A hard 50K token session cap and a three-tier memory system are implemented to manage context bloat and memory decay in long-running Claude Code agents. This approach ensures the agent remains efficient by externalizing memory across daily notes, long-term memory files, and a knowledge graph, preventing performance issues and excessive API costs. Developers should monitor token usage closely to implement similar stability measures for their AI applications.
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