Better Offline - The Hater's Guide To The AI Bubble, Pt, 2
Episode Date: July 24, 2025In part two of this week's three-part Better Offline, Ed Zitron walks you through how little money there is in generative AI, how Anthropic and OpenAI are killing their own customers, and why there ma...y never be a profitable LLM company. YOU CAN NOW BUY BETTER OFFLINE MERCH! Go to https://cottonbureau.com/people/better-offline and use code FREE99 for free shipping on orders of $99 or more. --- LINKS: https://www.tinyurl.com/betterofflinelinks Newsletter: https://www.wheresyoured.at/ Reddit: https://www.reddit.com/r/BetterOffline/ Discord: chat.wheresyoured.at Ed's Socials: https://twitter.com/edzitron https://www.instagram.com/edzitron https://bsky.app/profile/edzitron.com https://www.threads.net/@edzitronSee omnystudio.com/listener for privacy information.
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Hello and welcome to Better Offline. I'm your host, Ed Zittron.
Subscribe to the newsletter, buy the merchandise, it's all in the notes.
And we're on the second installment of our three-part haters' guide to the AI bubble
and the cracks within the generative AI industry.
And how they're becoming bigger and scarier in the potential economic meltdown
caused by a collapse in generative AI spending.
Well, it's not really a generic AI spending.
It's literally just fucking GPUs.
And I think it might be sooner and likelyer than many think.
toward the end of the last episode, we talked about one of the inane comparisons we hear between
today's nation-state-sized spending on JNAI capital expenditures and the investments that Amazon
made when scaling Amazon Web Services, which was literally the foundation of cloud computing
at scale, I would say. Someone's going to email and say I'm wrong, not going to read it.
And I had to cut things short because we ran out of time, but I want to continue the conversation
because I think it's important to examine this comparison thoroughly, if not just to explain
why it doesn't work, it's also I want to stop hearing it. I want when people say it to me,
I just want to send him this fucking episode and say, leave me alone, buddy boy. But, but, but, but, but,
the first point I want to make in this episode is that Generative AI and large language models
do not resemble Amazon Web Services or the greater cloud compute boom, and Generative AI is not
infrastructure. Now, some people compare LLMs and their associated services to Amazon Web Services
or services, or services like Microsoft, Azure or Google Cloud, the giant multi-billion
dollar operations that basically share their server capacity with companies wanting to run stuff
on the internet or within their own systems. A very fudgy way of putting. They help make sure
that applications work online. These are very, very useful services. And by the way, people are wrong
to make the comparison between them and their own as I'll get into. And now, Amazon Web Services,
when it launched, comprised of things like, and forgive me how much I'm going to dilute this,
Amazon's Elastic Compute Cloud, EC2, where you rent space and space and
Amazon service to run applications in the cloud, or Amazon Simple Storage, S3, which is enterprise
level storage for applications. And storing things is not just like a simple hard drive. It's redundancy. It's
making sure it's copied in places. So latency comes down, tons of other things. But in simpler terms,
if you were providing a cloud-based service, you used Amazon to both store the stuff that the service
needed and the actual cloud-based processing. So compute, so like you compute loads and runs
applications, but delivered to thousands or millions of people online. And this is a huge industry.
Amazon Web Services alone brought in web revenues of over $100 billion in 2024,
and while Microsoft and Google don't break out their cloud revenues,
they're similarly large parts of their companies,
and Microsoft is used as you're in the past to patch over shoddy growth.
These services are also selling infrastructure.
You aren't just paying for compute,
but the ability to access storage and deliver services with low latency,
so users have a snappy experiences, wherever they are in the world.
And I know I just said a snappy experiences.
I'm not editing it.
The subtle magic of the internet is that it,
works at all, and a large part of that is the cloud compute infrastructure and oligopoly of the
main cloud providers having such a vast data centers. This is much cheaper than doing it yourself
into a certain point. Dropbox moved away from Amazon Web Services at scale, for example. But this
also allows someone to take care of the maintenance of the hardware and make sure it actually
gets your stuff to your customers. You also don't have to worry about spikes in usage, because
these things are usage-based, hence the elastic, and you could always add more compute to meet
demand or just have it in a particular time. There is, of course, nuance. Security-specific features,
content-specific delivery services, data-based services. There's nuance behind these clouds. You're buying
into the infrastructure of the infrastructure provider, and the reason these products are so profitable
is that, in part, you are handing off the problems and responsibility to somebody else, and also,
most web applications are not that demanding of cloud compute. They might be at scale, expensive,
to provide to millions of people, but Facebook was not a super complex, I don't know,
website depending on thousands or millions of GPUs. And based on that idea, there are multiple
product categories you can build on top of something like AWS, because ultimately cloud
services are about Amazon, Microsoft and Google running your infrastructure for you.
Large language models and their associated services are completely different, despite these
companies attempting to prove otherwise, and it starts with a very, very simple problem.
