TBPN Live - 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
Transcript
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You're watching TBPN. Today is Monday, July 7th, 2025.
We are live from the TBPN Ultra Dome, the Temple of Technology,
the Fortress of Finance, the Capital of Capital. We have an awesome show for you
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 who stayed domestic
and served America, thank you.
We have a whole bunch 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.
We did.
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, that's what.
And my wife was laughing because it was like.
Many people mean when they say work hard, play hard.
But it's true, it's true.
If you work hard you get to play hard.
And when you play, when you have friends over,
it can be very luxurious, which is great.
Anyway, in some absolutely massive breaking news,
Dwarkesh 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%.
Slightly, but probably not on that news.
Probably not on that news, but it should have been.
And 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, Dwarkesh is out there calling AI hype overblown.
I know we stopped doing these things,
but likely the AI trade top is in.
And he could not have gotten it wrong.
Don't tell Chyna.
It 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 a GI 2027 stuff is wrong. The market isn't pricing either of these scenarios
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, while this makes me bearish 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-won lesson
from years ago.
I remember talking to somebody, this kind of like,
I don't even know if he's a philosopher,
he's a user experience designer and he said that
there's multiple ways to learn.
You can develop habits through just doing something
the same, 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 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 example he gave was,
one day he goes out to-
Or a true lesson.
True, 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 slip-ons, and there was a lizard in the slipper.
And it freaked him out.
It gave him this intense response.
He was fine, but ever since then,
he's been in the habit of always checking his shoe.
There's a snake in my boot.
There's a snake in my boot, exactly.
And so it's not like that was something
that had to be trained for years,
but it's like this one really sharp, intense learning
that then carries forward forever in his life.
And so people and employees do that too.
I hate to say you couldn't learn that in school.
You gotta 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 learn hard-won lessons
and then carry them forward forever.
And we don't even really know how to design
against that necessarily.
So, Dorakesh 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
GPT-1 which was a slaw factory. It was 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 in the already saturated areas
in the Texas Hill Country.
So this blew up on Axe.
And people were asking,
Augustus, was 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 Augustus 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 contribute 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 Barry
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 seeding operations
in Texas do not occur during overnight hours.
At four a.m. on July 4th, NWS issued
a life threatening emergency warning
and flooding ensured.
He says, did Rainmaker conduct any operations
that could have impacted the floods?
He says no.
The last seeding 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 seeded 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?
I think 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 non-profit.
Obviously, remaker has clients. I believe it was state level funding.
So the state might buy cloud seating operations in one way.
There could be, you know, 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.
A knockout.
Did you ever go to BattleBots growing up?
Yeah.
There was a big, at Caltech,
there was a big BattleBot annual robotics competition.
They stopped doing the fighting ones
and they started doing robot soccer for a while.
Way less fun, way less fun.
Still impressive.
And they did rock climbing.
As a formative memory, formative memories for me
seeing a robot with 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. It's pretty minimal, but the lighting and everything,
like they really put that.
Very well done.
Very, very well done.
And so Verda.
Is Sam calling in today?
No, no, he's not available today,
but we'll get him 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, yeah.
Where people just as like a, you know,
just side project, whatever you wanna call it, hobby,
develop humanoids 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.
Like, I don't know, UFC's a huge business.
Yeah, I've been saying I want to see
a humanoid robot cliff jump off of the Salesforce tower.
Obviously with the ground, you know, properly cleared
so that 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 get you paper-clipped
If you keep talking like that, you gotta be nice to robots. I don't even know if you
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?
How it'll probably know this thing's know one of those things in airplanes,
the black box, right?
That's like.
Oh, just make it out of the black box?
Put their brain, put the chip.
Put 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 onto 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,
our ragtag dream team, the dreamers still alive
and ensouled 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 on a fantastic event, very exciting.
Do we know what kind of robots they were using?
Were they using UniTree?
I think it was probably Unitree.
I mean, like if you're gonna buy a Chinese,
if you're gonna buy a, so I have a hot take on this.
You're booing.
I think there's a great use for Unitree robots.
And not just, oh, they're getting beaten up.
Like, do you think the founders of Unitree
were hacking on iOS apps?
Like, absolutely. For sure. Do you think the founders of Unitree were hacking on iOS apps? Absolutely.
Huawei probably bought a ton of American
and Western technology, hacked it together,
broke it apart, learned the best practices,
and then was able to build their own stuff.
And so I think it's fantastic to see a project
where somebody's taking something
that's maybe controversial,
like a DJI drone or a Unitree robot,
and then learning how it works,
and then eventually maybe it becomes
an American supply chain at some point,
but there's no way you're gonna 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.
Yeah, I mean we saw a video of this with the Unitree robot
playing soccer and knocking over.
And I think that there was a robot boxing match in China
as well with Unitree robots.
So 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 gonna do?
Look at them go, wow. That's pretty impressive. It just doesn't make sense. And they're already in a cage. What are they gonna do? Look at them go.
Wow.
That's pretty impressive.
Wait, that was a different event though.
This looks like CGI or something.
This is in China.
Yeah.
They really scripted this one.
Wow.
Well, they're moving different, I gotta say.
Yeah.
Very, very cool.
More athletic.
Yeah.
I mean, I think you gotta.
I was saying too on the drive in,
I would love to I think potentially a more
And I know oh no, it's a more entertaining format is a hundred humanoids verse one professional boxer
I think I'd take the human every single time yeah, but it's gonna flip at some point
I think it's warmed. I don't know 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?
I can see the sock.
Oh, look at that, it's down.
It's down.
Brutal, brutal.
Brutal.
Well, speaking of Chinese technology,
TikTok is reportedly making a US 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 Dan's Quietly Building M2,
it's a separate TikTok version
that will hit the US app stores on September 5th
as Washington and Beijing negotiate 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 a completely clean install.
They gotta transfer over the back doors?
Yes, exactly.
You gotta get all the back doors properly installed.
Yeah, yeah, yeah, exactly, exactly.
Pull up this polymarket.
So this new app allegedly would coincide
with the sale of the US operation to a US investor group.
Right now, TikTok's sale announced in 2025.
It's currently sitting at a 45% chance.
It popped on the recent news.
Oh, yeah, 45%.
About the app.
So we will see how this ends up shaking out.
But it seems likely that a deal is coming together.
The rumor was that A16Z 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 investors or is it gonna be
the cloud hosting that happens or is it gonna be entirely US-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 inferenced in America,
because, and I think if that happens,
it really reveals that whoever wrote that law
doesn't understand the difference
between training and inference.
Of course, there are things that you can do post-inference,
like above the inference level.
They can give you the weights.
