Seven parts built the individual layers. This final part assembles them into a complete, deployable production system with a full reference architecture, infrastructure configuration, monitoring setup, cost model, and a decision framework for when to use each memory type.
Tag: Qdrant
AI Agents with Memory Part 3: Semantic Memory – Building a Long-Term Knowledge Layer with Qdrant and Python
Episodic memory records what happened. Semantic memory stores what the agent has learned. This part builds a production semantic memory layer using Qdrant and Python, with fact extraction, importance-weighted upserts, and similarity retrieval that lets agents build genuine knowledge about users and domains over time.
Vector Databases: From Hype to Production Reality – Part 3: The Vector Database Landscape
With the technical foundations established in Parts 1 and 2, we now face the practical question every development team encounters: which vector database should we
