AI是威胁？还是机遇？软件股多点开花预示什么？哪些公司能率先迎来爆发？

Hello everyone, I'm MINGJIAOJUN, your "Megapod" explorer. Software has always been a favorite of the tech world in the past decade. They grow fast and have high market share. If

you choose a good company, you can easily bring a rich return to the investors.

However, a batch of market favorites like this have been in unprecedented crisis in the past six months. With the outbreak of AI AGENCY, AI subversion is on the rise.

The entire software industry has been wiped out and almost no one is alive. The

ITF IGV fell nearly 40% and many star stocks were cut off. But recently, the situation seems to be turning around quietly. With the continuous release of software stock financial reports, we saw that the 0-star software stocks began to burst. For example, after Snowflake's financial report, it rose 36%, after Datadog's financial report, it rose 32%, after Team's financial

report, it rose 30%, etc. But at the same time, most software companies are still punished by the market. Even if the performance is bright, it cannot turn the tide.

What kind of investment logic is hidden behind such a contradictory phenomenon? Familiar with Meta, the viewers know that over the past period of time, I have expressed my views on the current software stock more than once. I said that now, instead of chasing those basic levels that have risen to the sky, it is better to ambush these reasonable and soon to be popular apps. This is also one of my favorite US

stock investment opportunities in the second half of this year I promised you that I would do a special research on application-level software companies I will fill in the hole in this video Let's start with this financial quarter today Let's see what kind of software companies can prove themselves and get the recognition of Wall Street And what kind of companies will continue to be punished In these trading logics Can we find the

next opportunity for software to explode? In the end of the video, I will also give my personal specific software selection method and software layout. At the beginning of the video, I want to share something interesting with you first. The topic of this video was actually made two weeks ago. During these two weeks, my team of analysts and

I have studied the latest financial reports of dozens of software stocks, and initially got some inspiration. Following these inspirations, we were very optimistic about Snowflake's financial report, and we

some inspiration. Following these inspirations, we were very optimistic about Snowflake's financial report, and we also published our views on Metopro. As a result, this company completely exploded this week.

After the financial report, the stock rose by 40% in two days. Next, I

will report the results of this research to you in detail. Maybe it can help you find the next good company worth paying attention to. Let's take a look at which software companies are performing well in this financial reporting season. First of all, it's Snowflake, which we mentioned above. This company that does database and data analysis has increased

by 36.4% after financial reporting. Its business is to collect data scattered in various systems of companies and then carry out real-time survey and analysis. Datadog, a company that does data monitoring platforms, also rose by 31.3% after the financial crisis. Its service is the most popular GPU for monitoring the company's server,日志, network traffic, and AI era. It's

like installing a camera on an IT system. After a certain abnormality is diagnosed, it will call the police or do automatic processing. Atlassian, also known as Team, is a project management software used by almost all software development teams. Its financial crisis also rose by 29.6%. Its flagship products are Jira and Confluence, which everyone can imagine. Twilio,

by 29.6%. Its flagship products are Jira and Confluence, which everyone can imagine. Twilio,

a company that makes communication API platforms, has a 23.8% increase after the financial crisis.

It provides services for apps to call, text messages, and email. The information you receive from Uber, the verification code received by banking apps, the probability behind all of this is Twilio. Figma, a software design company, has also increased by 13.2% after the financial

is Twilio. Figma, a software design company, has also increased by 13.2% after the financial crisis. It provides a multi-person product design tool. In addition to these five companies, there

crisis. It provides a multi-person product design tool. In addition to these five companies, there are three network security companies with a bigger increase. CrossTrack and Pilot Auto, these two network security giants have already rebelled from the bottom 100% And Fortinet, a full-time network security company that does hardware and software, also rose by 20% after the financial report

This 8-company company looks like it's a very large business from the database to network security, from communication to design, it seems to be a big deal But when you put them together, there is actually an unnoticeable logic hidden in it Then we will combine their latest financial reports to draw a line and find the consensus The first more obvious signal is that these winners are all 2B software companies and

almost all are 2B software companies. This trend is different from all the large model companies that we shared with you before. The transformation from C to B is not a surprise this year. As the leader of this wave of AI, large model companies naturally led to the upgrade of business in all B-level service-based enterprises and naturally brought

them direct business growth. On the other hand, B-end services are more irreplaceable than C-end services, and the sensitivity of users is also lower. These software companies are almost the top of their own industry, and have been in the mining industry for many years.

Not only do they have a large user group, but most of them have a complicated ecosystem, and it is difficult for business users to leave their software services. On

the contrary, we see that C-end software companies are generally more sensitive and vulnerable in this financial crisis. For example, Intuit. Although they are not a simple 2C company, the decline of this financial report is largely due to the personal tax-accounting business TurboTax's softness.