Why did any of these companies build these giant data centers and why did they fill them
full of GPUs. Amazon Web Services was created out of necessity. Amazon's infrastructure needs was so
great that it effectively had to build out the software and hardware necessary to deliver a store
that sold theoretically everything to theoretically anywhere, handling both the traffic from customers,
delivering the software that runs Amazon.com quickly and reliably, and well, making sure things
kept working, making sure they were stable. And it didn't need to come up with a reason for people
to run web applications. They were already running applications client side on their computers.
they realized that doing so at scale would be cool or they were already doing so at a way that
was likely not particularly cost-effective. And the ways they were doing so they were inflexible
and they required specialist skills and indeed physical infrastructure personnel, they were quite
expensive. So Amazon Web Services took something that people already did and what there was
actually a proven demand for and made it better and scaled it. Eventually, Google and Microsoft
copied them because that's all they can do. And that appears to be the only similarity with
Generative AI that due to the ridiculous costs of both data sentence and GPUs necessary to
provide these services, it's largely impossible for others to enter the market.
Yet after that, Generative AI feels more like a feature of cloud infrastructure rather than
the infrastructure itself.
AWS and similar megac clouds are versatile, flexible, and multifaceted. Generative AI does what
generative AI does?
Well, that's about it.
You can run lots of different things on AWS.
What are the different things you can run using large language models?
What are the different use cases?
and indeed user requirements that make this the supposed next big thing.
Perhaps the argument is that generative AI is the next AWS or similar cloud service
because you can build the next great companies on the infrastructure of others,
the models of say, open AI and Anthropic and the service of Microsoft.
Okay, okay.
Let's humor this point too.
You can build the next great AI startup and you have to build it on one of the megaclounds
because they're the only ones that can afford to build the infrastructure.
One incy, wincey, teeny, teeny, small problem.
Companies built on top of large language models don't make much money, and in fact, they're almost all deeply unprofitable.
But let's establish a few flacts to get going. I said flacts?
Flax? Jesus Christ. Facts. Here are the flacts I'm establishing.
Outside of one exception, mid-jury, which claimed it was profitable in 2022, which may not still be the case, I've actually reached out to ask them and they didn't get back to me.
Every single LLM model is, company, is unprofitable, often wildly so.
outside of OpenAI, Anthropic in Ennisphere, which makes the AI coding app cursor,
there are no large language model companies, either building models or services on top of
others models that make more than $500 million in annualized revenue, meaning month times 12.
Outside Mid-Journeys, 200 million ARR and ironclad's 150 million ARR, also fucking perplexity.
There are only 12 generative AI powered companies making $100 million annualized or $8.3 million a month in revenue.
Though the database, and this is the information's AI, generative AI database, doesn't have
Replit, which also announced it hit 100 million in annualized revenue.
I've included it in my statement of facts.
Of these companies, two of them have been acquired.
Moveworks acquired by Service Now in March 2025 after the company shit the beg big time,
and WinSurf, which was acquired by Google and Cognition in July 2025,
and one of the most annoying deals of all time.
But for the sake of simplicity, I've left out companies like surge, scale, cheering, and together,
all of whom run consultancy selling some.
services and training stuff for training models. Otherwise, there are seven companies total that
make $50 million or more annual recurring revenue, which is $4.16 million a month. Now, none of this
is to say that $100 million isn't a lot of money to you and me. I just want to be clear if you
want to give me $100 million, I'll do anything. I'll only like a pig for you. Anyway, but in the
world of Software as a Service or enterprise software, this is jump change. HubSpot add revenues
to $2.6 billion in its 24 financial year.
three years into this crap, and General of AI's highest grossing companies outside of Open AI,
10 billion annualized as of June and Anthropic, 4 billion annualized as July. Don't like saying that
word. Both of them lose billions a year after revenue. There are really three problems here.
Businesses powered by generative AI do not seem to be popular. Those businesses that are
remotely popular are deeply unprofitable, and even the less popular generative AI powered
businesses are also deeply unprofitable. But I want to start somewhere because I keep hearing about
fucking cursor.
Fucking, let's start with any sphere and cursor.
And their app, cursor, it's an AI-powered coding app, and they have $500 million of
annualized revenue.
Pretty great, right, huh?
It hit $200 million in annualized revenue in March and then hit $500 million in June after
raising $900 million.
That's amazing.
Ed, Ed, it's time.
Walk to the garage, Ed, it's over for you.
Wrong.
It's a mirage.
Curser's growth was a result of an unstable.
business model that it's now had to replace with opaque terms of service, dramatically restricting
access to models and rate limits that effectively stop its users using the product at the price
point they were used to. Go to R-slash cursor on Reddit. Take a look. Take a look at how happy
everyone I is. I want to know why my peers in the media don't seem to have the ability to talk
to actual fucking customers. It's ridiculous. This company is circling the drain and nobody seems to
want to talk about it, despite how big a deal that is. Oh, also, curses is horribly unprofitable,
and I believe they're a sign of things to come in generative AI.
