Let AI teach you how to use AI

Ask AI where it could help and you will usually get broad suggestions.

Write faster. Summarize documents. Automate repetitive tasks. Brainstorm ideas.

Their breadth makes them hard to act on. The model needs to learn about your work before it can help you find a useful starting point.

Let the model interview you

Describe your role in plain language. Include what you are responsible for, what you repeat, what takes too long, and what must be done especially well.

Then ask the model to interview you one question at a time. For example:

Help me find practical ways to use AI in my work. Ask about my recurring tasks, bottlenecks, decisions, quality standards, and risks. Wait to recommend solutions until you understand the work.

A plain description is enough to begin. The interview creates the detail that a generic prompt lacks.

A restaurant owner and a commercial real estate analyst may both spend too much time on research. A few questions expose the different decisions, information, and standards hidden under that label. Their strongest AI opportunities will differ too.

Ask for three experiments

After the interview, ask for three small opportunities worth testing.

For each one, have the model explain the part of the work it could support, the information it would need, what a good result should look like, and how to test it safely.

Treat each recommendation as a hypothesis. Models can miss a constraint or invent a detail with complete confidence. Check product behavior in official documentation, follow your organization’s data rules, and involve a qualified person when the consequences are serious.

Choose the smallest useful experiment. You might test whether AI can create a decision log from meeting notes or compare vendors against criteria you provide. Use work you understand so you can evaluate the result.

Keep what you learn

After the test, record what became easier, where the output weakened, which context helped, and what still required a person.

Those notes become your own AI playbook. They reflect your work, standards, and mistakes, which makes them useful the next time you face a similar task.

At Ozian, confidence and competence grow together through this process. You see what is possible, test it against work you understand, and keep the methods that improve the result.

AI can help you discover the next useful step. Each experiment makes you better at choosing it.