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EP694 | 🥖

Gooaye 股癌·8 min readFinance
Key points
  • AI tools will cause a surge in content supply, but audiences will still rely on familiar, trustworthy creators; cheaply made work will be filtered out even more easily.
  • Public-market investing emphasizes momentum, while entering early-stage markets calls for a return to value investing: deeply researching teams and products, then supporting companies through long-term compounding.
  • Taiwan should not focus only on gaining visibility overseas. It should build successful examples of investing in local startups and content teams, proving that Taiwanese IP can become a long-term asset.
  • AI stocks still have strong fundamentals, but the benefits have already been priced into many large companies. For now, reduce leverage, stay patient, and wait for the market to shift back toward momentum.

AI Creates More Content, but Makes Trust and Great Work Scarcer

The host believes that as AI tools and platforms become widespread, anyone will be able to quickly create games, videos, and other media. Content supply will indeed increase substantially, but that does not mean content as a whole will lose its value. Audiences can still tell whether a work is creative and polished, and they will continue to actively follow familiar directors, producers, and studios.

The teams most likely to be eliminated are those that merely want to copy products while they are popular and lack core ideas. As choices multiply, credibility becomes an even more important filter. Once creators burn their reputations chasing quick money, the market can easily keep a permanent record, and may not be willing to give them a second chance. Good content may actually stand out more easily, like a lighthouse amid a sea of rough, low-quality work.

Public Markets Chase Momentum; Early-Stage Investing Returns to Value and Patience

The host explains that AI-related investments in public markets often use momentum trading: even without fully understanding a company’s technical details, investors may trade on the expectation of rising prices as long as they confirm that the business has meaningful AI exposure and is riding the market wave. The reason is that by the time the industry logic becomes completely clear, the stock price has often already risen in anticipation.

But after entering the early-stage market, the strategy is exactly the opposite. Investment teams deeply study the founders, product pipeline, and execution capabilities, then hold their investments for the long term through an evergreen fund, hoping to grow alongside the companies. This approach does not depend on short-term themes; it builds returns through team quality, accumulated product value, and long-term compounding.

Taiwan’s Content Industry Needs Case Studies, Not Vague Internationalization

The host believes that internationalization is not simply reading overseas media, discussing foreign markets, or treating AI as a social talking point. A more concrete approach is for Taiwanese capital to invest overseas and help local teams bring their products to global markets. Taiwan’s market may be small, but it has abundant capital and strong consumer spending on games and anime, giving it a solid environment for cultivating content companies.

Nanfang Capital hopes to serve as infrastructure for the content industry, helping teams handle fundraising, contracts, agents, and distribution channels—areas that creators may not be good at. Citing existing Taiwanese game teams and successful titles as examples, the host believes that once enough case studies accumulate, the market will gradually come to believe that game IP is not merely a dream or a one-off product, but a long-term asset capable of generating ongoing revenue.

Small Studios Can Use AI and Global Distribution to Increase Their Odds of Success

The host compares startup game teams to IC design companies: the team handles the design, while AI tools and game engines are like production equipment available for rent, and Steam provides global distribution and exposure. This division of labor reduces the cost of building servers, hiring large numbers of engineers, and establishing distribution channels independently, giving small teams a chance to bring their work to a global audience.

In the past, the game industry tended to follow a “one hit means success, failure means shutdown” Hit-Driven model. If capital can be spread across multiple teams, it may increase the odds of producing successful titles consistently and allow strong IP to attract new players repeatedly in the long tail of the market. The host hopes that real-world examples over the next few years will prove this model viable.

泚意

“Diversifying investments across multiple teams increases the odds of success” remains an intuitive claim. It does not explain how success is defined, the observation period, or the benchmark for comparison with the old Hit-Driven model. If we look only at the successful IP that eventually emerges, it is easy to overlook the failures. When evaluating this kind of model, first ask what metrics it uses to prove that it has actually improved the odds of winning.

AI Fundamentals Remain Strong, but Stock Prices Have Entered a Phase Requiring Patience

The host points out that the market has recently shifted from the strong momentum environment of April through July to a volatile, range-bound pattern. If investors continue chasing highs and cutting positions in a hurry, significant losses could appear within a few weeks. By contrast, reducing exposure and holding companies whose fundamentals continue to improve may still allow net worth to rise gradually. The market may not have become worse; there are simply fewer short-term opportunities to chase.

On the earnings front, Broadcom provided strong medium- to long-term guidance. The host believes that demand for AI infrastructure, optical communications, and interconnects remains real, and that a temporary lack of share-price appreciation should not be used to infer that the company’s fundamentals have weakened. Microsoft also continues to have high capital-spending expectations, while Nvidia is part of an industry-chain interaction involving AI-company financing and equipment construction. The market’s concern that demand may merely be created by companies investing in one another is not currently supported by fundamental data.

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