Agent Memory with LangChain4j and Oracle AI Database

One of the quickest ways to make an impressive agent is to prepare a clever prompt. One of the quickest ways to make that same agent fall apart in production is to give it no durable memory. In this article, we'll build a small, memory-backed assistant with LangChain4j and Oracle AI Database. The assistant can search prior incidents, runbooks, decisions, and shift handoffs to answer questions. It can write new memories back to the database so they become searchable in any session. Additionally, all user, agent, and tool messages are logged to database table for observability and auditing.