Why Agentic Systems Need Ontologies — Frank Coyle, UC Berkeley

Channel: AI Engineer

A second refund on the same order. A payout sent to the support desk instead of the buyer. An order status of “probably shipped.” These are the kinds of mistakes a probabilistic agent makes and a paragraph of instructions cannot reliably stop. Frank Coyle argues that most agent failures, from brittle tools to fragile handoffs, are symptoms of one missing layer: a formal ontology sitting outside the model as logical guardrails. LLMs reason probabilistically over domains they only half understand, and no amount of prompt engineering closes that gap. His fix is neurosymbolic: probabilistic reasoning inside, logic outside. An ontology is just typed entities, relationships, and constraints, expressed with old and boring standards like RDFS and OWL, that let you say a payment status must be one

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