Featured Leanpub Book
LadybugDB for Edge Agent AI memory
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.
Memory Graph 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.
