Software Stocks Going to Zero? by Adam Khoo

So, what's up with these software stocks? Why are they getting whacked so

stocks? Why are they getting whacked so hard, especially this year where the share price is dropping almost every single day? And could they really go to

single day? And could they really go to zero as some people claim? Let's find

out in this video.

Our new AI tools and AI agents have already been pressuring software stocks last year with Salesforce and Service Now and Adobe and even like Dualingo down double digits last year. But this

year, the sell-off has gotten even worse. So, for example, this year alone,

worse. So, for example, this year alone, Salesforce down another 28%, in it down 34%, service now down 33%, Adobe down

another 23%, ADP down, and so and so forth. So, what's happening? What is

forth. So, what's happening? What is

scaring the living out of software investors? Well, the main culprit is

investors? Well, the main culprit is actually Anthropic. Now, if you didn't

actually Anthropic. Now, if you didn't know, Anthropic's biggest shareholder is, tada, Amazon, right? So, Amazon,

Nvidia, Microsoft, and Google are the biggest shareholders of Anthropic. So,

Anthropic has an AI uh model which of course competes with Chat GPT. In fact,

I think it's way better than ChatGpt.

use Anthropics Claude now a lot more for my finance work rather than chat GPT right and of course they compete with Gemini as well but I use both I

basically use Gemini and Claude now cla what's so special about clot basically anthropic they released a new version of claude called cla coowork and that

really really scared uh people who own software companies why let's find out why now what is claude coowork clot coork is an auton autonomous AI agent

system. So, this is kind of like you

system. So, this is kind of like you watch um Iron Man where um Tony Stark had this guy called Jarvis and Jarvis

was like his AI assistant, his digital employee and he could go in and do everything for Tony Stark. Well, that's

Claude Co-work. It's like a Javis, right? So, Claude Co-work functions like

right? So, Claude Co-work functions like a digital colleague that you can have.

And this agent has direct permission to access your local files. You can go into your computer, operate your browser and execute multiple step workflows

autonomously. So for example, using

autonomously. So for example, using cloud co-work or any AI agentic system.

It you can use it to read, edit, move, rename and create files in your PowerPoint, your Excel and even your PDFs. And when you pair with a browser

PDFs. And when you pair with a browser extension, it can navigate websites for you. It can extract data for you. It can

you. It can extract data for you. It can

fill up forms for you. It can book airline tickets for you. It can research competitors or without your guidance. It

works by itself.

So AI is no longer something you chat with. It does stuff for you like your

with. It does stuff for you like your personal assistant, like a digital colleague. And it they just released a

colleague. And it they just released a set of 11 open-source starter plugins that provide preconfigured workflows for specific jobs like legal, sales,

marketing, and finance. So what does it mean? So what it means now is that

mean? So what it means now is that companies literally you don't have to hire a marketing executive or marketing manager. They are all they can all be

manager. They are all they can all be done by these AI agents. No need for a legal team in your office. AI agents act as your legal team. You don't need a finance manager, finance uh assistance.

All done by the gentic AI. So what

what's a fear? Well, there are two fears. The first fear is that claude

fears. The first fear is that claude cowwork allows anyone like you and me with no programming background to code any kind of software that we want in

minutes. We they call it vibe coding.

minutes. We they call it vibe coding.

So, for example, you come in one day and you look at your co-work and you say, you know, I wanted to create a software where I've got a local dashboard that

tracks my company's coffee consumption from all these 50 spreadsheets and display it on a web page which I can track every day and in minutes that software is done for you. So, the first

fear is that with this tool basically anyone can replicate Adobe's software.

They can replicate services. now

software they can replicate zoom software they can replicate a slack software in minutes using this cla

coowwork tool right and so why would I buy software from Adobe when I can create the exact same software in minutes that that's the number one fear

the second fear is the collapse of seatbased pricing so think about it traditionally companies like Adobe and service now um how do they charge They

charge per employee. So if a company has got a 100 employees, they need to buy a 100 licenses. Let's say they are all in

100 licenses. Let's say they are all in sales, right? And each license or each

sales, right? And each license or each seat, they charge $500 a month. But now

with AI agents taking over employees, you notice a lot of companies are now retrenching people and not hiring people anymore. So now the company that used to

anymore. So now the company that used to have 500 salespeople now only only needs maybe 50 salespeople and the other 450 are replaced by AI agents. So with 50

people what does it mean? You you

require less seat licenses and so uh Adobe and Salesforce will have less revenue because they sell less licenses.