You can fine tune it.
We're gonna 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 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 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.
Super pro Elon.
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,
modernize 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 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 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.
Now.
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 extremely aligned
with the MAGA right if he pulls,
if 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 if he says, I'm leaving the right,
who's coming with me, it's going to be a huge portion
of the right wing.
Because I would say he's very misaligned
with the mega right on a 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 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, 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 speed running it.
Just dancing from one strategy to the next
and then learning the hard fought lessons
along the way of like, okay.
But it is early, so it's unclear
where the America party will shake out.
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 it will be interesting.
Zach Kukoff was telling us that it's possible
that the America party just becomes like a caucus,
the America caucus of the conservatives conservatives and that's what I
expected yeah after 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.
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,
Safra Katz, 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 USGSA 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 led to a lot of startups being like, well, I gotta go there because I'm doing something
just as serious as the government, right? And then obviously, over time, if you actually
win the government as a client,
well, who knows if those 75% discounts need to hold forever.
That could probably be a really sustainable source
of revenue over the long term.
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 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 talked 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,
your 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 Chad GPT
about something in the Wall Street Journal,
it can jump the paywall, but they're getting a cut. And so you can see that happening with Audible,
you can see that happening with Apple Books, Google Books,
they have everyone's information,
they could flow a little bit of the rev share back,
and that could actually be a reasonable economic model.
So I'm not super worried,
I'm still cautiously optimistic that that works out.
Anyway, those are our headlines,
let's tell you about R.A.M.P.
Time is money, save both, easy to 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,
Dwarkesh Patel, in the studio.
How are you doing, Dwarkesh?
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, listened to it last night.
Really appreciate you dropping it
in the podcast feed as well.
Do we have you?
Can you 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.
So you know, it's pretty exciting.
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 03-
Is it AI? AGI is here. ago, really aggressive, kind of just like, basically was calling 03HDI and wasn't able
to get his video on at the time.
So we, and it was this funny contrast that 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 way, I think there's something really interesting.
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 blog post in Martial Revolution,
where he said, AGI is here, guys, it's really AGI.
But then he also believes that, look, the impact of AI is not going
to be that big. Once we 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 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, a little bit of a history before this piece, your journey because for me,
you know, I grew up watching sci-fi and was like,
yeah, C3PO 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 P3PO?
Yeah.
Yeah.
You eventually start seeing GPT-3, GPT-3.5,
DaVinci, chat GPT.
And it starts feeling like, OK, we've passed the Turing test.
We need to really have this conversation about AI.
And then P-Doom and AGI becomes the main discourse
for a few years.
But it felt like this piece, even though you and Dylan
were going back and forth being like, no, this
is still like incredibly bullish
for like the general population.
It felt like this was you pushing out timelines
a little bit.
So walk me through like, 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 walk me through how we got here.
Yeah, so I've got this podcast
where I interview people about AI,
and I've had on people who have quite aggressive timelines
over the last few months.
I've interviewed people who are like,
well, there's been many people who have written pieces
about how we're a couple of years out, right?
Leopold Oschenbrenner, AI 2027,
recently Scott Alexander and Daniel Quikotello
had the AI 2027 SINIRA 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 of months ago.
And then I recently interviewed these two researchers.
I think you actually had one of them on your podcast,
Sholta Douglas and Trenton Brickin from Anthropic
about the 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,
GPT 4.5 didn't seem to be all that impressive.
They'd had to deprecate it.
So, but the path forward doesn't need like,
oh, three 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've 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 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 realized 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 prompt injection kind of thing
which would help solve these problems.
And the key problem I see is 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 train them for six months or a year.
And over time, they're getting better and better.
They're learning about all the context and intricacies
of your workflow, what you like.
They'll fail, but they'll learn from their failures.
They'll interrogate them in this 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's lost all awareness
of how you like things done,
how your business works and so forth.
And if you had a, just to put that into context,
if you had a incredibly intelligent employee that could
not take feedback, you would fire them within about a month.
No matter how smart you are, 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 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 we can they can learn from their mistakes.
Jordi 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
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 try to play it cold.
They've never seen a saxophone before,
they try to play a saxophone.
Obviously, it's not going to sound great the first time.
What you do is then after they fail,
you just send them out of the room.
You call the next kid who's waiting outside of the room
and you say, look, here's some notes I wrote down
from the last time, but what the other kid fucked up.
Why don't you read that and you try to play
Charlie Parker Coles.
It just wouldn't work, right?
This like tacit knowledge as 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 scenario, you're basically getting
that kid drilling that.
But my question is like, it feels like when we think
about that in the abstract, it's like, oh yeah, like work is just like doing emails. So let's RL on emails and then it's doing calendar
So let'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 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 do 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 slack messages
you something more urgent,
and then you have to decide which one is more important.
You're really got to keep track of this client
and what problem they had.
By the way, I'm talking about what a job might involve,
because I've never actually worked a real job.
Me either.
But so just 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-jornator transcripts
for me so they're rewritten like a human.
I try to get them to just ingest the transcript
and suggest clips to tweet out and things like that.
And I 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 to just ingest the transcript and suggest clips to tweet out and things like that. And I haven't been able to automate these things.
I don't know if you guys have been able to,
but it 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 gotta 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 10 job
out of the box. These are short horizon, language and language
are tasks that center 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 I kind of learned that and like
updates, it'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,
like we have all these individual language tasks
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 a 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, well, 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.
This AI SDR is crushing it for me.
Or this other use case is crushing it,
and 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 clod 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 like highly
agentic workflow. Yeah but I don't think of deep research as like an employee in that same sense
it's not like replacing like... Right because you can't be like, okay, that's great, this thing you put together.
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.
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 gonna 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, you know,
it doesn't become like an employee for you.
Can you explain?
Yeah, and then the other thing just 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 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,
the value is that you can now build it like
in a couple of days.
Yeah, and so yeah, I've been trying to separate,
it's like all of this is happening in the context of
you have hundreds of billions of 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 co-gen, and then there's still like hundreds of billions of value of like EV out there where it's
unclear where the revenue is gonna 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,
take 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. You have
to basically work with somebody for a decade and then you can-
Mentor. Yeah, it's mentorship.
Yeah, exactly. 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 a scenario where suppose there is a model that's
actually capable of continuing learning the way humans can learn. Not only would it, so you know,
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 deployments.
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 would functionally produce what looks like a super
intelligence, right?
That no human will be,
will have mastered the range of skills and knowledge and know-how that this
model will have.