A couple of weeks ago, I wrote up the dramatic changes that cursor made to its service
in the middle of June on my premium newsletter and discovered that they timed these changes
precisely with Anthropic and Open AI to a lesser extent, adding service tiers and priority processing,
which is tech language for, pay us extra if you have a lot of customers or face rate limits or service delays,
asshole. These price ships have also led to companies like Replip,
having to make significant changes to their pricing model that disfavors users.
people are finding in really simple terms that what they used to get for 20 bucks is much, much, much, much, much smaller.
Cursor users hit rate limits.
Replit users are hitting rate limits and even them when they try and do the same things,
they're spending way more money if they go pay as you go.
It's a complete fast.
But I'm going to repeat some of the stuff from the premium newsletter because there is a time of events
that I believe are going to be in the big short two AI boogaloo, all right?
In around May 5, 2025, cursor closed the $900 million.
dollar funding round. In around May 22nd, 2025, Anthropic launched Claude, four opus and Sonet,
new models with Sonnet and Opus, both them kind of well known for coding. And on May 30th,
2025, they added service tiers, including priority pricing specifically focused on cash-heavy products
like cursor. And the cash is when you put stuff that you're going to be looking at regularly,
take a look at it, and you can use it more readily. Cash is generally, the C-A-C-H-E, by the way,
is generally something that's for efficiency. The idea that you would add a toll
onto the cash is fucking disgusting and only targeted at coding startups. But on May 30th,
2025, Reuters reported that Anthropics annualized revenue hit $3 billion, with a key driver being
code generation. This translates to around $250 million in monthly revenue. June 9th, 2025
CNBC reported OpenAI had hit $10 billion in annualized revenue. And yeah, when they said annual recurring
revenue, they meant annualized. But the very same day, they cut the price of their 03 model by 80%, which
competes directly with Claude Four Opus, by the way. And this was a direct and aggressive
attempt to force Anthropic to kind of like make two other lower prices or compete. It's just
shitheads fucking going around with assholes. But on around June 16, 2025,
curse of changed its pricing, adding a new $200 a month ultra tier that, in their own words,
was made possible by multi-year partnerships of Open AI, Anthropic, Google and XAI,
which translates to multi-year commitments to spend, which can be amortized as monthly amounts.
A day later on June 17th, Cursor dramatically changed its offering to a for its $20 a month subscriptions to usage-based,
where one got at least the value of their subscription, so a $20 a month person would get more than $20 of API calls.
In compute, along with arbitrary rate limits and unlimited access to Cursor's own slow model that its user's hate.
Then on June 18, Replit, another VibeCode and company that I previously mentioned, announced their effort-based pricing increases that were massive.
July 1st, the information report at the Anthropic hit $4 billion of annualized revenue,
making $330 million a month, an increase of $83 million a month,
were just under 25% in the space of a month.
Hmm, where could that money have come from?
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In simpler terms, Cursor raised $900 million and very likely had to hand large amounts of that money over to open AI and Anthropic to keep doing business with them,
then immediately changed the terms of service to make them worse with their customers.
said at the time, and this is a direct quote from my news letter.
Well, some may...
No, I can't do the Kevin Ruse voice and doing my own stuff.
Pardon me.
While some may believe that Open AI and Anthropic hitting annualized revenue milestones
is good news, you have to consider how these milestones were hit.
Based on my reporting, I believe that both companies are effectively doing steroids,
forcing massive infrastructural costs onto big customers as a means of covering the increasing
costs of their own models.
There is simply no other rate to read this situation.
By making these changes, Anthropics is intentionally making it harder for its
larger customer, largest customer to do business. By the way, Curser is their largest customer,
creating extra revenue by making Cursor's product worse by proxy. What's sickening about this
particular situation, it doesn't really matter if Cursor's customers are happy or sad. They, like
OpenAI's Enterprise Priority Access API, Anthropic in this case, require a long-term
commitment which involves a minimum throughput of tokens per second as part of their tiered access
program. If Curses customers drop off, both Anthropic and Open AI still get their cut. And if
Cursor's customers somehow outspend those commitments. They'll either still get rate limited,
or anisphere will concur more costs. Why do you care about this? Well, Cursor is the largest and most
successful genetic AI company by far, and these aggressive and desperate changes to its products
suggest that A, that its products are deeply unprofitable, and B, that its current growth was a result
of offering a product that was not the one it would sell in the long term. Cursor misled its
customers, and its current revenue is, as a result, highly unlikely to stay at this level. Worse still,
two Anthropic engineers left from the Claude Code team to go and work at Cursor two weeks ago,
and they have already come back. This heavily suggests that whatever they saw over there
wasn't compelling enough to make them stay. As I also said, while Cursor may have raised $900 million,
it was really Open A.I Anthropic XAI and Google that got that money. At this point,
there are no profitable enterprise AI startups, and it's highly unlikely that the new pricing
models by both Cursor and Reply are going to help. These are now the new terms of doing business
with the big model companies, a shakedown, where you pay for priority access or tiers or face
indeterminate delays or rate limits. Any startup scaling into an enterprise integration of
AI, which means in this case anything that requires a level of service uptime, has to commit to
both a minimum amount of months and a throughput of tokens, which means that the price of starting
an AI company that gets any kind of real market traction just dramatically increased. Well, one could
say, oh, perhaps you don't need priority access. The need here is something that can be entirely
judged by Anthropic and Open AI in a totally opaque manner.
