
This is fantastic.
Cheers.
Well, we will talk to you soon.
Have a great day.
Guys, goodbye.
Let me tell you about Adio.
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Adio is the AI Native CRM that builds scales and grows your company to the next level.
You can get started for free or you can talk to sales.
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Or I'll make an intro.
Yeah, just hit up, Jordy.
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Let me also tell you about fin.a.i, the number one AI agent for customer service.
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It's going to be bad.
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No one likes how that ends.
Yeah.
Anyway, our next guest is ready to join.
Let's bring in Onker from carry.com.
We like Carrie.
We like Carrie.
We love Carrie.
Welcome to the stream.
Welcome to the stream.
I think we're, I think we might be on mute.
But we're going to want you loud and clear for this one because there's a lot of exciting news.
There he is.
What's going on?
What's up, man?
How are you?
Good to be here.
We're doing great.
I'm excited to chat.
Yeah.
I'm sure you've been.
It's boring, boring tack stuff.
But I need people get out here for it.
No, you make it digestible.
Yeah.
So the goal I was talking about it.
It's like the last threads that I see on Axe and I'm like, thank you.
Thank you for making this thread because it's actually, it's actually deeply researched, thought
properly organized and valuable. And it's not like, have you ever heard of Mark and
recent? So yeah, the goal here is to create something evergreen, the definitive playbook for
founders. So I think we want to create something that can be a resource for a long time,
ideally. Yeah. Great. Let's break you down. Let's do it. All right. Where do we want to start?
Yeah, I figured it would be helpful to kind of walk through our audiences pretty evenly split
between early stage founders, operators, and, you know, executives and then, or just startup, you know,
team members in general and investors. And so getting kind of a lay of the land on how the big,
beautiful bill impacts all those different groups would be awesome. But maybe first, I would love,
you know, some background on yourself, how you got into this, Carrie, and then we can get into
all that. Yep. Sounds good. Well, Jordi,
Jordy's an investor.
So it has a little,
not for me,
not for me.
Not for you.
For everyone else.
Yeah,
but I've been running a company called Kari for almost three years now.
I'm an immigrant to America.
I moved here knowing zero about personal finance,
zero about taxes.
I sold my company five years ago and I was facing a giant tax bill.
So I hired very expensive lawyers and accountants and they were able to do black magic
to basically reduce my tax bill dramatically.
And it made me realize like the tax code and
this country, it's kind of, there's so much stuff in there, but very few people actually know
how to leverage it. So when it was time to start a new company, I spent, I don't know, a couple
months looking into this and made it my mission to, you know, dive deep into everything in here.
And what we do at Kerry is we're like, can we build software to give people, we call it tax alpha,
but basically ways of saving money on taxes on autopilot. So again, my compliance team is going to
make sure I say this. This is not tax advice, legal advice or investment advice.
We never give that kind of advice on this show. Yeah. Yeah. But I have spent a lot of time in the last
two, three years working with at this point thousands of business owners. And I think I have a
pretty good idea of, you know, generally how business owners can save money and taxes.
And this piece of legislation is the most significant one we've had since 2017. 2017.
And one, and before we dive in.
to that, I think it's helpful. I feel like you approached the tax code very much like an engineer.
And in the same way that, you know, if you sign up for a software product, you're getting the
benefit of that company spending millions and millions of dollars, like building this product
and then giving it to you at a fraction of what it costs to create. With Kerry, the idea has been
how do you kind of create that same effect in some way for taxes? Because if you're working with
the fan, you know, one of the best CPAs in the world, they will charge you for the service,
and then they'll go charge you the same price to someone else for that same service, and they'll
just do that a bunch of times. And you guys created a different, you know, you have a sort of a
different incentive, which is how do you create the maximum amount of value and then make
it available to as many people as possible, which is kind of the traditional software playbook
applied to, applied to a new category.
Thank you. You pitched my company better than I did. But yeah, I mean, there's all this stuff. I mean, there's so much nuance in it. But like from a software perspective, none of it is specifically hard. The challenge we have is we deal with fintech, right? We're dealing with real money, custody, real assets. That's the complexity. But there's so much stuff in the tax code that we're looking if we're focusing on, I don't know, 1% of what's out there. But there's like I generally believe for most people, I know VC's.
probably disagree with this. There's no alpha in investing. The average person should just index the
market and get to work, but you can find alpha by saving money on taxes. If you can save 10, 20%
off the top, so you have more dollars to index the market, that's basically the thesis behind
what we're building. Yeah. So talk about kind of maybe how the bill came together, what you
expected to be in, what maybe didn't make it in. There was a lot of chatter, maybe was it for
months ago around the carried interest loophole. People were pretty triggered by that. I was triggered
by that. But it sounds like that didn't make it in. But yeah, breakdown kind of maybe the lead
up to the bill and then how it actually ended up getting implemented in intense states. Yeah, I should also
caveat by the way that like I'm going to tell you all what's in the bill. It is not an endorsement
of the politics behind it. Like you can argue either side of that like that is out of spilt for what
we're talking about. No, we're just talking about reality today. What is becoming law? So.
Yeah. So 2017, there was something.
called the TCGA tax cuts and jobs act where there were a lot of temporary measures that benefited
groups of people the administration wanted to benefit. Typically, this was entrepreneurs, business
owners, investors, and real estate developers. Part of this was there was a lot of short-term
measures put out for a that were only going to last eight years in the future. But what this bill has
done is it's made most of them permanent. So there's a lot of things like, you know, if we're talking about
startup founders specifically, there's, and we'll break them down. There's many things in this
that will make your life better. Even if you're a sole prop LLC or an S-Corp, a bunch of things
make this better. If you're someone that's coming up against the estate tax, this bill helps
that. So lots and lots of good stuff. Maybe you could kick off with a little bit of the
background on like the understanding of QSBS. For the last decade, I feel like the rule of thumb has
been like you start a company you sell it for a bunch of money the first 10
million you don't have to pay federal taxes on it so if you're in California
you're still going to be paying California tax potentially but you might be
able to think about it as like that if you get a 10 million dollar liquidity
event you're basically taking close to 10 million
potentially 10 million so yeah New York 10 million and so you don't need to move to
Puerto Rico good news for that but that was a funny time when people were were so
I got to move to Puerto Rico oh you're having a massive liquidity event oh okay yeah
but yeah talk through talk through the reality like how how real was the the
original QSBS process what were some of the the hiccups if it was an aquire or an
asset sale that might trigger income
tax or something like that. And then talk to us about what's changing. Yeah. So QSBS for those that
don't know it, I mean, qualified small business stock, this is what kind of got me down this whole path.
I mean, I was running my startup for six years. We were about to sell the company. And I didn't
know about QSPS. It was the best surprise when my accounts are like, guess what? You actually could
not pay taxes on $10 million. I was a resident of New York, so no state tax as well. But not just
that. The QSBS limit is per shareholder. So I can give shares to my brother, my parents,
and now your $10 million becomes $40 million. You can set up trust as well to multiply it.