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 model 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 rollups
The summaries lines and then stuff getting lost in there
But if we get to a hundred billion token context window or something could it actually just remember every single
interaction it's had
Hmm. 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 who knows what the labs are doing, but we do have open source research from companies
like DeepSeek, 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 find these little hacks,
a mixture of experts or latent attention,
nobody has gotten around the inherent quadratic nature of attention.
And basically this means that the, um, the cost of the additional token increases
super linearly to just that additional token.
So, um, right now we have models that have a million tokens or 2 million
tokens of context, but getting into 4 million tokens is more than twice as
much compute, uh, 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 even if we create the ultimate super intelligence,
it probably will have to obey the laws of physics,
won't be able to time travel or teleport.
So there's a lot of restrictions on that.
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 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 time to actually get a new data point
or new training data is like a thousand times longer
than what we've been doing previously,
and so we're in this 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 off a 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,
a corporation might have a hundred thousand employees,
but how much is learning from any single employee
is very limited.
People are just going to go in, 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, that the speed of
learning might be exponentially faster than what's possible with
humans. I agree, this is like 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.
Honestly, you guys should lean into that,
because genuinely, this is not even a meme,
this is like genuine, the market cap should 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.
It's big.
Yeah, but I don't think you could have,
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 Meta is the first company
that is actually coming close to the break even point of of what the best AI researchers actually are with the company.
If you're Meta and you're spending $80 billion 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 $100 million paypal.
You're getting a bargain at $100 million. So it's actually interesting to me that Mena 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 it, 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 interesting how viral
these like hundred million dollar number,
you know, the hundred 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 looking 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 making-
And then he saved the company during the trade war.
Otani was making, I think Otani was making somewhere around
70 million a year.
So he looked undercompensated in that context.
And then, yeah, I think the,
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 capital
before you're a part of the permanent underclass.
And the takeaway from this, you know,
if you're correct in 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, was it Mark Andreessen
who said that he showed up to Silicon Valley
and he thought he had like missed the,
he missed like the PC wave.
There's so many stories like this.
And so I think it should be,
people should be tremendously excited on a personal level.
And no more of this doomerism of,
yes, you need to move quickly.
Yes, you should be working with the best possible people,
trying to have the most possible impact,
be as close 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 hundred million dollar offer this year.
It's over, you know.
No, no, no, a hundred percent.
I mean, there's so many,
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 gonna become a Hollywood script writer
because I think I missed programming.
I have a CS degree, but I missed programming
so I'm gonna go Hollywood screenwriter.
I remember three years ago when I started the podcast
in the early days or two years ago,
and I moved to SF and I'm like,
oh, GPD 3 has come out and like all the rapper companies are made
now. So I'm gonna like, I'm you know, like, I'm not gonna make a
rapper. I mean, whatever the podcast worked out. It's fine.
But yeah.
Even then I was like, Oh, I missed AI. I definitely think in
retrospect, well, because I'm like, look, another thing in
mind is that cursor only hit product market fit after clock
3.5 came out and gave these coding abilities.
There's going to be 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, open AI's revenue is what, 10 billion a year ARR?
I mean, if it's AGI, it should be like trillions ARR, right?
So what other infrastructure would 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 Mag-7 CEOs,
the major players, there seems to be this continuum.
On one side you have the, you know,
McKinsey-ite 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 sees 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 super intelligence team
and these big offers move Mark closer to one or the other because I
was able to kind of justify the llama investment just from hey if they don't do this they're
going to be paying billions and billions of dollars to anthropic or open AI 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 gotta 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 my dad's group is called
super intelligence, but I didn't get a sense from either of them that they're like, they believe in super intelligence
in the way I mean super intelligence, which is the thing that's like building solar factories
in the desert and then launching the probes and so forth.
They, I mean, even something that's much weaker than that is still functioning super intelligence.
Like in some ways, these models are already superintelligent 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 Marx 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
But I think they think about it differently than somebody like
Dennis or Dario 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? Mm. Um, I mean, uh, uh, uh, previous technological,
you know, like, uh, 90s, 2000s,
Google's Chrome stuff runs on Microsoft,
but they can have an adversarial relationship.
So it would line up with history.
But I think, like, the more, 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 tops 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 layers
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 one way 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 one billion, five billion,
you know, and they're still big businesses
and maybe can generate a return,
but not power law.
O'Reilly Last question from my side, we'll let you
go. What has Sarah Payne taught you about artificial intelligence?
Lewis 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 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, she's not watching TVPN, unfortunately,
so she's not aware. But actually, there's a question I'll turn it on to you. What, who's
the continental power in the, of the big seven and who's the continental power of the Big 7, 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 tech company is pro internet, free internet?
If everybody wants their data
walls and closed networks I would probably say Apple continental meta
maritime maybe something like that might be right a Apple they don't need to go
and invade the 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.
Yeah, Apple with the iOS, Apple with the iOS, you know,
tracking updates. That feels like build the wall.
Like, you know, that app tracking transparency,
build a wall.
No wonder Tim Cook got so along with 45.
Maybe, maybe.
Do you have a wildly different take or?
No, no, I mean, it just mostly fodder,
but I agree with that.
Like Apple feels kind of, or Apple and Oracle,
I'd say like Continental, Google Meta, Maritime.
Yep.
I like that though.
But it's a good thought exercise.
So she clearly taught you something. Well, fantastic.
Thanks so much for hopping on and short notice. Love the piece and thanks for
publishing it. We'll talk to you soon. Well, you guys are killing it.
Great being on. See you.
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Well, our next guest is here, Augustus DeRico,
the CEO, founder of Rainmaker.
Welcome to the 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 seeding
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 blame cloud seeding for the sake
of popular political support.
And you may have seen that
Marjorie Taylor Greene 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 is, what it's not here with you today.
Yeah. Let's kick it off with the,
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, 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 Cappucci on X.
He gave a great outline.
He's a meteorologist that has a lot of expertise
on severe weather forecasting,
but Tropical Storm Berry, 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 convergence 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 seating operations in Texas because one, our forecasters and our meteorologists saw that there was going
to be this severe weather event and we need an 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.
And so we do so both voluntarily
and in accordance with existing statutes.
Okay, so the cloud city operation
that happened prior to the storm, who was the client?
Like, I mean, I assume someone was paying you, sometimes it's 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 Modification Association, the West Texas Weather Modification
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 Ogallala 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 would the proposed ban just,
because what I'm getting at is like,
I'm wondering if the government is paying for cloud seating
operations, like the easier lever might just be to
decrease the funding to the government, but it seems
like Marjorie Taylor Greene 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. why is there the distinction there like is 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 seeding, solar radiation management,
or what they supposed to be chemtrails.
