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Treat the context window as RAM, not storage
Chris Harper
1 min read
Jun 6, 2026
AI
Developer Tools
A Mem0 post from June 5 makes a clean distinction that explains a lot of agent failures: the context window is working memory (RAM), and stuffing it like persistent storage is what causes drift and degradation. The fix is a memory hierarchy — separate short-lived working context from a persistent store, and retrieve narrowly (their algorithm stays under ~7K tokens per call vs. 25K+ for full-context dumps) while scoring better on long-memory benchmarks. Practically: compress and summarize old turns, curate what persists, and lean on retrieval instead of an ever-growing prompt.
Sources: Mem0