Sherrie Pan

Error messages are a critical touchpoint for software-to-user communication. The quality of their expression directly impacts problem-solving efficiency and user satisfaction. However, traditional error message management suffers from systemic issues: developers write using technical jargon that users find difficult to understand; content is scattered throughout the code without unified management; multilingual translation quality is inconsistent, with terminology discrepancies; and users face complex, inefficient paths to find and access information. These pain points fundamentally reflect the absence of a technical content management system. This talk presents a systematic methodology covering the complete lifecycle of error messages: • Content Design: Establish user-centered information architecture and writing standards, translating technical language into understandable and actionable user language • Intelligent Production: Leverage AI to automatically identify error sources in code, intelligently generating user-friendly expressions that comply with technical writing standards based on context • Professional Localization: Build domain-specific terminology databases and translation memories to ensure accuracy and consistency of multilingual content • Efficient Delivery: Enable natural language queries and personalized diagnostic recommendations through an intelligent knowledge base This methodology has been validated through practical implementation and can provide technical communication teams with actionable insights for their intelligent transformation.