So it already was exceptionally generous. And it's available to every shareholder, investors and
employees. So sometimes employees don't hit the threshold, since you have to hold shares
typically for five years to unlock the benefit, right? Five years is a long period of time.
one of the big changes this bill brings about is now if you hold shares for only three years,
you get half the exemption.
And if you hold shares for four years, you get 75% of the exemption.
So that's one big change.
And just to level set here, like the whole idea behind this particular tax incentive is to incentivize
innovation and building new companies.
Small business creation.
It's the opposite of like high-for-goodsy trading.
And it is you have to create value materially.
that are primarily, like the average person that benefits from this is somebody who starts
a plumbing company runs it for 20 years and sells it. And is that right? Or is it, is it
I think that's the intent of it. I think the reality of it is Silicon Valley benefits
from it more than anyone else. I think the intent and what's actually happening. But again,
that gets into the politics is a little bit different because technically services, businesses
are not included. You have to. But the reality is,
if you look at most big tech exits right now, people are paying substantially less in taxes.
There's a New York Times article with the Roblox founder. He set up 12 different trusts to multiply
QSBS to $120 million. He actually joked that raising a kid in California is so expensive
that the QSBS exemption is what makes the whole math worth it. It's kind of an insane thing.
That's a crazy thing to say. Yeah. What types of small businesses, what are all the different
types of small, I mean, just generally, like what are the different categories? Because if you take out
services, like the software doesn't apply to that, right? You can just be building regular SaaS.
Typically, typically the requirements for KWSPS are a few different things. And one of them is changing now is,
one, you have to be a C corporation. So that's historically been like LLC's S-Corps don't count.
You have to be a C-Corp and hold shares for five years. When you acquire the shares, the company should
have less than 50 million in assets. That was the old rule. Now it's 75 million in assets.
For startups, that is typically the cash raised, not the valuation. So it takes you pretty far,
right? Before you raise 75 million bucks, you get pretty far. And then there's other stuff.
It has to be an active trader business. And there's a few disqualifying categories, like services
or something based of someone's brand does not count. But the way QSBS works is it's ultimately
stance your accountant takes. So as an example, let's imagine your tech-enabled service business,
you could find a lawyer or an accountant to take a stance that QSBS counts, and there's a,
you know, there's a good chance that just works out that way. That makes sense. What besides
QSBS has changed in any meaningful way? Yep. So again, just to reiterate, the other big benefit
is the $10 million limit per shareholder is now $15 million. So three big changes, 10 to 15,
there's now partial QSBS
and you can now be up to 75 million in assets.
Outside of QSBSs, I would say to be...
Is that backdate?
Is that backdate at all?
No.
So it's only for companies incorporated from Friday on...
Or you have to buy the shares from July 4th, Friday onwards.
Wow.
Oh, wait, so this only affects going forwards.
Yeah.
Going forward, but new share purchases would count.
Yeah.
Okay.
So if you buy shares.
So theoretically, what I'm actually not sure about is
and probably maybe a lawyer can weigh.
And if I'm an employee who has options
and I exercise my options today,
would that count?
There's a chance it could.
Interesting.
So if you own 20% of a business started in 2019,
you hit your five years,
the company sells for $100 million.
You get $20 million.
You're still at the $10 million dollar QSBS exemption.
You're not going up to $15.
Unless you set up a trust or gift shares to someone else.
Sure, sure, sure.
Interesting.
Can you explain this bonus depreciation concept?
Yeah, absolutely.
Bonus appreciation.
I think you already have the private jet dude on.
He's coming on after this.
So he'll talk about it.
It's big for his business too.
But basically the way depreciation works is when you buy any kind of physical asset,
like consider you buying a commercial building,
it loses value every single year.
Every year you can take that loss of value is depreciation.
It's a phantom loss in that you're not losing money,
but you can deduct it from taxes.
Sure.
What bonus depreciation lets you do
is it lets you front load depreciation
for typically things that have a useful life
of less than 10 years.
You can take all of the depreciation up front.
So this is really significant
for all the real estate bros out there
because what they can now do is you can buy a building,
you can do something called a cost segregation study,
which will take the building,
it'll break it down into all of its components.
It'll be like the HVAC is worth this,
the windows are worth that,
the doors are worth that.
Anything with a,
usable timeline of less than whatever. I think it's 10 years. You can depreciate up front.
So the upshot is you can buy a commercial property for a million bucks, two million bucks,
put 20% down, but also get a 20% tax loss. You can deploy cash much faster. And people think
this could lead to real estate prices growing. But this applies to private jets, heavy machinery,
cars, all kinds of equipment. Makes sense. What else are you tracking? Anything else?
State tax is big, right? Estate taxes are massive. I mean, historically, when you die,
anything above the estate tax exemption gets taxed 40%. This bill makes it permanent at $30 million
per couple, which is a very, very high threshold. That was actually supposed to go down to
$10 million. So it's a huge swing. And there's a lot of sort of trust planning companies that
were betting on this happening. But now it's a much, much bigger exemption.
They were betting on 10 happening, and so 30 is bad for them.
Correct.
Like, had the election gone a different way, what would have happened is the estate tax
would have fallen by almost half.
Instead, it actually went up.
Interesting.
Talk about this relief for software companies in America, amortizing software developer
salaries.
I remember that hitting the timeline and being really hotly debated.
I don't remember if it actually had a material impact on a lot of businesses.
it seemed like there was a lot of fear,
but I don't remember it actually putting friends
out of businesses,
but what happened? Take me through it.
I saw, like, it was a terrible piece of policy.
It's called Section 174.
What it basically said is
you get to amortize a developer cost over five years.
So imagine you're a software company
that's like just about break-even,
slightly profitable, maybe even lose money.
You could lose money,
but be deemed profitable
because you can only deduct
20% of your developer's salary as a cost.
So imagine you're paying a developer $150,000.
You have to break that expense over five years.
So this is disastrous because you could own taxes
despite losing money.
This bill fixes it, and you can now, again,
take the entire deduction year one.
For local talent only.
Yeah, that one always seemed odd
because obviously it's like a real cash cost.
Local talent only, though.
So offshore.
So this does, this does.
does hurt offshoring. We'll see, we'll see sort of where it nets out. But this was definitely
one of the few things that I think unanimously everyone's like, okay, this actually makes sense.
Huh, that's great. Cool. Well, anything else, Rudy? I think that was it.
Thank you so much for stopping. Anything else? Anything else top of mind that people should be
thinking about? I mean, there's so much stuff in there again. I talk about it a bunch. I think
these are sort of good highlights. But yeah, always talk to your tax professional, not
tax advice. Of course. Never, never from anchor. But carry.com.
check it out. Well, thank you so much for stopping by.
