
SEM-OS is a memory management architecture for conversational LLMs that solves context loss during automatic compaction. Derived from the SEM of Cherie OS, it externalizes intelligence into structured .md files so memory survives compaction. Includes 14 operational laws generated via ASE v7 analysis, empirical results (80% token reduction, 5x context duration), and independent validation by Microsoft Copilot and Claude Code G3. Prior art: 108 DOI Zenodo. All Rights Reserved Stephane Ochej 2025-2026.
LLM memory, LACF, ASE v7, SEM-OS, Cherie OS, context compaction
LLM memory, LACF, ASE v7, SEM-OS, Cherie OS, context compaction
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