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Road to NODES | Actionable Knowledge with Context Graphs & Agent Memory

Work hands-on against a running Neo4j Agent Memory Service (NAMS) instance to build a memory layer holding three kinds of memory in one graph: short-term conversation history, long-term entities modeled with POLE+O, and reasoning memory that captures decision traces and tool-call provenance as first-class nodes. Author and validate a domain ontology against live extraction previews, work through validation modes and entity-resolution review queues, then instrument an agent loop to distill its recorded reasoning traces into reusable skills.
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