So it is this fear that's causing people to think oh my god you know all these software companies their sales and profit going to drop 50% 80% some of

them are going to go bust okay so is this true it could this really happen right so first understand that this is a prediction it has not happened if you

look at the revenue and profits of service now of uh salesforce the revenue is still growing the profits are still growing nothing has changed It's a

prediction that this could happen. So

the first thing to understand is that there have been a lot of predictions that have sounded very scary in the past that just never happened. Right? If you

remember not too long ago in January of last year, there was this Deep Seek out of China where Deepseek claimed that hey, we built this uh AI large language

model with $3 million in 3 months where you guys spend billions and billions and months and months to build your AI. We

can do it at a fraction. And when the news was released, what happened? people

thought, "Oh my god, you know, Meta and Amazon, they're overspending on on stuff that uh just takes a few million and Nvidia is going to go bankrupt because now Nvidia is not going to sell chips

anymore because who needs their chips?

They can get it for far cheaper." And

that fear sparked a 43% drop in Nvidia in January last year. And people thought that, okay, that's the end of Nvidia, the end of AMD. But what happened? It

didn't happen, right? In the end, like Deep Seek disappeared, went to the went into deep and Nvidia and AMD are selling, you know, more chips than they ever did, right? And the share price

then went to new heights. So, that

didn't happen. And then, of course, you recall that again, uh, in May of last year, you know, a lot of people were still saying that Google is dying

because ChatGpt is eating Google's lunch and no one is using search anymore.

They're using all these um chat GPT LLMs and you know search is dying. But did it happen? No. Right now Google search

happen? No. Right now Google search market share is growing faster than ever. Their ads are growing faster than

ever. Their ads are growing faster than ever. Their cloud is growing faster than

ever. Their cloud is growing faster than ever. They just had blowout earnings,

ever. They just had blowout earnings, great earnings, but the stock still dropped because of all this short-term u irrational fear. But the company's doing

irrational fear. But the company's doing really really well. And Gemini is kind of like going to overtake CG GPT. And

again from that news what happened?

Google dropped 35%. People thought it's the end of Google but then Google went to all-time highs. So the first thing to understand is that you know anyone can make these predictions and more often

than not these predictions never turn out to really happen the way people predict. Okay. So could it be the same

predict. Okay. So could it be the same thing with this prediction that AI will kill software companies? Now of course we can't just brush it aside and say oh you know the prediction won't come true.

is rubbish. Let let's just buy. You know, we we have to look at it

buy. You know, we we have to look at it and really see is there a threat. And

the answer is uh it's more nuance. In

other words, I think there are certain software companies that could really be disrupted and others not so much. So, it

depends on the particular software company. So, in this video, I'll run

company. So, in this video, I'll run through some of the more popular ones like Adobe, like Salesforce, like Service Now, like Microsoft. And let's

take a look which ones would be more resilient to this potential disruption from AI agents and which would be more vulnerable.

Now one of the first things to understand is that yes with with with claude cowwork and with a lot of these new AI tools sure we

can create software very easily. You

know we could we could replicate any kind of software very easily. But the

thing to understand is that these enterprise software companies their main mode their main competitive advantage their main product is not the software itself because yeah you and me we can

create the software but can we scale the software can we maintain the software can we integrate it into the company that that's a whole other thing right so

these enterprise software companies their main value is not just providing the software okay they provide three main layers of value. What are the three

main layers? Number one, they act as a

main layers? Number one, they act as a system of record for the company or we call it sor. Now system of record is kind of like they act as this central

memory bank of the company as a single source of truth for the company where all the important data lies in this system of record. So this system holds

the master list of who are the customers, what are the products, who are the employees, bank accounts, and it tracks the who, what, when, why of every

single transaction to ensure there's a clear audit trail for every transaction for legal and tax purposes. So you can create a software. Yeah, we we can

create a software but can your software track every single transaction to create a clear audit trail for legal and tax purposes. So the system of record is a

purposes. So the system of record is a strict set of rules where managers like security like who in the company gets to see what data or gets to change what data. you know creating a software by

data. you know creating a software by itself you know doesn't give you that right governance the approval change uh chain sorry for example making sure that

a manager signs off before a payment is made to a supplier or consistency ensuring that when you sell an item in a company is automatically removed from

the inventory and added to the sales report simultaneously it must all be connected into this system of record now system of record is not easily replaceable

Yes, you can create a software, but you can't easily replace the system of record or the memory bank of the company.

