Memory Without Expiry: How Persistent AI Context Undermines Accuracy

Persistent AI memory systems, once promoted as a path to personalized intelligence, are actually degrading model performance by accumulating stale context and reinforcing user biases. This problem extends beyond consumer chatbots to affect coding agents relying on configuration files and learned weights. Implementing recency windows and context relevance checks is critical to prevent outdated information from steering AI decisions.