Implementing Conversation Memory in AI Apps: Short-Term, Long-Term, and Context Compression

Most AI chat applications lose context after each session. The user has to re-explain their project, their constraints, and their preferences every time. That's a bad product. Here's how to implement persistent conversation memory that makes your AI app feel genuinely intelligent across sessions. Two Types of Memory Short-term memory: The current conversation history. Claude can reference anything said earlier in the same session. Long-term memory: Facts, preferences, and context that persist across sessions. This is what most apps are missing. Storing Conversation History Start with the basics -- persist messages to the database. // prisma/schema.prisma model Conversation { id String @id @default(cuid()) userId String title String? createdAt DateTime @default(now()) updatedAt DateTime @updatedAt user User @relation(fields: [userId], references: [id], onDelete: Cascade) messages Message[] } model Message { id String @id @default(cuid()) conversationId String role String // "user" | "as