Why ad models need fresh context at decision time

This post emphasizes the critical importance of data freshness at decision time for AI models, especially in advertising. It details how stale data leads to financial inefficiencies (wasted budgets, missed opportunities) and trust issues for AI agents. The post critiques the common practice of adding separate feature stores and vector databases, advocating instead for a unified data engine that can serve vectors alongside SQL filters on real-time data. This approach aims to consolidate data sources and improve the performance of AI workloads by ensuring models operate on the most current context, contrasting this with batch-oriented lakehouse usage for training.