Why Agentic Systems Need Ontologies — Frank Coyle, UC Berkeley
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AI Engineer
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AI Engineer
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Terms in this piece · Glossary
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
Why it matters
Names a specific structural fix for the class of AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → errors that prompt engineering reliably fails to eliminate.
Key quotes
“People worry about hallucinations, but that's the feature.”
Frank Coyle
“LLMs can't do anything. All they can do is give us the next word with a high probability.”
Frank Coyle
“you want to check your types with Pydantic and then check your results with the ontology”
Frank Coyle
“Nothing is a mistake. There is no win. There's no fail. There's only make.”
Frank Coyle
“Loops can drift as agents start talking to each other, things get all go off off the rails.”
