As enterprise platforms shift toward conversational reasoning interfaces, the stateless nature of LLM APIs creates an architectural gap. Statelessness gives models horizontal scalability but pushes the entire burden of session state and semantic memory onto client applications. To address this, the Hydration Proxy Pattern is introduced. Its core idea is to detach session persistence from the reasoning engine and place it in an independent proxy layer. This layer stores conversation context in a KV store or database and, before each LLM call, injects the required semantic fragments into the request payload, thereby granting the platform sovereignty over conversational data while keeping the model invocation transparent. The pattern supports multi‑stage semantic grounding, allowing secure context transfer across subsystems. To reconcile sovereign state management with KV caching, the Context Stabilization Mandate is proposed, mandating consistency checks and version control before writing to the cache to avoid context drift caused by concurrent updates.
Review