This Doomsday Article Is Causing Investor Panic

It seems as though every day we wake up to the market going down and a new viral article that's being passed around speaking doomsday of SAS companies and the world as we know it. Now, we've seen

this happen before with articles like big things are happening, right? There's

ones about big changes and disruptions in technology companies. We've also seen ones that are essentially the doom of SAS companies. That's caused a lot of

SAS companies. That's caused a lot of companies that we know and are invested in to go down dramatically every single day. And there's more and more of these

day. And there's more and more of these articles. Again, every single day it

articles. Again, every single day it seems like there's just two or three more of them that are going viral around X, around social circles, around investment circles. But the one that was

investment circles. But the one that was shared over the weekend is perhaps the final boss. It's like a video game.

final boss. It's like a video game.

You're getting to the end. You've gotten

through all the smaller bosses, all the bigger challenges and hurdles along the way, and now we're facing the final boss. This is Citroen Research. Why is

boss. This is Citroen Research. Why is

Citroen Research the final boss? Well,

because out of all the hundreds and thousands of different Substacks out there, out of all the ones that you can read, all the different financial authors giving takes and thesises,

there's one that's listened to and paid attention to more than any others. That

is Citrony, the top selling financial substack in the world. It's based on macro. It's based on large events, big

macro. It's based on large events, big takes. Investors listen to it. Hedge

takes. Investors listen to it. Hedge

fund managers listen to it. Thousands of

investors subscribe to this and pay good money to hear their takes. It's so

influential that their takes routinely land on Bloomberg. They land on the Wall Street Journal. And what they wrote over

Street Journal. And what they wrote over the weekend is no exception. It is now on the front page of the Wall Street Journal. This viral doomsday report lays

Journal. This viral doomsday report lays bare Wall Street's deep anxiety about the AI future. Citriny research thought experiment rattles investors already

wary of tech disruptions. That's right.

No, this is not a article that's on some obscure forums on the internet. This is

mainstream. This is all over CNBC, Bloomberg, the Wall Street Journal, the Financial Times. Citrony's article went

Financial Times. Citrony's article went hyper viral and it caused many of the most powerful, biggest companies in the world, their stocks to get crushed. Door

Dash is down like 7% on the day.

American Express, it's down big, 3% plus. We have Blackstone going down. We

plus. We have Blackstone going down. We

have Visa and Mastercard, two companies that you think are a little bit more resilient. Yeah, those ones went down as

resilient. Yeah, those ones went down as well. This article is impacting

well. This article is impacting investors thoughts. It's impacting their

investors thoughts. It's impacting their decisions. Investors are human and

decisions. Investors are human and they're selling as a result of this.

Now, I didn't think I was going to spend all of 2026 reacting to viral articles online, but here we are. This is what we're doing, and this is what I'm going

to be doing in this episode. We'll be

going over the thesis of Citrory, why it is so engrossing, why investors have so much anxiety about what they're talking about. We'll be reviewing their

about. We'll be reviewing their arguments, and importantly, I'll be tearing some of them apart because frankly, some of them are ridiculous.

They deserve to be torn apart. Now, it's

no blame of Citrony. They say that this is all hypothetical, but I think even a hypothetical argument can have severe flaws, and I'll be going over many of them in this article today. I'll be

going through in detail some of the core thesises that are causing these stocks to sell off and addressing what I believe are some of the biggest logical leaps and mistakes in this article. This

will be a fun episode. We do have some other news we'll be touching on today.

For example, Warner Brothers Discovery received a revised offer from Paramount, a higher bid. We don't know what it is, but we're now in this limbo where we're waiting for Netflix's next move. I'll be

giving some thoughts on that. We have

Meta agreeing to buy a hundred billion more worth of chips from AMD. And we

have the fail of the week, which in this case is a DJI robot vacuum that had security so poor that this man remotely accessed thousands of them. This guy

accidentally hacked like 7,000 robots.

We'll be going over that as well. Now,

if you're not paying attention to every detail, you're not listening to every little thing going on, you may have missed what caused this most recent panic. what caused many of the biggest

panic. what caused many of the biggest companies in the world to sell off 3 to 8% in the past day and that was this viral article. This was the cause. Many

viral article. This was the cause. Many

people believe that Substack and these articles can't cause this type of effect. They can especially when they

effect. They can especially when they have the distribution of a Citroen research article. They are one of the

research article. They are one of the biggest if not the biggest publisher in the financial world on an independent basis. The article that they published

basis. The article that they published is called the 2028 2028 global intelligence crisis, a thought exercise in financial history

from the future. Now, they preface this and they say what follows is a scenario.

It's not a prediction. So, they give a bit of a disclaimer and say they're just modeling out a scenario. Now, like most disclaimers, this has been ignored because many people were fearful as a

result of this. And I'll note that this scenario they're modeling out also does benefit them personally. See, Citroen is not just someone that publishes takes and thoughts on the market, but they're

also investors and they are bearish on many of the companies that they're sharing these scenarios on. They have

short positions on them.

>> We are constantly sort of, you know, turning our book and and we certainly had shorts in some of these businesses.

We generally have a set of shorts out against businesses that we think are going to be disrupted by AI.

>> He mentions right away that we are short. many of the businesses that we

short. many of the businesses that we mention in this article. So, in a way, this is an article representing their view, which there's nothing wrong with that. I have bullish takes on companies

that. I have bullish takes on companies that I'm invested in as well. The

difference is I'm not able to move the market in the same way that Citroen is.

So, just keep that in mind as you're reading this that they are short sellers on many of these companies. We won't go over the whole thing, but I want to summarize what I believe are some of the biggest points of this article. In a

couple years, we'll move past Vibe coding to agentic technology. an agentic

technology will cause what they they say is when friction goes to zero. And

again, this is a future hypothetical.

