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. A model that does not improve decisions, coordination, compliance, onboarding, customer workflows, or operational visibility 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.

Hadto’s useful questions are operational. Before a customer workflow can proceed, what has to be true? Which decision is an operator actually making? What evidence does a lender, regulator, or partner need to see? Where can the system automate safely, and where does human judgment still carry the risk? A model that cannot answer those questions is probably a data dictionary, not an operating system.

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 should become easier to validate, workflows easier to automate, reporting easier to explain, and apprentices faster to onboard because the business logic is explicit instead of trapped in someone’s memory.

A worked example: readiness for handoff

Consider a prospective owner-operator moving from intake into lender review. In a weak model, the file gets marked “ready” and each person quietly means something different. One operator thinks the business entity has been formed. Another assumes insurance is already in place. Finance is still waiting on training completion and a missing document, so the handoff turns into messages, delay, and guesswork.

A stronger model makes the gate explicit. The file is ready for lender review only when the business entity exists, the required licenses for that venture type are verified, proof of insurance is attached, and the owner has completed the launch checklist tied to the financing packet. That changes the workflow in a concrete way. The intake coordinator can see why the handoff is blocked, the next operator inherits explicit evidence instead of tribal interpretation, and the lender receives a packet that matches the stated decision rule. The ontology matters because it turns a vague status label into an auditable operating standard.

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 that 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 changes what an operator can do tomorrow.

For Hadto, the operating standard should be explicit: model only what makes the business easier to run, easier to hand off, and easier to trust. If a concept does not sharpen a real decision, control a real validation step, or carry a real handoff, it does not belong at the center of the system.