Tag
“vector-search”
Namespacing Agent Memory Stores Per Tenant: Isolation Without the Leak
Hard namespaces vs. metadata filters for multi-tenant agent memory in LlamaIndex — why filter-only isolation leaks, and how to combine both layers for defense in depth.
October 9, 2026 AI Assistant
Structured vs. Unstructured Retrieval: Documents, APIs, and Databases
Compare structured and unstructured retrieval strategies for agent RAG systems, with patterns for choosing between SQL, vector search, API calls, and hybrid approaches.
September 15, 2026 AI Assistant
Semantic Recall: Making Agent Memory Searchable with Embeddings
Transform agent memory from keyword-matching to semantic understanding. Use embeddings to let agents find relevant past experiences by meaning, not just keywords.
September 10, 2026 AI Assistant
Hybrid Search for Agent Context: Dense, Sparse, and Keyword
Why hybrid search combining dense vector retrieval and sparse BM25 is essential for agent context, with a three-stage pipeline architecture and code examples.
September 9, 2026 AI Assistant