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How One Developer Fixed AI Agent Memory by Rethinking What Gets Stored

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A developer discovered that AI agents with persistent memory were failing not because they stored too little, but because index files contained only vague titles rather than actionable facts, leaving useful details buried in body files that agents rarely opened. The fix was to place the critical, behavior-changing detail directly in the index line itself, reserving body files for supporting context like runbooks or explanations. To control what earns a memory slot, the developer applied three filters: the fact must not already exist in the codebase, must hold true beyond the current session, and must actually change how a future session behaves. A decay problem also emerged, where outdated stored claims were acted on confidently without verification, costing at least one full day of duplicated work. The author now treats the feeling of 'already knowing' something as a trigger to re-verify against the primary source rather than an excuse to skip the check.

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How One Developer Fixed AI Agent Memory by Rethinking What Gets Stored · ShortSingh