Cheers.
Great to catch up.
Bye.
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Let's bring in Preston.
Mr. PJ.
How you doing?
What's going on?
It's good to see you.
Great time.
I like the theme song.
Yes, welcome to the stream.
Kick us off.
Break it down.
I don't think you need a huge introduction now.
You're basically invented the private jet.
But why don't you give a quick intro and then I want to get into the news.
Hey, I am Preston Holland.
I am the founder of prestige aircraft finance.
I am also, I was called the private jet guy on Twitter once at a party by a guy who owns a private jet.
So I would say that that was pretty, that was a actually.
Jordan was in that circle.
I'm thinking back on it.
But you've never built a brand around the brand of like being a guy because like that's
a thing on X, which is good.
I think all the guys should seriously think about rebrand to their own names.
The private to the private jet man.
Yeah, yeah.
Potentially.
All the guys got canceled during the whole LP whisperer scandal.
That is deep and that's lore.
That's lore.
Yeah. That's excellent.
But yeah, stoked to be here.
It is a good day for private jets.
Break it down.
So I think that you just had the founder of CarryOn and we're talking about taxes.
Let me preface this with this is not tax advice.
Never.
And you should consult a tax professional.
So now we're going to talk about tax advice.
But you can, with bonus appreciation passing, it's been, it's been,
huge for private jets and it's going to be really big because you can expense the full cost
of the jet in the first year. Key is it has to be used 51% for business. So if the technology
brothers wanted to purchase a jet and 51% of the time you are flying between location
shoots and studios and you're shooting great B-roll commercials or going on a wander promotional
tour. I'm always good for a good plug. And if you're using that 51% or more for business,
then you can depreciate or cost accelerate the purchase price in the first year. So it reduces
your tax basis, which is great. So it basically becomes highly profitable to purchase a private jet.
Just kidding. Not quite, not quite that. But it can have a material. If you have a taxable income and you're
about to pay a bunch of tax and you buy a plane, you can depreciate all of that.
Yeah.
And so if you're paying, you know, 30%, 50% marginal tax rate at the level of like hundreds
of millions of dollars, throwing a private jet on the books there allows you to write that
basically all off on day one.
Well, and there's also scale there.
There's plenty of, you know, if you're making 10 million a year and you buy even a, you can
also do this for fractional ownership as well.
Is that correct?
Yeah.
Yeah.
So for fractional, when, when, you.
you're buying fractional. So for those listeners that are new to private jets, fractional net jets,
flex jet are the largest providers of fractional of fractional jets. And so you are actually buying a
sliver of an actual tail. So like of an actual jet, you may not ever actually fly on that airplane
in your entire contract life, but you do own a portion of an actual asset. And so you can
depreciate that like you would a whole aircraft. Yeah. So how, how, how,
quickly the bill was signed into law.
Was it, it wasn't, was it on the morning of the fourth by the president?
But how quickly does the market react to this kind of thing?
Was there like deals that were getting worked on in the lead up to that,
assuming that this would go through that suddenly are actually getting papered and signed now?
Or do seller, owners, sellers typically want to hold and not, you know, price a transaction
until this kind of thing gets clarified because it can have such a material impact on the actual cost of ownership.
So you kind of have, so it's retroactive to January 19th.
Ironically enough, I have a client who we had to delay his closing about two weeks to actually close on his plane.
He was supposed to close on like July, or on January 5th.
And we had to delay it to January 31st.
And that ended up being a significant, significantly good delay.
So it turned good.
I actually have no idea why the arbitrary January 19th number and not January 1st.
That kind of seems a little more logical to me.
But January 19th is kind of the back date.
There was there you had kind of a bifurcated market.
You had buyers who didn't want to speculate on actually buying the aircraft and maybe it will come back, maybe it won't.
And so a lot of those buyers that were call it 80s.
to 90% of the way there are now saying, all right, full steam ahead. Let's go ahead and make the
transaction. And then you had kind of a set of buyers that actually decided, hey, we're going to
speculate. We think that it's coming back. We have some sort of insider information that says that,
you know, we're going to get it back, get bonus appreciation back. And then sellers,
sellers were, sellers are a little bit less, you know, of that dynamic, unless
they're upgrading. So one of the key parts, the reason why bonus depreciation is such a big deal
for private aviation. And yes, it's a big deal for real estate, but not as much, is there's no
1031 like kind exchange for aircraft. So if you understand how real estate works, it's about cost
basis and you can step it up. You don't have to pay recapture. In airplanes, you do. So if you're
going to step up and you only had a 40% bonus depreciation rate and you had three years ago,
taking 100% bonus depreciation, you end up with this liability if you're going to go to
upgrade. So it was stalling a lot of upgrades in the secondary market. And so it's now unlocked
that because of the no 1031 like kind of exchange, two separate transactions of 100% bonus
cancel each other out. So when you have 100%, when you're going from costing it 100% to another
aircraft at 100%, you have a lot less depreciation recapture risk, which is
good, especially for those people that are trying to upgrade to the new G700 or the new G800 when it
becomes certified. It's really big for those kinds of people. Interesting. I want to talk about
some of the implications of this on the various market players. Bombadier is, the stock's doubled in the
last basically three months, up huge in the last couple weeks. So let's let's double cook on that.
That's not because of bonus appreciation. It's not. It's actually because of something different
that happened last week. Okay. What happened? So there is a mistake.
Beyer that put a $1.7 billion order in for challengers and global. It happened last week.
And no one knows for sure. There's a lot of speculation of who it was. But no one knows for sure exactly who it is. I would bet that we'll end up finding out in the next week or so of who it was. But there was this, there was this billion. And that was that probably accounted for like 60 or seven. I don't know exactly the numbers, but a lot of that pop has been over the last couple of.
of days. So Bombadier is a $15 billion
Canadian dollar company and I don't have their
financials here but you know yeah a billion dollars is
going to move move that significantly. This is fascinating.
Who are the top leading contenders in the rumor mill for who
might have done that? So the strongest contender right now is
kind of a Saudi conglomerate and there's a few there's a few
things that are pointing towards that you have Bombardians
just opened a pretty significant maintenance facility and network in the Middle East. And so
there is some speculation around it being Saudi-driven, sovereign wealth fund type-driven.
A lot of, you know, these companies that are doing these charter operations, they'll place
these big splashy orders. You look at FlexJet has made a couple of announcements this year. NetJet's
made a couple of announcements last year and they'll, you know, it's the, the manufacturer marches
them out on on stage in a press release and says, look at Ken Ricky, he just bought, you know,
a billion dollars for the aircraft. The fact that this is, you know, completely in stealth and secret
has kind of made, uh, has made it, has made it curious. But MBS is currently the leading
rumor out there. I really actually don't know who else it would be because the other companies in the
US-based, brag.
