Memory Engineering: The System That Gives Your AI a Past
The practical guide to persistent memory, retrieval, forgetting, graph memory, token control, and agents that improve across sessions.
TL;DR
- AI agents currently forget lessons learned when a session ends, starting from zero in subsequent sessions.
- Saving entire conversations is not an effective solution as models can perform worse when rereading everything.
- Memory engineering teaches AI systems what to keep, recall, update, and forget, enabling experience to carry forward.
- The guide covers building a memory layer, distinguishing context from long-term memory, and the four types of memory agents need.
- It also explains how to prevent repetitive mistakes, store and retrieve relevant information, reduce token spending, and implement safe forgetting mechanisms.