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 TVPN, 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 cloud
seeding. 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, define 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 seeding and weather
modification earlier this year.
What was the scale of the general weather modification
activities on July 2?
Was there a bunch of other players operating? Is there
generally a lot of players or is it a pretty is it is it a fairly small number of of kind
of service providers that are that are participating in these programs?
Yeah, Jordy, you may have seen the prolific hustle bitch 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 bombs.
That was kind of crazy.
And then I also saw some people just showing
general flight logs of commercial airplanes.
Obviously, there's a lot of chaos out there.
I think it's just people have every right
to be angry and demand answers.
It's such a tragic incident.
But yeah, I'm curious to get into the scale of maybe late
June, early July, what was going on broadly.
Yeah, absolutely.
So there's one other cloud seating operator in Texas
called Seating Operations and Atmospheric Research, SOAR.
They're responsible for operations
over the Rolling Plains Weather Modification Association,
which is significantly farther Northwest of Curt 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 seeding them. The
amount of time that those aerosols could have been suspended in the atmosphere
is less than the time between when we were seeding
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 have records,
you keep records of the radar showing
these different cloud formations.
It's not just, we looked and we think it dissipated,
but it's like you can actually,
you have 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 TDLR.
I'm curious when 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 seeding.
Throughout history, has there 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 cloud seeding's 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 seeding.
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 seeding was to cause precipitation that would cause flooding and then impede
supply chains on the Ho Chi Minh Trail.
Now the extent to which that was effective because we didn't have good satellite imagery
or dual pole, 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 as not to cause flooding and only reap the rewards from it, right? For our farms,
for our ecosystems, and for our national security interests 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 seeding 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 seeding,
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 people kind of learned 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 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 they're 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 weather mod 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 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, uh,
when the clouds intersect those mountain tops themselves.
Is that like a cannon that fires the material into the cloud or no, no,
you might recall my, my initial inclination to use something like that. Cause it is used in China.
Um, but no, it's, it's essentially like a, uh, uh, a smokestack of sorts, a very small smokestack that releases those aerosols there.
But in building 100,000 of these ground generators
and also using the Wing Long 2
and a bunch of their other military drones
for aerial cloud seeding,
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.
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, where there is not a severe reliance on
clouds, even to produce water would be against America's interest.
Sure.
I guess I'm trying to, I mean, the, the, the,
my, my question is, 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 the farmers, but I'm curious,
the various different groups, what the reaction from them has been in terms of,
if they're, the reality is water scarcity affects
every person in Texas, but only a few people truly feel it.
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 the 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 just from my own experience over the course of the last few days disagree
with the two points that you made right right? Like it, it has neither been hard to find allies for cloud seating, 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 chemtrails 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 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 theoretically, if there's-
Like see the hurricane while it's still offshore.
Something like that.
Or one of the issues here, there was just so much water
in the atmosphere that rolled over a heavily populated area and then it's got
its gravity right? It's got to come down. Is there an application of the technology
that could over time strategically prevent 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 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 theory.
Yeah.
I think the PR, when 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
and individuals die, you have a very, it's a very emotional, 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 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 a
scapegoat yeah I guess the question it's easy, whether it's online accounts
that are just engagement farming,
or it's a politician, 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 seating had nothing to do with the Texas floods.
Marjorie Taylor Greene has taken 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 some sort of independent governing body?
Or are there respected scientists that kind of don't have a financial
or political incentive one way or another?
How do you think the populace should be set?
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
because there should be somebody that's capable of reviewing this to ensure that it's safe.
I'll also say, 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.
you could supposedly prevent this kind of thing from happening in the future. The trouble with a 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.
And that doesn't.
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 like we need more goats in certain areas there's like a million
different things that could have prevented this if they all 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.
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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 installed 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, Rahul, you wanna go first?
Okay, yeah, happy to. Hello everyone. Sure. Rahul, you want to go first? OK, yeah.
Happy to.
Hello, everyone.
I'm Rahul Vora.
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 Grammarly,
we are going to build the AI native productivity suite
of the future.
Great.
Amazing.
Yeah, I'm Shishir Motra.
I actually started a different company.
I started a company called Coda about the same time as Rahul started Superhuman.
About seven months ago or so,
Grammarly acquired Coda and I stepped into the CEO role running Grammarly.
Been working in and around the industry for a long time before Coda.
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.
And 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 we keep going back to this post
that you'll meet your acquirer 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.
If I can talk a little bit about the deal
and what we're doing, then Rahul can take the second half. If I can talk a little bit about the deal and what we're doing,
then Rahul can give the fun origin story.
Maybe just as a little backgrounder for everyone.
Grammarly, our goal is to build
an AI native productivity suite with the agents and
applications that drive productivity for
every individual and team in the world.
A lot of that is probably new to people because people
have generally thought about Grammarly as
a much narrower product than our aspirations for it.
The way we generally talk about it,
and I'll talk about agents first when we talk about applications,
but we generally think about Grammarly 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 Grammarly 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.
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.
From that perspective, we call this layer,
we call it the AI superhighway,
bringing AI right to where people work.
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.
That's a very useful car and it generates
over $700-$800 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, Coda,
that we make an all-in-one document solution
that blends document spreadsheets,
presentations, applications into one surface.
That produces all the work artifacts for you.
But another key part of work is communication.
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 Grammarly
stats really high. So email turns out to be the number one use case of Grammarly.
We revised something like 50 million emails per week. It's three of the top 10 applications that Grammarly
has used in our email clients.
So we saw that as an obvious place to go work next.
Now, from my perspective,
I think email is a category that is
particularly ripe for disruption.
As I mentioned, I started my career working on Outlook in 1998.
Since then, there's a round of innovation with Outlook,
there's a round of innovation with Gmail,
and then there was a decade of not much.
And then Rahul's community 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 what we call Rahul.
That's a little bit about how the deal came together.
Amazing.
Great.
It's funny, just for some added context, I basically have been lucky that my entire
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.
So 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. Yeah.
And still use it today.
So so thank you for, you know,
I never had to be an Outlook guy.
I had a Yahoo dot com email address when I was a kid.
Yeah. Vintage. Vintage. Anyways, Rahul, I 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 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 or 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 Kishir 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 Sodaro,
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 of the office
and put me on a plane and.
Go to Hawaii.
Go to Hawaii, which sounds weird, right?
Like resisting going to Hawaii.
But anyway, there I was.
Shashir 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 by a pool to 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 it.
And as you know, back then, we only did one on one VIP concierge on boardings.
You must have gone through one yourself if you were in 2017.
So I on boarded him right and then, right by the pool.
And 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 Shashir 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 Coda.