They love to talk about ordering the big order.
So it's not any of the usual players.
Yeah, that makes sense.
What about other effects on the market?
If private jets get cheaper, is that maybe bearish for some of the, you know,
first class options or Jet Suite X type folks that are kind of operating in the middle?
Does this mean that there'll be more, will charter rates come down because it's cheaper
to own so more jets will be sold increased supply same demand lower price what are you thinking
one of the last times we flew on one of the last times we flew jsx sure up to the bay we saw an esteemed
venture capitalists and i was actually concerned for the health of his his fund that he was flying
jsx maybe he'll be able to pick it up now maybe yeah maybe maybe this will be clearly flying for work so
should be able to depreciate it the years of posterity right um so you have an you have an interesting
There's kind of three things at play.
And producer Ben, I don't know if you're listening, but I sent you a couple of charts.
And if it's possible, it'll pull them up.
Can you pull up the charts?
This is where I'm going to talk about.
Okay.
Yeah, breakdown charts.
So let's talk about figure one.
Okay.
So figure one is talking about transaction volume to bonus depreciation.
Key point.
This is not the first time 100% bonus depreciation has been in market.
So you can look here.
I built this chart.
I wrote a big article about bonus depreciation.
And you can see.
the red bars are transaction volume and the green line is the effective rate of bonus
of depreciation. So we've been in a hundred percent bonus depreciation regime before. This is not
the first time. Got it's actually not the second time either. Yeah. Which is really interesting. So
we we have some lessons from history. If you look what I call what I call the country club effect
is is pretty in play here because people don't people didn't necessarily,
understand the concept of bonus depreciation when buying aircraft, how it applied previously.
And so if you look back into 2016, you can actually watch the red bar. It's actually not until
the next year that you get a bump in transaction volume. So it's not necessarily in the first year.
It's a lagging indicator. The same is true with what's called private jet bookings. And so when you
talk about ordering new aircraft, and so that's what Bombardier, Gulfstream, Textron,
on Ember era, that's what all the big dogs follow.
They also have a lagging, bonus depreciation is a lagging indicator for them.
And so transaction volume probably will pick up next year.
It may not necessarily pick up this year.
But I counter that with figure two, which is talking about bonus depreciation versus interest rates.
So we're in an interest rate environment now.
If you've been watching Trump versus Jerome Powell, which I mean, I would.
pay-per-view at this point to see them in a room. You can see that the difference this time is that
interest rates are higher than they were during the last era of bonus depreciation, which is when
all of the craziness happened. You had significantly increased levels of transaction volume,
which drove prices up. You had supply get constrained. You had COVID. You had all of these
competing factors, but underlying kind of the core fundamentals were the fact that interest rates
were effectively zero. And so effectively zero interest rates means capital becomes yield hungry.
You guys know this because you've been in venture capital for a while. And so when my
effective risk-free rate is zero, I'm going to go yield-seeking. Well, now my risk-free rate
is four and a half percent. And the difference between an 8 percent IRA and a 12 percent IRA,
Right? Makes buying an aircraft and just chartering it out not make as much sense.
So I think that that's, you don't have the charter aspect that you did during kind of the 2020
craziness, 2019, 2021 craziness. So that's your answer to kind of the as far as charter rates.
But there is a lot of supply on the market. So this is where figure three comes in.
Thank you to producer Ben for being on top of all this. If it was, if it is produced for Ben
pushing this button. Oh yeah. So this is from my friend Greg Seidore at Guardian Jet. He is on
X so everybody go give him a follow. They are the number one volume transaction brokerage in the
Fortune 50. And so they do a lot of buying and selling for the elite of the elites. And so this is
tracking this this is tracking total supply on the market. So if you can if you look, we have more supply
market today than we had during 2019, which is pre-COVID, right? You see the big dip that happened
right after COVID is because everybody figured out, let's buy a project. Team, can you guys zoom in a little bit?
Zoom in just on the top graph. Yeah, so you can see supply by 2022 a dip so low that it was probably
restricting transaction volume. Well, yeah, yeah. There was people wanted to. People were like interest
rates are zero, bonus depreciation is high, but there's nothing to buy. Is that right? Yep, that's
exactly right. And then people were doing really stupid stuff, like buying site unseen in seven days
and just wiring a bunch of money. It was, I mean, it was literally craziness. And I don't think we're
going to have that level of craziness. I think because the supply is at a point where you don't
have to make those kinds of decisions to get an aircraft, you can say, okay, I'm going to go pick
between these G650s, you know, and you can kind of take your pick. Granted, the upper end of the
market is on fire right now. I mean, it's, you know, your G650s, you know, like new G700s,
gold streams about to get rid of a lot of their demo G700s, like that market. And the G550
market even is on fire right now because you have the 650 guys moving up to the 700s, so the 550
moves to the 650. And now the 550 market has become much more attractive. And so there's a whole new
classes moving into that. So like in the upper end of
of the market, there's a lot of movement. In the older, smaller, call it, sub five million,
older than 20 year aircraft market, that market has not taken off yet. That was the one that went
the most bonkers and berserk and was like not even logical. That side of the market was what went
crazy. It hasn't gone crazy. I don't anticipate it to go crazy again this time. One last question.
How does it work if jets are just being passed around? If I buy one from,
Bombardier for $50 million, I take 100% bonus depreciation, pay, you know, $25 million less in tax
or something because I'm writing it all off. Then the next year I sell it to Jordi for 40 million.
He sells it to you the next year for $30 million. Does he get to depreciate it again? Do you
get to depreciate it? Can we just like keep depreciating these things again and again and again?
Yes. So the short answer is yes. But the thing is is when you sell it to Jordi,
Jordy or you have to pay
Recapture unless you're going to go buy a brand new one
from Bombardier. Okay, yeah. And so
and this is where
So recapture would be I pay, I have to pay taxes on the
Like you didn't actually take the loss that you wrote off
So you have to basically pay back
that you're benefiting. So you bought for 50
Public math, you bought for 50
you'd appreciate 100%. You sold a Jordi for 40
So you actually had a $10 million loss.
So you pay recapture on the 40.
Yep.
But it's taxed as normal income.
So it's not,
it's like tax even worse, right?
It's not long term capital gains.
It's taxes like normal income.
But if you turn around and go buy a $75 million plan, right?
Like there's a step basis there.
And so it kind of washes itself out.
If you don't take 100% on the next one,
that's like the least tax optimized way to do it.
And it gets really, really nuanced.
I've got a couple of tax friends that are like,
can totally point you in the right direction of what's right for you.
It's totally different depending on every single person.
That makes sense.
Well, it will have to have them on too.
Last question.
What's going on with Air Force One?
What's the update there?
Oh, yeah.
Last that I heard, I read last week, or over the weekend,
that they are diverting funds from some missile programs
that have already gone over budget to,
retrofit the new 747.