This 2C software service is more likely to be hit by a large model. In

the past year, the AI sub-computer stock that the market was worried about was two points. One is that the AI wave no longer needs so many traditional employees, so

points. One is that the AI wave no longer needs so many traditional employees, so the traditional SaaS software has permanently lost a lot of users. The second is that AI models directly make similar software and directly compete with SaaS companies. The result also weakened the traditional SaaS user base. But in this financial quarter, these big companies have

told a completely different story. AI not only does not threaten their existing users, but will bring new income. For example, Snowflake. This quarter's income has increased by 34%. There

are further proposals based on the last quarter's 30%. The management said that the most important engine in this proposal is the two AI tools, Cortex Code and Snowflake Intelligence.

Cortex Code is an AI application that helps engineers write code in the Snowflake database, and Snowflake Intelligence is an AI agent in the Snowflake version. These two AI tools have already started to contribute income to the company and promote customer growth. The financial

data shows that in the past year, Snowflake has reached 779 large customers with more than $1 million, which is 29% of the total growth. You can see that the old users not only did not relax, but spent more money on bigger hands. On

the other hand, Datadog also recorded a growth of more than the previous year. This

quarter, the company's increase is up to 32.2%. Last time, the company had an increase of more than 30%, and it will continue to increase to the first quarter of 2023. This time, the increase also comes from AI. Guanlin said that the monitoring and

2023. This time, the increase also comes from AI. Guanlin said that the monitoring and observation needs brought by the company's AI workload have increased dramatically, and the AI native customer group has expanded by more than 20% in a year. Their newly launched monitoring GPU products directly brought them two super-large AI customers. It is rumored that one of them is the most popular one, Anthropic. The one that brings the most revenue is

Voice AI. This voice AI customer service brings a lot of new customers and new

Voice AI. This voice AI customer service brings a lot of new customers and new revenue to the company. Thanks to Voice AI's great success, the company's income this quarter directly accelerated from 12% to 16%. TIM also made a profit by using the AI tool Rovo. Rovo is an AI assistant that pays for the usage of points. The

tool Rovo. Rovo is an AI assistant that pays for the usage of points. The

company's new quarter's share use has increased by more than 20% with the use of Robo customers. The increase in ARR of the users is twice as much as that

Robo customers. The increase in ARR of the users is twice as much as that of non-Robo customers. The net income rate has also increased to 120%. It can be seen that Robo, the AI assistant, has not only become a revenue engine, but also led customers to buy more services and have a higher annuality. The income of Figma this quarter has increased by 46%, and has accelerated growth for two quarters in a

row. Figma is one of the most questioned software companies in this round, with its

row. Figma is one of the most questioned software companies in this round, with its share price falling by nearly 85% Everyone is worried that the big model can easily achieve the design of most products, and no more designers will be needed However, this time, the company not only did not have a slight decrease, but instead, under the encouragement of AI, the design of this thing has pulled more people into the workflow.

The financial report shows that the conversion of the Pro team to the payment plan has increased by more than 150% These are the companies that I chose for you to compare their performance with other software companies. I took them and compared them to other software companies. I found that what attracted these companies was a very specific point.

They all specifically achieved income growth through AI functions. If you only have AI applications and no corresponding income growth, that won't work. For example, Shopify, the company has almost spread the entire workflow of AI applications. Among all SaaS companies, it is considered an AI adoption leading company. But its income is just a heavy weight, and the stock price has still fallen sharply. On the other hand, even if AI is effective, it

is useless to use AI to reduce the cost and increase profits. For example, Workday, they use AI to achieve a lot of optimization internally, and their profits are far above the expected. But the income is flat, and the stock price has still fallen sharply after the financial crisis. So the conclusion is that you have to bring new,

predictable income through AI features. The market is only willing to reward companies like this.

As for what kind of company can achieve this effect, how do we choose a company, I will put it in the last unified sentence. Let's first analyze the consensus of all winners. The third common point of these big companies is the fee for the amount of money. Snowflake, Datadog, Twilio, these three companies are purely fee-for-money. Now they

have added the price of AI features on the original flow basis. while Team

and Figma are more special These two companies were originally paid by the market position After the AI came out they all opened a separate AI module that pays by volume The market is most concerned about is really pushing the stock market up which is the part of the public relations that is revealed in the financial reports the positive effect of the service of paying by volume Why is the market so interested

in the volume of the payment? Is this just a coincidence? Absolutely not To answer this question we have to understand the two hard-to-understand business in the era of AI in the traditional market position First, the market is worried that AI will bring in a wealth of employees. No longer needing so many employees, naturally no longer needing so many seats. Then the software company will naturally be affected. Second, in the age of