They say by early 2027, LLM usage had become default. People were using AI

become default. People were using AI agents who didn't even know what an AI agent was. In the same way people who

agent was. In the same way people who had never learned of cloud computing was using streaming services, they thought of it in the same way that you think of autocomplete or spellch check, just a

thing that they just did. Now, the next chain was already breaking.

Intermediation. Over the past 50 years, the US economy built a giant rent extraction layer on top of human limitations. Things take time. Patience

limitations. Things take time. Patience

runs out. Brand familiarity substitutes for diligence. And most people are

for diligence. And most people are willing to accept a bad price to avoid more clicks. Trillions of dollars of

more clicks. Trillions of dollars of enterprise value depends on those constraints persisting. It started out

constraints persisting. It started out simple enough. Agents removed friction.

simple enough. Agents removed friction.

So, they explore the consequences of agents removing friction. subscriptions

and memberships that passively renew despite months of disuse. Introductory

pricing that sneakily doubled after the trial period. Each one was rebranded as

trial period. Each one was rebranded as a hostage situation that agents could negotiate. The average customer lifetime

negotiate. The average customer lifetime value, the metric that enterprise subscription economy was built on distinctly declined. Consumer agents

distinctly declined. Consumer agents begin to change how nearly all consumer transactions worked. Humans don't really

transactions worked. Humans don't really have the time to price match across five computing platforms before buying a box of protein bars. but machines do. So

part of their thesis is when you're buying something online, you're just going to buy like the first thing that you see because you don't have time to go look everywhere to save a dollar. But

if you can do that on an agent, if you can say, "Hey, I want to buy this." And

it can go and price match 50 different websites, you're going to let the agent do that. The agent does have the time to

do that. The agent does have the time to make those to make those comparisons.

Travel booking platforms were an early casualty because they were the simplest.

By Q4 2026, our agents could assemble a complete itinerary, flights, hotels, transport, loyal, loyalty optimization, budget constraints, refunds faster and

cheaper than any platform. Insurance

renewals, where the entire renewal model depended on policyholder inertia, were reformed. agents that reshop coverage

reformed. agents that reshop coverage annually dismantled the 15 to 20% premiums that insurers earned from passive renewals, financial advice, tax prep, routine legal work. Any category

where the service provider's value proposition was ultimately quote I will navigate complexity that you find tedious was disrupted as agents found

nothing tedious. Even places we thought

nothing tedious. Even places we thought insulated by the human value of relationships proved fragile. real

estate where buyers had tolerated five to six percent commissions for decades because of information asymmetry between agents and consumers crumbled once the AI agents equipped with MLS access and

decades of transaction data could replicate the knowledge base instantly.

So now they're saying that the real estate market is going to be disrupted because the real estates that intermediary layer will be taken out by agents. This is all just fiction.

agents. This is all just fiction.

They're they're making this up. They're

exploring this hypothetical. So this

hasn't happened. They're saying that uh real estate agents are are getting disintermediated by agents and that's just all in the future. That's going to happen in the future is what they're

predicting here. We had overestimated

predicting here. We had overestimated the value of quote human relationships.

Turns out that a lot of what people call relationships was simply friction with a friendly face. That was just the start

friendly face. That was just the start of the disruption for the intermediation layer. Successful companies had spent

layer. Successful companies had spent billions to effectively exploit quirks of consumer behavior and human psychology that didn't matter anymore.

Machines optimize for price and fit that do not care about your favorite app or your website that you've habitually been opening for the last four years, nor fill the pole of a well-designed

checkout experience. They don't get

checkout experience. They don't get tired or accept the easiest option by default to quote, "I always just order from here." that destroyed particular

from here." that destroyed particular kinds of moes habitual intermediation.

Okay, so that sets the premise of their main core thesis here. Their core thesis is that agents remove friction. They

bring friction down to zero. So any type of company or product that specializes in removing friction at a price, that company will be essentially useless. It

won't need to exist anymore because agents will do that already and not charge you in the process. And this is where the thesis goes from what I think is an intriguing premise to offering

some of the worst examples you could offer, logically flawed ones. For

example, one of the ones that they point out that will be displaced or disintermediated is Door Dash. And this

was a stock that was hit hard yesterday.

Door Dash was the poster child of a moat being disrupted by agents and their removal of friction. Now Door Dash stock since this released is down about 6%. So

let's go ahead and hear their argument.

The V Door Dash is going to be doomed when it comes to agents. Coding agents

had collapsed the barrier to entry for launching a delivery app. So now you can you can uh code a delivery app very quickly. They say a competent developer

quickly. They say a competent developer could deploy a functional competitor in weeks and dozens did enticing drivers away from Door Dash and Uber Eats by

passing 90 to 95% of the delivery fee through uh to the driver. So again, this is hypothetical. hasn't happened. But

is hypothetical. hasn't happened. But

they're saying now that vibe coding allows you to easily code things like delivery applications, which is true, make it easier to code things, you can basically make a competent functioning

competent competitor in weeks to Door Dash and Uber Eats. Then those competent competitors cannot have the greed that Door Dash has. Instead, they can just

pass the savings along to the driver.

Multi-app dashboards let gig workers track incoming jobs from 20 or 30 different platforms at once, eliminating the lockin that the incumbents depended upon. The market fragmented overnight

upon. The market fragmented overnight and margins compressed to nearly nothing. Agents accelerated both sides

nothing. Agents accelerated both sides of the destruction. They enabled the competitors and they used them. The Door

Dash moat was literally quote, "You're hungry, you're lazy, this is the app on your home screen." and agents doesn't agents don't have a home screen. It

checks Door Dash. It checks Uber Eats, the restaurant's own website, and 20 new vibecoded alternatives so that it can pick the lowest fee and the fastest delivery time. Habitual app loyalty, the

delivery time. Habitual app loyalty, the entire basis of the business model, simply didn't exist for the machine.

This was oddly poetic as perhaps the only example in this entire saga of agents doing a favor for the soontobe replaced uh displaced white collar workers when they ended up as delivery

drivers. So there's the argument with

drivers. So there's the argument with Door Dash. It's basically that Door Dash

Door Dash. It's basically that Door Dash and Uber Eats contain high margins. They

charge a lot when you order from them.

