Establishing robust web performance metrics for AI-powered websites requires a multifaceted approach, extending beyond traditional Core Web Vitals. While Largest Contentful Paint (LCP), Interaction to Next Paint (INP), and Cumulative Layout Shift (CLS) remain foundational, it's critical to also track AI-specific performance. Key practices include measuring AI model inference time on both client and server sides, as well as API response latency for cloud-based AI services. Monitoring JavaScript execution time and network payload size is essential, given the potential for heavy AI script processing and data transfer. Furthermore, custom metrics should be defined to gauge the responsiveness of AI-driven features, such as the time to first personalized recommendation or chatbot response, ensuring a superior user experience. More details: https://forum.himko.vip/proxy.php?link=https://4mama.com.ua