Top fund Coatue's latest thoughts: How AI is changing investment?

When everyone is chasing after ChatGPT and generative AI, the giant investment firm Coatue, which manages nearly $70 billion and focuses on technology and innovation, is pondering a deeper question: How will AI reshape the underlying logic of the entire investment industry? In a conversation on the Sourcery podcast with Molly O'Shea, Michael Barton, head of the technology sector at Coatue, draws on his experiences navigating market bull and bear cycles, witnessing the volatility of the GameStop incident, and the hundredfold growth of AppLovin to explore how investors should rethink "real competitive advantages" in the AI era.

From the AI-driven transformation of the digital advertising industry to the AI-native evolution of workflows within hedge funds; from the changing market structure driven by retail investors to insights behind OpenAI's valuation logic—Barton shares how Coatue builds information barriers between primary and secondary markets and presents a compelling argument: The greatest dividends of AI may not belong to new unicorns, but rather to existing great companies that become stronger through AI empowerment.

This is a conversation about the deep evolution of investment methodology, recommended for all readers interested in technology investment and the AI industry.

01. After GameStop: Investment Enters the Social Media Era

The GameStop short squeeze incident in early 2021 was an earthquake for Wall Street. For Michael Barton, this earthquake was particularly intense—at the time, he was working at Melvin Capital, the hedge fund that lost 50% of its assets in two weeks due to shorting GameStop.

"At that time, we might have been the best-performing hedge fund in the world, but we didn't realize how powerful retail investors could be when they focused all their energy on a single stock." Barton recalls that experience calmly, but it clearly profoundly changed his understanding of the market.

This was not a traditional "short squeeze." Past short squeeze events always had clear catalysts—such as the potential acquisition in the Volkswagen-Porsche case. But GameStop was completely different; its driving force came from countless ordinary people on internet forums who spontaneously organized through platforms like Reddit and Twitter to collectively buy a particular stock, ultimately triggering a frenzy in stock prices.

This fundamentally changed the risk framework of investing. Previously, investors primarily focused on fundamentals, valuations, and industry trends—these "traditional variables." Now, social media sentiment, retail participation, and online buzz have become key indicators that must be tracked. "If you go to Wall Street Bets now, you'll find that what people are posting there is real research work." "Barton said, "The way information is disseminated has completely changed."

This change brings not only risks but also opportunities. In the new market structure, ideas can come from anywhere—no longer limited to quarterly earnings reports, management conference calls, and The Wall Street Journal. Now, a business model innovation that is being fervently discussed on Reddit, or a product experience that has been shared tens of thousands of times, can all be clues for uncovering investment opportunities. Coatue now tracks the frequency of stock mentions on Reddit, analyzes trends on Twitter, and pays attention to various discussions online—these have all become part of the investment decision-making process.

02. Discovering AppLovin: The First Real Business Battlefield for AI

What truly solidified Barton’s position at Coatue was his experience discovering and betting on AppLovin. This story well illustrates how investment opportunities are captured in the new information environment.

The name AppLovin sounds like a "meme," easily mistaken for a joke company. But at that time, this company, valued at about $20 billion, primarily focused on advertising in mobile games—when you see people around you playing card games or Candy Crush on a plane, the ads in those games are likely provided by AppLovin.

Barton initially knew nothing about the company until a friend pointed it out: "You should take a look at this company; although it's still small, something unusual is happening, and its growth rate has suddenly become very fast."

So Barton invited AppLovin's CEO Adam Foroughi to the Coatue office. "I will never forget that moment," Barton said, "within five minutes of meeting Adam, I texted my then-boss saying: 'You have to come meet this person right away.' He replied: 'I'm busy.' I said: 'Trust me.'"

What excited Barton so much? The answer is: he saw early evidence of AI starting to generate real revenue in the digital advertising space, and AppLovin was at this turning point.

To understand this, one must first grasp the essence of digital advertising. Platforms like Facebook and Google have a core goal of "showing the right ad to the right person at the right time." All the advancements in AI over the past few years—large language models, machine learning optimization—have directly enhanced this ability for "precise matching."

When Barton first joined Coatue, he needed to argue why Facebook's ad revenue could grow by more than 10%. At that time, Facebook had just experienced Apple's IDFA (Identifier for Advertisers) Impact of Policy Changes - Apple has restricted the ability of apps to track users, leading many to question whether Facebook can maintain double-digit growth. However, two years later, Facebook's advertising revenue growth exceeded 25%.

