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A model gives you an answer and it sounds right. A README names an owner who left last year. A config field has been wrong since March and nothing has read it. Each is a claim nobody checked — not a lie, and not a bug, because no line of code is broken. The claim was simply never held against anything with the authority to refuse it.
Key Course Features:
- Write a SHACL node shape with cardinality, datatype, value sets and closed constraints, and read the validation report it produces
- Separate terminology from assertions, and see a fixed set of facts become inconsistent without a single fact changing
- Choose between open-world and closed-world validation, and know what the other one would have answered
- Detect vacuous success — a shape that conforms because it matched nothing at all
- Keep a reasoner out of the gate by materialising its closure offline and diffing what it derived
- Run every example offline against pinned tools, with the demos recorded from real terminals
Perfect for:
- Engineers putting an agent's output somewhere it matters and needing something outside the model that can refuse
- Data and platform engineers asked to put a semantic layer under an agent programme
- Anyone who has shipped on a green dashboard and later learned the check was in scope for nothing
None of this makes a model correct. It makes wrongness land somewhere you can see it — on a line, with a name attached — before it reaches anybody who would have believed it.