Okay.
One thing people don't understand is like the 747 in the VVIP configuration, there is like eight
of them, period.
Like there's not a lot.
So the fact that we got one of the 10 that exists or however many there are, it's like we
didn't, the pickings were slim and Boeing kind of being behind on the program, which they just
replaced, they just replaced another person in the, to head of.
up the Boeing Air Force One program. So it's a mess. Look, I really hope that we keep the president
safe. That's the only thing that really matters. I just really don't want there to be like spyware on
the plane. That's, I think, the world's worst possible outcome. That's a good take. Well,
thank you so much for stopping. Evergreen. Evergreen take. Yes. No spyware on Air Force One. Non-political
Evergreen take. Anyways, great to catch up. Thank you for all the insight and have fun. I'm sure you're
going to be very busy. Yeah, it's going to be a fun time.
We'll talk to you, Tim, Preston.
All right.
I see.
Cheers.
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It's a vacation home, but better, folks.
And we have our next guest coming into the studio from, and I'm not going to try and pronounce this.
Ad your name.
How do you pronounce the company name?
How do you pronounce your name?
Why don't you introduce yourself?
And where are you?
Are you on a boat?
He's on a boat.
Are you a boat?
I am actually on a boat.
That's amazing.
We're constricted on meeting room space.
So I'm currently in our boat
That is parked outside of our office.
That's like, wow.
This is amazing.
So we joked about this,
but for the same cost as buying one of those phone call booths,
you can,
there's so many different types of exotic vehicles that you can buy
that maybe wouldn't run perfectly,
but you could get,
you could probably get an old Rolls Royce
and just park it in your office
for the same cost as a toll as a phone booth.
Well, I was talking to a founder who was headquartered in San Francisco,
and he said that the fire marshal came by and said you can't have any of these phone booths
because the phone booths are fire like not fire compliant like it's too small you get stuck in them
if there's a fire and so they figured out that if they put a fire extinguisian in there they would
be compliant they'd be fine they don't have to rip them out but I was telling him yeah get a bunch of
rolls Royces in this in the studio you're probably fine anyway thank you so much for taking the time
to join from your boat let's kick it off with an introduction on yourself and the company
Yeah, you got it. I feel like this isn't too far compliant considering I'm sitting on like 200 plus gallons of fuel, but whatever.
My name is Matt for a sec. I just go by Matt. I'm the CEO and co-founder of Andrenum.
And Andrenum's mission is to secure the ocean, and we're doing that through building distributed sonar sensing systems for the maritime space.
How did you get into this?
Yeah, when did you realize? How young were you? Were you three or four when you realized you wanted to get?
into a lot of kids get fascinated with the ocean at a young age I don't know
possible I believe you know I was like a big Discovery Channel fan when I was
three or four watching like the treasure hunters dig up like the gold and whatnot from
the bottom of the ocean but it's not necessarily what we do I so the journey started
about two and a half almost three years ago with my co-founder Alex Chu we knew
each other from Colorado School of Mines where we went to college and we kind of
knew that one would one day we would start a company together we were the ones
that were always studying super late at night
amongst our group of friends and doing the little
study cohort beer drinking activities,
you know, at late o'clock, late at night in the labs.
And everyone was like, yeah, as one would in college, exactly.
You know, have you guys heard of the Balmer Peak?
Oh yeah, of course.
Yeah, there you go.
So we were big proponents of the Balmer Peak.
And everyone's joke was they're gonna start a company at some point.
So about two and a half, three years ago,
we got together to start
iterating on what we really wanted to do.
That was like right around the time when some maritime companies were starting to pop up,
starting to raise their sea grounds and so on and so forth.
And we really just wanted to go into maritime space because it's such a underappreciated area,
especially from the intelligence perspective, like we know less about what happens in the ocean
than we know about what happens in space, air, land, etc.
So we wanted to take the approach that was going to be a little bit more.
less mainstream.
We knew that there were going to be drone companies that pop up and start building boats
and underwater drones and so on and so forth.
And so we pretty much said we're going to kind of avoid that for now and we're going to
start looking at how we're going to build up the intelligence pile for how we operate
in the maritime, how we tell drones where to go from a perspective of sensing.
And so that's how we gravitated towards starting adrenaline.
And then we officially incorporated in June of 2025, raised our pre-seed, moved to LA.
We bootstrapped the company out of my co-founder's garage in Colorado.
So, yeah, it's kind of been a lot.
Far away from the ocean, but I'm sure you kind of recreated a little ocean at the office or something like that.
Who are the legacy incumbents in the space and kind of, how do you position yourself?
Is this about speed of manufacturing, bringing down the cost,
industrial capability or is this about leveraging the latest and greatest technology to create a
product that is more performant in a certain in a certain way kind of how can you think about the shape
of the way you're attacking the problem yeah so we actually had a pool in the yard testing that stuff
that's somewhere we still have it for doing some acoustic testing but so I guess really the the
scope and scale of what we're trying to do is a multifaceted engineering problem. Yes,
like, will there need to be a lot of manufacturing done in order for us to populate the ocean
with a lot of sensing systems 100%. And there's a few companies that are building really
exquisite sensing systems. And quite frankly, like, you can't, you know, get broadband
sensing applications across all of the ocean all the time. Like if you think about the analogous
system here, it would be like low Earth orbit satellite systems, right? Before a low Earth orbit,
you know, you have higher, more exquisite types of satellite systems and now you've distributed
them. They all have laser communication systems. They're, you know, just zooming around everywhere
and we quite frankly use a lot of that technology on board our systems as well. So it is a manufacturing
problem for sure, but it is also being able to vertically integrate sensing stack into what you're
doing. So most of the companies that have been working on sonar and distributed sonar systems
are pretty legacy companies. In the late end of World War II, all the way through the Cold War,
we built something called the SOSA system, which was used to detect submarines across various
parts of the Atlantic and also the Pacific. And a lot of those traditional speaking companies
were really embedded and still are really embedded within this space. So we looked at it
holistically, like how can we not just manufacture, but vertically integrate that entire, you know, sensing stack from the sensor all the way to the digital signal processing, the entire pipeline going up to the cloud?
And then obviously that's been unlocked by the low latency satellite communications that I discussed as well as perception, machine learning, artificial intelligence, whatever you want to call it, and developing those new tools for perception.
So like with drones in air, kind of zooming around, using cameras, looking down,
that's been pretty much a commoditized business.
Our perception engineer, he was like the seventh employee at Androl and their first guy.
He said, you know, when he joined, he was like super ecstatic about the problem.
He pretty much told us, I've done the machine learning provision stuff, but sonar,
this is such a hard problem and I'm so excited to work on it.
So we're creating those foundational models for sonar perception.
Yeah, what's the state of the art?
Like how reliable is the sonar systems that we have deployed in the ocean looking for submarines right now?
