Unverified50% confidenceFactExact time
Current mainstream large language model-driven agents maintain memory through a context window, and once information exceeds the context window the agent loses that memory, potentially causing goal drift or going in circles.
1
Sources
50%
Confidence
Long-term
Relevance
9/26/2026
First Seen
Sources
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Related Claims
UnverifiedWhen AI remembers what a user has said, it is essentially the context window and memory mechanisms at work.76% similarVerifiedCognitive offloading refers to humans outsourcing memory and computation tasks to external devices, which can lead to the degradation of related cognitive abilities.74% similarUnverifiedBecause large model context windows are limited, long-horizon agents need to be designed with external memory mechanisms, encompassing three levels: short-term memory, long-term memory (vector database retrieval), and working memory.74% similarUnverifiedCurrent mainstream implementations of long-horizon agents include thought-action loops based on the ReAct framework and augmented architectures combined with external memory storage.71% similar
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