They can and they will throttle companies that are too demanding on their systems
as proven by the fact that they've done this to Curse them multiple times.
But okay, why does Curse them out so much?
And it's simple.
Generative AI will not get big on selling consumer software.
Without an enterprise SaaS story, they're dead.
And I realize, I know, okay, folks,
it's kind of a little boring hearing about software as a service,
despite the fact that it's a huge several hundred billion dollar industry.
But this is the only place where generative AI can really make money.
Companies buying hundreds of thousands of seats are how industries that rely on compute grow.
And without that growth, they're going nowhere.
To give you some context, Netflix makes about $39 billion a year in subscription revenue from consumers and Spotify about $18 billion.
These are the single most popular consumer software subscriptions in the world.
And OpenAI's 15.5 million subscribers suggest that OpenAI can't rely on them for the
the kind of growth that would actually make the company worth $300 billion, or more.
Curza, as it stands, is the one example of a company thriving using generative AI,
a software company selling software, and it appears its rapid growth was the result of selling
a product at a massive loss. As it stands today, Cursor's product is significantly worse,
and its Reddit is full of people furious at the company for the changes.
In simpler terms, Cursor was the company that people mentioned to prove that startups could make
money by building on top products on top of open AI and Anthropics models.
yet the truth is the only way to do so is to grow and grow is to burn tons of money.
While the tempting argument is to say that curses customers are addicted and will keep paying,
this is clearly not the case, nor is it an actual business model.
Like people that say this, I have never had a drug addiction, but I know people that do,
it's nothing like software.
Stop making that comparison.
It's insulting to the victims of addiction.
But anyway, this story showed that Open AI and Anthropics are actually the biggest threats to their customers,
and will actively rent-seek and punish any of their success stories,
looking to loot as much as they can from them before they copy their products.
To put it bluntly, because this growth story was a fucking lie.
It reached $500 million in annualized revenue selling a product
it can no longer afford to sell and could not afford to sell long term,
suggesting material weakness in its business and any and all coding startups.
It's also remarkable and a shocking failure of journalism
that this isn't in every single article about any spare.
I'm doing this part-time.
Why am I the asshole?
here. Like, I'm, I don't know. But really, though, I do have a question. Where are all the consumer
AI startups? I'm genuinely serious. What have you got for me? Poplexity? Poplexity.
Butplexity only has $150 million in annualized revenue, and they spent 167% of their revenue
in 2024 or $57 million of spending on revenues of $34 million on compute services from
Anthropic, Open AI, and Amazon. They lost $68 million. And we're staying.
they still have no path to profitability. And it's not even making anything new. They're a search
engine. They have an AI browser. But don't worry, professional gasbag Alex Heath just did this insane
and flummoxing interview with CEO Aravince Ravinas, who, when asked how it perplexity would become
profitable, appeared to experience what seems to be a stroke. I'm about to read something to you,
and it's going to sound strange. But this is exactly what was said. Maybe let me give you another
example. You want to put an ad on meta, Instagram, and you want to look at ads done by similar brands.
Pull that, study that, or look at AdWords pricing of 100 different keywords and figure out how to
price your thing competitively. These are tasks that could definitely save you hours and hours and maybe
even give you an arbitrage over what you could do yourself because AI is able to do a lot more.
And at scale, if it helps you to make a few million bucks, does it not make sense to spend
$2,000 for that prompt? It does, right? So I think we're going to be able to monetize in many more
interesting ways than chatbots for the browser. I want to be fucking clear about
something. Alex Heath seems like a nice guy. If someone said that to me, I'd ask them if they could
smell toast. I'd be like, Aravind, mate, are you okay? How many fingers am I holding up Aravind?
You were right. Did you hit your head on something? The ceilings don't seem that low in here,
but mate, you're just spewing utter fucking nonsense. I've read this paragraph multiple times.
I do not know what he's getting at. I think he's suggesting something about how you could
ask it to tell you what to do with ads. I don't know. I don't know. I don't. I don't. I don't.
don't know. This is the big, probably the biggest consumer AI company that isn't open AI, and they
speak like they're an insane person. Or a stupid person. Check out the business idiot trilogy for what I
think there. I also mentioned them earlier, but I don't, I don't want you to talk to me about
AI browsers. Anyone humoring AI browsers is being an imbecile for some reason. They are not
a business model. How are people going to make money on the browser? What do these products actually do?
Oh, they can poorly automate accepting LinkedIn invites. Wow. Wow, it's like God himself has personally
best my computer. Big fucking deal. In any case, it doesn't seem like you can really build a consumer
AI startup that makes any real money or approach being a real company other than chat GPT, I guess.
