הפיכת זיכרון של סוכנים למיומנויות שפועלות

תקציר מקורי באנגליתAgents finish a task, then forget what they learned. Retrieval alone won't fix that. Will Lyon, senior product manager at Neo4j, explains why agent memory built on embeddings and retrieval isn't enough: recall isn't actionable knowledge. Agents need knowledge that is connected, typed and traceable. He shows Neo4j's model of agent memory as a context graph with short-term, long-term and reasoning memory, covering entity extraction and resolution, shared ontologies, and decision traces that let many agents learn from each other. Then he turns memory into action: distilling grounded, governed skills from the graph, based on Neo4j research that treats skills as typed execution graphs, with checks for grounding, coverage and coherence, and alerts when a skill goes stale. He demos the Neo4j Agen