So an agent could come along and it can shop it can shop across all the different food delivery networks. And

since you can vibe code a new app in just a couple of weeks, there's going to be a lot of them, 20 to 30 of them.

Since the agent, which is like a chat, GBPT or Gemini, since it can shop for you frictionless, and it can go to all these different uh potential delivery companies or just the the website of the

restaurant itself, it can find the lowest prices, which will naturally compress the margins to zero. And that

seems good at first glance. It seems a little bit convincing until you dive in a little bit deeper and highlight some of the big problems with this type of argument. One of the problems with this

argument. One of the problems with this thought process is if you just put yourself in the customer's position here. Let's say that you're you're using

here. Let's say that you're you're using ChateBT and you're getting hungry. So,

you notice that you're hungry. In that

case, you notice that you're hungry, but you don't know what you're going to eat.

So, you could tell CatchBT, "I'm hungry." And it can say, "Hey, you've

hungry." And it can say, "Hey, you've liked these type of foods. Would you

like to order them again?" and you go, "Nah, what are some other foods out there?" And then it has to assemble and

there?" And then it has to assemble and create a list of foods that you can order. It has to bring in all the

order. It has to bring in all the images. And then you have to say, "Hey,

images. And then you have to say, "Hey, what about you're typing this in again.

You're typing all this in. What about

restaurants that are within 30 minutes?"

Because I want to get it fast. Then it

has to revise and give you another answer. Restaurants within 30 minutes.

answer. Restaurants within 30 minutes.

But then you want to see the reviews of all those restaurants to know which ones are are good and which ones aren't. So

you want fourst star reviews and up. So

you have to type that in. Now order them by by reviews. Okay, so then you're on the restaurant level. You're looking at reviews of it and let's say that you finally narrow down which restaurant you want to order from. Okay, you say, "Hey,

Chachi, I want to order from this restaurant, but I don't know exactly what they have or what the prices are.

Can you tell me that?" And then it has to assemble a list of the the menu from that restaurant of all the different items, what the feature is, what the daily special is. Okay, so you you have

that assembled by Chat GPT now. And

again, you're having chatbt build this menu on the fly as you continually type in. Now, you're on like the six message

in. Now, you're on like the six message now, and you say, "Okay, I want to get a number three. I want to get that meal."

number three. I want to get that meal."

But there's lots of customizations in every single meal from every single restaurant. For example, if you order

restaurant. For example, if you order from Five Guys, do you want the small burger or the normal one? Do you want the double patty or the one with cheese?

Do you want the one with bacon? Do you

want it to have mayo, ketchup? Do you

want it to have onions on it? Do you

want to have pickles on it? There are

hundreds of permutations and customizations within a single order.

Literally hundreds of them in some cases. Chick-fil-A, just that

cases. Chick-fil-A, just that restaurant, has hundreds of different customizations on a single order. All

the all the way to what type of sauce you want to get. Are you going to prompt ChachiBT all the way through this process? By the time you're done, your

process? By the time you're done, your fingers, your thumbs will be sore from the amount of typing you do. You'll have

to gone through so many different customization layers. And the idea that

customization layers. And the idea that chatpt will just know, that's another thing that uh a lot of people argue here. They'll say, "Well, you've talked

here. They'll say, "Well, you've talked to ChatBT so much, it'll know you inside and out. It'll know you better than

and out. It'll know you better than yourself." I was a top 1% user of Chat

yourself." I was a top 1% user of Chat GBT and Gemini in 2025. Top 1%. And I

promise you, it has no clue what I want to eat tonight. It has no idea what what restaurant, what menu, what items, because it changes all the time. Food

preferences change all the time. And

even though there may be something that you order on a routine basis, maybe you get the same Starbucks drink every morning, when it comes to food delivery, this is something that's hyper specialized. Thousands of different

specialized. Thousands of different customizations and orders and of course different restaurants that are open different hours. Every single time that

different hours. Every single time that you would have to order through an agent, you'd have to rebuild a menu, prompt it to death because you're doing prompt by prompt to rebuild all of these

things to get to the point of actually ordering your food. Now, when we're talking about friction in this case, does the agent actually save you on friction? Compare it to just opening up

friction? Compare it to just opening up the Door Dash app. The Door Dash app is already hyper specialized in food delivery. You open it up, it shows you

delivery. You open it up, it shows you all the restaurants that you recently ordered from, all your favorite meals from all of them, all the toggles and switches like 30 minute distances or below. You have everything perfectly

below. You have everything perfectly tested in an AB tested user interface.

You don't have to prompt anything, but if you want to, Door Dash has an AI search engine built into it as well. So,

you have that option available to you if you want, but you don't have to. And in

most cases, people won't because they rather just tap a couple images on the screen, hit confirm order, than endlessly prompt an agent that's an open

text interface. What you lose with

text interface. What you lose with agentic ordering is an interface. You

lose the ability to see the food. People

don't know exactly what they want to eat, and any server will tell you that.

They want to see images. They want to browse. They want to see things that are

browse. They want to see things that are brought up when you're looking at one restaurant. Maybe there's some food

restaurant. Maybe there's some food that's similar in a different one. You

want to see different colors and images.

That's what creates hunger. And that's

when you say, "Oh, that looks really appetizing." And agents don't solve that

appetizing." And agents don't solve that problem. So, inadvertently, by saying

problem. So, inadvertently, by saying that agents are going to remove friction by bypassing Door Dash and Uber Eats app, they're actually creating more friction. There's no way around it. It

friction. There's no way around it. It

is more difficult to get to the point of ordering through an agent than it is to just go to the app that's already hyper specialized in the specific task. A

comparison that I would make is you know how Amazon has that ability to order through Alexa. Like you can have the

through Alexa. Like you can have the speaker there and you can say, "Hey Alexa, get me some more Tide Pods."

