Context Graphs: AI's Next Big Idea
Context graphs capture decision traces, exceptions, precedents, and cross-system signals explaining why past choices occurred and making automated decisions auditable. Analysis contrasts traditional systems of record and data warehouses with cross-system agents requiring accessible decision lineage for reliable automation. Implications include context engineering, organizational change management, and design approaches enabling agents to discover organizational schema from real usage rather than predefined schemas. The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614 Get it ad free at Join our Discord: https://bit.ly/aibreakdown

Building Context Graphs for AI Agents, Will Lyon, Neo4j

The Next Wave of Enterprise AI

Prompt Engineering is dead.

Context Graph and Process Knowledge, Jessica Talisman, Contextually LLC

What is a Context Graph?

Karpathy's Wiki vs. Open Brain. One Fails When You Need It Most.

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Context Graphs in Action | TrustGraph

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Taxonomy, Ontology, Knowledge Graph, and Semantics

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Context Engineering: Connecting the Dots with Graphs — Stephen Chin, Neo4j

GraphRAG: The Marriage of Knowledge Graphs and RAG: Emil Eifrem

What is a Context Graph? | Guide to AI | TrustGraph

Don't learn AI Agents without Learning these Fundamentals

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⚡️Context Graphs: according to the authors — Jaya Gupta, Ashu Garg, Foundation Capital

First Impressions of the New Opus 4.8

Context Engineering Clearly Explained