"This was almost unimaginable at the time," Barton said, "but the underlying advertising engine has improved due to AI."

The situation for AppLovin is even more dramatic. Adam Foroughi told Barton that they applied GPUs (graphics processing units) to their advertising business, and advertising revenue, which was originally growing at 15%, suddenly began to grow at rates of 50% and 70%.

"I remember after hearing him speak, if you believe what he said is true and then plug those numbers into a discounted cash flow (DCF) model, even in the most pessimistic scenario, you can't get the valuation below three times the current market value," Barton said, "This is the most incredible thing I've seen in my career."

Here, a brief explanation of the DCF model is needed: it is a core tool in valuation analysis that predicts a company's future cash flows and then discounts those future cash flows to today's value using a "discount rate" (reflecting the time value of money and risk). If a company's present value of future cash flows under "the most conservative assumptions" is three times the current market value, it means the stock is severely undervalued.

The story of AppLovin reveals the first main battlefield where AI creates real revenue: digital advertising. This is not generative AI, nor is it chatbots, but rather machine learning accelerated by GPUs, making ad placements more precise. The advertising revenue growth rates of companies like Meta, Google, and AppLovin have all significantly accelerated under the influence of AI.

"The first real use case of AI is to drive the growth rate of these advertising businesses beyond your expectations," Barton summarized.

03. Where is AI Revenue: From Advertising to Agency Business

When people worry about an "AI bubble," the most common question they raise is: hundreds of billions of dollars are being invested in AI infrastructure, but where is the revenue? ChatGPT charges $100 per month; how can that possibly support such massive investments?

Barton’s answer is straightforward: If you look closely, you'll find that AI revenue actually already exists in large amounts; it's just that its forms are different from what many expect.

First is advertising, which is the largest source of actual revenue created by AI. Two years ago, the market might have expected Meta's advertising revenue to grow by 15%, but the actual growth reached 25%. That extra 10 percentage points of growth—hundreds of billions of dollars in incremental revenue each year—comes from AI. Google search advertising was originally expected to grow by less than 10%, but now it has grown by over 15%. This is not theoretical future revenue, but today's financial report numbers Secondly, there is the improvement of recommendation engines. "You may have noticed that the Reels (short videos) recommended to you on Instagram have become more addictive," Barton said. Data shows that the average daily usage time of Instagram users has increased by 15% over the past six months—from 40 minutes a day to 46 minutes. This is because Meta has utilized GPU computing power in its recommendation system, allowing the algorithm to more accurately predict what users want to see. Longer usage time means more opportunities for ad displays, which is also a direct revenue brought by AI.

But the more transformative change may still be ahead: Agentic Commerce.

In the old world, the shopping process was like this: you want to buy something, you search for "red skateboard shoes" on Google, and Google shows you a series of results. The next stage might involve going to Gemini or ChatGPT, entering the same request, but because AI knows more about you—your style preferences, purchase history, budget range—it can recommend more suitable products. In this model, there may not be traditional "advertising" in the conventional sense.

However, Barton believes the most disruptive scenario is: "Many times, the product ads you see on Instagram, the things you click to buy, are actually not 'impulse purchases.'" He cites the viewpoint of Shopify founder Toby Lütke: "These are actually things you've always secretly wanted, but no one has ever shown them to you. You would never actively search on Google for that special steak knife, but when it appears in front of you, you buy it."

Now imagine this: you are chatting in ChatGPT or Gemini, and the AI is not passively waiting for you to ask questions, but actively says: "Hey, you're going on a skiing trip, I think you might need a new ski jacket." Or: "Based on what we discussed in another conversation, I found this product that you might be interested in."

This will significantly boost consumer spending. From the merchants' perspective, they may have previously spent 20% of their revenue on marketing (most of it going to Meta and Google), with 2% paid to platforms like Shopify. In the era of Agentic Commerce, the distribution of this profit pool will change—more will flow to Shopify or the AI agents themselves (OpenAI, Google), but overall marketing spending may increase because conversion efficiency is higher.

"It's still early days," Barton emphasized, "OpenAI announced integrations with Shopify and Etsy a few weeks ago, but today's products are not good enough yet. However, you can see where it's heading."

04. AI Speed: Winners and Losers are Being Repriced Every Day

In the AI era, the biggest challenge in investing in tech stocks is not judging long-term trends, but adapting to the speed of change.

"I have worked at Coatue for eight or nine years, and I have never seen a moment like this," Barton said. "A few private equity firms are influencing such a massive public market capitalization."

