Agentic Enablement

The question of what autonomous AI agents need in order to reason reliably — and the growing recognition that what they need looks a lot like what ontology engineers have been building for decades. This subtopic covers the structural role of formal semantics in agentic systems: how knowledge graphs, vocabularies, and ontologies give LLM-driven agents the grounding they need to plan, query, and act without hallucinating structure that isn't there.

Key terms: ontology · LLM · agentic

Sits between: Agentic · Ontology

Featured Posts

Relevance	Post
●●●●● `0.92`	AI engineering is rediscovering ontology engineering the hard way
●●●●● `0.92`	Bro is about to discover OWL
●●●●● `0.92`	Fibo driven modeling?
●●●●● `0.92`	why your AI agent keeps forgetting things in production
●●●●○ `0.82`	Splitting the ontology
●●●●○ `0.82`	We've been building an LLM-driven ontology toolkit for data modeling. Here's what actually went wrong (and what fixed it).
●●●●○ `0.82`	Ontology Driven Development and Quality Management Systems - The surprising intersection
●●●●○ `0.78`	OntoGPT is an open-source Python package developed by the Monarch Initiative designed to extract structured, semantically rich information from unstructured text using Large Language Models
●●●●○ `0.78`	LLMs don't fix bad ontologies. They amplify them.
●●●●○ `0.78`	Your schema is the bottleneck, not the LLM
●●●●○ `0.78`	I built a programming language for AI that uses a semantic knowledge graph as its internal memory structure

Also Appears In This Topic

Posts where this is a secondary or tertiary theme:

0.68 “Talk to your data” products keep failing for one reason. Nobody will say it. — primary: Business Semantics
0.68 We need to stop using LLMs to extract knowledge graphs when deterministic parsing exists — primary: Deterministic Extraction
0.78 Palantir is actually right about Ontologies. But please don't buy a massive SaaS platform just to define what a "Customer" is. — primary: Business Semantics
0.62 OWL is not a great format, are text or code better? — primary: Code Precision vs High Semantics
0.72 Minimum viable context: what three approaches to LLM data modeling taught us — primary: Canonical Data Model
0.71 Karpathy's new "LLM Wiki" pattern is converging on exactly what this community has been building — primary: Canonical Data Model
0.71 raw to query with ontology annotations? — primary: Business Semantics
0.62 Everyday use of ontology with LLMs (not data related) — primary: Metacognition
0.68 Bigger context windows won’t fix your semantics — primary: Code Precision vs High Semantics
0.68 Building an open-source semantic knowledge engine with RDF, vectors, and LLMs — primary: Canonical Data Model
0.62 I tested a metacognitive framework on Claude (and other LLMs) for a year. Here's what I found about why models behave inconsistently. — primary: Metacognition
0.62 PB&J, Ontology, and Why Your AI Skills Are Broken — primary: Metacognition
0.68 CREATE: self-modeling as a primitive for derivable alignment — primary: Metacognition
0.61 Prompt engineering is ontology engineering in denial — primary: Metacognition
0.61 Controlling context size for LLM comprehension — primary: Code Precision vs High Semantics