Recently, the rapid development of artificial intelligence technology has given rise to a large number of "AI shell" products. These products are often simply seen as lightweight applications that use existing AI models or APIs, with relatively simple development processes and easily overlooked by the market. However, a new analysis points out that these "shell" applications should not be underestimated. Whether they can survive in the fierce competition depends on whether they can effectively integrate into users' workflows, accumulate unique data, and cope with challenges from industry giants.

Firstly, the article clearly distinguishes between "functional" and "product-based" AI shell applications. Functional applications usually only solve a specific problem, such as interacting with PDF documents, lacking independence, and once major platforms integrate such functions, these applications may be eliminated from the market. Product-based applications, on the other hand, can build their own moats through deep integration and data accumulation, enhancing competitiveness.

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Secondly, startups face dual challenges. On one hand, they need to rely on technical support from large model providers, while on the other hand, they have to compete with these giants in distribution channels. For example, coding assistant applications like Cursor are trying to transform into integrated development environments, but they still face the problem of API call limitations. At the same time, giants like OpenAI and Google may quickly integrate similar features into their own products, so startups must seize the market opportunity.

Finally, the article analyzes the competitive strategies of traditional enterprises in the AI era, emphasizing the importance of controlling user processes and accumulating their own data. Successful "shell" products need to be closely integrated with users' daily work processes, not just a simple tool, but an effective solution to real problems.