Changing a company's system of record is like doing a heart transplant on a person who is running a marathon.

All right, the company is like the company is operation. It's like running a marathon. You're doing a heart

a marathon. You're doing a heart transplant in the middle of that. It's

it's almost impossible. So AI can generate content for these systems and make decisions but it cannot render a legally robust and consistent state for these companies. The second layer that

these companies. The second layer that software companies provide is a system of engagement or they provide the dashboard for the company or the front

office of the company. So it's the work interface for the people to use the software and is built to be easy to use so that employees actually want to use it. So this includes your graphical user

it. So this includes your graphical user interface, your dashboards, your forms, your task list. What are examples of software companies that provide this system of engagement? Well, example be

Zoom for video conferencing or Wix for building websites or docuign for signing documents. All these software companies

documents. All these software companies provide a system of engagement.

Now, unfortunately, this is the most vulnerable layer that can be replaced by AI agents. Why? Because historically,

AI agents. Why? Because historically,

humans like you and me had to manually click through the menus of these uh software companies, fill out the forms and operate it, right? But now it's all

done automatically autonomously by AI agents and they're replaced by conversational interfaces where you talk or chat your software, do this, do that, and it just does it for you.

The third layer is the system of intelligence and automation, the digital operator of the company. So this is where the software company provides the

agent or the operator layer for you for the company where this agent will interpret your goals where you tell it what you want to achieve. I want to

onboard this employee. It goes figures out the steps and then executes the task autonomously. And it's also got

autonomously. And it's also got specialized intelligence. It can handle

specialized intelligence. It can handle complex and boring routines like classifying support tickets, creating sales quotes, or cleaning up messy data.

And it also acts as a conductor, making different systems work together in harmony throughout the enterprise, like taking data from a customer relationship management system and then checking it

against an enterprise resource planning system and then creating a record in support. In summary, a SAS company,

support. In summary, a SAS company, software as a service company, they don't just provide software because again you and me can now create software very easily, right? But they provide

three layers. Number one, they act as a

three layers. Number one, they act as a system of record for the company analogy like the memory data bank of the company. Number two, they provide the

company. Number two, they provide the system of uh engagement which is the dashboard layer. And thirdly, they can

dashboard layer. And thirdly, they can provide the intelligence layer or the brain which is the agent operator level.

Now, can all software companies do all three things? No. Some software

three things? No. Some software

companies can only do one thing. Some

can only do two. Some can do all three.

And so, how prone is a software company to disruption of AI agents depends on how many layers of enterprise tech they

offer the customer. So for example, stocks like Wix, like Zoom and Docu Sign are more prone to disruption because they only provide the system of

engagement layer that can easily be replaced by AI agents. Whereas companies

like your Microsoft, your Service Now, your SAP, they provide not just the system of engagement layer, but they also provide the system of record layer, even the system of intelligence layer.

For example, Salesforce has got their own agent force that provides the agentic operator layer, right? Microsoft

has their co-pilot studio which again is the intelligence layer and Service Now has got their own Service Now AI agents that again provides that operator layer as well. So they cover all three layers.

as well. So they cover all three layers.

These are software companies that are a lot harder to dislodge uh from their enterprise customers. The enterprise

enterprise customers. The enterprise customers cannot just go out there and vi put a software and then replace a system of record, system of intelligence overnight. Doing it is like again doing

overnight. Doing it is like again doing a heart transplant on a marathon runner.

It is almost impossible. Mr. Market is not so intelligent. Once they see software they sell and they just get out and ask questions later, right? And as a result, you get the baby thrown out of

the bath water. So as an intelligent investor, you have to look at the specific software companies. Yes, there

are certain software companies that can be disrupted and they are purely on seatbased pricing. Their revenue profits

seatbased pricing. Their revenue profits can drop 80% and that's it. But if the company provides all three layers of enterprise tag and the companies are

able to pivot from seatbased employee pricing to consumption pricing where the enterprise customer pays per prompt or

per action and not per employee, then they can still do very well. even if

their customers reduce their headcount.

