Vector Embeddings as Suboptimal Default for Agent Memory

Evaluate alternative memory architectures based on specific use case requirements: structured knowledge graphs for relational data, conversation buffers for sequential context, hybrid approaches combining embeddings with structured storage, and domain-specific memory systems. Vector embeddings excel at semantic similarity but may waste resources on simple retrieval tasks or introduce latency/cost overhead.