And that's because the generative AI software market is small with little room for growth and no profits to be seen.
arguably the biggest sign that things are troubling in the generative AI space is that we use the term annualized revenue at all,
which, as I've mentioned repeatedly, means multiplying a month by 12 and saying, that's our annualized baby.
The problem with this number is that, well, people cancel things.
While your June might look great, if 10% of your subscribers churn in a bad month, due to a change in your terms of service, for example,
that's a huge chunk of your annualized revenue gone and likely gone forever.
But the worst sign is that nobody is saying the monthly figures, mostly because the monthly figures fucking
suck. A hundred million dollars of annualized revenue is $8.33 million a month. To give you some scale,
Amazon Web Services hit $189 million, $15.75 million a month in revenue in 2008, two years after
founding. And while it took until 2015 to hit profitability, it actually hit break even in 2009,
though it invested in cash in growth for a few years later. And I should be clear,
them doing that justified so many startups burning cash. So many startups like, yeah, look at AWS,
they were investing in growth, which is a fair thing for.
companies to do, but I'm being an asshole. But right now, there is not a single generative AI
software company that's profitable, and none of them are showing the signs of the kind of hypergrowth
that previous big software companies had. Well, Cursor technically is the fastest growing software
as a service company of all time. It got there by basically lying. Curser is never bringing
back the product at the $20 price point that they were selling. They're never doing it. The money they
earned was earned. It's not fraud because they didn't do it. Deceptive. I guess it was deceptive,
but it's not really to the... It's just fucking lying. It's just lying. And who knows what happens to
the cursor now. But you know what? I'm harping on cursor a bit. What other software startups are
there? Glean? Gleen! Fucking Gleen. Everyone loves to talk about enterprise search company Gleen,
a company that uses AI to search and generate answers from your company's files and documents.
Fun fact, also, Salesforce, which own Slack has now blocked them from searching.
slack, just asshole on arsehole violence. In December 2024, Glein raised $260 million, proudly
stating that it had over $550 million in cash with best in class ARR growth. A few months later in February
2025, Glein announced it it achieved $100 million in annual recurring revenue in fourth quarter,
FY25, cementing its position is one of the fastest growing SaaS startups and reflecting a surging
demand for AI-powered workplace intelligence. In any case, ARR could literally mean anything, as it appears to be based
on quarters, meaning it could be an average of the last three months, I guess. Anyway, in June
2025, Gleyn announced it it had raised another funding round, this time raising $150 million in it.
Troublingly added that since its last round, it had surpassed $100 million in ARA.
Five months into the fucking year and your revenue is basically the same. That isn't good. That
isn't good at all. Also, what happened to that $550 million in cash? Why did Glein need more?
Hey, wait a second, take a look at this.
announced their raise on June 18th, 2025, two days after Cursor's price increase in the same day
that Repplet announced the similar price hike. It's almost as if the dramatic pricing increase
has affected them due to the introduction of Anthropic Service tears and Open AI's priority
processing, but I'm guessing. I know I'm guessing, but it is kind of weird that all of these
companies raise money and all announce these things around the same time.
Another podcast from some SNL late night comedy guy, not quite. Unhumor me with Robert Smygel
and friends. Me and hilarious guests from Jim Gaget.
African, to Bob Odenkirk, to David Letterman, help make you funnier.
This week, my guest, SNL's Mikey Day and headwriter, Streeter Seidel, help an
a cappella band with their between songs banter.
There's that worst singer in the group?
The worst?
Yeah.
Me.
Is there anything to the idea that because you're from Harvard, you only got in because
your parents made a huge donation.
The group.
The yard birds, right?
That's the name.
The Harvard Yard.
But they're open to change.
suggestion. We're open. Since you guys are middle-aged, one erection.
Listen to humor me with Robert Smigel and Friends on the IHeart Radio app, Apple Podcasts, or wherever you get your podcast.
Humor me. I need some jokes to make me seem funny. Run a business and not thinking about podcasting, think again.
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Will Ferrell's Big Money Players and IHart Podcast presents soccer moms.
So I'm Leanne.
Yeah.
This is my best friend, Janet.
Hey.
And we have been joining.
at the hips since high school.
Absolutely.
Now a redacted amount of years later,
we're still joined at the hip.
Just a little bit bigger hips,
wider.
This is a podcast.
We're recording it as we tailgate
our youth soccer games
in the back of my Honda Odyssey
with all the snacks and drink.
Sidebar.
Why did you get hard seltzer instead of beer?
They had a bogo.
Well, then you got it.
Do you want a white claw or something here?
Just take it.
What are y'all doing?
Microphones?
Are you making a rap album?
I would.
Come on.
How did you imagine?
I would buy it.
Cuts through the.
defense like a hot knife through sponge cake.
That sounds delicious.
Oh, you're lucky. I'm not a drug addict.
You're lucky I'm not an alcoholic.
You're lucky I'm not a killer.
I love this team and I'm really trying to be a figure in their lives that they can rely on.
Oh.
