Beyond the hype: building useful AI tools

The most interesting question about an AI feature is not which model it uses. It is what changes for the person doing the work. A summary that saves ten minutes may be more useful than a dazzling conversation that cannot be trusted.

Define a narrow job

Describe the input, the desired output, and the situations in which the tool should decline. A narrow task is easier to evaluate. Collect representative examples before choosing prompts so that success means more than one impressive demonstration.

Measure the errors people notice

Track omissions, invented facts, and failures to follow format. Review outputs against source material. When the task affects a consequential decision, provide the evidence and allow a person to review the result before acting.

A better practice begins with one decision you can repeat.

Design the recovery path

Assume that some requests will fail. Preserve the original material, show uncertainty clearly, and offer a simple manual route. A useful system earns trust by helping people recover, not by presenting every output with the same confidence.

Try this today

• Notice one habit connected to this idea.
• Choose a small change that fits your circumstances.
• Write down what worked after a week.

Progress does not need to be dramatic to be real. Give the practice time, and let your own experience shape what comes next.