many seats. Then the software company will naturally be affected. Second, in the age of AI agents, tokens became the cost of software companies. Before, software companies were all made up of high-power people. More people use software, almost no new cost will be brought to the company. But now it's different. Users use AI to burn tokens, it's the software company's own money. The more users use, the more software companies lose. Software companies

originally wanted to use AI assistance, but it turned into cost burden. On the contrary, the volume of the fee is completely without these problems. Even if AI brings in resources, there will be no drop in the amount of use. For example, in the design industry, there may be fewer designers. That's because a designer can do more work than before. But the demand for design will not decrease. Instead, it will bring more

than before. But the demand for design will not decrease. Instead, it will bring more product design needs because AI has lowered the threshold of product design. For the cost of tokens, the fee for token is also easy to digest because the token cost itself is also the fee for token. In fact, the fee for token will not only not be affected but also be directly benefited from the AI application. In fact,

after the fall of AI agents, it has become easier for people to use software to perform tasks, so the demand will naturally increase. If software companies can successfully manipulate AI, then software with fee for token can quickly promote AI to reflect on actual performance. And because of this, we see more and more software companies starting to transform

performance. And because of this, we see more and more software companies starting to transform in the business model. Like TIM and Figma, which are doing pretty well. Of course,

there are also failed attempts. For example, HubSpot, a company that does customer management software, has dropped 19% because of the failure of transformation and low income. But now it's too early to talk about success and failure. These transformations are not all positive. I

will analyze this later. Now we can at least see that the volume of fees is becoming the only way out for software companies in the AI era It is also the easiest company to make money directly from Adjantic AI in the current market Now we have found these winning companies through the software stock financial reports They

are: 1. 2B software, especially 2B software, is obviously better than 2C or 2B software

are: 1. 2B software, especially 2B software, is obviously better than 2C or 2B software 2. AI has clearly brought in new income, not just application AI or down payment

2. AI has clearly brought in new income, not just application AI or down payment Third, they use their business model as a price to charge or to introduce a price to charge model and successfully do it. The companies with these three characteristics are more likely to take the lead in the outbreak of stock price. And the same

goes for the companies that are against these three characteristics. It's much more difficult to get market recognition. Then someone said, is it just a coincidence that you are looking for a consensus? Can these communists be repeated in the future? In fact, from the above analysis, you can see that these three points of cohesion have a clear underlying logic support, not just the performance. In the air investment layout video at the beginning

of the year and in the recent red-light analysis, I have analyzed these logics with you in advance. This financial season is just a market that finally verified them. This

is why we can find the reason for Snowflake in the dark. But it's not enough to just have these. I have some deeper discoveries in further research. First of

all, I think from the current market's trading logic, the risk of AI subversion of software stocks as a whole may have been pressed in. I have analyzed the risk of AI subversion of software stocks many times before. I think the AI subversion theory does exist. This risk will indeed systematically suppress the valuation of the entire software industry

does exist. This risk will indeed systematically suppress the valuation of the entire software industry for a long time. So has this financial report solved the problem for these companies that have grown? No. Even if some of these companies have increased their usage, some have increased their market share, and some have made new AI functions, But to be honest, these bright performance can only show that it is doing well in the short

term, but it can't eliminate any long-term AI subversion concerns. But what do we see?

Even if the AI subversion concerns are not resolved at all, the market will also recognize their performance because of the short-term performance line. This may mean that after a half-year of valuation rebate, the risk of AI subversion has been completely pressed in. And

this is very important. Because the risk is under the premise of "press in" The opportunity becomes more worth paying attention to I said that AI is actually an incentive for most software companies, not a threat And in the background of AI application layer transformation, there is a very good chance that software stocks will run out of opportunity

first In addition, we must admit that AI is actually making software stocks more useful and the threshold is lower Starting from the principle of low-value, under the premise of risk-free, a product is more useful, then it is destined to have more people to spend more money, spend more money and be more year-round. So maybe at this stage, at the stock level, who benefits and who threatens still exists uncertainty. But for the

entire software stock, at this time, I think it is a very high moment of profit-risk ratio. Then software stock ETF, IGB is a good choice. If you are not

profit-risk ratio. Then software stock ETF, IGB is a good choice. If you are not satisfied with the overall industry and want to find a more explosive opportunity in the industry, what should you do? First of all, the three points of consensus mentioned earlier or the three investment logics are absolutely worth referring to. In addition, we also found that those software that is more on the infrastructure level have a better chance of

winning and their risk will be relatively low. For example, Datadog, Twilio, Snowflake, these three companies are on the infrastructure level. Some of them are essential software for AI large models, some are essential accessories for cloud manufacturers, and some are the bottom-level service providers of large companies. Another major category we just mentioned is network security companies. They are

also the same principle, they are all the bottom-level infrastructure that must be in the age of AI. We just said that this type of company can come out because of 2B and the amount of fees, but these are actually just the performance. The

real core is that their needs are directly linked to the amount of use of AI agents. The more AI agents are used, the higher the income brought to these

