A technical guide to building persistent memory systems for AI agents. Learn the architecture, data model, and implementation patterns.
AI agents need memory to maintain context across sessions. Without it, every interaction starts from zero, wasting time and producing inconsistent results.
The best memory systems use a layered approach: observations (raw data), beliefs (derived knowledge), and a knowledge graph (connections between memories).
Squish implements these patterns with SQLite for storage, vector embeddings for semantic search, and MCP for agent integration. Install with npm i -g squish-memory.