Everybody has the ability to do that.

You have open-ended ordering on Alexa devices. But how much has that really

devices. But how much has that really taken off? Amazon doesn't really give

taken off? Amazon doesn't really give the numbers because it's not that popular. Sure, there's cases that you

popular. Sure, there's cases that you can site where people have done it and maybe it's actually growing really fast, but in the whole it's not popular at all. And the reason why is because

all. And the reason why is because people don't just want to talk to a a bot. They don't want to talk to

bot. They don't want to talk to something. They want to visually see

something. They want to visually see precisely what their order is, how much it costs. They want to see it visually

it costs. They want to see it visually in front of them. So, most people, the vast majority, order through Amazon.com.

They go to the website, they put in their order, they see it in the checkout, they know exactly what they're ordering, and they complete the process.

They don't like ordering through a speaker, just like most people won't like ordering their food through an AI that has endless prompting, endless texting. And that's not the only problem

texting. And that's not the only problem with this one example, which is Door Dash. There are more critical flaws with

Dash. There are more critical flaws with this type of thought process. One of

them is the simple fact that when you're ordering food, your goal is not to get the lowest price. Now, from a tech investor perspective, from Citrony, they probably look at it as the only thing

the agent really cares about is getting the lowest price. So, you put your order in for a McDonald's burger and fries.

And the agent goes and finds 50 different delivery platforms that can pick up from McDonald's, and it selects the one that is the lowest price. Maybe

it's 50 cents lower than Door Dash. So

now your order instead of being routed to Door Dash is now routed to some third-party smaller company that's offering a cheaper take rate than Door Dash by 50 cents. You save 50 cents, but in the process you got your order routed

to a different company, and that company doesn't have as good of logistics. It's

not as saturated with drivers, so it takes longer to get your order. Your

order arrives 10 minutes later than it normally would. Your food's soggy and

normally would. Your food's soggy and cold. All of a sudden, you're frustrated

cold. All of a sudden, you're frustrated at the agent for routing your order to some third-party delivery service that doesn't have its act together. So, you

tell the agent, "Please only route it to big mainstream uh logistics companies like Door Dash and Uber." All of a sudden, the whole thesis of fractional cost going down is gone. And the biggest

companies continue to succeed. The truth

is, people ordering from Door Dash and Uber do not care solely about fees. If

they cared only about the fees and getting the lowest price, they wouldn't be ordering food delivery. What they

care about is a combination of price as well as service and quality and consistency and being able to get refunds and being taken care of if there's any issues. And an agent

destroys nearly all of that. Consider

the fact that part of the reason that I can get refunds on Door Dash, part of the reason they're so eager to refund me if I ever have a problem is because Door Dash knows that I'm a a good customer. I

do lots of orders with them. Most of

them are good. So when something goes wrong, they can look at my history. They

can say, "Hey, most of the orders from this guy are good. So when something goes wrong, we should give him a full refund because he's overall a good customer. We want to keep him happy."

customer. We want to keep him happy."

Having a healthy order backlog is important to a customer. It allows you more leverage as a customer. If an agent routes your orders to 50 different

companies, you have no outstanding order backlog and therefore makes it harder to be taken care of as a customer. Because

if you only have one random order from some random place, then you're not going to be able to get a refund nearly as easily as if you have 50 orders from them. This destroys the customer

them. This destroys the customer relationship with the company, their order history. You also have the problem

order history. You also have the problem of memberships. Both Door Dash and Uber

of memberships. Both Door Dash and Uber Eats have extensive memberships. We have

Dash Pass and we have Uber 1 which give you lots of perks. People that use a Door Dash membership are not going to want to order outside of Door Dash and it will make it cheaper after they already paid for that membership. The

same thing with Uber Eats. So you have further customer lockin by these memberships which make it even more difficult to have the scenario where there are dozens of different food

delivery networks. Why would anybody use

delivery networks. Why would anybody use multi-app dashboards in different food delivery networks when they have their membership with Door Dash or their Uber One Pass that makes this one uniquely

cheap where they get benefits from it and rewards from ordering routinely? The

whole scenario here, this hypothetical is that agents are making it so that there's way less friction so that they can shop around, they can lower the margins down to zero. In reality, these agents would make it substantially more

friction on behalf of the user. Users

want interfaces. They want routines.

They want to be able to know and see what they're ordering with precision.

Ordering food is not an open-ended game where you just want to be surprised of what comes to your doorstep. So, these

are the type of arguments that are being given here. And again, this one isn't

given here. And again, this one isn't just some random argument. They

highlight this as the poster child, the prime argument. This is the example of a

prime argument. This is the example of a company that will be disintermediated.

But it's it couldn't be further from the truth. Door Dash is perhaps one of the

truth. Door Dash is perhaps one of the most insulated companies from Agentic Technology because of how difficult it is to replicate a menu to replicate the hundreds of of different customizations

for every single item. Food is a very visual game. People want to see things

visual game. People want to see things when they're ordering. And it takes far more work to constantly text and prompt something to build it in the way that you want than already going to a

wellbuilt application already a unified user interface one that's familiar one that people have used one that's AB tested for customers inadvertently the

agent would be more friction in more situations and there's far more issues than it than just that so when I look at these type of arguments they are convincing on the surface until you

really start to dive in to the nuances and that's where you get lost. That's

where a lot of investors don't make it.

They just sell because Citrine said that Door Dash is going to be replaced. The

stock market goes down. These companies

drop 6 to 7% in a single day. Hundreds

of billions of dollars worth of market cap was wiped out on a completely fanfiction false premise. Now, the Door Dash example is bad because it undermines the case that they're making.

They're saying it's the poster child, but in reality, it's very resistant. But

the next example that they name is it goes from bad to comical. Now we're

going from delivery food networks like Uber Eats and Door Dash to the payment networks Visa and Mastercard. They say

once the agents controlled the transaction, they went looking for a bigger paperclip. There's only so much

bigger paperclip. There's only so much price matching and aggregation to do.

