Judy Li

Technical documentation is undergoing a seismic shift from static publishing to dynamic, intelligent assembly. While Generative AI has promised to revolutionize support, many implementations fail because they lack awareness of the user’s specific environment, role, or system state. This session explores how the Model Context Protocol (MCP) and context-aware design principles are bridging this gap, enabling a new generation of AI agents that do not just summarize text but actively resolve user problems based on real-time system data.

The speaker examines the limitations of current Retrieval-Augmented Generation (RAG) approaches and introduces the concept of the Context Gap. Attendees discover how to transition from writing flat documentation to architecting dynamic content systems that integrate with live user context. The presentation details practical strategies for structuring metadata and taxonomy, ensuring that AI agents can retrieve and assemble the correct information for a specific user's configuration.

Participants leave with a clear understanding of the emerging technical requirements for AI-ready content. The session provides a roadmap for evolving from traditional technical writing to content architecture, equipping professionals to lead their organizations in building adaptive, personalized, and system-integrated information experiences.