The Problem Is Not the GraphKnowledge graphs do not limit an AI system by themselves. The architectural question is whether the system can revise and extend its state assumptions.
Testing AI When Specifications Cannot Capture RealityThe hard testing problem in AI is epistemic: a system can satisfy every contract and still miss the relationship that matters. Reliable practice combines automated checks with evidence, counterexamples and ongoing evaluation.
Retrieval Relevance vs. Ontological PersistenceRetrieval relevance may decay, but ontological existence persists until an explicit event changes the world.
Generative AI Production ArchitectureExplore how models, agents, knowledge graphs, workflows and validation fit into a controllable generative AI production architecture.
Graph RAG vs. Agent Memory vs. World StateChoose Graph RAG for connected retrieval, agent memory for reusable experience and world state for authoritative current truth.
Knowledge Graphs as the Control Plane for AI AgentsUse a knowledge graph to give AI agents an inspectable map of entities, relations, provenance, permissions and dependencies.
World Model AI vs. Studio ArchitectureWorld models learn useful physical dynamics, but production systems still need explicit semantics, state, coordination and geometry.
