AI 创业最大的问题，不是 FOMO，而是没想清楚

Core Insights - The article emphasizes the importance of asking the right questions in the rapidly evolving AI landscape, rather than seeking immediate answers [4][10] - It discusses the potential impact of AGI on various aspects of business, including recruitment, market strategies, and product development, urging founders to plan for a future shaped by AGI [8][16] - The article raises concerns about trust in AI models and the companies that create them, highlighting the need for transparency and accountability [28][29] Group 1: AI Entrepreneurship - Founders should consider how AI will disrupt their strategies, products, and team dynamics, as the answers to these questions may change rapidly [12][16] - The article suggests that while focusing on a niche is often advised for startups, it is equally important to be aware of broader trends and challenges [13][19] - The potential for software to be fully commoditized raises questions about the future of SaaS companies and whether businesses will develop their own software internally [20][21] Group 2: Trust and Reliability - Trust in AI models and the companies behind them is crucial, especially as teams may become smaller and more automated [27][29] - The article discusses the need for new trust mechanisms, such as AI-driven audits, to ensure accountability in AI applications [30][32] - It emphasizes that users need to trust not only the AI models but also the intentions of the companies that create them [28][29] Group 3: Future of Software Development - The concept of on-demand software generation raises questions about the necessity of pre-developed applications, suggesting a shift towards real-time code generation based on user needs [24][25] - The article posits that while automated code generation may improve software quality, it also necessitates a focus on user interface design and interaction simplicity [24][25] - The future of software may involve a blend of AI capabilities and human creativity, leading to higher quality applications [22][23] Group 4: Competitive Advantage - The article questions whether data will continue to provide a competitive edge in the age of powerful LLMs, suggesting that specialized knowledge may still be crucial in certain industries [35][36] - It highlights the importance of addressing complex challenges in sectors like manufacturing and energy, which may not be easily solvable by AI alone [42][43] - The need for companies to identify their unique competitive advantages becomes increasingly critical as AI capabilities evolve [40][41] Group 5: Societal Impact and Responsibility - The article reflects on the potential societal implications of AI, urging entrepreneurs to consider the broader impact of their innovations [44][46] - It stresses the importance of creating trustworthy AI products that contribute positively to society, rather than merely focusing on profitability [47][48] - The call to action for founders is to leverage their insights to drive meaningful change in a rapidly transforming landscape [48]