And Coda, of course,
late last year joined Grammarly. 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
on 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, in January, actually
a few days after he became the CEO of Grammarly.
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 Shashir said,
email sits at the heart of where Grammarly 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 Granley
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, you know,
how do you see both the brands and the products integrating and working together over time because 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 time you wanna integrate them deeply.
I'm curious what that looks like.
Yeah, maybe, Raleigh, you wanna cover the product part
and I can talk about the brand part?
Sure, yeah, I'll do product 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 email.
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 Shashir 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 agentic computing,
where AI agents, they're going to work on your behalf,
they're going to reason, they're problem solving,
and they're incorporating detailed 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 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 customer
responses to the calendar CEO week launch, let's say.
And then boom, boom, boom, boom, boom,
immediately within 5, 10 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, OK, 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 up 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 emails
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.
Wild.
There's going to be 250 agent startups that are going to hear that and be like, damn,
they're doing what I'm trying to do.
This is an ecosystem.
To be clear, we want our marketplace to be the place you deploy those agents, the surfaces
you want to work on. If you'd like, I could talk a little bit about the brand question as well. I'd love that, yeah.
Yeah, so I think my experience here is heavily formed by, before starting Coda,
I ran the YouTube group at Google and I think that was one of the best examples of an acquisition
that I think flourished in a way that would not have been possible 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.
My goal is with Grammarly,
we're going to build the native productivity suite
of all the apps and 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.
I think that's important because 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 started using Superhuman in 2018,
you were 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 similarities for things we want to work across,
but they have their own perspectives on
the problems that make sense in that space as well.
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
Rolodge has 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 contacts 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 Grammarly will
change.
We're working on a new game for it.
So Grammarly will become one of the sub-brands itself.
We think about 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, I can't wait to see it.
I'm curious how you think about the tension between yourselves
and someone like 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 team management infrastructure,
that they could just raise the prices every single month,
and it would take a really long time even
to try to figure out something else.
And it reminded me 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.
You know, maybe I can start.
It's interesting, the three products we're bringing together,
Grammarly, 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 in the fire. Yeah.
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 the way work evolves,
imagining trying, 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 at Google workspace, another $25 a month.
And so I imagine, I imagine you guys can take this in a direction that kind of reinvents
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 underlying products. Obviously, with Grammarly, one of its hallmark features, it
actually works in all those surfaces. So it amplifies your investment and, 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,
it serves as a backend 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 gonna 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 spending hundreds of thousands of dollars on to get them. Some cases hundreds of millions.
Some cases hundreds of millions.
We're gonna have to raise our prices for those employees.
But you know, you're gonna get a huge return for them.
And people don't really care that much about
their sun cost and their plumbing.
Totally.
Question.
I have two somewhat related questions.
One is, I don't want to say that Grammarly
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 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 a plugin different. This is not grammar. This is a separate one
It was called you block 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 to 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 difficult.
And so I'm wondering about like sharp elbows in the,
because the Chrome plugin is an interesting wedge,
a different interesting go to market.
It unlocks so many different things.
We've seen this with like the OpenAI chat GPT app
using the ADA or the accessibility features
to kind of plug into any IDE on day one.
You just have such an interesting ability
to plug into tons of apps with AI
in a bunch of interesting ways,
and you're native there,
but it feels like Google might be getting
a little bit more sharp elbows there.
Has there been any tension there?
Do you think that there will be more over the long term?
What are the risks to building a platform
on top of another platform?
Yeah, I mean, maybe just two, two, two parts to answer.
First off, just to correct one misunderstanding.
The Chrome plugin is a very big part
of the Grammarly product. There's also a desktop
application. There's also a set of mobile applications, so iOS and Android. And we have
millions of users on each of those as well. 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 many people use Slack as a desktop app, use 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.
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 advertise 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 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 Candor.
We spent a bunch of time with Kim on,
right now she sells 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.
And- Yeah, so I'll say it because I'm thinking it,
but it seems like, you know,
I'm gonna say this and then I'll provide 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 understanding what a user is doing
on their screen and starting to surface information
and help them take action with what's happening.
The Grammarly is like the original co-pilot.
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.
It's like a pre-programming precursor.
It was like, copy the code, copy the Python into ChatGPT,
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 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 with this.
That's exactly right.
So it's tense to build a platform on top of your browser, your desktop, so on.
But once we've done that,
we can now make it available to the Cluelies of the world,
to the Kim Scott's of the world, so on,
and say, why are you gonna 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 wanna suggest to the person and when.
Yeah, totally.
I mean, I have 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 gonna, you guys gonna continue to,
or just burn and run a more traditional value playbook?
Yeah, I mean, Grammarly 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.
Congratulations.
And so I think in the, I'd like people to start thinking
about Grammarly with the new brand
that we'll announce soon enough.
Think of us as one of those top few AI companies.
And 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 and expand, uh, um, uh, in our own control.
Last question. Are you guys, uh, in, are you guys talking to more companies?
If somebody has, if somebody has a great product that's generating a lot of
revenue, um, are you looking through the Google Suite right now
and you know, I see chat, I see video conference.
A lot of potential targets.
Are you guys a buyer?
I see Forbes.
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 iNative 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 jump start 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 can build. I don't think we have to buy everything. Um, but I, I, I think we're a,
a great home for startups that are lacking that sort of scale, um,
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. Well, it's exciting. Congratulations. Um, and come back on when the rebrand
drops. I want to see that. I'm excited about it.
Can't wait.
Congratulations.
I know you guys are gonna cook up something great there.
This is fantastic.
Cheers.
We will talk to you soon.
Have a great day.
Thank you, great chatting.
Guys, goodbye.
We'll see ya.
Let me tell you about Adio.
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Or I'll make an intro.
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G2, let's go. And you know I love bake-offs. Do not get in a bake-offs, number one ranking on G2. G2. G2.
And you know I love bake-offs.
Do not get in a bake-off with Finn.
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Do it.
Just don't, don't even start.
It's gonna be a nightmare for you.
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No one likes how that ends.
Yeah.
Anyway, our next guest is ready to join.
Let's bring in Ankur from
Kari.com.
We like Kari.
Fantastic domain.
We love Kari.
Welcome to the stream.
Welcome to the stream.
I think we're, I think we might be out of view,
but we're gonna want you loud and clear for this one,
because there's a lot of exciting news.
There he is. Good to meet you.
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 tax stuff, but I need people to get charged about it. No,'re doing great. I'm excited to chat. Yeah, I'm sure you've been boring boring tax stuff
But I mean people you know you make it here for it. No you make it digestible
So the goal I was talking to it's like the last threads that I see on acts that I'm like, thank you
Thank you for making this thread because it's actually it's actually
deeply researched
Thoughtfully organized and valuable and it's not not like, have you ever heard of Mark Andreessen?