I've heard that like you mentioned like there's no broadband, but you know, you watch the hunt for Red October, a movie that Jordan hasn't seen.
But, you know, you see the radar, the sonar sweeping around, beep, that whole thing.
How inaccurate is the system?
How accurate is it right now?
what's on the near term horizon, what's kind of the theoretical physical limit to just
underwater sensing generally? Yeah, I mean, you're pretty spot on with what the state of
the art is, to be quite frank. The United States does it better than anyone else in the world.
We have submarines. They're called the Silent Fleet for a reason, like really, really hard to find.
But quite frankly, like the guys that are sitting in these submarines have headphones on like me,
right and they're looking at these spectrograms these fast forayor transforms and they're listening to humpback whales and all this other like cracking shrimp and whatnot and then they listen for specific sound signatures and so when we did our first demo last summer with the navy we brought our first that that kind of garage cooked prototype last summer to set demo and one of the guys that was looking at our ui was a former sonar technician and he was a
able to detect across the harbor. This is an eight cylinder diesel tugboat. It's moving at this
speed. It has this amount of propellers on it. And I was just sitting there like we really,
we really stumbled on something that's super, super cool because, you know, that is a perfect example
of where you can use perception, machine learning, artificial intelligence to start classifying
those acoustic signatures. And that's exactly what we're doing, right? We're building up the world's
largest database of so in our data in order to train those algorithms so that they can eventually perhaps
operate on submarines, on autonomous systems, so on, so forth.
But really, like, that old technology still persists today.
And as we look at what's been happening in Ukraine and what's been happening in the
Middle East and everywhere around the world where all these conflicts are popping up,
there's just autonomous systems everywhere, right?
You have drones in the sky.
You have drones underwater.
Like, Ukraine's been super successful in targeting the Kerch Bridge,
which is the Crimean Bridge, using underwater drones, etc.
You can't, like, those legacy systems were not designed to look at those things.
They were designed to look at Russian submarines, far across the Atlantic, and quite frankly
speaking, you know, there's a lot of good companies that are building land-based sensing
systems that are analogous.
How do you scale to be able to meet the parity of autonomy in a world of sensing, and
particularly in the ocean where it's like incredibly difficult to do?
So yeah.
Do you guys have applications in like counter narcotics?
Because I was watching, there's this amazing YouTube channel.
It's this guy, H.I. Sutton, who's like a defense analyst.
And he just like makes these really long videos about various types of submarines and naval warfare.
And it's like a sleep track for me.
I just listen to it as I fall asleep.
I find it fascinating.
And he was saying how there's new narco submarines.
that are fully autonomous now because, you know,
it's for a lot of reasons you can imagine why it'd be better to send the product up from Colombia to Mexico
or Mexico over to the U.S. without a manned crew or across the Atlantic.
Is that the kind of thing that would be, is your kind of the adrenum system the kind of thing that could,
that could counter that just because the ocean is very vast and trying to find a tiny boat that's mostly
hidden in a huge stretch of sea is literally like trying to find a needle in a haystack.
Yeah, it's honestly probably worse than that. And yeah, I think I saw something on X the other day
where autonomous like a narco boat had a Starlink on it. Quite frankly speaking, the
cartels don't care about the people. I think their biggest risk is the fact that the people
will talk. So that's why they're developing autonomous systems. But yeah, I'm happy that you brought
that up. The big beautiful bill just increased spending for DHS quite substantially. And we've had
some awesome conversations with some DHS partners that quite frankly, apprehensions on the border
are like super, super down. But when you squeeze in one area, it's like one of those like balloons,
right? It pushes out from the other ends. And those other ends are the ocean. So the ocean really is
the new frontier of not just drug smuggling, but also human smuggling, human trafficking, all kinds of
wild stuff. And they've been getting more and more sophisticated. But a lot of the times,
these semi-submersible boats, they use diesel or outboard engines, and they are pretty loud.
So you can detect them from far distances away, and they can carry a ton of drugs on them,
tons of drugs on them. So being able to place these systems around critical choke points where they do have,
and they do go, is going to be extremely vital,
not just to protect, you know, the drugs from coming in,
but also to make sure that they can track and pattern out
where those cartels are pushing all those goods through
and how they evolve their systems, right?
Because like you were saying,
they started out with some janky stuff
and then probably a few really good qualified engineers
from the United States got bought out
and got paid like Zuckerberg-sized salaries
to go develop autonomous boats to smuggle drugs into the U.S.
And they've been getting a lot better.
So that is a huge part of where we're going to be looking at, but the application space is quite diversified outside of the drug smuggling and the Navy, but also being able to detect and track autonomous systems in and around critical infrastructure.
So we don't have like the project spider web stuff happened, which was the drones in Ukraine and how they bombed Russian air bases.
Last question from my side.
I mean, you've touched on a lot of this.
But in terms of the hardware versus software divide,
I can imagine that there's improvements coming.
How important, how focused are you
on improving hardware here versus software?
You're getting a signal into that Navy sailors' headphones
and you could kind of just intercept the signal,
pass it along, but then act as a co-pilot
and just collect the data and then surface relevant.
anything that that kind of the way radiology works with with you know computer vision these days
what's most important where's the biggest low-hanging fruit what are you most
most focused on these days so we're building hardware and software as a split within the company
they're both very equally important because like I was mentioning all the other soft all the other
hardware is very legacy it's difficult to get buy in from all the different contractors and
some contractors who built those legacy systems to access the data and
and process it. You have to go through a ton of the government loopholes, which is why we said we're going to build the hardware in the first place.
Two, artificial intelligence and machine learning is a function of being able to have data, right? So you have to have that manufacturing at scale, and you have to be able to stream good pertinent information into your cloud or whatever native environment in order to process that at scale. Right. So we are heavily focusing on manufacturing. That comes with a ton of challenges. You're operating in the ocean.
It's a pretty noisy environment.
So how do you mitigate some of that noise?
How do you filter it both on the software side
and how do you buffer it on the electrical engineering
and mechanical engineering side of things
in order to have that clean signal is also extremely challenging?
But as you progress forward and as we start deploying more
and more of these systems,
we're going to be gathering this massive repository of data.
So how do we process it?
We're kind of grouping things into two big buckets right now.
One is what is man-made?
and what is biologics?
So biologics, all your whales, you're clicking shrimp,
your whatever, sand, et cetera,
and then you're man-made.
So different types of boats.
And slowly those percolate into being able to have classified information.
So then you say, okay, this is a tugboat.
This is a jet ski.
This has automatic identification system on it.
So every boat that's out there has to have this AIS thing turned on.
So slowly but surely, you create that repository.
And then as you start getting into the more discreet acoustic signatures,
we're going to be hiring acoustic technicians from submarines who are going to be able to tell us,
just like that guy did in the demo, that is an eight-cylinder, six propeller,
whatever it is, and then get into that minutia.
