NEWLAND(SZ:000997) 3 6 Ke·2025-08-12 23:10Core Insights - The traditional Product-Market Fit (PMF) framework is outdated in the AI era, necessitating a new approach to align with rapidly evolving user expectations and technological advancements [1][2][3] Group 1: AI PMF Paradox - Achieving PMF is simultaneously easier and harder in the AI era; AI enables faster iterations and deeper user insights, but user expectations have skyrocketed, making "good enough" no longer sufficient [2][3] - The concept of PMF has become a moving target, as users continuously interact with superior AI systems, altering their definitions of what constitutes an intelligent product [2][3] Group 2: Limitations of Traditional PMF Framework - Traditional PMF frameworks assume a stable problem-solution relationship, which is disrupted by AI products that often address unknown user problems or create new workflows [3][4] - AI solutions are not limited by traditional software constraints, leading to unpredictable user experiences due to varying capabilities in different areas [4] - User expectations grow exponentially once they experience effective AI, raising the bar for all AI products [5] Group 3: New AI PMF Framework - A new framework for AI PMF consists of four iterative, data-driven stages that require constant recalibration to meet evolving user needs [6][11] - The first stage involves identifying unique pain points that can only be addressed through AI capabilities, focusing on "invisible pain points" that users may not recognize as problems [7][10] Group 4: AI Product Development - The second stage emphasizes the need for an AI Product Requirements Document (PRD) that differs from traditional methods, focusing on probabilistic outcomes rather than deterministic behaviors [11][12] - The third stage involves strategic frameworks for scaling AI products, ensuring performance consistency and data quality across diverse user scenarios [16][19] Group 5: Sustainable Growth and Optimization - The final stage focuses on creating sustainable growth loops, where AI products improve over time through user interactions, enhancing both model performance and user trust [22][23] - Companies that master the new AI PMF framework will likely dominate their markets and expand rapidly into adjacent sectors due to their AI's increasing intelligence [24][25]