Most people think AI isn’t quite as effective as everyone says it is. However, this isn’t true. In reality, AI isn’t the problem. It’s the way people use it. When the instructions are vague, the response to those instructions is also going to be vague. This is the problem with most people. They simply don’t use AI correctly.

The definition of AI prompting is simply giving instructions to the AI in a manner in which it can effectively use them. In other words, the results are directly proportional to the quality of the instructions provided to the AI. In other words, better instructions mean better results.

Why Most People Get AI Wrong

This can be seen in the real world. When people use AI, they’ll type something like “help me with my business,” and then expect a thoughtful response. But what they get instead is something vague and unhelpful. However, when one really thinks about it, even a human wouldn’t really know how to properly respond to this type of request.

There’s no real direction, no real context, and no real end goal in mind. So what does the AI do instead? It does what it can with the information provided to it. In this case, it would simply fill in the gaps and provide general information. In other words, this is where the age-old concept of “garbage in, garbage out” comes into play.

This is also the reason why two different people may use the same AI tool and yet obtain vastly different results. One makes a vague request and receives a vague response. The second makes a clear request and receives a clear and useful response.

Prefer seeing this in action?

If you’d like to see how these concepts were explained step-by-step in the actual mentorship session, watch the full walkthrough below:

How to Prompt AI Effectively

If you want to obtain better results from an AI tool, it is essential to consider it a machine that only understands instructions literally and does not assume context or fill in the blanks like a human brain does. The more clear your instruction is, the more accurate your result will be.

If you follow a basic structure, it will make a big difference. The first step is to clearly tell the AI tool what it is that you want. The second step is to provide context so that the AI tool understands your context and your situation. The third step is to clearly define your task so that it does not misunderstand your request. The fourth step is to refine your result rather than stopping with the first result.

For instance, if you want to improve your communication skills, you should describe your situation and the tone you want to achieve. For example: “I’m writing an email to a client who has delayed payment for two weeks and I need it to sound polite, professional and assertive. This by itself will produce a vastly better result for you. Finally, you can refine it by asking for different tones and when to use each tone.

If you look at the difference between the two different prompts side by side, it becomes crystal clear that the level of clarity in your request makes a tremendous difference in the quality of your result.

Common Prompting Mistakes to Avoid

There are a few mistakes that are consistently made and they reduce the quality of the output. One is being too vague. If the instruction is too vague, then the output is not specific. Asking too many unrelated questions at once is another one.

Another problem is not providing enough background information. If background information is not provided, then the AI will default to general assumptions, rather than providing more personalized output.

Finally, one of the largest problems is not refining the output after the first pass. That is where the real power is.

If you want to increase the quality of your output, then you should be more specific with your instructions, specify how you want the answer and refine the output after the first pass. These are small steps, but they will make a huge difference.

Final Thought. The power of AI is huge, and it is completely dependent upon how you use it. When you learn how to properly prompt, then you stop wondering and start getting results that are clear, relevant, and practical.

If your results are not yielding good output, then it is not the AI’s fault; it is your fault for not providing proper instructions.