Start with the business problem, not the schema

Keet’s opening chapter makes a useful point outside academic ontology work: judge an ontology by what it helps a system do, not by how tidy the taxonomy looks on its own.

That fits how we think at Hadto. We are not building software to admire diagrams. We are building operating systems for real businesses: companies that help domain experts become owner-operators instead of staying employees inside someone else’s cap table. If a model does not improve decisions, coordination, compliance, onboarding, customer workflows, or operational visibility, it is not doing enough.

Model around work, not just nouns

A weak ontology project inventories concepts. A stronger one ties those concepts to the jobs they support.

For Hadto, that means our models should answer operational questions such as:

• what has to be true before a customer workflow can proceed?
• what decision does an operator need to make?
• what evidence does a lender, regulator, or partner need?
• what can be automated safely, and what still needs human judgment?

If we cannot answer those questions, we probably have a data dictionary, not an operating model.

Trace the model to a use case

Hadto’s mission is to convert employees into business owners. That only works if the businesses we help launch can run with unusually high leverage.

Ontology work earns its keep when it reduces ambiguity across that stack:

• customer records are easier to validate,
• workflows are easier to automate,
• reporting is easier to explain,
• apprentices can understand the system faster,
• operators keep more control because the business logic is explicit.

Structure compounds

Hadto is building repeatable company infrastructure, not one-off custom projects. If we can capture the core problems, use cases, and decision points in a reusable form, each new venture starts with a better foundation.

In our model, domain experts should be focused on trust, craft, and customer relationships while the platform absorbs more of the administrative and technical burden. Better ontologies help make that possible.

Chapter 1 is a good correction against overbuilt abstraction. The right ontology is not the most sophisticated one. It is the one that makes a real business easier to operate.

For Hadto, the test is simple: does this help a future owner-operator run the business with more clarity, speed, and independence? If not, go back to the business problem.