LadybugDB for Edge Agent AI Memory (Graphs for AI Agents Book 2)

LadybugDB for Edge Agent AI Memory (Graphs for AI Agents Book 2)
English | March 9, 2026 | ASIN: B0GRWCNV5Y | 312 pages | Epub | 3.01 MB
Vector stores don't think - they search. They find fragments that sound like your query, then forget they ever looked. Every session starts from nothing. Every context window is a memory that dissolves at sunset.But the deeper problem isn't amnesia. It's that when agents do remember, they remember in someone else's house - on servers you don't control, in formats you can't inspect, under terms you didn't write.It is a book about building something different: persistent, structured, queryable memory that lives inside your application - no external servers, no data leaving your process, no infrastructure you don't own. An embedded graph database that travels with your agent the way a nervous system travels with a body.You'll learn how to model not just facts, but relationships between facts. Causality. Temporal ordering. The layered structure of meaning that makes memory more than a search index. You'll build ontologies that enforce what can be known and how. You'll combine graph traversal with semantic search - so your agents find not just what's similar, but what's connected.The result is an agent that remembers the way you do: structurally, contextually, privately - with memory that belongs to you.