Shared Selective Persistent Memory for Agentic LLM Systems
· By Antonio Sedino, CTRO · Published by Reinventy Solutions Corp.
Apple researchers identify that agentic LLM systems lose productive context across sessions, requiring persistent memory to retain configuration and tool-use patterns.
Agentic LLM systems discard configuration choices and domain constraints each session, facing a fundamental context problem in multi-turn tool use.
Read the original source at Apple Machine Learning Research ↗