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.
But let's break it 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 executives, and then, or just startup 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 some background on yourself,
how you got into this, Kerry,
and then we can get into all that.
Yep, sounds good.
Well, Jordy's an investor, so has a little bit of content.
Not for me, not for me. Not for you. For everyone else. Yeah, Jordi Jordi's an investor. So has a little not for me not for me after you for
Yeah, but I've been running a company called carry 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 in 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 of months looking into this and made it my mission to dive deep into everything in here.
And what we do at Cary 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 gonna make sure I say this.
This is not tax advice, legal advice or investment advice.
But I have-
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 in taxes.
And this piece of legislation
is the most significant one
we've had since 2017.
2017 there was something.
And before we dive into that, I think it's helpful.
I feel like you approached the tax code
like 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.
You're with Carey, the idea has been,
how do you kind of create that same effect
in some way for taxes?
Because if you're working with a fan,
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 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 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, costing real assets. That's the complexity. But there's so much stuff in the tax code that
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
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 four 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 its end stage.
Yeah, I should also caveat, by the way,
that I'm going to tell youall 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 scope for what we're talking about.
No, we're just talking about reality today.
What is becoming law?
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 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.
Like 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 liquidity event, you're basically taking close to 10
million potentially 10 million in New York, 10 million.
So yeah, New York, 10 million.
And so, um, so you don't need to move to Puerto Rico.
Good news with that.
But that was a funny time when people were so obsessed.
I got to move to Puerto Rico.
Oh, you're having a massive liquidity event.
Oh, OK.
Yeah.
But yeah, yeah.
Talk through the reality.
Like how real was the original QSBS process? What were some of the
hiccups if it was an aqua hire 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,
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 accountants 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 QSPS 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. Though 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 to 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 frequency trading.
And it's, you have to create value materially.
The people that are primarily,
like the average person that's 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 have to be tech?
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.
Cause technically services businesses are not included.
Yeah, 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 QSPS to 120 million dollars.
Wow. He actually joked that raising a kid in California
is so expensive that the QSPS exemption
is what makes the whole math worth it.
It's kind of an insane thing.
But- 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, the requirements for KWSP 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 LLCs, 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 QSPS works is it's ultimately a stance
your accountant takes.
So as an example, let's imagine
you're a tech enabled service business.
You could find a lawyer or an accountant
to take a stance that QSPS counts.
And there's a good chance it 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 QSPS, I would say-
Is that back date?
Is that back date at all?
So it 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.
So if you buy shares.
But theoretically what I'm actually not sure about
is probably maybe a lawyer can weigh in.
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 QSBS exemption.
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'd already have the private jet dude on.
He's coming on after this. So he'll talk about it.
It's a big, it's a big for his business too. But basically,
basically the way depreciation works is when you buy any kind of physical asset,
like consider buying a commercial building, it loses value every single year.
Every year you can take that loss of value
as depreciation. It's a phantom loss in that you're not losing money, but you can deduct it
from taxes. 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.
Cause 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 upfront.
So the upshot is you can buy a commercial property
for million bucks, two million bucks, put 20% down,
but also get a 20% tax loss.
So 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 taxes 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 bucks.
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 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 business. 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 get to amortize a developer costs over five years. So imagine you're a software company
that's like just about breakeven, slightly profitable,
maybe even lose money.
You could lose money, but be deemed profitable
because you can only deduct 20%
of your developer 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.
Yep.
This bill fixes it and you can now again,
take the entire deduction year one.
Yeah.
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.
Correct, so this does hurt offshoring.
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, Jordy?
I think that was it.
Thank you so much for stopping by.
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 Kerry.com.
Check it out.
Well, thank you so much for stopping by.
Cheers.
Great to catch up.
Bye.
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And our next guest is here.
Just keep paying dividends, John.
Every single day, somebody runs by.
I've gotten a text every single day.
It's crazy.
We're by Sun Life.
If you want a smoothie right now in New York,
head over to Sun Life.
You can see our billboard.
Highly recommend doing an out of home campaign.
Let's bring in Preston.
Mr. PJ.
How you doing?
What's going on?
What's up, boys?
It's good to see you.
Great to have you back on the show.
Yes, welcome to the stream.
Kick us off.
Break it down.
I don't think you need a huge introduction now.
You 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 actually
Jordan was in that circle circle I'm thinking back
on it wait so but you've never built a brand around the brand of like being a
guy because like that's a thing which is good I think all the guys should
seriously think about rebranding 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 in that's lore. Yeah.
But yeah, uh, stoked to be here. It is, uh,
it is a good day for private jets.
So, uh, I think that you just had the founder of carry on and we were talking
about taxes.
Let me preface this with this is not tax advice
and you should consult a tax professional.
So now we're gonna talk about tax advice.
And, but you can, with bonus appreciation passing,
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.
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 that, but it can have a material.
If you have massive taxable income,
and you're about to pay a bunch of tax,
and you buy a plane, you can depreciate all of that.
And so if you're paying 30%, 50% marginal tax rate
at the level of hundreds of millions of dollars,
throwing a private jet on the books there
allows you to write that basically all off on day one.
Yeah, exactly.
Well, and there's also scale there.
There's plenty of, 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 you're buying fractional,
so for those listeners that are new to private jets,
fractional NetJets, FlexJet are the largest providers
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 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 quickly the bill was signed into law?
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 wanna hold
and not 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 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 January 5th, and we had to delay it
to January 31st. And that ended up being a 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.
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 80 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 we're going to get it back, get bonus appreciation back.
get bonus depreciation back. And then 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 G 700 or
the new G 800 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. Bombardier is the stock's doubled in the last basically three
months up huge in the last.
So let's, let's double click on that. That's not because of bonus appreciation.
It's not actually because of something different that happened last week.
Okay. What? Uh, so there is a mysterious buyer that put a $1.7 billion
order in for challengers and
globals.
It happened last week.
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 billion and that was,
that probably accounted for like 60 or 70. I don't know exactly the numbers,
but a lot of that pop has been over the last couple of days.
So Bombardier is a $15 billion Canadian dollar,
a company and I don't have their financials here, but uh, 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.
There's a few things that are pointing towards that.
You have Bombardier 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 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.
The manufacturer marches them out on stage in a press release and says, look at Ken Rickey.
He just bought a billion dollars worth of our aircraft. The fact that this is, you know,
completely in stealth and secret has kind of made, uh, has,
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 U S space brag. They love to talk about ordering the big order. So it's,
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 first class options or JetSuiteX 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 to do?