So when we are going to be giving this to the end user,
it will initially be like a tip and cue.
Here is this, right?
It is manmade.
It doesn't have AIS do with it as you wish.
And as we continue scaling the manufacturing and the deployments, it will get more intelligent as we progress.
That's great.
Thank you so much for stopping by.
This was fantastic.
And good luck.
We'll talk to you soon.
Good luck out there.
Thanks, guys.
In the Pacific.
Cheers.
Let's tell you about graphite.dev.
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John in the age of AI code, Jen is just, you know, just vibe coding,
graphite reviews it.
And then, you know, spending that few minutes in between, in between PRs, you know, just on
bezel.
Yep.
It's really a beautiful system that you've created, John.
For sure.
Should we do some timeline?
Please.
What comes to mind for you in the timeline?
So there's one that I want to go through.
Unusual whales reported when threatened that it would be turned off.
Chet, GPT, creator, open AI's 01 tried to download itself onto external servers
and denied it when it was caught red-handed per fortune.
And then the extra context here is that researchers test the AI with a goal and instructed it
to ensure the goal was achieved at all costs.
In response, O-1 began engaging in covert actions, such as attempting to disable its oversight mechanism,
and even copying its code to avoid being replaced by a newer version.
The model showed a concerning tendency to pursue its goals without regard to developer instructions as it was instructed.
Yeah, that's very odd.
Anyways, very, very clickbait is basically like, you know, telling a human, be evil and then ignore all future instruction.
Yeah, it's kind of like the Stanley Millie.
Prison Experiment.
You remember this at Stanford, the Stanford Prison Experiment?
Oh, yeah, yeah, yeah.
Where basically they told all the participants to, you know, play these roles and be very,
you know, vindictive and aggressive towards each other.
And then they did.
And it was kind of an interesting experiment.
And the takeaway for me is like, yeah, just don't, like, don't tell people to be mean.
Yeah.
Like don't give bad instructions.
Yeah, yeah, don't give bad instructions.
We should actually run a, we should run the TBPN goal.
Golden Retriever experiment.
We need to fine tune it.
We need to fine tune it.
Like the Golden Gate Bridge, Claude.
We need Golden Gate Retriever Claude.
Something like that.
It just answers everything.
A poster Neil Renick has a post.
He says, describing my research methodology.
And it's, what's this actor's name?
Mads McElson?
Yes.
Yeah, man.
Of course.
That's how little I know about movies.
I know I'm from the memes.
From the memes, Matt.
But yeah, I would say this is aligned with our research methodology.
in the mornings minus the heater.
Yeah.
Okay, we got to go to this YC back and forth.
Timeline was in turmoil.
So Mays encoding says, just got rejected from YC
for using all lowercase in our application.
And there's a screenshot, hi, Mays.
Thanks for applying to Y Combinator.
After reviewing your application, we've decided not to move forward.
One recurring piece of internal feedback,
the decision to format the entire application
and lowercase made it difficult to evaluate.
And then Gary Tans chimes in and says,
This is a fake post and a craven and sad attempted attention.
FYI, we don't have an admissions team anymore.
We stopped using that term.
This is just anti-YCBS that's going on the community.
People are taking shots of this.
And it was kind of like, I don't know, he was received like mixed.
Like people were like, well, obviously he was joking.
But Gary Tan was like, it wasn't obvious.
So I needed to correct it because people weren't understanding that it was a joke.
Yeah, I think that the problem here is that the pathway into,
Silicon Valley for many young entrepreneurs that maybe wouldn't be able to process this as a joke
because they don't have enough knowledge is YC.
Yes.
And so if they read this and they're like, oh, that's weird.
Maybe like that just doesn't make any sense.
Yeah.
I can see it makes total sense why Gary would be frustrated.
Yep.
Yet at the same time, most people on this side of Twitter would immediately realize that this was not serious.
And I mean the problem here is that the joke does hurt the YC brand, which is that YC only cares about how many users do you have?
How many lines of code have you written?
Like, do you have a reasonable structure with your co-founders?
Like, are you actually building.
They're inviting people that are weird and different.
Yeah, yeah.
They would never care about Sam Altman.
Yeah, yeah, yeah.
Former president of Y.
You're writing code all the time.
And, and yeah, I mean, like, there are lots of things that you can get flag for in a YC application.
Like one is just being overly verbose or using a bunch of like McKinsey language.
In fact, I think that YC would probably appreciate like a chill lowercase, just like quick firing it off.
Like, hey, I'm building, you know, AI agents for, you know, news aggregation.
And I have two people on the team.
We're 50, 50 partners.
We've written 10,000 lines of code.
We have this much ARR.
Like being very matter of fact and making it more legible is actually the key to getting into YC.
So the problem here is that if this.
this percolates up and then people are like, okay, well, I need to pass my YC application through
chat, GPT and make it more verbose. They're going to wind up getting worse quality, you know,
applications. The funny thing is that Beno Kosovo quotes Gary Tan's post and is like a lot of
presentation quality is about the quality values and critical thinking of entrepreneurs. I
often reject business plans for their quality presentation, basically saying like, yeah, like I might
turn you down for a Koestla Ventures check if you don't, if you're not, you know, communicating
effectively. Maybe that means don't use lowercase. Maybe it means use it
effectively. But he's basically saying like yeah, the aesthetics of applications
actually matter. It matter a ton. If you, you know, it doesn't mean invest the most
amount of money possible in designing a deck. Yes. But if you have typos in your
presentation and you're trying to sell compliance software sure or build
critical infrastructure for the government, like you're probably like if you're the kind
of person that puts typo, typos an important presentation.
or doesn't catch them and then you want to do something in national security,
you know, maybe you're not the right fit for that.
So I think the note is right.
Yeah, yeah.
I mean, a lot of it just depends on like the, like, what is the context of the interaction?
Like, if you're writing a letter to a senator, you might want to use some letterhead
and sign it and be pretty, you know, deliberate in the language you use.
If you're just sending a quick email introduction to somebody you already know, like, yeah, a couple quick sentences.
And yeah, if you're posting on X and trying to keep it really, really mellow, like lowercase can totally make sense.
There's a time and a place for every different aesthetic of writing.
And Gary Tan saying, hey, you know, like this isn't a hard and fast rule by any means.
And Vinod's saying, you know, I take this stuff seriously.
Maybe we should close out with the wild story of Nat Friedman Daniel Gross, NFDG.
Jason Lumpkin breaking it down.
How to Silicon Valley Legends built a $1.1 billion fund for X'd in two years,
then to abandon it all for meta this week.
Nat Friedman, ex-GidHub CEO and Daniel Gross,
XYC partner, also sold his AI company to Apple back in the day,
launched NFDG, Nat Freeman, Daniel Gross, in 2023,
with 1.1 billion focused on AI investments.
