We'll End Up Where We Started. Except with Different Technology.

A critical look at two dominant approaches to AI data infrastructure — adding specialized layers (semantic caching, CDC, memory stores) versus consolidating everything into an existing backend database. Both approaches are shown to share the same fundamental gap: they capture current state but not the full history of how that state was reached. Drawing parallels to Redis architecture debates from a decade ago, the author argues that state-first architectures lack auditability, causal ordering, and deterministic recovery. The proposed alternative is an event-native approach where immutable, ordered event streams serve as the primary data primitive, enabling replay instead of re-inference, natural auditability, and vendor independence. KurrentDB is positioned as the missing event-history layer that complements rather than replaces existing AI stack components.