He mentioned that a16z partner Alfred Lin said at an AI conference: "What happened three months ago is no longer relevant. What happens today will also not be relevant in three months. Things are changing too quickly; you have to stay active, keep paying attention, and collect as many data points as possible to adjust accordingly."

This rapid change is reflected in daily investment decisions. Stock prices fluctuate daily, and in the AI era, any signals about "AI winners" or "AI losers" will be priced into stock prices extremely quickly.

Barton gave a vivid example: OpenAI recently held a Developer Day event. If your company is mentioned in the presentation, the stock price can instantly rise by 5%. "The funniest part is Mattel—a company that isn't even a tech company. They were mentioned in the presentation, and the stock price immediately jumped by 6%."

But there is a paradox: is being integrated into the OpenAI platform good or bad for a company? In a sense, if everyone uses your service through ChatGPT, you might be "commoditized"—the user relationship is controlled by OpenAI, and you are just one of many suppliers. But the market will rise first out of respect, as this at least proves you are "related to AI."

This is what Barton means by "winners and losers are being priced every day." Any sign that shows you are an AI beneficiary or victim will be immediately reflected in the stock price. This requires investors to understand the implications of technological changes in real-time.

"That's why we spend a lot of time not only communicating with the CEOs and management of public companies but also talking to private equity firms, engaging with OpenAI and Anthropic, and communicating with researchers—because these people are in contact with this technology every day, and they have super interesting insights," Barton said. "If you are just sitting in front of your computer building models and predicting the next quarter or the next five years, you will miss these big waves."

05. Coatue's Unique Advantage: Bridging Public and Private Markets

Coatue manages about $70 billion in assets, with approximately $25 billion in public market stocks, and the rest distributed across private equity and credit businesses. This structure is not common among large asset management firms, but it creates a unique informational advantage.

"The most successful aspect of Coatue, both in the past 20 years and today, is that we stand at the forefront of technology," Barton explained. " Technology emerges in different forms—Web 1.0, Web 2.0, mobile internet—each wave of technological change produces winners and losers, and new markets "We believe the biggest wave right now is AI."

This is not a unique insight—everyone knows AI is important. But Coatue's advantage lies in the way information flows.

When Barton needs to understand how AI affects public market companies (like Google, Meta, Nvidia), he can communicate directly with the private equity team, which maintains close ties with cutting-edge labs like OpenAI and Anthropic. Conversely, when the private equity team evaluates an AI startup, Barton's deep understanding of the digital advertising market and cloud computing market can provide critical perspectives.

"I will never forget a conversation in the summer of 2024," Barton said. At that time, the market was in an "AI panic"—hundreds of billions of dollars were poured into infrastructure, but aside from ChatGPT, people couldn't find other clear sources of revenue. Related stocks plummeted, with utility companies, infrastructure companies, and many tech stocks falling 15-20% within three weeks.

At that moment, Barton had a conversation with a chief engineer from xAI (Elon Musk's AI company). The engineer said: "Let me tell you how I see this. Today's technology—the model from July 2024—is good enough to support many applications that can generate revenue."

He used a metaphor: each AI model is like a child; with every breakthrough in model architecture and every time more GPUs are used for training, this "child's" IQ improves. "At that time, he said, I think today's IQ is about 100." Barton recalled, "An IQ of 100 can do a lot of work in this economy. But remember, it's a child; a child can't work immediately. You need time for the child to 'grow up' and learn how to use these abilities."

The core of this insight is: the technology is good enough, but there is a time lag from technological maturity to application landing. A year later, this prediction proved correct—programming assistance tools (like Cursor, GitHub Copilot, Cognition, etc.) began generating significant revenue, and applications in other areas also emerged.

This cross-market flow of information allows Coatue to see technological trends earlier than pure public market investors and to understand better how these technologies create value in scaled companies compared to pure private equity investors.

06. How Coatue Prices Stocks in the AI Era

For a hedge fund focused on technology investments, valuation methodology is crucial. Barton explained how Coatue prices stocks in the rapidly changing AI era.

"Coatue's core focus is on picking long-term winners," Barton said, "which means investing over a multi-year time horizon. For example, for Meta, I currently have a model predicting its revenue, EBIT (Earnings Before Interest and Taxes), profits, and free cash flow by 2031. I am forecasting its long-term performance, what kind of valuation multiple the market will give it at that time, what the stock price will be, and what the return rate will be." "**

They also use DCF analysis—discounting the future free cash flows generated by the company to today to calculate the 'intrinsic value.'

