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HeadGym — Memory Architecture for AI Agents: The 2026 Production Stack

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2026-07-11

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2026-07-11 / SKILLSChoose your agent-memory pattern by its latency/accuracy point — KG+vector hybrid tops accuracy, flat vector wins speed2026 production memory splits into five patterns with a real trade curve: a Knowledge-Graph + vector hybrid reaches ~72.9% task accuracy but ~17s p95 latency, while a flat external vector store lands ~66.9% at ~1.44s — roughly 6 points of accuracy for a 12× latency swing. Pure vector similarity is fading because retrieving facts through entities and relationships (graph) captures what embeddings alone miss, but neither is sufficient alone. For builders: pick the pattern from your latency budget and task type rather than defaulting to a single vector store; start MVPs on a buffer + SQL/NoSQL + lightweight in-process vector index and graduate to a hybrid only when accuracy demands it.

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