Listen to soccer moms on the IHeart Radio app, Apple Podcasts, or wherever you get your podcasts.
Hey, I'm Deanna Maria Riva, actress, mother, lover, and a Jenna
woman walking through life one hot flash and hormonal crying jag at a time. You ladies know what I mean.
I'll bet you a perimenopausal chin here you do. So let's talk about it. Join me on my new podcast. How
Hard Can it be with the Adamani Arriba where I call on my Gen X squads from Ohio to Hollywood as we
navigate midlife's most fantastic BS. All of a sudden I'd had hanginess happening on my own.
I was like, what the hell is that? I was married when I had her. So I didn't even consider how empty
that nest is going to be.
Mood swings, night sweats,
fupas, sex drive.
Wait, what sex?
Dating at 45.
How hard can it be?
Getting naked at 50 with the new guy.
That one's kind of hard.
Well, that's lighting.
They say we can't polish a turd,
but we're sure going to try.
So let's get blunt with laughs,
tears, or tears of laughter,
and dive into it,
unfiltered and unbothered
and ask, how hard can it be?
I cannot believe I'm about to say this out loud in public.
Listen to how hard can it be
with Diana Maria Riva
as part of my Cultura podcast,
network available on the IHeart Radio app, Apple Podcasts, or wherever you get your podcasts.
Hey, that reminds me. I got another problem. I got another problem here, because I think that
there is another reason why the cycles kind of keep repeat and you get a company of the grows
and then they kind of go nowhere because, well, the company doesn't really seem to have a total
addressable market much bigger than 100 million ARR. And I think it's made a little simple.
It's quite simple. In fact, there really are no unique generative AI company.
and building a moat on top of LLMs is near impossible.
If you look, and man am I going to get some emails about this, but bring them on.
If you look at what generative AI companies do, the following is not a quality barometer,
it's probably one of the following things.
There are the chat bot, one either you ask questions or talk to,
this includes customer service bots,
searching, summarizing, or comparing documents with increased amounts of complexity of documents
or quantity of documents to be compared.
This includes being able to ask questions of documents.
Websearch, deep research, meaning long-form web search that generates a document where some parts
of it will inevitably be hallucinated or derived from low-quality sources, generating text, images, voice,
or in some rare cases video, using AI to generate of AI, I mean, to write, edit, or maintain code,
transcription, translation, or photo and video editing.
Every single generative AI company that isn't open AI or anthropic, and honestly, kind of those two,
does one or a few of these things, and I mean every one of them, and it's because every single
generative AI company uses large language models, which have inherent limits on what they can do.
LLMs can generate, they can search, they can kind of edit, they can sometimes transcribe accurately,
and they can sometimes translate, much more, well, much less accurately, I guess.
Within weeks of cursors change to its services, Amazon and Bightdance release competitors,
that for the most part do exactly the same thing. Sure, there's a few differences in how
they're designed, but design is not a moat, especially in a high-cost, negative profit business.
where your only way of growing is to offer a product you can't sustain.
The only other moat you can build is the services you provide,
which when your services are dependent on a large language model,
are dependent on the model developer,
who, in the case of OpenAI and Anthropic,
could simply clone your startup,
because the only valuable intellectual property is the models,
and those models are theirs.
You may say, well, nobody else has any ideas either,
to which I say I fully agree.
My rock-com bubble thesis suggests that we're all out of hypergrowth ideas,
and yeah, I think we're out of ideas related to any large language model,
too. At this point, I think it's fair to ask. Are there any good businesses you can build on top of
generative AI or large language models? I don't mean add features related to. I mean an AI company that
actually sells a product that people buy at scale that isn't called chat GPT or Claude. In previous
tech booms, companies would make their own models, their own infrastructure or the things that
make them distinct from other companies. But the generative AI boom effectively changes that by making
everybody built on stuff on top of somebody else's models. Because training your own model,
is both extremely expensive and requires vast amounts of infrastructure and just pure power.
As a result, much of this boom is about a few companies, really, too, if we're honest,
getting other companies to try and build functional software for them.
And these companies, OpenA.I. and Anthropic are their customers' weak point,
in a relationship that veers from symbiotic to parasitic at a moment's notice.
I cannot stress enough how bad Open AI and Anthropic are for their business customers.
Their models are popular, by which I mean their customers' customers will expect access to them,
meaning that Open AI and Anthropic can, as they did to cursor,
arbitrarily changed pricing, service availability and functionality based on how they feel
that they or whether they need to pump their annualized revenue for investors.
Don't believe me?
Anthropic cut off access to AI coding platform WimSurf because it looked like they might get acquired by OpenAI.
They never were.
They just harmed that business.
They just cut a hole in them.
Why?
Because they might touch another business.
The most anti-competitive shit in the world and everyone sat there clapping like a fucking
seal. Disgusting. Even by big tech standards, this fucking sucks, and these companies will do it again.
But you know what? Let's talk about the actual uses of generative AI, because the limited
number of use cases are because large language models are all really, really similar.
