Ontologies Are So Back: Why AI Agents Are Reviving the Semantic Web
Latent Space Richard MacManus
UC Berkeley professor Frank Coyle and other AI engineers are adopting ontologies—structured representations of knowledge domains—to add logical constraints to LLM-based agentic systems. Companies like Neo4j are implementing ontologies as a semantic layer that enables AI agents to maintain consistency and avoid errors, with established web ontologies like Schema.org already present in training data. The revival of ontologies addresses quality control concerns in agent loop engineering by providing guardrails to keep probabilistic LLMs aligned and verifiable.
Why it matters
AI engineers are rediscovering ontologies as a way to keep probabilistic agents inside deterministic boundaries.
