Core Insights - The article emphasizes the importance of Dify as a leading tool for AI product development, particularly for those involved in research and development in AI models [1][14] - It critiques the current mindset of AI product managers who focus solely on demand discovery without understanding the technical aspects of AI model configuration [2][14] Group 1: Dify as a Tool - Dify is identified as the most suitable tool for research in RAG configurations, offering capabilities for secondary enterprise development and a rich plugin application market [1] - The tool allows product managers to create agents with minimal development effort, significantly reducing research and development costs and time [1][14] - Dify supports API encapsulation, enabling the creation of backend services that can be integrated into product projects without requiring a front-end interface [3][12] Group 2: AI Product Manager Skills - The article argues that the core competency of AI product managers should be the ability to construct user scenarios, models, and task flows, rather than just demand discovery [2] - It highlights that product managers lacking knowledge in AI model parameters and configurations are at a disadvantage and may become obsolete in the industry [2][14] Group 3: Agent Configuration Process - The process of creating an agent in Dify involves configuring task flows, knowledge bases, and tools, which is relatively straightforward [4] - The article outlines the steps for configuring a web scraper to gather the latest sports news and generate social media posters, emphasizing the ease of use of Dify [6][7] - Continuous testing and optimization of the agent are necessary to achieve the best performance and user experience [9][10] Group 4: API Integration and Product Design - Once the agent is configured, product managers can proceed to design applications and web functionalities by encapsulating the agent as a fixed API [12] - Successful API integration allows for the management of AI models, parameters, and knowledge bases within Dify, facilitating cost-effective AI model development [14]