Because all large language models require more data than anyone has ever needed, including
like four times the amount of data on the internet, they all basically have to use the same
thing, either taken from the internet or bought from one of the few companies like scale, surge,
during, together, or whoever. While they can get customized,
data or do customized training and reinforcement learning, these models are all transformer-based
and they all function similarly. And the only way to make them different is by training them,
which doesn't make them that much different, just better things they already do. And good Lord,
is it so, is generative AI so ungodly expensive. And the training is as well, by the way.
They have to pay real humans as well, which they hate doing. And even when they're paying
outsource labor in Kenya at $2 a pop, they're still losing a ton of money. It's really crazy,
actually how badly built all of this is. And I already mentioned Open AI and Anthropics costs,
as well as perplexed these $50 million bill in a year to Anthropic Amazon and Open AI off of a measly $34 million
in revenue. These companies cost too much to run, and their functionality doesn't make enough money
to make them make sense. And the problem isn't just the pricing, but how unpredictable it is.
As Mattershare wrote for CIO dive last year, Generative AI makes a lot of companies' lives
difficult through the massive spikes in costs that come from their power users, with few
ways to mitigate those costs. One of the ways that company manages their cloud bills is by having
some degree of predictability, which is difficult to do with the constant slew of new models
and demands for new products to go with them, especially when said models can and do often
cost more with subsequent iterations, not necessarily for much return, except if you're a company
like a coding company, your customers are going to actually ask you for the new models.
As a result, it's half for AI companies to actually budget. But Ed. What's that? Ed. What's that? Ed.
What about agents? Aren't they the thing that will eventually make the insane broken calculus behind generative AI actually work? What is your accent made?
Anyway, let me tell you about agents. The term agent is one of the most egregious acts of fraud I've seen in my entire career writing about this crap, and that includes the metaverse.
When you hear the word agent, you were meant to think of an autonomous AI that can go and do stuff without oversight, replacing someone's job in the process, and companies have been pushing the boundaries of good taste and financial,
crimes in pursuit of them. Most egregious of them is Salesforce's agent force, which lets you deploy
AI agents at scale. That's a quote, and brings digital labor to every employee department and
business process. Another quote from Salesforce's website. These are two blatant fucking lies. Agent
Force is a goddamn chatbot program. It's a platform for launching chatbots. They can sometimes
plug into APIs that allow them to access other information, but they're neither autonomous
not agents by any reasonable definition. Not only does Salesforce not actually sell agents,
its own research shows that the agents and agents in general only achieve around 58% success rate
on single-step tasks. And I'm going to quote the register here. This means tasks that can be
completed in a single-step without needing follow-up actions and more information. Or multi-step
tasks, so you know most tasks, they succeed a depressing 35% at the time. Last week, OpenAI announced its own
chat GPT agent that can allegedly go and do tasks on a virtual computer. In its own demo, the agent
took 21 minutes or so to spit out a plan for a wedding with destinations of eight calendar and some suit
options and then showed a pre-prepared demo of the agent preparing an itinerary of how to visit
every major league ballpark that's baseball for the non-Americans out there. In this example's case,
agent took 23 minutes and produced arguably the most confusing map I've seen in my life. You can see
the map in the newsletter version of this episode. It's hilarious. It missed out every single major
ballpark on the east coast, including Yankee Stadium and Fenway Park, which are two of the most
well-known stadiums in sports, and added a bunch of random ones and one in the middle of the Gulf of
Mexico. What team is that, Sammy? The Deepwater Horizon Devils. Is there a baseball team in
North Dakota? Clammy, Sammy! Sammy! I also should be clear this was a pre-prepared example.
This is the best they had. I want to see the cutting room footage on this, because you best bet
that that map looked like straight dog shear.
As with every large language model product,
and yes, that's what this is,
even if Open AI won't talk about what model.
Results are extremely variable.
Agents are difficult because tasks are difficult,
even if they can be completed by a human being
that the CEO thinks is stupid.
What Open AI appears to be doing is using a virtual machine
to run scripts that its models trigger.
Regardless of how well it works,
and it works very, very, very, very poorly and inconsistently,
it's also very likely expensive to run.
In any case, every single company you see using the word agent is trying to mislead you.
They're lying.
Gleans AI agents to chatbots with if this, then, that functions that trigger events using APIs,
which means if an event happens, another thing will be triggered.
Not taking actual actions because that is not what LLMs can do.
ServiceNow's AI agents that allegedly act autonomously and proactively on your behalf are,
despite claiming they go beyond better chatbots, still ultimately better chatbots,
that use APIs to trigger different events using if this, then that functions.
Sometimes these chatbox can also answer questions that people might have or trigger an event
somewhere.
Oh, right, that's literally the same thing.
The closest we have to an agent is any kind of coding agent, which is they can make a list of
things that you might do on a software project and go and generate code and push stuff
to GitHub when you ask them to.
