Graphs have been instrumental in AI engineering, solving problems in knowledge representation, retrieval, and agent control flow. The article details how knowledge graphs, graph databases like Neo4j, and graph computation have provided structure and deterministic answers. It argues that the next frontier is using graphs to represent the agent's own plan or reasoning process, making it reviewable and persistent beyond a single session. The author introduces the Agentic Graph Specification (AGS) as a solution for this, implemented in tools like Loro and MagAgent. AI
IMPACT Proposes a novel approach to making AI agent reasoning transparent and reviewable, potentially improving debugging and reliability.
RANK_REASON The article discusses the application and evolution of graph structures in AI engineering, proposing a new use case for agent planning, rather than announcing a new product or research breakthrough.
- Agentic Graph Specification
- Ai Engineering
- Cypher
- Dremio
- Graph Query Language
- knowledge graph
- langgraph
- Loro
- MagAgent
- MagGraph
- Marie Curie
- Neo4j
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