The biggest way to repeatedly save the users money, especially when the agents start transacting themselves, was to eliminate fees. In machine to- machine

eliminate fees. In machine to- machine commerce, the 2 to 3% card interchange rate became an obvious target. Agents

went looking for faster and cheaper options than cards. Most settled on using stable coins via Salona or Ethereum, where settlement was near instant and the transaction cost was

measured in a fraction of a penny. And

then they have a hypothetical. Again,

this is a fake headline of the future.

Mastercard Q1 2027 net revenues plus 6% year-over-year. Purchase volume growth

year-over-year. Purchase volume growth slows to 3.4% year-over-year from 5.9% the prior year. Management notes that agentled price optimization and pressure

and discretionary categories. Bloomberg

April 29th, 2027. It was Mastercard's Q1 2027 report that was the point of no return. Agentic Commerce went from being

return. Agentic Commerce went from being a product story to a plumbing story.

Mastercard dropped 9% the following day, Visa 2, but paired their losses after analysts pointed out its stronger position stable coin infrastructure.

Agent Commerce routing around Interchange posed a far greater risk to card focused banks and monoline issuers who collected the majority of that 2 to 3% fee and had built an entire business

segment around rewards programs funded by merchant subsidies. American Express

was hit the hardest. A combination from headwinds from white collar workforce reductions gutting its customer base and agent routing around interchange gutting the revenue model. Synchry, Capital One,

and Discovery fell more than 10% the following weeks as well. Their Moes were made of friction and friction was going to zero. That's the whole thesis there,

to zero. That's the whole thesis there, right? Friction is going to zero. And

right? Friction is going to zero. And

this is where Citrony, with all due respect, and I I really like this. I

think it's an interesting hypothetical, so I'm not trying to bash them, but with all due respect, they couldn't be more wrong here. One of their assumptions,

wrong here. One of their assumptions, and this is a very tech kind of nerdfocused assumption. A lot of

nerdfocused assumption. A lot of investors have this assumption, too, is that all customers want is less friction. That's all customers want. And

friction. That's all customers want. And

that's an assumption that's correct in some cases. Customers don't like

some cases. Customers don't like friction in a lot of cases. But in

reality, there's some cases, some unique ones, where customers do like friction, where they love friction. They don't

want friction to go to zero and settlement is one of them. Payments is

one of them. Customers love friction in payments. They absolutely adore friction

payments. They absolutely adore friction and they would hate for it to go to zero. Customers re reject, they

zero. Customers re reject, they continually reject propositions where friction goes to zero in payments. Let

me give you a couple examples. The whole

value of a credit card is friction.

That's why highincome people use credit cards. It's why people like me use a

cards. It's why people like me use a credit card is because of the additional friction. Allow me to explain. When I

friction. Allow me to explain. When I

swipe a credit card, I don't want settlement to happen instantly. I want

it to show that I paid money, but I want there to be friction in the process. I

want it to be routed through my bank. I

want it to be the bank's money that paid that money, not mine. I want my money to stay put, to have a delay. I want there to be a period of review where I can look at what the bank purchased on my

behalf. I can review it and make sure

behalf. I can review it and make sure that it was charged correctly, that I received the product, and I don't need to dispute it. I want to be able to review all of it before I actually put

my money into the process. That's

friction. That slows down the process.

When you're purchasing things and you're transacting, you want to slow down the process. In fact, the fact that I don't

process. In fact, the fact that I don't have to pay the money right away to buy something means that I can hold it in my savings account and earn 4% interest for another two weeks or another month. that

gives me the time, money, value. So by

having friction in this process, by having a slower period of me paying for something that is advantageous and consumers want to delay payment for as long as possible. That's why you have

buy now pay later. That's why you have credit cards where you can buy something today and pay for it in a month. That is

friction. Furthermore, the thought process of money immediately moving from my account to someone else's account the instant I hit the buy button is terrifying. That's the last thing that I

terrifying. That's the last thing that I want to do. I don't want money to immediately exit my checking account when I buy something online on some random website. I want to be able to

random website. I want to be able to have time to review it and make sure I got the thing that I ordered before money moves from my account. And again,

that's friction. In this specific case, I want as much friction as possible. I

wish there could be more guard rails and time, money, value in the process. So,

this is a a a premise where the entire premise of what they're building this on is wrong. The premise that customers in

is wrong. The premise that customers in the financial world want zero friction is entirely wrong. Customers don't want zero friction in the financial world.

They want as much friction as possible.

And so, when you build an assumption on a wrong premise, every single other assumption based on that is also wrong.

Another problem with the idea that agents will just wipe away that credit card fee and save the customer money is that in the eyes of the customer, that fee isn't real. Customers aren't paying

that 3% fee. Customers get credit card rewards whenever they swipe their card.

The merchants are paying that fee. The

merchants have hated that fee forever.

Merchants, any merchant doesn't like paying a credit card fee. They don't

like it at all. They wish that it could go away. They've tried to legislate

go away. They've tried to legislate reasons for it to go away. The merchant

is already on board with wanting that fee to go away. Okay. And there's

already many alternatives that would make that fee go away, like a debit card. But there's a reason that

card. But there's a reason that highinccome earners don't like using debit cards because they're instantaneous. Because they are

instantaneous. Because they are frictionless. We already have that

frictionless. We already have that option that brings friction to zero, which is a debit card, and customers don't like it because it has no friction. Their hypothetical of what

friction. Their hypothetical of what could destroy Mastercard, already exists today, and it's not destroying Mastercard. Because when you study these

Mastercard. Because when you study these companies, you know that the high-income earners want friction upon their purchases and they want the rewards. And

they're fine if the merchant pays the reward. See, whenever I swipe a credit

reward. See, whenever I swipe a credit card, I get a reward of 2 to 3%. I get

that money back. When I spend hundreds of thousands of dollars on business expenses, on paying AWS hosting fees or what have uh I get lots of money as a result in credit card rewards paid back

to me. I have no interest in using

to me. I have no interest in using stablecoin. None at all. Why would I

stablecoin. None at all. Why would I want to give up the 3% fee so that the merchant can save money? That's a bad proposition for the customer. So, I

would never adopt a Gentic technology that brings that fee to zero, making it so that I don't earn a reward. That's

not in my interest or any other highincome earnner's interest at all.

