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Explore how vector databases serve as the foundation for workflow engineering in AI systems through this 16-minute conference talk from Qdrant's Vector Space Day 2025. Learn to move beyond simple prompt engineering toward orchestrating comprehensive, context-aware AI workflows that maintain state, provide observability, and include proper guardrails. Discover two critical capabilities that vector databases enable: state management and persistence for storing and retrieving workflow context to ensure resilient and repeatable system behavior, and long-term memory implementation for LLMs and agents that allows systems to capture durable memories and improve over time. Examine production-ready patterns including indexing strategies, memory chunking techniques, and retrieval design through practical code examples. Gain insights into high-level architecture principles that connect to real-world implementation challenges, and develop a framework for using vector databases as the backbone of workflow engineering to build AI systems that are better orchestrated, production-stable, and measurably more effective.
