Neo4j's Graph Engineering: compiling skills into graphs to make AI agents predictable
AI Engineer · youtube · 2026-11-03
Zachary Blumenfeld of Neo4j argues agents need a map of the logic they should follow, not just a pile of text. The talk covers: three types of graphs and Neo4j's knowledge layer; context graphs and agent memory; compiling skills and past decision traces into graph-shaped skills; distilling skills from memory graphs; customer use cases; and a live demo of a loan-approval agent that follows compiled skills, with observability on graph branches. Graph engineering makes agents more predictable, governable and portable.
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