Context Graphs: Building Production World Models for the Age of AI Agents
AI struggles in production because enterprises store state, not decisions. Code, CRMs, and tickets show what happened—but not why. Context graphs solve the “two clocks problem” by capturing decision traces across time, ownership, semantics, and outcomes. As agent trajectories accumulate, they form production world models that enable simulation, auditability, and compounding organizational intelligence.
https://hackernoon.com/context-graphs-bu...source=rss
AI struggles in production because enterprises store state, not decisions. Code, CRMs, and tickets show what happened—but not why. Context graphs solve the “two clocks problem” by capturing decision traces across time, ownership, semantics, and outcomes. As agent trajectories accumulate, they form production world models that enable simulation, auditability, and compounding organizational intelligence.
https://hackernoon.com/context-graphs-bu...source=rss
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