But having a long-term view is not enough: 'Stock prices fluctuate every moment. So you must have a long-term view of a company—what will happen in the industry, whether they are gaining market share, how profit margins evolve, and how earnings change. But you also better have an accurate judgment about the next quarter's situation.'

The evolution of the hedge fund industry is quite interesting. In the early days, investors like Julian Robertson (founder of Tiger Fund) and Phipe invented the method of 'fundamental analysis + multi-year investment cycle'—doing in-depth research, holding long-term, and ultimately being proven right.

Then came shorter-term oriented strategies that focused on quarterly performance using new data sources like credit card data. Next was the multi-manager model—each manager focuses on their own sector, digging for excess returns (alpha), while the fund level controls other risk factors to maintain market neutrality.

'Now, I think the winning strategy is: you need to have a clear judgment on who the long-term winners and losers are, while also paying close attention to the short term.' Barton said, 'I spend a lot of time on the short term because I believe the long term is just a series of quarters.'

Understanding the path from now to long-term goals is crucial, as it also creates trading opportunities. Barton gave the example of Netflix: 'You know what the endgame for Netflix will be, but every time there’s a small setback, the stock price might drop 20%. You need to ensure you’re not heavily invested before the stock price drops—even if you are a long-term investor, it would still be a very bad day in the office. But you also need to know when these drops are overreactions, so you can increase your position during the pullback.'

This approach requires a continuous real-time understanding of industry dynamics, rather than just building a five-year model and waiting.

07. Is OpenAI's $500 billion valuation reasonable?

When it comes to AI investment, the topic of OpenAI cannot be avoided. This company recently completed a new round of financing, with a valuation of about $500 billion. Many people question whether this valuation is reasonable.

'We are investors in OpenAI,' Barton stated directly, 'A $500 billion valuation seems reasonable to me.'

His logic comes from comparisons in the public market: 'OpenAI has about 800 million weekly active users, and the time users spend on it—according to my estimates—is close to the time they spend on Instagram. Facebook (Meta) is a $2 trillion market cap company. OpenAI is valued at $500 billion.'

'Can OpenAI grow from $500 billion to $2 trillion, reaching the level of Facebook today? By the way, I think Facebook will triple in five years, reaching $6 trillion. So if $2 trillion becomes $6 trillion, how much can $500 billion become? "The basis for this valuation is:

1. There is already a huge user base and frequency of use.
2. A moat is being built in real-time— the more users use it, the deeper ChatGPT understands the users, and the better it can serve them.
3. There is significant optionality— they might develop social features (like Sora video generation), potentially establish cloud services, and there are many possibilities not yet included in the models.

"Even if the foundational model can operate, it is already reasonable. If you add these additional opportunities, along with the talent density you have, with a CEO actively acquiring computing power and infrastructure, building data in real-time, and they have this cultural zeitgeist— it makes sense."

But Barton also acknowledges that investing in the AI field has become more challenging: "With AI, starting a company has never been easier. With just programming agents, two people in a dorm can build software that was previously impossible to create. So you see a surge of new companies."

The Total Addressable Market (TAM) is indeed enormous: global labor spending is about $20 trillion, and the software industry is about $1 trillion. "So that $20 trillion could potentially be impacted by AI— the market opportunity is huge. But picking winners and losers in this field is really difficult."

The biggest risk is being "Sherlocked"— you invest in a startup, and then at OpenAI's developer day, they release an integrated version with the same functionality, and your investment target is instantly commoditized.

08. Betting on Reddit: The Misunderstood AI Data Goldmine

Barton emphasizes that in the AI era, differentiated data analysis capabilities have become more important. He shared the case of Coatue's investment in Reddit, demonstrating how unique insights can be gained through data science.

Coatue is an investor in Reddit. "We like CEO Steve Huffman, we like this team. We believe Reddit will become a bigger business and a great advertising platform. In the AI era, there is actually only one place where real human-generated content exists— and this content is highly valuable because it can help train models."

Consider a scenario: if OpenAI wants to build a shopping assistant, where are all the product reviews in the world? On Google. Today, they are not on ChatGPT. So where do they have to go? To Reddit. "How much would they be willing to pay Reddit to use this data to ultimately build a shopping assistant that will dominate the market? The answer is: probably a lot."

