以下文章来源于白鲸出海 ，作者白鲸小编 白鲸出海 . 白鲸出海，泛互联网出海服务平台，白鲸专注于具备互联网属性的行业、公司、产品和服务的出海，包 括应用、游戏、电商、区块链、智能手机及硬件、旅游、网络文学、影视、动漫、教育、体育和金融 等。 此前的选题，我们曾经多次观察过"明星创业者"入局 AI 播客的案例，包括张月光推出的 ChatPods 和焦可推出的来福。 ChatPods 和来福近 90 天的双端下载量｜图片来源：点点数据 但是一段时间过去，从数据上看，两款产品都不甚理想，点点数据显示，ChatPods 9 月份全球下载 量 3.5 万，但由于体量较小，第三方数据没有捕捉到活跃用户，其月流水也仅有不到 100 美元；而 上线更晚的来福，数据更低，9 月下载量仅有 2000 左右，未能捕捉到 MAU 和收入数据。 来源丨 白鲸出海（ID：baijingapp） 作者丨 张凯然 编辑丨 殷观晓 图源丨 Aibrary官网 李可佳（Ethan KJ Li）的工作履历｜图片来源：LinkedIn 即便前者遭遇挫折，也并没有影响后来者的热情。最近，曾任字节智慧教育业务线 CEO 的李可佳 （Ethan KJ L ...

此前的选题，我们曾经多次观察过"明星创业者"入局 AI 播客的案例，包括张月光推出的 ChatPods 和焦可推出的来福。 ChatPods 和来福近 90 天的双端下载量｜图片来源：点点数据 但是一段时间过去，从数据上看，两款产品都不甚理想，点点数据显示，ChatPods 9 月份全球下载量 3.5 万，但由于体量较小，第三方数据没有捕捉到活 跃用户，其月流水也仅有不到 100 美元；而上线更晚的来福，数据更低，9 月下载量仅有 2000 左右，未能捕捉到 MAU 和收入数据。 | Experience | | | --- | --- | | | 创始人 | | | Ouraca · Full-time | | | May 2024 - Present . 1 yr 6 mos | | | Palo Alto, California, United States · Hybrid | | | Ouraca's vision is to create the leading lifelong learning ecosystem in the age of Al. Our first product Aibr ...

Core Viewpoint - The article discusses the challenges and opportunities in the AI startup landscape, emphasizing the need for a shift from traditional metrics like Product-Market Fit (PMF) to a focus on continuous value delivery and user outcomes in the AI tools sector [4][5][9]. Group 1: Product-Market Fit and Value Creation - The concept of PMF is being misused in the AI tools market, where subscription models do not equate to actual value realization for users [5][6]. - Many AI tools are currently catering to early adopters, leading to a potential revenue decline as user budgets stabilize [6]. - A new model of value creation is emerging, where continuous value delivery is essential for long-term user retention and growth [7]. Group 2: Outcome vs. Output - The traditional B2B model focuses on selling products, while the new paradigm emphasizes creating outcomes for customers [9]. - AI products should not just provide capabilities but should ensure users achieve tangible results, integrating customer success mechanisms into the product [9][10]. Group 3: AI Evaluation Systems - Finding PMF is just the beginning; the real challenge lies in building effective AI evaluation systems that understand user behavior and measure performance [10]. - The shift from a waterfall model to a discovery-based approach allows for rapid iteration and testing, enhancing collaboration and reducing development time [12][13]. Group 4: AI-Native Organizations - AI-native organizations are reshaping management paradigms, reducing the need for middle management and promoting a flatter organizational structure [14]. - The traditional management theories are becoming obsolete as AI tools enhance decision-making and execution efficiency [14]. Group 5: Human-AI Collaboration - The "1+N" model promotes collaboration between humans and multiple AI agents, enhancing productivity and efficiency [17]. - New roles are emerging within teams, such as "Product Owners" and "Infrastructure Builders," to better leverage AI capabilities [18]. Group 6: Lifelong Learning in the AI Era - The future of education is shifting from content delivery to feedback-driven learning, emphasizing continuous improvement and personal growth [22][25]. - The design of effective feedback mechanisms is crucial for creating a closed-loop learning system that fosters individual development [25]. Group 7: The Unique Value of Humans - In a world where AI can replicate knowledge and skills, the unique human perspective and creativity become invaluable [26]. - The ultimate goal of education should be to help individuals become unique and irreplaceable, leveraging their personal experiences and insights [26].