Why Your Company Needs a Context Graph (and How to Build It) — Gil Feig, Merge

This post introduces the concept of a 'context graph' as a company-wide brain for AI agents, extending existing knowledge management frameworks. It details an architecture that combines synced copies of third-party data with live API lookups, managed by a router and summarizer. The context graph explicitly includes company-specific skills and memory, emphasizing traceability and provenance of data. It proposes four tiers of context, including derived summaries, and a decision flowchart for selecting between cached and live data, addressing the limitations of MCPs alone for answering complex, historical queries.