Any American Express user signs up for those cards specifically for the rewards so that they can get paid every single purchase. By taking the friction to zero

purchase. By taking the friction to zero and wiping away that fee, you also wipe away the rewards. You can't have one without the other. You cannot have the 2

to 3% reward without the 2 to 3% fee from the merchant. So in the process of wiping away and bringing friction to zero, you also wipe away the primary value proposition of the credit card and

that just won't happen. I don't know anybody. I don't know a single person,

anybody. I don't know a single person, not one wealthy person that wants to do transactions through stable coin. Not a

single one. So when your entire premise is built on a false premise that customers want friction to go to zero, everything else falls apart. Customers

like friction in payments. They like the time value of money. They like the security of being able to buy something now and pay for it later and dispute it in the process. They like the credit card rewards. They don't care if the

card rewards. They don't care if the merchants's paying them. They never

have. So all the arguments here fall flat when faced with actual consumer behavior. Now this doomsday article

behavior. Now this doomsday article continues on, but this time it expands its horizon. It broadens itself from

its horizon. It broadens itself from individual companies like Door Dash and American Express or Mastercard to this time a daisy chain of correlated bets

where everything starts to unravel one domino at a time. And I will say this is one of the most beautifully written and architected bearcases. It's like a

architected bearcases. It's like a dream, a beautiful dream of destruction.

Let's go ahead and just take a look at it. I I really do respect the writers.

it. I I really do respect the writers.

This is fantastic writing. They go over how private credit had grown from under 1 trillion in 2015 to 2.5 trillion in 2026. A meaningful share of the capital

2026. A meaningful share of the capital had been deployed into software and technology deals. Many of them leverage

technology deals. Many of them leverage buyouts of SAS companies. So in the future SAS companies are SAS companies are so toast in this future uh bare case that the valuations go so low that

private equity is buying them up left and right using debt and buying up SA SAS companies taking them private. So

that's the future of SAS. It's just

these companies that become worthless.

They're like dying burrito chains or you know sandwich chains which uh we have private equity coming in and buying up left and right. We have a headline here

again from Moody's. This is in April of 2027. Moody's downgrades 18 billion of

2027. Moody's downgrades 18 billion of PE back software debt across 14 issuers, citing secular revenue headwinds from AIdriven competitive disruption, the

largest single sector action since energy in 2015. This is another fictional future headline that's that's Moody's now talking about the

destruction of SAS companies. Secular

revenue headwinds. Everyone remembers

what happened after the downgrade.

Industry veterans had already seen the playbook following the 2015 energy downgrade. Softwareback loans began

downgrade. Softwareback loans began defaulting in Q3 of 2027.

Private equity portfolio companies in information services and consulting followed. Several multi-billion dollar

followed. Several multi-billion dollar leverage buyouts of well-known SAS companies entered restructuring. Zenesk

was the smoking gun. Zenesk misses the covenants as AIdriven customer service automation erodess um annual recurring revenue. Five billion direct lending

revenue. Five billion direct lending facility marked to 58 cents. And this

section continues on detailing the domino effect of when all of these SAS companies eventually go to zero. And

like the rest of this, there's a number of logical problems with these assumptions. First of all, you again

assumptions. First of all, you again have Zenesk here is the one that they highlight. Now, when we look at Zenesk,

highlight. Now, when we look at Zenesk, this is also a company that's in many of the Fortune 500 companies. This article

suggests that those companies will simply just rip out Zenesk and replace it with an agent. But how long would that actually take? Consider how deeply integrated HR software is in the

processes, the embedded nature of these products. Even if Agentic technology was

products. Even if Agentic technology was vastly superior to Zenesk, it would take half a decade plus to get to the point of actually replacing it. And that's a

big if, but the integration cost, the cost of actually doing anything is incredibly difficult in a Fortune 500 company. In most cases, the solution has

company. In most cases, the solution has to be dramatically better to even consider it. That's switching costs,

consider it. That's switching costs, which are entirely ignored in this article. The other thing that I I just

article. The other thing that I I just look at when I'm reading this is that when you're reading articles like this, they almost assume that humans are inflexible. That humans don't adapt.

inflexible. That humans don't adapt.

That humans don't have a brain and can figure things out when things change, which is the complete opposite of all human history. Humans are highly

human history. Humans are highly flexible and adaptable. Humans take on new tasks all the time. They they adapt to situations and different disruptions all the time. One of the big concerns

here is that all these SAS companies go to zero. Well, if that's the case, if

to zero. Well, if that's the case, if Zenesk and all these other SAS companies went to zero, that means that all the other companies paying for them, imagine all those companies that are paying money to all these SAS companies, all

those companies would have margins go up. So, every company that's paying for

up. So, every company that's paying for a SAS company, let's say you're paying for Salesforce, Adobe, Zenesk, Monday.com, you name it, you're paying for all these different services. You're

paying $500 a month per employee for all these different licenses and seatbased services. If you could erase all of

services. If you could erase all of those, imagine the margins of all these companies paying for all that. Every

other company that's not SAS would have dramatically higher margins as a result.

Every other company that's not SAS would have entirely bigger budgets to be able to hire more people, to be able to expand, to be able to do land grabs, to be able to create entirely new products

and departments and developments, to compete in new verticals, which whenever you do that, no matter how technologically advanced you are, it requires humans. That's the problem with

requires humans. That's the problem with this assumption overall. It's talking

about the destruction of one category, which is SAS, without mentioning that when that happens, the companies that are paying for all of that, that now have those services being automated by agents, are dramatically more

profitable. Profitable companies expand.

profitable. Profitable companies expand.

