Unverified50% confidenceFactExact time
The context window is the capacity for holding historical records; a window that is too small causes the model to forget earlier conversation, while cramming everything in is costly and tends to scatter attention.
1
Sources
50%
Confidence
Long-term
Relevance
10/20/2026
First Seen
Sources
The 12 Core Principles of AI Agents Explained Clearly: From Messages to Multi-Agent Systems
bilibiliAgent零基础入门10/20/2026
Related Entities
Related Claims
VerifiedThe larger the context window, the more information the model can remember in a single call, but it also brings rising inference costs and the problem of intermediate information being ignored.79% similarUnverifiedStuffing large amounts of historical records into a prompt not only incurs token costs, but may also cause important information to be drowned out due to attention dilution, producing worse results than a curated short summary.78% similarUnverifiedAs interactions accumulate, raw historical records will exceed the model's context window limit, requiring periodic summarization or tiered storage for memory compression.77% similarVerifiedContext loss in online customer service often stems from improper token window management in multi-turn conversations; when conversation history exceeds the model's context window, the Agent will lose memory if there is no memory compression or summarization mechanism76% similarUnverified在线客服的上下文丢失往往源于多轮对话中历史记录累积超出模型上下文窗口上限，导致最早内容被截断75% similar
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