Start with a different operating assumption.
An AI-native company is designed around capabilities that change the work the business can do. The question is larger than which tasks a model can complete. It is whether those capabilities make a different product, service, cost structure, or customer experience possible.
Consider a service that previously required a person to collect documents, reconcile records, and prepare every case from scratch. AI might change how that work is assembled. But the company still needs a buyer, dependable delivery, and a reason for customers to change their behavior. A compelling demonstration is the beginning of that inquiry.
Design the whole workflow.
We look at the path from a customer’s need to an accepted outcome. Where does information originate? Which system is authoritative? Who can approve an action? What happens when the evidence conflicts? These decisions determine whether an AI capability becomes a working business.
Anthropic distinguishes predefined workflows from agents that choose their next steps, and recommends starting with the simplest approach that meets the need. Our business-building implication is similar: choose the degree of autonomy the workflow deserves, rather than treating autonomy as the product’s purpose.
Prove the economics beyond the model call.
A useful test includes acquisition, integration, review, exceptions, and ongoing support. A cheaper first draft creates little advantage if somebody must rebuild it before it can be used. Equally, a carefully bounded product may create substantial value without replacing an entire role.
We would test a narrow outcome against the existing process: time to an accepted result, fully loaded cost, avoidable errors, and willingness to pay. These are evaluation criteria, not claims about a particular venture’s results.
Build for capability changes.
Models will change. A business needs durable reasons to exist: customer access, workflow knowledge, trust, distribution, and a delivery system that improves with use. The product architecture should make it possible to adopt better models without abandoning those advantages.
Our starting question is therefore concrete: what could this business deliver today that would have been impractical to deliver before? The answer should hold up in the customer’s operation, not only in a prototype.