That's typically what they do all throughout human history. They expand,

they grab more territory, they go into different categories, and that requires more people. So, this is a a very rigid

more people. So, this is a a very rigid look at the future. It's completely

unrealistic. It ignores human behavior.

If focus is hyperfocused on a few companies and then even those companies that it hyperfocuses on, it gives very flawed arguments that don't really represent reality. Saying that people

represent reality. Saying that people want zero friction in transactions with Mastercard, saying that people want to order things through a text message.

These are assumptions that on their surface are just on the false premise.

Yet, it's enough to move the markets down dramatically. Now, I don't mind

down dramatically. Now, I don't mind responding to these type of hypotheticals and and giving my defense of them, my rebuttal of them, and explaining why I think a lot of this is completely ridiculous, but I'd also ask

investors, ones that are listening to this, ones that are learning investing and trying to take themselves seriously as an investor, can we just get a grip?

I mean, can we can we for a minute in this market just get some sense and have some stability and be levelheaded? Can

we go a day without the market being ripped and tugged and pulled in different directions by a hyperviral fanfiction article? This reads like

fanfiction article? This reads like fanfiction. It reads like a Marvel

fanfiction. It reads like a Marvel story. So much of it is completely

story. So much of it is completely flawed. So much of it is embellished. So

flawed. So much of it is embellished. So

much of it ignores important market dynamics. Now again, no offense to the

dynamics. Now again, no offense to the author. It's an interesting article and

author. It's an interesting article and it's well written, but it's also completely unrealistic. Yet, it's moving

completely unrealistic. Yet, it's moving the market just like many of these ones before them. They have compelling

before them. They have compelling narratives that sound good on the surface, and it's causing investors to question their own reality. It poses a a future where AI is this unstoppable

alien force that takes over the world that no one can do anything about, that destroys everything. In fact, in every

destroys everything. In fact, in every time period known to man, there's people talking about the end of the world, the doomsday, the doom and gloom, how nothing will be the same and the future will look like nothing you've ever seen,

and how the stocks you own today are essentially worthless. This is what

essentially worthless. This is what Peter Lynch literally talked about decades ago. Okay, now we'll get to the

decades ago. Okay, now we'll get to the important stuff. There's always

important stuff. There's always something to worry about. Uh,

this is the difference. This is what happens in the stock market because see, everybody's got the brain power to dwell in the stock market. question is whether you have the stomach for it. That's the

key organ in the body. There's always

something to worry about. I mean,

there's always something to worry about.

In the 50s, it was depression and nuclear war. The 50s was the best decade

nuclear war. The 50s was the best decade this century. Do you remember when oil

this century. Do you remember when oil went from four to 40? Remember that?

Remember that period? And all the countries of the world are going to go bankrupt. And then and the big banks go

bankrupt. And then and the big banks go bankrupt and we're going to have a great depression and the stock market's going down and you're going to wind up selling pencils and apples. You know,

>> doesn't that sound familiar? You're

going to end up selling pencils and apples. the whole stock market's going

apples. the whole stock market's going to go bankrupt. This is Peter Lynch saying this prediction has happened before in almost the same exact way. The

only thing that's changed is the time.

History repeats and we're seeing again another repetition of it. So, I'm asking investors today to realize that right now you're in a time period where there's a lot of uncertainty. There's

questions in the air and nothing about that is new. Nothing's abnormal. You'll

be in the same situation in 5 years and in 10 years. As Peter Lynch highlights, his entire investment career has been filled with uncertainties and predictions of doom and gloom. Whether

it's oil collapsing the market, whether it's uh nuclear warfare, the Great Depression or the recession or the the even greater depression, whatever it may be, there's always something to worry

about in all times of the market. So, if

you're investor, get a grip. Lock in.

This is a time to be optimistic.

Not to be greedy, not to be unprudent, but we should be optimistic about the future. Optimism is what makes money in

future. Optimism is what makes money in the end. You can look at the biggest

the end. You can look at the biggest examples. And although there's investors

examples. And although there's investors that try to look smart by always having bearish calls and when the market will collapse and there's some of them like that. You have the Michael Burries of

that. You have the Michael Burries of the world, there's always way more investors that have made way more money through optimism of having realistic positive assumptions of the future knowing that many of these companies are

going to be highly successful, extremely prosperous. That if money is destroyed

prosperous. That if money is destroyed in some companies that can't maneuver and adapt to Gent technology, many of them will. And the ones that go away

them will. And the ones that go away will mean higher margins for the existing companies that will be able to expand and grow in the process. What we

have right now is investors selling off great companies for entirely unrealistic presumptions of the future, ones that are seated in fear and doubt, not

realistic optimism. So that's my

realistic optimism. So that's my thoughts on this and that's how I'm responding as an investor. Uh, I'll

continue to invest in the companies that I think will be incredibly profitable in the future. And I think that the

the future. And I think that the disruption risk is dramatically overstated by many of these articles.

And this certainly isn't going to be the last. As we see more AI technology

last. As we see more AI technology emerge, more demos, more clawed plugins, we're going to see more of this doom and gloom. But that's the latest as of now.

gloom. But that's the latest as of now.

Now, moving on, we get to some big news.

Over the past 7 days, uh, Netflix gave the opportunity for Warner Brothers to go back to Paramount and say, "Hey, look, you have 7 days to revise your offer and give us your best and final

offer." And that has happened. Warner

offer." And that has happened. Warner

Brothers Discovery says that Paramount made a higher bid. And the board will weigh the offer against the Netflix deal. Basically, what's going on here is

deal. Basically, what's going on here is the offer that Paramount submitted is private. So, we know that they submitted

private. So, we know that they submitted an offer. It was higher than their

an offer. It was higher than their previous one, but the details are private. We don't know the number.

private. We don't know the number.

