RAG-systemen negeren tijd: hoe ik dit in productie oplostte

A developer discovered that Retrieval-Augmented Generation (RAG) systems lack awareness of time, causing an AI tutor to provide outdated information. The issue arose because these systems retrieve the most similar documents rather than the most current ones, which is problematic for knowledge bases that change frequently. To solve this, the developer created a temporal layer that filters expired information and prioritizes time-sensitive data, ensuring the system delivers accurate, up-to-date answers instead of merely matching relevant content.