Mnesis launches deterministic memory engine for LLM agents
Mnesis is a Python library that solves "context window degradation" in long-running LLM agents by moving memory management out of the model layer and into a deterministic engine. It ensures high-fidelity reasoning in complex workflows by replacing prone-to-error LLM summarization with structured compaction, immutable storage, and token-efficient parallel operators.
Mnesis provides the architectural rigor needed to scale LLM agents into robust production systems by employing a three-level compaction strategy and an immutable SQLite-backed log. Its use of parallel operators and structural AST summaries ensures context health and auditability without sacrificing performance.
DISCOVERED
18d ago
2026-03-24
PUBLISHED
18d ago
2026-03-24
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