Core Viewpoint - The successful implementation of AI products relies more on understanding customer business scenarios and industry know-how rather than just technical capabilities [2][10][11]. Group 1: Challenges in AI Product Implementation - The main challenge in transitioning AI products from internal testing to customer delivery is effectively matching the product to the customer's business context [2][5]. - AI products must be designed with a customer-centric approach, integrating industry-specific knowledge to ensure success [2][11]. - Patience is crucial during the product refinement process to ensure maturity before scaling sales [2][4][36]. Group 2: Strategic Shifts and Product Development - In 2024, the company shifted its strategy to focus on chargeable AI products that address specific end-to-end business problems [3][34]. - The development process for AI products has been adjusted to allow for rapid iterations, with cycles shortened to two to three weeks [4][6]. - The company has identified seven key AI agents to target specific business needs, including AI recruitment assistants and interviewers [3][34]. Group 3: Customer Engagement and Feedback - Engaging with customers during the product development phase is essential to gather real-time feedback and ensure the product meets their needs [4][6]. - The company emphasizes the importance of understanding customer requirements and adapting the product accordingly, which may involve significant customization [20][21]. Group 4: Market Positioning and Pricing - AI products should be positioned as standalone solutions that solve high-value business problems rather than mere extensions of existing functionalities [7][8]. - The pricing model for AI products varies, with options including per-seat fees or charges based on usage metrics, such as the number of interviews conducted [34]. Group 5: Future Directions and Industry Trends - The company recognizes the evolving landscape of AI technology and its potential to disrupt traditional business models, leading to a more open approach to AI integration [18][19]. - There is a growing demand for AI solutions in the SaaS sector, with clients increasingly favoring AI-related products [31].