Introduction to Prompt Engineering: Unlocking the Potential of Language Models with Google Sheets and Google App Script


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In recent years, AI-powered language models like GPT-3.5 Turbo and GPT-4 have gained significant attention for their ability to generate human-like text. They have been used for a wide range of applications, including content generation, text summarization, translation, and more. A crucial aspect of leveraging these models effectively is prompt engineering. In this blog post, we will introduce prompt engineering, explain its importance, and explore how it can be applied using Google Sheets and Google App Script.

What is Prompt Engineering?

Prompt engineering is the art of designing and refining the input text or “prompt” given to a language model to obtain the desired output. It involves carefully crafting prompts and iterating on them to improve the model’s understanding and responses. With the right prompt engineering techniques, you can optimize your AI model’s performance and generate better results.

Why is Prompt Engineering Important?

The quality of the output generated by a language model is heavily dependent on the input prompt it receives. A well-structured, unambiguous prompt will help the model understand your intention and generate more accurate and relevant responses. Conversely, an unclear or poorly formatted prompt may result in incorrect or irrelevant outputs.

Prompt engineering can also help you overcome some of the inherent limitations of AI language models. For instance, it can help mitigate model biases, provide better control over response length and randomness, and enhance the overall output quality.

Using Google Sheets and Google App Script for Prompt Engineering

Google App Script is a scripting platform that allows you to automate tasks, integrate with Google services, and create custom applications using JavaScript. By combining the power of Google App Script with AI language models like GPT-3.5 Turbo and GPT-4, you can create powerful, AI-driven applications with minimal coding.

In this tutorial, we’ll demonstrate how to integrate AI language models with Google Sheets using Google App Script to harness the power of prompt engineering.

Setting Up Google Sheets and Google App Script

  1. Create a new Google Sheet and give it a name.
  2. Click on “Extensions” in the menu bar and then select “Apps Script.”
  3. In the script editor, delete any placeholder code.

Now that you have set up Google Sheets and Google App Script, you can begin integrating AI language models like GPT-3.5 Turbo and GPT-4 using prompt engineering techniques.

Integrating Language Models with Google Sheets and Google App Script

To integrate an AI language model like GPT-3.5 Turbo or GPT-4 with Google Sheets and Google App Script, you will need access to an API key from the respective provider (e.g., OpenAI). Once you have an API key, follow these steps:

  1. Add a new script file to your project (e.g.,
  2. Define a function to call the AI language model’s API:

function callLanguageModelAPI(givenPrompt) {
  const apiKey = 'your-api-key-here';
  const apiUrl = '';
  // Set up the message format for the prompt
  var messageForAI = [
    { role: "user", content: givenPrompt },

  const options = {
    method: 'POST',
    headers: {
      'Authorization': 'Bearer '+apiKey,
      'Content-Type': 'application/json'
    payload: JSON.stringify({
      messages: messageForAI,
      model: "gpt-3.5-turbo,

  const response = UrlFetchApp.fetch(apiUrl, options);
  const json = JSON.parse(response.getContentText());

  // Access the generated message content
  const generatedMessage = json['choices'][0]['message']['content'];
  return generatedMessage;
  1. Create a custom function in the script that you can use in your Google Sheets:
function GET_AI_RESPONSE(givenPrompt) {
  return callLanguageModelAPI(givenPrompt);
  1. Save your script, and return to your Google Sheet.

Now you can use the custom function =GET_AI_RESPONSE() in your Google Sheets to generate AI-driven responses based on the prompts you provide.

Using Prompt Engineering Techniques in Google Sheets

With the integration in place, you can now apply prompt engineering techniques in Google Sheets to improve the quality of AI-generated text.

  1. Craft explicit and clear prompts: Write prompts that are specific, well-structured, and provide enough context for the model to understand your intention.
=GET_AI_RESPONSE("Write a summary of the benefits of using renewable energy sources.")
  1. Use few-shot examples to guide the model: If necessary, provide examples of the desired output before submitting the main prompt.
=GET_AI_RESPONSE("You are a helpful assistant. Write a list of three, original, attention-grabbing titles for the subtopic 'The Home Search Process' for the category 'Buying Homes' that: 1. follow the prompt: Pretend you are seeking to create a blog that helps educate people on real estate, specifically buying and selling different types of homes from the perspective of an expert in the field, 2. Are not numbered, AND 3. These article titles need to be independent with very little overlap. Perfect! Now, write a brief introduction for an article on 'The Benefits of Hiring a Buyer's Agent.'")
  1. Iterate on your prompts and experiment with different styles: Refine the prompts based on the AI-generated responses and test different formats (e.g., questions, statements, conversations) to find what works best for your desired output.


Prompt engineering is an essential skill for leveraging the power of AI language models like GPT-3.5 Turbo and GPT-4 effectively. By combining Google Sheets and Google App Script, you can create a seamless, easy-to-use interface for generating AI-driven content while applying prompt engineering techniques.