[D] Production gaps in context-window compression for AI agent memory

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've been working on AI memory infrastructure and recently spent a few weeks reading through the source code of an open-source context-window compression system — the kind that replaces retrieval entirely by having background LLM agents compress conversation history into structured observations, then prefix the entire block into every turn. The approach just hit 90+% on LongMemEval, which is impressive. But after tracing the full lifecycle: observer prompts, compression thresholds, reflector b...