Core Viewpoint - The competition in the AI Agent sector has shifted from technical specifications to the ability to implement solutions in specific scenarios, with a focus on projects that can address industry pain points and achieve commercial closure [22]. Group 1: Market Dynamics - The recent withdrawal of Manus from the Chinese market has reignited discussions around the AI Agent sector, particularly in the general-purpose Agent field [2][16]. - Investors are increasingly interested in projects that demonstrate a deep understanding of vertical industries and can effectively translate complex industry rules into software solutions [11][14]. - The market is witnessing a trend where companies are focusing on practical applications in vertical industries, moving away from generalized models that may not meet specific needs [18][22]. Group 2: Investment Preferences - Investors are more inclined to support projects that can leverage both domestic and international markets, enhancing their value proposition [14]. - The core barrier for successful projects lies in the industry data flywheel effect, where initial entry may be easy, but accumulating clients and data creates a unique advantage over time [13]. - Projects that can quickly accumulate data and users globally are particularly valuable in the AI application space [14]. Group 3: Challenges and Opportunities - The general-purpose AI Agent market faces significant challenges, especially for startups competing against established giants like Alibaba, which possess both model and traffic advantages [10][11]. - Despite the high difficulty level, the potential for new giants to emerge from technological revolutions remains, although the probability is low [10][15]. - Approximately 40% of AI Agent projects may be eliminated from the market due to unclear business models [16]. Group 4: Case Studies and Examples - Companies like Jiyue Xingchen are focusing on specific applications in smart terminals, collaborating with major domestic smartphone manufacturers to enhance user experience [19]. - Other companies are exploring vertical applications in finance, manufacturing, and trade, demonstrating the diverse opportunities within the AI Agent landscape [21][22]. - The shift towards scenario-based applications is evident, with various companies showcasing their solutions at industry events, indicating a competitive landscape focused on practical implementations [18][22].