AI agents. The more AI agents are used, the higher the income brought to these companies, and the closer to the basic layer, the better the value of AI is calculated. And we can almost be sure that this year will be the year of

calculated. And we can almost be sure that this year will be the year of the outbreak of Agentech AI. Related software companies have a very high potential for growth and are relatively more sure. In other words, this network security company is a relatively special type. Unlike the other three, network security is not a performance-driven growth, but a

special type. Unlike the other three, network security is not a performance-driven growth, but a news-driven growth. In early April, Astropic was going to launch its new model, Mesos. But

news-driven growth. In early April, Astropic was going to launch its new model, Mesos. But

the company announced that because the model was too powerful, it might bring network security issues, so it planned to postpone it. This news made the market aware of the huge demand for network security software. Therefore, CrossTrack and Palo Alto have nearly doubled their sales after this news. But the problem is that Cloudflare and Zscaler, which have already

issued financial reports, are not doing well. So their demand is indeed there, and they are strong in certainty. But whether the performance can be realized in time still depends on the variables. In this research, I found that some AI tools companies were very embarrassed. On the one hand, we see companies like Team and Figma, which

bring performance growth with AI functions. On the other hand, we also see more companies like Microsoft, Salesforce, and Shopify. They are all very happy about AI functions, but their real contributions are completely in vain. In fact, this reflects the embarrassing status of the current old-fashioned software companies. Most of these companies are paid by the market. They are

now forced to convert to the volume charge. For example, Microsoft's GitHub Copilot is about to convert to the volume charge. The team I mentioned before is also converting to the volume charge by AI tool Rovo. But the problem is that just the conversion of the payment model can't save them. Their real problem is that they can't keep up with the big model. For example, Microsoft's M365 Copilot. Why do you think it's

not easy to use? Because the current big model has entered the age of AI agents, AI can go directly to perform tasks. We call it Harness Engineering. And the

M365 Copilot is still in the last generation. AI understands the stage of the problem by the above and below. That is the so-called Context Engineering. So of course users don't like to use the backward products of the previous generation. So we would rather connect Office to the big model to perform tasks, and not use AI on the Copilot in the Office. while the Microsoft Copilot is definitely not a special case. As

long as software companies develop their own AI applications, they will inevitably face this problem.

They will always slow down the polishing process. When the previous generation of features is just polished, the next generation of layers of polishing will probably directly subvert the logic of use. This is the most embarrassing part of traditional software companies. Before the polishing

of use. This is the most embarrassing part of traditional software companies. Before the polishing is completely done, this problem will always be around all software companies. So I think, software companies that simply have AI applications will not build up new interlaces for themselves.

AI is now more like a commodity. Anyone can use it. The effect is basically the same. Don't expect anyone to develop a new AI function and let themselves fly.

the same. Don't expect anyone to develop a new AI function and let themselves fly.

That's not possible. So I'm more cautious about companies like TIM that want to turn over a small AI function. At present, it is still most likely that the companies that lead this round of AI applications are the leading models. But that doesn't mean that software companies have no chance. In my opinion, they have a huge potential to

grow just by drinking soup. In the AI era, their real advantage is no longer the technical capabilities we talked about before, but their ability to define needs. It is

the complex ecosystem they have established, and it is their solution to a series of problems such as data security, rules of thumb, and token usage efficiency. As I have always emphasized, AI is indeed a threat to some software companies, but it is more likely to promote it to more software companies. This is also the basis for me to look at software companies at this time. I'm saying this today to let you

know that even if you are good at software, you can't be brainless. You must

know their problems. We need a reasonable expectation to make long-term investments. Well, that's all for the initial analysis of software stocks. Finally, let's make a summary. Through the financial reports of dozens of software companies, we found that those 2B companies that charge the amount and bring income through AI are the most likely to be the first to

explode. At the same time, I think the software with the basic facilities is now

explode. At the same time, I think the software with the basic facilities is now the most worth paying attention to because they directly hook up to the use of AI. On the other hand, companies that are alone testing AI functions and want to

AI. On the other hand, companies that are alone testing AI functions and want to transform may need longer time to prove themselves. Finally, standing at this time, I think the risk of AI subversion has been fully pressed in. It's time to pay attention to the opportunity of the entire software stock to appear. Today's research perspective is to find the possible opportunity to invest in the past and find a repeatable investment. We

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