SCM (Sleep-Consolidated Memory) is a lifecycle memory architecture for language agents. Instead of leaving stored observations static between conversations, SCM treats user absence as compute for consolidation, adaptive forgetting, schema extraction, wake summaries, and bounded curiosity-driven gap filling. The evaluation includes a 1, 500-run canonical ALB matrix, a 4, 000-run reference-adapter matrix, a 1, 200-run ablation matrix, a 500-run official upstream Mem0 baseline, and a gated OpenAI gpt-5. 4-mini evaluation. The results support a focused claim: lifecycle memory is a distinct architecture for agents whose memory must transform between sessions, particularly under interference, contradiction, recurring-pattern, and curiosity-gap workloads. Open-source implementation, reproducibility manifests, and benchmark artifacts: https: //github. com/clyrai/SCMOpenSource
Saish Shinde (Sun,) studied this question.