Everybody's speculating of what it could be. It could be anywhere from like $31

be. It could be anywhere from like $31 with better terms to $34 on the high end. And either way, this is Paramount's

end. And either way, this is Paramount's last ditch attempt to steal Warner Brothers away from Netflix to say, "Hey, uh, Warner Brothers, we want to go with Paramount over Netflix because their

offer is so much more attractive." Now,

they can't necessarily do that unless Netflix looks at their offer and decides not to beat it. So Netflix can look at it and they get the first call. They can

match the offer or beat it. So Netflix

is going to simply look at it, look at the revised offer and see if they want to adjust theirs at all or if they need to do anything to beat that offer. And

that's up to them. Netflix has all the power in this situation. I think that Netflix is going to look at it and say, you know what, if we have to pay an additional four to six months of free cash flow to buy this service, to make

it so that we own all of this for the next 20, 30 years, so that we can draw upon this well of incredibly valuable content and distribute it through our massive distribution, that's probably

worth it. Internally, Netflix knows

worth it. Internally, Netflix knows exactly what they're willing to pay and what is overpriced. They already have that modeled out. They already have their numbers, so they can look at this and weigh it against what is their price

of what they believe this asset is worth. And as Ted Sarando says, they are

worth. And as Ted Sarando says, they are disciplined buyers. If they don't like

disciplined buyers. If they don't like the deal, if it's simply just too much and it makes it not worth it, they will walk away and Netflix will be able to collect over a $2.5 billion fee. So even

if they walk away, they get something out of this. But if I have to guess, and again this is hypothetical, maybe they won't. My guess is that Paramount

won't. My guess is that Paramount submits a higher offer. I think that Netflix makes theirs more attractive and locks it down and then it's done from there, but we'll have to wait and see.

Now, moving on, we have another bit of news here. This is a big headline. Meta

news here. This is a big headline. Meta

and AMD agree to AI chip deal worth more than $100 billion. These deals used to be really cool. Like, we'd see these and everybody would get excited. Oh my gosh, a hundred billion dollar deal with a

chip company between a big tech company.

But now that they've happened so frequently, it just seems like another day. Like every other day there's a deal

day. Like every other day there's a deal like this. It seems like I'm getting a

like this. It seems like I'm getting a little bit numb to looking at these deals. The instant reaction to this deal

deals. The instant reaction to this deal is AMD of course is up big. They got a new customer so they're up nearly 10%.

And Meta is up a little bit. So Meta is not even being hurt by this. Most

investors already know that Meta's they're buying big that they're investing in Capex. So nothing is new about that. Now I've recently invested a

about that. Now I've recently invested a substantial amount of money in Meta.

I've made it my third largest position.

It's about $150,000 invested in it. And

I love what the business is doing.

They're becoming one of the few supercomputing powers. Many people are

supercomputing powers. Many people are bearish on this capex spend. I'm not

long-term. I realize that it will hurt the financials in the short term. It'll

make it so that their accounting and the fact that they're depreciating these assets over time will hurt their earnings, but I think long term this sets these companies up to be so uniquely strong. Meta will have one of

uniquely strong. Meta will have one of the strongest moes in the world. Both a

network moat and an infrastructure mode.

It'll be virtually indestructible. So, I

view this company as incredibly moheavy, super wide and deep moat with ample growth opportunity priced at a 22 Ford PE. To me, that feels like a very

PE. To me, that feels like a very attractive value proposition, an attractive situation to invest in.

That's why I continue to feel good about this one. Now, finally, we move on to

this one. Now, finally, we move on to the fail of the week. In this case, it's an unintentional, this is an accidental hacking of about 7,000 robot vacuums. We have Sammy as Dufall. He claims that he

wasn't trying to hack every robot vacuum in the world. He just wanted to remote control his brand new DJI Romo vacuum with the PS5 gave PS5 gamepad. He tells

The Verge because it sounded fun. But

when his homegrown remote control app started talking to DJI servers, it wasn't just one vacuum cleaner that replied. Roughly 7,000 of them, all of

replied. Roughly 7,000 of them, all of them around the world, began treating as Dwfall like their boss. He could

remotely control them and look and listen through their live camera feeds.

This means that this guy inadvertently hacked other people's robot vacuums, which have cameras on board, meaning that he hacked cameras of other people's homes, 7,000 people. He would watch them

map out each room of a house, generating a complete 2D floor plan. He could use any robot's IP address to find its rough location. I found my device was just in

location. I found my device was just in one of the ocean of devices. So, it has a map here of like a a we have an area map of all the different devices that he's found. And here it has like a live

he's found. And here it has like a live camera feed. Like some of these have

camera feed. Like some of these have onboard cameras so they can see objects and avoid them. But it also inadvertently operates as a camera going around your home. You could just drive

around and film people at will and they don't even know they're being filmed.

They might just think that their robots acting a little funny. And this has to be one of the worst hacking or personal invasion of people's privacies possibly ever done. I mean, have we had a

ever done. I mean, have we had a situation where 7,000 devices that are mobile and have cameras have been hacked in people's homes? In most cases, if you hack a camera in someone's home, at

least it's just one location. These ones

are literally mobile. You can drive them around. So, he has a camera that he can

around. So, he has a camera that he can stare in other people's homes. He says

right now that DJI hasn't even fixed all the vulnerabilities that he's found. One

of them is the ability to view your own DJI Romo video stream without needing its security pin. Another one is so bad I won't describe it until DJI has more time to fix it. So DJI has a massive

critical failure in their security here.

And if you have one of these robots, especially with the camera, you might want to just put the robot away, take it off its wheels, flip it upside down, make sure it can't drive anywhere without your permission because as of

right now, it could literally be viewed by anyone with a Claude Code plugin. And

until the update happens, until the company publicly acknowledges it and it fixes all these these security exploits, it might be a concern. That's gonna be it for this time. Hope you enjoyed. See

you in the next one.