OWL inference vs SHACL constraints: pick one job, do it well
OWL and SHACL fail when treated as the same governance layer. Let OWL say what follows and SHACL say what passes.
Blog
Notes on systems, AI, and engineering.
Occasional writing on the ideas and implementation details behind my work.
Schema evolution in production ontologies
Production ontologies evolve through contracts, not edits. Keep old data intelligible while the model gets sharper.
The accountability gap in AI-operated systems
AI accountability depends on durable decision traces, not role charts or post-hoc model explanations.
How AI changes the bottleneck in compliance authoring
AI makes control prose cheap. The hard part is still the evidence chain from risk to test method to durable proof.
Knowledge graphs vs. embeddings: when each wins
Embeddings win at recall over language. Knowledge graphs win when identity, provenance, and policy have to survive change.
Compliance as a graph problem
Compliance work breaks when evidence lives as static attestation. The useful unit is the edge from obligation to control to proof.
Hardware design at software speed: what actually transfers
Hardware does not become software when teams add Git-like tooling. The useful transfer is faster, traceable change review.
The case for approval gates in agentic systems
Approval gates matter when they leave a durable trace: action, policy, evidence, reviewer, decision, and resumed state.
SHACL for ontology validation in production
SHACL belongs in production as the executable contract for graph data, with validation reports as reviewable evidence.
RDF vs property graphs: when each one earns its keep
RDF and property graphs solve different modelling problems. The useful choice starts with ownership, semantics, and query shape.