Beyond Chat Transcripts: How Intelligent Memory Architecture Scales LLM Agents

As LLM-powered customer support agents enter production, injecting raw chat history into system prompts creates a performance cliff—token bloat, context confusion, and latency spikes become inevitable. This piece demonstrates why semantic memory banks outperform naive history injection and vector databases, offering engineers a practical blueprint for solving one of the most common scaling walls in production LLM systems.