Week 4 of my AI Engineering Fellowship ā Memory for AI Agents š§
One of the biggest unlocks in AI systems isn't bigger models, it's memoryāØ
This week we broke down what "agent memory" actually means and how it shows up in real systems. It's a subsystem that lets an agent persist, retrieve, update, and forget information across model calls, sessions, and time, and pull the right context back in when it's needed.
LLMs don't naturally remember anything. Memory is what makes continuity possible.
The five operative verbs:
ā
Persist ā survive beyond a single model call.
ā
Retrieve ā bring back relevant info, not just recent.
ā
Update ā revise old knowledge with new facts.
ā
Forget ā delete, decay, or consolidate outdated info.
ā
Feed back ā re-inject useful memory into context when it matters.
Without these, you don't have an "agent", just stateless prompts stitched together.
We also covered the history of memory in AI systems, a full taxonomy of memory types, and CRUD operations as the backbone of memory design.ā¤ļø