Episode notes
Tired of AI agents with the memory of a goldfish? 🧠 We're revealing how to use n8n and Zep to build agents with a real, long-term memory using a relational knowledge graph, so they can finally understand your users.
We’ll talk about:
- The complete guide to building n8n AI agents with a persistent, human-like memory using Zep's knowledge graph.
- The "Token Problem"—how a great memory can lead to surprise five-figure bills, and the advanced architectures to cut costs by over 76%.
- The Hybrid Memory Architecture: a "two-brain" approach combining Zep's knowledge graph for long-term understanding with a fast PostgreSQL database for short-term chat history.
- How to use direct HTTP requests in n8n for a "surgical approach" to context filtering, dramatically reducing token usage.
Keywords
AIn8nAI WorkflowVector Database