But at some point, Reddit encountered a small setback. User growth stagnated, related to AI Overviews. In the past, when you searched for a question on Google, Reddit links often appeared in the top results But now Google has launched AI Overview—an AI-generated answer summary at the top of the search results page, taking up a large amount of screen space, pushing Reddit's links down.

"The market's reaction is panic," Barton said, "because it's easy to conclude: Reddit's growth was just due to Google driving traffic, and now AI Overview has taken their spot, this company will never grow again. That's it—stock prices plummeted."

But Coatue's data team conducted an in-depth analysis. They found:

• In the old Google search, Reddit links appeared about 10% of the time (this is a representative figure).
• When AI Overview was first launched, it only covered 5% of searches, and within that 5%, Reddit was cited 2% of the time—indeed lower than 10%.
• But two months later, AI Overview covered 50% of searches, and within those overviews, Reddit's citation rate rose to 15%—actually higher than the old world’s 10%.

"The moment we saw this data, our conclusion was: first, these issues will be fixed. Second, this proves that Reddit is actually more valuable in the AI world because it is shown more frequently—because users want to see Reddit's answers and citations."

This is how data science creates investment advantages: not simply tracking sales data or user numbers, but understanding the mechanisms of technological change, quantifying its impact, and drawing the correct conclusions faster than the market.

"With confidence in this data, you can say: I figured out the technological change, now we are more optimistic about this stock, and we know user data will recover. Then the narrative will change—from 'uncertain whether AI is a winner or loser' to 'they will be AI winners.' This means valuation multiples will increase, and when the market realizes this, stock prices will soar."

09. How AI Will Change Employment: Not Layoffs, But Hiring Freezes

Regarding the impact of AI on employment, Barton has a distinct view: "Any job in the U.S. that requires working in front of a computer may eventually be automated—including my job."

But his view is not the doomsday scenario of "AI will lead to mass unemployment." Instead, he believes the change will occur in a more subtle yet equally profound way.

"There are now two camps," Barton said. "One camp believes AI will make workers ten times more efficient, so companies will want to hire more workers—if your employees are ten times more efficient than your competitors, you certainly want to hire more people. The other camp believes efficiency gains will far exceed ten times, and companies will choose not to increase headcount."

Barton stands in the second camp. "My dream is that instead of having a few analysts working for me, I have 20 AI agent analysts, and those two real analysts each have 20-30 agents working around the clock." "**

But the key change is not "layoffs," but "hiring freezes." This trend can be seen from macro data: in the past, the revenue and workforce of large tech companies grew in sync—20% revenue growth, 20% increase in headcount. Now, what happens if a company's revenue continues to grow by 20%, but the number of employees remains flat?

Profit margins will significantly increase, earnings per share will accelerate, and stock prices will soar.

"This is good for the stock market," Barton bluntly stated. "I believe this will happen across all industries."

But he also recognizes a deeper issue: "If many jobs in various industries are replaced, first, what will these people do? Will new industries emerge for them to work in? Second, if not, Amazon's stock price may rise significantly, but if unemployment is high, who will buy products on Amazon?"

Barton is relatively optimistic that changes will occur more slowly than the alarmists expect, and that new industries will emerge. But he emphasized one point: "This is one of the important reasons why ordinary Americans should invest in the stock market right now. Because AI will benefit these companies, the stock market will rise, and we may be at the beginning of a multi-year bull market—these companies' revenues will grow faster, costs won't be as high as you expect, profit margins will improve, and the market will rise."

In other words, in the age of AI, having capital is more advantageous than having labor—this has profound implications for social distribution.

10. The AI Transformation of Hedge Funds

If AI is to change all industries, hedge funds are no exception. And Barton is driving Coatue through a profound workflow transformation.

"One important theme at Coatue is that we will apply the technical practices learned from public and private companies to ourselves," Barton said. "Phipe (Coatue founder) and Thomas are early investors in cloud transformation, so Coatue itself has also become a cloud-native company. When the best companies start talking about how to leverage all this data and conduct data science analysis, we built our own data science platform—which has been very useful over the past few years."

Now, the same logic is being applied to AI. "My belief, and something I spend a lot of time thinking about, is how we use AI internally, how we build future-oriented workflows, especially in financial services companies—whether hedge funds or banks—who are often the last to adopt technology. So we see a huge opportunity to create a 'future investment fund,' and that is happening."

