The Art of Prompt Engineering

Imagine a world where every interaction with AI in your business results in innovative solutions and accurate answers. That is the power of prompt engineering. As language models based on artificial intelligence, such as GPT-3 and GPT-4, are transforming the business landscape, knowing how to formulate effective prompts has become an invaluable asset for businesses.

Understanding the underlying language model

‍In the professional context, understanding the capabilities and limitations of AI language models is crucial. These systems learn vast amounts of textual data and respond accordingly. A thorough understanding of how they work makes it possible to create prompts that maximize their potential while minimizing errors.

Principles of Writing a Good Business Prompt

➡️ Clarity and Business Objective: Prompts should be formulated clearly and aligned with specific business goals.

➡️ Professional Background: Providing a business context helps AI generate responses tailored to business needs.

➡️ Accuracy and Relevance: Prompts should aim for relevance and precision to ensure useful responses in a professional setting.

Examples and Business Use Cases

‍For example, instead of vaguely asking, “How can operational efficiency be improved?” , a more targeted prompt could be “What specific AI-based strategies can improve operational efficiency in the logistics sector?” This directs AI towards solutions that are more adapted and applicable in a business context.

Best Practices and Tips for Businesses

‍Businesses should encourage experimenting with different types of prompts to find out what works best in their specific areas. It is also important to train employees to the art of prompt engineering to optimize the use of AI tools.

Practical applications in a professional context

‍Prompt engineering finds its place in various business functions: from automatic report generation to customer service, through market analysis and strategic planning. The opportunities to improve efficiency, innovation, and decision-making are vast.

Here are 25 quick principles for an effective request to MLLs.

1 - There is no need to be polite with language models, so there is no need to add expressions like “please”, “if you don't mind”, “thank you”, “I would like”, etc., and to get to the point.

2 - Integrate the targeted audience into the prompt, for example, the audience is an expert in the field.

3 - Break down complex tasks into a sequence of simpler prompts in an interactive conversation.

4 - Use affirmative instructions such as “do,” while avoiding negative language like “don't do.”

5 - When you need clarity or a thorough understanding of a topic, idea, or any information, use the following prompts: o Explain [insert specific topic] in simple terms. o Explain to me as if I were 11 years old. o Explain to me as if I were a beginner in [field]. o Write the [essay/text/paragraph] in simple English as if you were explaining something to a 5-year-old child.

6 - Add “I'm going to tip $xxx for a better solution! ”

7 - Implement prompts based on examples (Use prompts to a few examples). When formulating your prompt, start with “## #Instruction ###”, followed by either “## #Exemple ###” or “## #Question ###” if relevant. Then, present your content. Use one or more line breaks to separate instructions, examples, questions, context, and input data.

8 - Incorporate the following sentences: “Your task is” and “You MUST.”

9 - Incorporate the following sentence: “You will be penalized.”

10 - Use the phrase “Answer a question in a natural and human way” in your prompts.

11 - Use introductory words like writing “think step by step.”

12 - Add the following sentence to your prompt: “Make sure your response is unbiased and not based on stereotypes.”

13 - Allow the model to solicit specific details and requirements from you by asking you questions until it has enough information to provide the necessary result (for example, “From now on, I would like you to ask me questions to...”).

14 - To learn about a specific topic or idea or any information and you want to test your understanding, you can use the following sentence: “Teach me the [whole theorem/topic/rule] and include a test at the end, but don't give me the answers, but don't give me the answers and tell me if I have the correct answer when I answer.”

15 - Assign a role to large language models.

16 - Use delimiters.

17 - Repeat a specific word or phrase several times in a prompt.

18 - Combine Chain Thinking (CoT) with quick examples.

19 - Use exit primers, which consist in concluding your prompt with the start of the desired output. Use exit primers by ending your prompt with the start of the anticipated response.

20 - To write an essay/text/clause/article or any type of text that needs to be detailed: “Write a detailed [essay/text/paragraph] for me on [topic] in detail by adding all the necessary information”.

21 - To correct/modify a specific text without changing its style: “Try to review each paragraph sent by users. You should only improve the user's grammar and vocabulary and make sure it sounds natural. You shouldn't change the writing style, like making a formal paragraph casual.”

22 - When you have a complex coding prompt that may be in different files: “Now, whenever you generate code that spans more than one file, generate a programming language script that can be run to automatically create the specified files or make changes to [existing files] to insert the generated code. According to your question]”.

23 - I am providing you with the beginning [song lyrics/story/column/essay/...]. [Insert words/words/phrase]. o End according to the words provided. Maintain the consistency of the flow.

24 - Clearly state the requirements that the model must follow to produce content, in the form of keywords, regulations, clues, or instructions.

25 - To write text, such as an essay or paragraph, that is intended to be similar to a sample provided, include the following instructions: o Use the same language based on the paragraph /title/text/test/answer provided.

‍Source: Principled Instructions Are All You Need for Questioning Llama-1/2, GPT-3.5/4)

Conclusion

‍By mastering the art of prompt engineering, businesses can make the most of AI language models to drive innovation, improve processes, and remain competitive. As the integration of AI into the business world intensifies, those who master this skill will be at the forefront of shaping the future of their industry.

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