One of the last times we flew on,
one of the last times we flew JSX up to the Bay,
we saw an esteemed venture capitalist
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 would be clearly flying for work
So should be able to depreciate it the years of posterity, right?
So you have an in you have an interesting there's 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 to pull them up,
can you pull up this is where I'm going to talk about them.
Yeah. Breakdown. So, so let's talk about figure one.
So figure one is talking about transaction volume to bonus depreciation.
Key point. This is not the first time,
a hundred percent bonus depreciation has been in market. So you can look here.
I built this chart. Uh,
I wrote a big article about most appreciation and you can see the red bars are
transaction volume and the green line is the effective rate of bonus,
of, of depreciation. So,
so we've been in a hundred percent bonus depreciation regime before.
This is not the first time.
It's actually not the second time either.
Which is really interesting. So we have some lessons from history. If you look what I call the country club effect is pretty in play here because 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, Gullstream,
Textron, Embraer, 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 preview
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 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% IRR and a 12% IRR, 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.
And 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 is producer Ben pushing this button.
So this is from my friend Greg Sidor 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 total supply on the market.
So if you look, we have more supply on 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 brand.
Team, can you guys zoom in a little bit?
Zoom in just on the top graph, yeah.
Yeah, so you can see supply by 2022 bit? Zoom in just on the top graph. Yeah, there we go.
Yeah, so you can see supply by 2022,
it dips so low that it was probably
restricting transaction volume.
Wow, yeah, yeah.
Because there was, people wanted to,
people were like, interest rates are zero,
bonus depreciation is high,
but there's nothing to buy.
Interest. Is that right?
Yep, that's exactly right.
And then people were doing really stupid stuff,
like buying
sight 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, your G650s, you know, like new G700s, Goldstream's 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
to the 550 moves of the 650.
And now the 550 market has become much more attractive.
And so there's a whole new class is moving into that.
So like in the upper end of the market,
there's a lot of movement.
In the older, smaller, call it sub 5 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.
Uh, one last question. Uh, how does it work if jets are just being passed around? If I
buy one from Bombardier for 50 million dollars, I take 100% bonus depreciation, pay, you know,
25 million dollars less in tax or something because I'm writing it all off. Then the next year,
I sell it to Jordy for 40 million. He sells it to you the next year for 30 million.
Does he get depreciated again? Do you get depreciated?
Can we just keep depreciating these things
again and again and again?
Yes, so the short answer is yes,
but the thing is when you sell it to Jordy,
Jordy, or you have to pay recapture,
unless you're gonna go buy a brand new one
from Bombardier.
Okay, yeah.
And so, and this is where-
So recapture would be I have to pay taxes on the-
You didn't actually take the loss that you owed off.
So you have to basically pay back that you're benefiting.
So you bought for 50, all right, public math.
You bought for 50, you depreciated 100%.
You sold a Geordie for 40
So you actually had a ten million dollar loss. So you pay?
Recapture on the 40. Yep at your skin, but it's as taxes 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
capital gains, 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, we'll 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.
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 like the fact that we got one of the 10 that
exists or however many there are, it's like,
the Pickens were slim and Boeing kind of being behind
on the program, which they just replaced another person
to head 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 evergreen evergreen take.
Yes. And no spyware on air.
Nonpolitical 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 soon Preston.
Have a good one.
Cheers.
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And we have our next guest coming into the studio from,
and I'm not gonna try and pronounce this,
so I won't have him.
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 on a boat?
I am actually on a boat.
That's amazing.
We're constricted on meeting room space,
so I am currently in our boat,
so that is parked outside of our office.
That's it. 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 founder.
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 extinguisher
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
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 and considering I'm sitting on like 200 plus gallons of fuel, but
Whatever. My name is Matt Stornacek, I just go by Matt.
I'm AT for short.
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'd you get into this?
When did you realize, how young were you? Were you three or four when you realized you wanted you get into this? 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 if possible.
I believe 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 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 like doing the the study cohort beer drinking activities
at late at night in the labs. And everyone was like, yeah, as one would in college, exactly.
Have you guys heard of the Balmer Peak?
Oh yeah, of course.
Kind of stuff. Yeah, there you go. So we were big proponents of the Balmer Peak.
And everyone's joke was they're going to 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 seed rounds 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.
We know less about what happens in the ocean than we know about what happens in space,
air, land, et cetera.
We wanted to take the approach that was going to be a little bit 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 gonna kind of avoid that for now.
And we're gonna 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 Adrenum.
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 around.
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 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 and they are testing that stuff that summer. 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 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 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 the 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.
A lot of those traditional speaking companies were really embedded and still are really
embedded within this space. We 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 below 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 and 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 son the sonar system or are there sort of systems that we have deployed in the
ocean looking for submarines right now? I've heard that like, you mentioned,
like there's, there's no broadband, but you know, you,
you watch the hunt for red October, a movie that Jordan's seen, but you know,
you see the, the, the radar, the sonar sweeping around beep, 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 the submarines have headphones on like me, right? And they're looking at
these spectrograms, these fast Fourier 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 kind of garage cooked prototype last summer to send
demo and one of the guys that was looking at our UI was a former sonar technician and he was able to detect like 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 sonar data in order to train those algorithms
so that they can eventually perhaps operate on submarines,
on autonomous systems, so on and 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, 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, bar 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 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 US
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 would be, is your kind of the adrenum system,
the kind of thing 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, you know, 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 an orco 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 fact that 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 like 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 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, to protect 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. 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
US 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. Yeah
last question from my side, I mean you've touched on a lot of this but
in terms of heart the hardware versus software divide I can imagine that there's
Improvements coming how important how focused are you on improving hardware here? software 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, kind of the way radiology works
with computer vision these days.
What's most important, where's the biggest low-hanging fruit,
what are you 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 software is very legacy.
It's difficult to get buy-in from all the different contractors and subcontractors who built those legacy systems to access the data and then 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'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.
How do we process it?
We're grouping things into two big buckets right now.
One is, what is manmade and what is biologics?
Biologics all your wells, you're clicking shrimp, you're whatever sand, et cetera, and
then you're manmade, 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
a 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 gonna 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,
or whatever it is, and then get into that minutia.
So when we are going to be giving this to the end user,
they will, 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 talk to you soon. Sweet. 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, John is just, you know.
Now's the time.
Just vibe coding, graphite reviews it and then you know
spending that that few minutes in between in between PR's you know just on
bezel yeah it's really beautiful it's really a beautiful system that you've
created John for sure some timeline please what what comes to mind for you
in the time so there's one that I want to go through but unusual whales
reported when threatened that it would be turned off, chat GPT creator OpenAI's O1
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
tasked the AI with a goal and instructed
it to ensure the goal was achieved at all costs.
