This paper introduces shared selective persistent memory for agentic LLM systems that generate and maintain code through multi-turn tool use. Instead of storing entire conversations, it preserves reusable task specifications, data schemas, tool configurations, and output constraints, while discarding session-specific reasoning traces. Shared workspaces support cross-user reuse through role-based access control. In three enterprise scenarios, the system reportedly reached 96% task completion, compared with 79% without memory and 71% with full-history persistence. A zero-token refresh mechanism enabled recurring artifact updates without LLM re-invocation, reducing task time 14x; summary-driven generation reduced token cost 97x versus raw data injection.
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