I Gave an AI Tutor a Memory That Survives Restarts — Here’s the Tiered Architecture (and Tested…

A developer built a tiered persistent memory system for an AI tutor agent that survives restarts, using importance scoring, decay, and fact consolidation, and verified it with a full pytest suite. The architecture enables the agent to retain context across sessions, improving continuity in educational interactions.

Member-only story I Gave an AI Tutor a Memory That Survives Restarts — Here’s the Tiered Architecture and Tested Code That Made It Work Building a tiered, persistent memory system for an AI tutor agent — with importance scoring, decay, and fact consolidation — verified end-to-end, including a full pytest suite, before publication. Estimated Reading Time: 17–20 minutes Table of Contents - Introduction - Problem Statement - Background - Core Concepts - Technology Deep Dive - Architecture - Mini Project: MemoryTutor - Implementation - Code Walkthrough - Testing - Performance - Limitations - Best Practices - Common Mistakes - Production Considerations - Future Improvements - Conclusion - Further Reading - Official References Introduction Think about the last time you called customer support about the same issue twice. The first agent understood…