A four-part series

Meaning as Code

Answers you can defend — from your own data.

An AI that answers from what your data means, not just what it stores: it shows its reasoning, refuses what it can't ground, and gets sharper each time you teach it — in plain language, by the people who know the business. A four-part series, worked end-to-end on a public demo.

● early-stage conceptworking proof-of-conceptMIT / public data

The series

01The Layer You DeletedAn LLM can replace most of your application layer — but not the part that made the numbers mean anything.Read →02Meaning as CodeInside the home for meaning: what's in it, why it's prose a human owns and a machine runs, and why we keep it like code.Read →03From Data to MeaningWhere the ontology comes from: the model drafts the structure from your data; you author the meaning it can't.Read →04Meaning That GrowsThe model tells you where it's thin. You teach it — in plain language — and it grows, provably and legibly.Read →

See it & run it

Try the /ask demo →Ask the ontology in your browser — real recorded runs, disclosed reasoning, zero setup. No install. Browse the model →The live explorer: 8 concepts, 13 rules, every binding — the ontology, clickable. Run it yourself →The code on GitHub: the warehouse, the ontology, and the live /ask app. MIT.