So these are the companies where I'm not too worried about. I know that uh eventually the share price will bounce back to new all-time highs and no worries. But of course there are other

worries. But of course there are other software companies that we should be more concerned about. These are the ones that could be more easily disrupted because they don't have uh all three

layers of enterprise tech uh for the customer and they could be more easily displaced by uh aentic AI. So, which are the companies that are more prone to disruption and which are more resilient?

I know some of you will be having that question. Now, I won't go too much into

question. Now, I won't go too much into the technical details because then this video is going to be like 3 hours. I'm

just going to show you a quick summary of some of the more popular software companies and I'll do a bit of a ranking for you. Yeah. Okay. So, first most

for you. Yeah. Okay. So, first most popular company of course Microsoft. So,

on a scale of 1 to 10, 10 is the most resilient. one means it's going to die

resilient. one means it's going to die tomorrow. Microsoft is ranked 9.5.

tomorrow. Microsoft is ranked 9.5.

Why? Because again it's ranked based on its uh ability to provide these layers to its customers. Number one based on

system of record it's 80 out of 100 ranking system of engagement 85 system of intelligence 90 data model depth 78

agent monetization ability 95 AI infrastructure which it provides itself through Microsoft Azure it provides its own infrastructure layer uh 98 out of

100. So in my opinion, I think Microsoft

100. So in my opinion, I think Microsoft is one of those uh very resilient software companies and I have been personally adding uh shares uh slowly because again during a correction you

never know how low it's going to go. So

I never like add too much at one time. I

just nibble very very slowly to kind of like average down my cost. Next, Service

Now. So Service Now has got a ranking of 9.2. Yeah, it's a rare company that

9.2. Yeah, it's a rare company that spans all three layers. So again, system of record, system of engagement, uh system of intelligence, again it's got

its own AI agentic layer, data model depth 92 and agent monetization ability 90. So what does agent monetization

90. So what does agent monetization mean? Again, in the past uh service now

mean? Again, in the past uh service now uh like Salesforce, they they charge per employee. So the more employees, the

employee. So the more employees, the more they charge per license, but they're pivoting towards uh not charging per employee, but charging per agent and

charging based on consumption and outcome pricing. So that's a 90 out of

outcome pricing. So that's a 90 out of 100. So service now, Viva Systems, Viva

100. So service now, Viva Systems, Viva Systems is kind of like a CRM but specialized for the health sciences industry. So they are very specialized

industry. So they are very specialized with a lot of regulations. So you just can't build a software to replace them because that software doesn't have all the regulations and the knowledge base

required for these very very um sensitive industries like like healthcare and pharmaceuticals.

Um so again they are viva vault platform stores regulatory submissions, clinical trial master files, quality records and compliance documentation for life

sciences. They are all legally mandated

sciences. They are all legally mandated audit auditable data that AI cannot replace.

The data model is extraordinarily deep and domain specific. Switching costs are enormous given validation requirements.

Moving off Salesforce onto its own vault CRM further deepens their mode. So um

again they provide system of record, system of engagement, system of intelligence. Now this is not too high.

intelligence. Now this is not too high.

They don't really have uh their own agents so to speak but their data model depth is very high because of again uh

the regulatory requirement for the health sciences industry. Next we've got constellation software. This is a serial

constellation software. This is a serial acquirer of vertical uh software companies. So this has a resilience

companies. So this has a resilience score of 8.5. Still pretty good right?

Uh, Constellation has a portfolio of 800 vertical market software businesses, many of which are system of record, hence 80 of 100 in different niche

industries in transit, utilities, golf course management, funeral homes, all very very niche uh parts of the industry. The diversification across

industry. The diversification across hundreds of verticals is itself a hitch.

AI won't disrupt all verticals simultaneously and many of these subsidiaries have deep domain specific data and mission critical workflows.

However, some of their portfolio companies may be more system of engagement oriented oriented and those may be more vulnerable but not the majority of the the companies they own.

So in terms of system of record 80 of 100 on all these niche industries system of engagement not so much system of intelligence not so much as well but uh

deep data model depth agent monetization also not that much. So you can see that for constellation software their main resilience comes from their system of

record in niche industries as well as their data model depth which is basically uh their deep domain specific data and mission critical

workflows in the many subsidiaries that they own. Now let's go on to Salesforce.

they own. Now let's go on to Salesforce.

