Start With the Goal

The first step in good prompting is understanding what success looks like. If the task is vague, the output will be vague too.

A useful prompt usually provides:

• the task to perform,
• the expected format,
• the constraints to honor,
• and the quality bar to meet.

Write the Instruction

A strong instruction is specific without being overcomplicated. It should tell the model what to do, how to do it, and what kind of response to return.

In practice, prompts often work better when they include:

• a role or perspective,
• clear examples,
• and explicit boundaries.

Review the Response

The review step is where AI work becomes engineering. You check whether the answer is correct, complete, and safe enough for the intended use.

This is where you look for:

• hallucinations,
• missing detail,
• weak reasoning,
• and policy or safety issues.

Iterate to Improve Reliability

Prompting is rarely a one-shot activity. You improve the result by adjusting the prompt, adding context, and re-testing until the output is consistently useful.

That is the core habit of effective AI work: not “guess once,” but “evaluate and refine.”