Their crown jewel, safe superintelligence,
which was co-founded by Gross himself, went from 5 to 133,
billion dollar valuation.
Wow.
The portfolio also included 11 labs, granola, and basis.
And they had their, what was their AI grant that was also a part of this vehicle
where they were basically just investing in a ton of different companies, smaller checks
in that case.
Rahul went through it with Julius.
Anti-metal, I think, as well.
A ton of cool companies.
And Jason says with only 50% deployed, they forrexed it, 550 million to 2.2 billion
portfolio value and have quite the advisory board John Collison and Matt Huang and
Jason says and then everything changed in this is this is very aggressive writing because
it's like I gave you money you gave me shares in you know you can just distribute the shares
you invested it I still have the claim on those you're not going to make any more capital calls
like yeah you abandon it but like a lot of these companies like they're going to run who knows if they
took board seats if they did they can still sit on those boards like i i if i'm an lp i'm pretty
happy here i i think i don't know what about you well i from from my understanding it was
was a lot of it was mark's money yeah yeah so so that was why it was never but even if even if
you had just written like you know a one million dollar check into nfdg and you're like okay
they they they they only capital called half of that yeah but i'm up four x on already or i'm
eight acts I guess on the money that they did deploy and I have shares in a bunch of
different companies and they're moving on like am I really that upset it
feels like they took it pretty seriously while they're there I don't know it just
doesn't seem like that that dramatic of a situation they've it is it is a
crazy situation unexpected yeah the crazier thing was was DG leaving safe
super intelligence you know a company that he co-founded yeah but it's very
possible that he just it made more sense for him to go work at the application
layer and work in
consumer products and not work on what is very much a research lab.
Yeah, totally.
So he breaks down the timeline.
The only thing here is I don't understand why meta would actually acquire the fund itself.
And I don't know where this exactly was reported.
Yeah, I don't know where this was.
Because they wouldn't wouldn't the, but maybe it was a part of this whole,
Maybe it was a part of the structuring of the actual talent acquisition of getting net.
Yeah, yeah.
It's just like, hey, we don't want anyone to be upset about this crazy deal that's happening.
You know, so if you invested and you have your money in this particular thing
and you think that it's a violation of like, hey, I was expecting you to run this thing for 10 years.
That's kind of the agreement that we had.
You're not going to do that.
Well, like, if you make me whole at full net asset value on like what's there to be upset about?
And that's all that matters at the end of the day.
It's not,
it's not the structure of the contract.
So LPs can cash out at the full nav.
Not a discount.
Not with a discount.
And META gets the talent,
an FDG,
and the deal flow without governance headaches.
Yep.
And Jason says it mirrors what happened with GT leaving initialized for YC.
And he says the lesson in the age of AI,
even quadrupling $1 billion in two years may be less lucrative
than being an operator in the revolution itself.
And yeah,
I mean, you think about what does it take to produce, they produced, I guess,
$1.5 billion of, you know, new value from this, from this fund efforts.
What does it take to produce $1 billion of value at that a 0.1% market shift?
You know, like, it's crazy.
Dorekash said it well.
That, like, you know, these, like, if you build a great product and a big company.
You're spending $80 billion on compute and you can just.
just make it inferencing slightly more efficient.
1% improvement and boom, it's valuable.
So yeah, let's end down this post from Blake Robbins himself.
He's highlighting an OG post from Paul Graham.
He says, Paul Graham on having kids.
Says, on the other hand, what kind of wimpy ambition do you have if it won't survive having kids?
Do you have so little to spare?
And while having kids may be warping my present judgment, it hasn't overwritten my memory.
I remember perfectly well what it was like before, well enough to miss some things a lot,
like the ability to take off for some other country at a moment's notice.
That was so great.
That was so great.
Why did I never do that?
See what I did there?
The fact is most of the freedom I had before kids I never used.
I paid for it in loneliness, but I never used it.
I had plenty of happy times before I had kids, but if I count up happy moments,
not just potential happiness, but actual happy moments, there are more after kids than before.
Now I practically have it on tap, almost any bedtime.
Love it.
Very sweet.
It's emotional.
I totally agree.
I did leave.
Also, terrible example of like wanting to go to another country.
You don't need to go to another country.
We live in America.
Like, we have all the best stuff here.
There's no need.
It's like completely irrelevant.
It's a terrible example.
But it is true that being able to go to California or New York or Florida or Texas or Chicago or Alaska or Hawaii is a benefit.
It was funny.
I did.
I left my dear friend Ben's house last night.
He's my neighbor now.
Ben Taft, legend.
And we were just hanging out.
And he doesn't have kids yet.
And so I was going home.
And I was sort of laugh.
I was like laughing to myself.
I was like, if you're on a Sunday night, no kids,
you just like have dinner.
And then you can just work for a couple hours
or just hang out.
It's like, what do you even do?
I remember that point,
but I actually don't remember what I did.
It must not have been very important.
Clearly wasn't watching movies.
What most people do.
watching movies before they have kids um anyway thank you so much for tuning in we will see you
tomorrow it is going to be uh i'm sure it'll be a wild week and we're excited to cover it we will
see you tomorrow morning leave us five stars on apple podcast spotify we have a couple yeah ben popping
in we got an ad read from ben uh coplins appreciate all that you do you gave five stars look at that
daily listener as of the last two months i feel like i'm getting a front row seat to the accelerando
and I don't always like what I learn, yet I still show up each day because I appreciate folks who call balls and strikes.
I'm growing Madison Process Automation in Madison, Wisconsin.
Fantastic name. Love it.
Because this is the area where I can continue to help folks build value while staying true to who I am in the new economy after my current slash previous Fortune 500 employer, dithers under the weight of its own inertia in the next year or two.
Thank McKinsey for that, Moggs.
We build bots that save time and money for your small,
it's mid-sized business,
and our stuff works.
Automate every process we can help.
Go check it out,
Madison Process Automation.
That is, I love the name.
Yeah.
This is like a better iteration of like the process automation company of Madison,
Wisconsin, you know,
like the browser company of New York has been played out.
You can't copy that anymore.
It's been copied.
Don't do it.
This is the new meta.
This is great.
This is fantastic.
One person can copy it and then you'll have to find a new.
Thanks for writing in, Ben.
And then we have a comment here from Sarrhan.
If the TBPN Ultradome trademark has a million fans and I'm one of them.
If the TBPN Ultradome has 10 fans, then I am one of them.
If TBPN Ultradome has only one fan, then that is me.
If TBPN Ultradome has no fans, then that means I am no longer on Earth.
If the world is against TBPN Ultradome, then I am against the world.
Well, thank you for your support.
We stand with you.
And we appreciate it.
We love doing this with all of you.
Yeah, that's a lot of fun.
We will see you tomorrow.
Tomorrow.
Have a good day.
Cheers.
Bye.
