RAG Is Blind to Time — I Built a Temporal Layer to Fix It in Production

Source: Towards Data Science

Overview

Three weeks into testing, a learner told me my AI tutor gave her the wrong answer.
Not obviously wrong — just outdated enough to mislead.

That was the moment I realized something most RAG systems quietly ignore: they have no sense of time. My system retrieved the most similar document, not the most current one. In a knowledge base that changes constantly, that’s a serious flaw.

The fix wasn’t in the retriever or the model. It was in the gap between them. I built a temporal layer that filters expired facts, boosts time‑sensitive signals, and makes the system prefer what’s still true — not just what matches.