Now Salesforce resilience not as high as the rest but still possible right we give it a 7 out of 10 resilience score.

Now Salesforce does span all three layers but they are more vulnerable than service now than consolation software and viva systems. Why? because their CRM

data which are their contacts, opportunities and accounts. It is a system of record but the data model is thinner than enterprise resource planning grade systems such as service.

Now much of the value is in the engagement layer. Now they also have

engagement layer. Now they also have their CRM agent force which is their system of intelligence layer and they have recently started to pivot from

seatbased employee pricing to consumptionbased pricing. But again

consumptionbased pricing. But again question is can they execute it well? Will it work?

Again a bit of a question mark. Now if

they can then no problem. Their revenue

and profits can still grow very well even though their customers reduce their headcount but again it's not 100%.

Right? So again they're still in that pivot transitory transitory process if you will. uh at the same time uh CRM

you will. uh at the same time uh CRM data, customer relationship management data is a bit more exportable uh than regulatory or financial system on record

data. So in other words, their switching

data. So in other words, their switching cost is high but not as high as say service now or or viva with high uh

regulatory hurdles to clear.

Next, Adobe. A lot of you have been asking about Adobe. As you guys know, I sold Adobe long ago. I sold it like almost a year ago at like 500 bucks because at the time I was already a bit

concerned that um all these free or low price um video editing and photography tools could replace Adobe's enterprise suite

of tools, right? And uh well, I'm quite happy I sold it, right? And I definitely won't buy it now because I think out of all the major software companies, I

think it's the most vulnerable. So, we

give it a rank of 5.5 out of 10. Still

passes, but it's not like super resilient like the rest of them. Why?

Because Adobe is overwhelmingly a system of engagement SAS company. You can see this is 95 out of 100. Whereas its other layers like system of record and system

of intelligence and data model depth uh is weaker. Uh why? because their main

is weaker. Uh why? because their main value proposition is their creative user interface and workflows like their Photoshop, their Illustrator, Premiere Pro where you physically go in there and

you do all the work, right? So while it owns certain format standards, it owns PDF for example and there is switching cost, the article's framework

specifically warns that products whose main value lies in fancy user interface and manual click work are more likely to lose out because in the future all this

can be done by AI agents without humans lifting a finger and AI native tools like Canva, Figma, Runway and Midjourney

are democratizing creative work where more and more people can do it even without an artistic background. Seed

compression risk is real if one designer plus Firefly can do the work of uh three you know agents that use Adobe will retrench employees and cut seeds and

that could affect their revenue and profits in the future. Now again bear in mind that everything I said again they are assumptions.

So far all these companies has their revenue dropped? No. Have their profits

revenue dropped? No. Have their profits dropped? No. They are still growing

dropped? No. They are still growing their revenue and their profits. All

these are assumptions. So because of that you notice that the intrinsic value that is calculated is based on their free cash flow on their growth rates.

That hasn't changed. Yeah. But it's

important to again think ahead.

Again, remember this could end up to be a big nothing burger. Just like the deepseek fear or the fear that check GPT will kill Google. It could end up to be nothing. But it is still worth looking

nothing. But it is still worth looking at it. It's worth analyzing it. And if

at it. It's worth analyzing it. And if

you ask me uh if I would add any of these companies, I do have some of them in my portfolio. Um I think it'll be more like Service Now, it'll be more

like Viva, it'll be more like um Constellation Software. For Salesforce,

Constellation Software. For Salesforce, I do have a small position. I'm not

adding. I'll be holding. But for Adobe, personally, I won't I won't add it. All

right. Again, this is not a recommendation for what you should do.

Just sharing my insights of this software selloff. Thank you for

software selloff. Thank you for listening and I'll see you guys in the next video. If you want to catch my

next video. If you want to catch my latest videos, click on the subscribe button right now. Click on the bell so you get instant notifications once I upload my latest video. If you want to

check out my online courses, go on to piranhaprofits.com where you're going to learn how to invest and how to trade the financial markets and create an income from all around the world. If you want to join my

live Wealth Academy program, go on to wealthacademy global.com and find out more about how you can learn investing and trading live online. This is Adam Coup and may the markets be with