Barton once told a friend something that sounds like a joke, but he is serious: "85% of the work I do today can be done by AI. This is not a question of whether the technology is ready, but how we implement the technology." They are recruiting a group of new analysts specifically to help solve this problem—reimagining every aspect of the investment process:

• Checking emails in the morning and reading all the sell-side analysts' research reports—this used to take two hours because you had to read them all, but only a few were truly important. Can AI filter and highlight the key content?
• Building financial models—can a complete model be generated with the click of a button?
• Integrating different data sets—can this process be automated?
• Every step of the investment process—can AI almost completely automate it?

"If you can do this, the six new analysts we hire will become sector heads with 25 around-the-clock working agents in three years," Barton said.

He is very confident in his work: "The benefit of the hedge fund industry is that it is not labor-intensive, so we don't need to cut labor costs. What we need to do is exponentially enhance our capabilities—we are looking for investment ideas, and the limiting factors are time and energy. I only have so much time to explore different areas. But if I have 25 agents working around the clock, I truly believe we can find better ideas faster."

More importantly, he believes this will create a competitive advantage: "I don't think other companies will adopt these technologies as quickly; we will be far ahead."

This is also Coatue's philosophy for hiring new analysts: "We will teach you the investment process, but we will reimagine how to do it with AI together. Three years from now, when you become a full-time analyst, you will be much more efficient than your competitors, who are just starting to engage with these things."

11. Advice for Investors: Positioning in the AI Wave

As the conversation neared its end, Barton summarized the investment opportunities in the AI era.

"I think this is the best time to be alive," he said, "this is the most exciting moment for investing in the public markets."

The reason is simple: AI will make great companies greater, and the speed may be faster than most people expect.

"If these companies' revenue growth accelerates, costs are not as high as you expect, and profit margins improve, the market will rise. We may be at the front end of a multi-year astonishing bull market."

But he also emphasized that risk management is crucial in a portfolio highly concentrated in technology. Here he specifically mentioned a core capability of Coatue founder Philippe Laffont: "One of Philippe's most amazing qualities is his risk management ability. He has a sense—he can feel when things are about to go wrong. It's truly incredible."

During market volatility, Philippe can quickly "cut total exposure"—reducing from a 100% position to 50%, holding 50% cash, and often timing it very accurately. "When Trump pulled out that board with the tariff prices written on it, I remember sitting there thinking, 'Oh my God,'" Barton recalled. In such moments, quickly reducing risk exposure is crucial Another suggestion is about how to persuade decision-makers. "Many people can pick stocks, but at Coatue what really matters is: can you do the analysis well, can you pick the bullish stocks that will rise and the bearish stocks that will fall, and then—crucially—can you persuade Phipe, Thomas, and the rest of the team to believe you are right, ultimately putting that stock into the portfolio and making it happen."

Barton has seen many smart people who are good at stock picking and have great ideas, but they can never persuade their superiors to include those ideas in the portfolio. "I think the most important thing is: you spend 95% of your time doing in-depth work and analysis, but can you condense that thousand-line Excel model, all the expert interviews, all the details about profit margins and growth rates, into a three-sentence investment thesis—when he hears that thesis, he is almost ready to buy the stock before even opening the model, because that thesis is so good."

"That is a skill I am still learning," Barton candidly said, "Thomas (Phipe's brother) may be the best I have seen in this regard. He can distill extremely complex things into three sentences, and when you hear it, you think: 'That's a good idea.' Then you dive deeper into the model and details to show why it will happen. But you have to spend a lot of time thinking about how to make the investment thesis very simple and then put it into the portfolio."

Conclusion:

This conversation reveals the core truth of investing in the AI era: true commercialization is not about ChatGPT subscription fees, but about enhancing digital advertising efficiency, algorithm optimization, and margin expansion; information advantages no longer come from static analysis, but from real-time cognitive flows across public and private markets; transformation is not about layoffs, but about reshaping profit distribution by halting hiring. In an era where technological iterations occur every "three months," the essence of investing is changing—it is no longer about predicting the future ten years from now, but about gaining insights into the present at a faster pace and expressing them more precisely to help the market understand your judgment. Investing has never been so close to technology and action itself. This is an era for doers.

Original source: FuturePlause, original title: "The Latest Thoughts from Top Fund Coatue: How AI is Changing Investment?"

Risk Warning and Disclaimer

The market has risks, and investment requires caution. This article does not constitute personal investment advice and does not take into account the specific investment goals, financial situation, or needs of individual users. Users should consider whether any opinions, views, or conclusions in this article are suitable for their specific circumstances. Investment based on this is at their own risk