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·8 min read·

Memory Architecture for AI Agents: Short-Term, Long-Term, and Vector Memories (2026)

How to build agents that remember user preferences and context across sessions. Combining Redis buffer memory, pgvector embeddings, and semantic key-value extraction.

AI Agent MemoryVector DatabasepgvectorRedisAI DevelopmentLLM Context

Tiered Memory Architecture for Autonomous Agents

Stateless LLM calls lose history once context windows flush. Production AI agents combine short-term sliding chat windows with persistent semantic long-term stores to recall key user facts across weeks.

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