And they can do so autonomously in the sense that you can just let them do what a model that
doesn't know anything and has no consciousness thinks is.
is right based on its corpus of data and the things you give it access to. And it's about as safe
as that sounds. When I say ask them to and go and I mean that these agents are not intelligent
at all. They do not have intelligence. And when let run rampant fuck up everything and create a bunch
of extra work, also a study found that AI coding tools made engineers 19% slower. Nevertheless,
none of these products are autonomous agents. Anybody using the term agent likely means chatbot.
And all of this is working because the media keeps repeating everything these companies.
say, it's a disgrace. We need to stop this. I realize we've taken a kind of a scenic route here,
though, but I needed to lay the groundwork because I really am alarmed. According to a UBS report from
the 26th of June, the public companies running AI services are making absolutely pathetic amounts of
money from AI. Microsoft, according to UBS, is making annual revenues of somehow less than the
information reported at $2.1 billion. Service now is making less than $250 million. Adobe, less than $125 million.
sales force less than a hundred million.
Now, Service now said $250 million ACV, annual contract value.
This may be one of the more honest explanations of revenue I've seen,
putting them in the upper echelons of AI revenue,
unless, of course, you think about it for a couple seconds,
and think, are these all AI-specific contracts?
Or perhaps they're in contracts where you've taped AI onto the side.
Ah, it gives a shit.
It's also year-long agreements that could churn,
and according to Gartner, over 40% of A genetic AI products will be cancelled by end of
2027. And really, you've got to laugh at Adobe and Salesforce, both of whom to talk such a goddamn
fuck ton about generative AI, and yet have only made a measly $1,125 million in analyzed revenue
from it. Pathetic! Crap! Dog shit! These aren't futuristic numbers. They're barely product
categories, and none of this seems to include costs. Oh, well, good grief. Look, a lot of what I've been
saying is reminiscent of the previous podcast, and I've gone over this a lot, because I really want to
make it clear that the signs are very troubling and that the things I've warned you about
for the past couple of years are only getting worse and the cliff's coming up. Things are
only getting closer and when we tumble off of it, things may get really, really bad and in the
next episode we'll talk about how and what that tumble might look like and the noises I'm going
to make when it happens. Thank you for listening to Better Offline. The editor and composer of the
Better Offline theme song is Mattersowski. You can check out more of his music and audio projects
at Matasowski.com,
M-A-T-T-O-S-O-S-K-I-com.
You can email me at E-Z at Better Offline.com
or visit Better Offline.com to find more podcast links
and, of course, my newsletter.
I also really recommend you go to chat.
Where's your ed dot at to visit the Discord
and go to R-S-Better-O-Line to check out our Reddit.
Thank you so much for listening.
Better Offline is a production of CoolZone Media.
For more from Cool Zone Media,
visit our website, Coolzonemedia.com, or check us out on the IHeartRadio app, Apple Podcasts, or wherever you get your podcast.
Another podcast from some SNL, late-night comedy guy, not quite.
Unhumor me with Robert Smigel and friends.
Me and hilarious guests from Bob Odenkirk to David Letterman help make you funnier.
This week, my guest, SNL's Mikey Day and head writer Streeter Seidel, help an acapella band with their between songs banter.
Where does your group perform?
We do some retirement homes.
People are starving for banter.
Listen to humor me with Robert Smigel and Friends on the IHeart Radio app, Apple Podcasts, or wherever you get your podcasts.
Why are we all so obsessed with romance?
On the Radio 831 podcast, join us, Sanjana Basker and Tyler McCall, as we unpack all the trending tropes,
fuzzy adaptations, book talk drama, and celebrity love stories with hot takes and sharp guests.
Each episode digs into what these stories reveal about desire, fantasy, identity,
and how we love now.
Listen to the Radio 831 podcast on the IHeart Radio app,
Apple Podcasts, or wherever you get your podcasts.
Will Ferrell's Big Money Players and IHeart Podcasts presents soccer moms.
So I'm Leanne.
Yeah.
This is my best friend, Janet.
Hey.
And we have been joined at the hips since high school.
Absolutely.
A redacted amount of years later, we're still joined at the hip.
Just a little bit bigger hips.
This is a podcast.
We're recording it as we tailgate our youth soccer games in the back of my Honda Odyssey.
with all the snacks and drinks.
Why did you get hard seltzer instead of beer?
They hit a Bogo.
Well, then you got them.
Listen to Soccer Moms on the IHeart Radio app, Apple Podcasts, or wherever you get your podcasts.
American Soccer is about to explode.
The World Cup is coming.
Ramos sending on to Ernie Stewart the chip.
Score!
I'm Tav Ramos.
I'm Tom Boca.
On our podcast, inside American soccer, you'll get the real storylines, the biggest decisions.
and the truth about the U.S. national team.
It wouldn't be a huge surprise if our team ends up in the quarterfinals
or potentially a great run into the semifinals.
Listen, Inside American Soccer with Tom Bogart and Tabramos
on the IHeart Radio app, Apple Podcasts, wherever you get your podcast.
This is an IHeart podcast, guaranteed human.
