Structured Agent Memory Slashes Token Costs by 75%

State-of-the-art benchmarks demonstrate that structured, selective memory retrieval architectures substantially outperform brute-force context window stuffing in production agent systems. Frameworks like Mem0, Letta, and LangMem extract salient facts after each turn and store them in vector databases, achieving over 92% retrieval accuracy on multi-hop evaluation benchmarks. This selective factual injection slashes API token consumption by up to 75% while avoiding long-context degradation.