Most tools built on large language models today are generic. They are more like frameworks than finished solutions. They are designed to be flexible, configurable, and reusable across many different domains.

Because of this, they can be set up to generate text that looks like expertise in almost any area. With the right instructions, a model can be told to act like a lawyer, a doctor, an engineer, or a consultant. On the surface, it will often look and sound like a real expert system.

You can instruct a language model to present itself as an expert in a specific field, and it will produce answers that non-specialists are likely to believe. The output uses the right language, has the right structure, and appears confident. For many people, this is enough to trust it.

This illusion is very attractive for companies that develop these tools. By keeping the core product generic, they can sell the same tool to many different customers in many different industries. With some light configuration or domain-specific prompts, it can be marketed as a solution for almost any field.

The vendors also avoid the heavy work of really understanding each professional domain and making sure the tool is actually good enough for that domain. They do not need to take responsibility for the difficult part: guaranteeing quality and reliability for specific tasks. It is easy to leave that burden to the users.

Customers, however, often want something different. Many of them do not want to develop their own solution on top of a tool. They have a concrete problem they want solved. They want a solution, not a flexible framework they have to shape into a solution themselves.

So the shortcut to building a real solution is not to make a language model appear as if it can solve the task. Making the tool look and sound like an expert system does not turn it into a proper, domain-ready system. It only changes the surface. The harder, more important work remains: understanding the domain, defining what “good enough” means, and building something that actually solves a specific problem in a reliable way.