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Last Updated on 6 months by Enise Ürek
ChatGPT is a tool that can be used for many different applications, from producing content to preparing strategies, just like a human. It works to give the best result through prompts. The concept that stands out at this stage is ChatGPT prompt engineering. In order to get the best result from this artificial intelligence, it is necessary to make the right prompts. ChatGPT produces content by guessing the next word in a written text. That is, it is the given prompt that shapes the prediction of this tool. This is the basis of ChatGPT demand engineering because it directs predictions of artificial intelligence. There are four basic principles that describe how the prompts should be. When ChatGPT is used correctly, many opportunities are available to businesses, so it is necessary to learn the most effective prompt strategies and take advantage of the possibilities of this tool. However, we recommend that you work with a content agency for SEO-compatible content.

Foundations of ChatGPT Prompt Engineering

ChatGPT prompt engineering is a method used to get the best result from this artificial intelligence. A properly prepared request must be made to get an effective output. You need to set the entry to get the responses from this tool in the desired direction. The response received with a basic prompt is not wrong, but ChatGPT can do much more. For this reason, the specification and elaboration of the request are one of the most ideal ways to direct the response. For example, instead of just doing data analysis, defining a role and listing its tasks in detail can give better results. This is called ChatGPT prompt engineering art.

Principles of Effective ChatGPT Prompt Engineering

Although ChatGPT prompt engineering seems complicated, it’s simple. The following principles form the basis of successful prompt engineering.

1. Prompt Wording

To get the desired directed output, it is first necessary to give an accurate input. Entries consist of prompts, so attention should be paid to prompt work. If you do not give input using the correct technical words, the answers you will probably get will not be in the direction you want. For this reason, you must make a request by giving details in the area where you are an expert. Despite this, giving extreme details is not always the best result. For this reason, it is sufficient to use the details only to describe the context.

2. Succinctness

Another important principle of this engineering is succinctness. As you can understand from its name, very long prompts can cause a deviation from the focus. For this reason, it is necessary to make a small but concise prompt. The balance is very important for this because it is necessary to strike a balance between too many details and excessive generalizations. When you explain what you want in the most accurate way, ChatGPT can also give a better answer than you expect.

3. Roles and Goals

Another important point is to define roles and goals. Giving a role to ChatGPT and making it easy to get the answer you want to set goals. For example, if you want to produce a marketing strategy for a new channel, giving ChatGPT a marketing expert role, identifying the target audience, and stating what you want to achieve will be of great help.

4. Positive and Negative Prompting

Making positive and negative guidance in ChatGPT demand engineering is a very important detail. In positive redirects, you must specify what you want to include in the answer, such as saying “Do this”. Negative prompting is likewise required to make a routing “Don’t these”. In this way, you include what you want in the answer you will receive and remove what you do not want.

Advanced ChatGPT Prompt Engineering Strategies

Although the principles above guide you to a large extent, they may not be sufficient in any case. For this reason, it would be useful to look at the effective strategies of ChatGPT prompt engineering and follow these strategies for more complex prompts.

1. Input/Output Prompting

It is a strategy that includes the answer you want to receive and the prompt you need to give for this response. For example, the request you will provide for input should clearly include the subject and details. In this way, it becomes easier to get an answer in the direction you want.

2. Chain-of-Thought Prompting

Chain-of-thought prompting is a strategy that includes providing several examples to get the desired response. This is an ideal method to improve your method input. Presenting the input with examples can give very effective results, especially for a new approach. For example, you can ask for a marketing strategy to create a strategy consistent with the new and past by providing a few examples that have been successful in the past and are compatible with your brand.

3. Zero-Shot Prompting

No examples are presented in this strategy; it is aimed at getting a response with only one input. For this reason, no context is offered in zero-shot prompting. This type of strategy is an ideal method to use when you want to get a general and quick response.

4. One-Shot Prompting

In this strategy, a response or a sample is partially directed toward the desired accuracy. Ideal for a slightly more purposeful response. For example, the orientation that can be made for 10 content ideas to be produced on Instagram may be to indicate that past content is in the field of health.

5. Few-Shot Prompting

Another strategy for ChatGPT prompt engineering is done in a similar way to others. This time, by giving a few examples, the answer is drawn in the desired direction. If you need to go through the above example, areas such as health, psychology, and social relationships can be cited as examples for 10 content ideas. The point that distinguishes this strategy from others that it offers more than one example.

6. Self-Criticism

It is also possible to take advantage of the power of self-criticism in this engineering. ChatGPT has the capacity to do many things, including self-criticism. If the response is incorrect, you can ask ChatGPT to make a self-criticism. In this way, ChatGPT can extract errors for you and give the most accurate result.

7. Iterative

Iterative is a ChatGPT prompt engineering strategy that involves directing answers by asking successive questions. In this strategy, a request is made first, and a response is received. Then a request is given again according to the response, and this situation is continued in this way. It is an ideal method for progressing step by step.

All the strategies included here make it easier for you to get maximum benefit from this tool through ChatGPT prompt engineering.

Orkun Koksalan

Orkun Koksalan graduated from Istanbul Kultur University, Department of Electronics. He has been working as an SEO Specialist at Cremicro since 2022.

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