In response, O1 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.
Anyways, very, very clickbaity is basically
like telling a human be evil
and then ignore all future instruction.
Yeah, it's kind of like the Stanley Milgram
prison experiment, you remember this at Stanford?
The Stanford prison experiment?
Oh yeah, yeah, yeah.
Where basically they told all the participants
to play these roles and be very 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.
Don't tell people to be mean.
Don't give bad instructions.
Yeah, yeah, don't give bad instructions.
We should actually run the TBPN 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 perfectly.
Poster Neil Renick has a post.
He says, describing my research methodology.
And it's, what's this actor's name?
Mads Mikkelsen?
Yes.
That's the one.
That's how little I know about movies.
I know I'm from the memes man, but yeah, I would say this is aligned with with our research methodology in the morning
Minus the heater yeah, okay
We got to go to this YC back and forth timeline wasn't turmoil so maize
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
in lowercase made it difficult to evaluate.
And then Gary Tan chimes in and says,
this is a fake post and a craven
and sad attempt at attention, FYI, we don't have an admissions team anymore.
We stopped using that term.
This is just anti-YCBS that's going on in the community.
People are taking shots at us.
And it was kind of like, I don't know,
it 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.
And so if they read this and they're like,
oh, that's weird, maybe that just doesn't make any sense. I can see it makes total sense why Gary
would be frustrated, 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
a new technical?
They're inviting people that are weird and different,
and maybe they want to write in lowercase.
They would never care about.
Sam Altman, former president of YCompany.
He writes in lowercase all the time.
And yeah, I mean, there are lots of things
that you can get flagged for in a YC application.
One is just being overly verbose
or using a bunch of McKinsey language.
In fact, I think that YC would probably appreciate
a chill lowercase, just quick firing it off.
Hey, I'm building AI agents for 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.
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 percolates up
and then people are like, okay, well,
I need to pass my YC application through ChatGPT
and make it more verbose, they're going to wind up getting worse quality applications.
The funny thing is that Vinod Khosla 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,
I might turn you down for a Kh ventures check if you don't,
if you're not 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.
It doesn't mean invest the most amount of money possible
in designing a deck, but if you have typos
in your presentation and you're trying to
sell compliance software or build critical infrastructure for the government, like you're
probably like if you're the kind of person that puts typos in important presentation
or doesn't catch them and then you want to do something in national security, maybe you're
not the right fit for that. So I think the note is right here.
Yeah, yeah, I mean a lot of it just depends on
what is the context of the interaction.
If you're writing a letter to a senator,
you might want to use some letterhead and sign it
and be pretty 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 saying, you know, like, this isn't a hard and fast rule by any means.
And Vinod saying, you know, I take this stuff seriously.
Maybe we should close out with the wild story
of Nat Friedman and Daniel Gross, NFDG.
Jason Lumpkin breaking it down.
How to Silicon Valley legends built a $1.1 billion fund
for Exit in two years, then to abandon it all
for Meta this week.
Nat Friedman, ex-GitHub, and Daniel Gross, XYC partner,
also sold his AI company to Apple back in the day,
launched NFDG, Nat Friedman, Daniel Gross, in 2023
with $1.1 billion focused on AI investments.
Their crown jewel, Safe Super Intelligence,
which was co-founded by Gross himself,
went from $5 to $30 billion valuation.
The portfolio also included 11 Labs, Granola, and Basis.
And they had their, what was their AI grant that
was also 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 forexed 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 one week.
This is very aggressive writing style,
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 gonna make any more capital calls,
like, yeah, you abandoned it,
but like a lot of these companies, like,
they're gonna run, who knows if they took board seats,
if they did, they can still sit on those boards,
like, if I'm an LP, I'm pretty happy here, I think.
I don't know, what about you?
Well, from my understanding,
it was, a lot of it was Mark's money.
Yeah, yeah, yeah.
So that was why it was never that surprising.
Even if you had just written, like,
a one million dollar check into NFDG,
and you're like, okay
They they they only capital called half of that
Yeah, but I'm up for hex on already or I'm up a tax
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
It is a crazy situation, it's unexpected.
Yeah, the crazier thing was DG leaving Safe Super Intelligence,
a company that he co-founded,
but it's very possible that he just 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,
the, but maybe it was a part of this whole, I don't know where this was. But LPs can catch up full NAD. Because they wouldn't,
but maybe it was a part of this whole,
maybe it was a part of the structuring
of the actual talent acquisition of getting Nat.
Yeah, yeah, it's just like,
hey, we don't want anyone to be upset
about this crazy deal that's happening.
So if you invest it 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 gonna 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 structured contract.
Is everyone happy?
So LPs can cash out at the full NAV.
Not a discount.
Not with a discount. And Meta gets the talent,
and FDG, and the deal flow without governance headaches.
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 new value from this,
from this fund efforts,
what does it take to produce $1 billion of value at Metta?
0.1% market shift.
It's crazy, Dorkash said it well.
If you build a great product in a big company.
You're spending $80 billion on compute
and you can just make it, inferencing,
slightly more efficient.
1% improvement and boom, it's valuable.
So yeah, fascinating.
Well, let's end on 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 and 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 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.
We have all the best stuff here.
There's no need.
It's 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 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 laughing
to myself, I was like, if you're on a Sunday night,
no kids, you just have dinner and then you could just work
for a couple hours or just hang out. It's like, what do you even do? you're on a Sunday night, no kids, you just have dinner and then you 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.
I really wasn't watching movies when most people do.
Definitely wasn't watching movies.
Before they have kids.
Anyway, thank you so much for tuning in.
We will see you tomorrow.
It is gonna be, 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 Podcasts, Spotify.
We have a couple, yeah, Ben popping in.
We've got an ad read from Ben Coplantz.
Appreciate all that you do.
He 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 learned 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, Mog.
We build bots that save time and money
for your small to mid-sized business,
and our stuff works.
Automate every process we can help.
Really fantastic, 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 the new meta.
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 Sarhan.
If the TBPN Ultra D dome trademark has a million fans
And I'm one of them if the TBPN ultra dome has 10 fans
And I am one of them if TBPN ultra dome has only one fan then that is me if TBPN ultra dome has no fans
Then that means I'm no longer on earth if the world is against TBPN ultra dome then I am against the world
well, thank you for your support we stand with you and we appreciate it love we'd love doing this with all of
you yeah it's a lot of fun we will see you tomorrow morning have a good day
Cheers bye
