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Unlocking the Secrets of Prompt Engineering

Unlocking the Secrets of Prompt Engineering

By : Gilbert Mizrahi
4.6 (16)
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Unlocking the Secrets of Prompt Engineering

Unlocking the Secrets of Prompt Engineering

4.6 (16)
By: Gilbert Mizrahi

Overview of this book

Unlocking the Secrets of Prompt Engineering is your key to mastering the art of AI-driven writing. This book propels you into the world of large language models (LLMs), empowering you to create and apply prompts effectively for diverse applications, from revolutionizing content creation and chatbots to coding assistance. Starting with the fundamentals of prompt engineering, this guide provides a solid foundation in LLM prompts, their components, and applications. Through practical examples and use cases, you'll discover how LLMs can be used for generating product descriptions, personalized emails, social media posts, and even creative writing projects like fiction and poetry. The book covers advanced use cases such as creating and promoting podcasts, integrating LLMs with other tools, and using AI for chatbot development. But that’s not all. You'll also delve into the ethical considerations, best practices, and limitations of using LLM prompts as you experiment and optimize your approach for best results. By the end of this book, you'll have unlocked the full potential of AI in writing and content creation to generate ideas, overcome writer's block, boost productivity, and improve communication skills.
Table of Contents (18 chapters)
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1
Part 1:Introduction to Prompt Engineering
4
Part 2:Basic Prompt Engineering Techniques
8
Part 3: Advanced Use Cases for Different Industries
13
Part 4:Ethics, Limitations, and Future Developments

Automating bulk prompting with spreadsheets

In the previous chapters, we explored creating social media posts (Chapter 2) and performing sentiment analysis, data classification, and data cleaning (Chapter 5). For these types of tasks, which are often performed for multiple records, prompting an LLM manually on a case-by-case basis can be tedious and inefficient.

While tools such as ChatGPT, Bard, and Claude 2 allow the usage of variables, you still need to copy and paste input text to process it through the LLM. Then, you have to copy the model’s output and paste it into a spreadsheet or another document.

Rather than manual prompting, it’s better to automate these workflows. By integrating your LLM with Google Sheets using Apps Script, you can create custom formulas that automatically rerun prompts on many inputs in bulk.

For example, you could write a formula such as =AI_GPT(A2) that takes the text from cell A2, sends it to the GPT-3/4 API, and returns the response...

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