A user discussion about Claude forgetting earlier details or giving weaker answers in long chats prompted suggestions to separate tasks and carry a concise decision summary into a new conversation. These experiences are not an experiment proving a defect in a particular model. Anthropic’s context-engineering guidance explains that information retrieval can weaken as input grows and describes compaction and structured external notes for long-running work. Aggressive compression can also discard critical constraints, so decisions, unresolved issues and supporting evidence need to be preserved deliberately.
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Long AI conversations call for deliberate context management
Preserve decisions and unfinished work instead of simply extending a chat, and check that summaries retain important constraints.