To effectively augment AI agents with external knowledge, developers should move beyond stuffing context windows. The narrator proposes a four-part taxonomy—skills, MCP, RAG, and memory—to categorize information by its source and function, arguing this approach prevents agents from stalling on tasks like diagnosing a web server error.

This taxonomy offers a practical heuristic for structuring agent systems that prioritize targeted data access over bulk context loading. While the narrator frames these methods as a clean framework, their real utility depends on how well you map your specific operational needs to these distinct knowledge sources.