Unlocking the Secrets of Prompt Engineering E-Book

Gilbert Mizrahi

• Herausgeber: Packt Publishing
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 436

Veröffentlichungsjahr: 2024

Beschreibung

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.

Leseprobe

Unlocking the Secrets of Prompt Engineering

Master the art of creative language generation to accelerate your journey from novice to pro

Gilbert Mizrahi

BIRMINGHAM—MUMBAI

Unlocking the Secrets of Prompt Engineering

Copyright © 2023 Packt Publishing

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Publishing Product Manager: Nitin Nainani

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First published: January 2024

Production reference: 1111223

Published by Packt Publishing Ltd.

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B3 1RB, UK

ISBN 978-1-83508-383-3

www.packtpub.com

To my incredible wife, Maria Olga – you are my rock and my best friend. Thank you for always believing in me. To my son, Daniel, and daughter, Andrea – you both make me strive to be a better person every day. Your unwavering belief in me gave wings to this dream. This book is for you.

– Gilbert Mizrahi

Foreword

In the dynamic and fast-evolving landscape of AI (artificial intelligence), Gilbert Mizrahi’s latest book on the new discipline of Prompt Engineering stands as a beacon of practical knowledge and insight. As Founder and CEO of Aptima, Inc., I have known the author for more than 20 years since we were colleagues in the Company, inventing novel ways to engineer productive collaborations between humans and machines. It is my distinct honor and privilege to introduce this comprehensive and pioneering work.

Gilbert has always been at the forefront of innovation and technology since his days at Stanford, and this book is a testament to his deep understanding and insightful approach to large language models (LLMs) and generative AI. This work is not just a technical guide; it is a journey through the complex world of prompt engineering, underscored by a commitment to sound practices and a deep understanding of the transformative power of AI.

The book begins with a solid foundation in the basics of LLMs and moves through the intricacies of prompt engineering with the precision and clarity rarely found in the computer science and engineering field. His emphasis on ethics throughout the book is particularly commendable, ensuring that as we advance technologically, we do so with a conscientious mindset. As we experience throughout the book, prompt engineering is akin to crafting a meticulous recipe, where each ingredient – or, in this case, each element of the prompt – must be carefully honed to guide LLMs towards desired outcomes.

As we delve into the subsequent chapters of this incredible journey, the book masterfully decomposes and then synthesizes the core concepts. It also highlights innovative applications of prompt engineering across various industries. We are given a vivid glimpse into the future where prompt engineering could revolutionize fields like healthcare, offering compelling applications in clinical decision support, patient education, and drug discovery.

Gilbert’s foresight in anticipating future trends and breakthroughs in LLMs underscores the need for collaboration and continual learning in this field. His exploration of the diverse applications of LLMs illustrates their potential to fundamentally transform nearly every industry and domain. The book not only serves as a technical guide but also as a behavioral compass in the digital age, emphasizing the need for wisdom, care, and transparency as these capabilities advance.

In conclusion, Gilbert Mizrahi’s book is an indispensable resource for both newcomers and seasoned professionals in AI. It is a guide to understanding and mastering the art and science of prompt engineering to establish a fruitful dialog between the human user and the artificial intelligence, and a reminder of the collaborative effort required to harness its full potential responsibly. This book is a beacon for those navigating the evolving landscape of AI, reflecting a profound understanding of the technological, ethical, and practical aspects of LLMs.

I recommend this book to all who seek to explore the extraordinary possibilities of AI and prompt engineering. It is with great pride that I introduce this significant contribution to the field of AI, celebrating the achievements of a long-time colleague and friend.

Daniel Serfaty

Founder and CEO

Aptima, Inc.

Contributors

About the author

Gilbert Mizrahi is a product strategist, educator, and seasoned entrepreneur with a proven track record across a variety of industries. He brings a wealth of knowledge and experience in interactive data visualization, product strategy innovation, generative AI, and Software as a Service (SaaS). As a co-founder of Twnel, Gilbert steers product R&D, leveraging his expertise in artificial intelligence to craft cutting-edge solutions that enhance communication and productivity for businesses. His passion for data science and product growth is mirrored in his ventures.

He holds a master’s degree in operations research from Stanford University and a bachelor’s degree in industrial engineering. Gilbert's extensive background includes serving as a mentor at MassChallenge and Newchip Accelerator, business strategy and product development consultant at Looi Consulting, and holding senior research and technology positions at Aptima Inc.

Gilbert's forward-thinking approach, entrepreneurial spirit, and dedication to fostering innovation make him a vanguard in the application of generative AI and strategy in product development.

About the reviewers

Daniel Mizrahi, a software engineer at Google, specializes in automating third-party service deployments to Google Cloud. Over the past two years, he has focused on creating systems that not only enhance operational efficiency but also pave the way for more advanced cloud-based applications. His experience has given him a profound understanding of the nuances of modern cloud-based systems.

Before his current role at Google, Daniel was on the Amazon Prime Video team, working specifically on a portal for content providers. This experience honed his skills in creating user-focused software solutions and deepened his appreciation of the intricate relationship between software engineering and digital content distribution.

Daniel holds a master’s degree in computer science from the University of Southern California with a focus on machine learning and artificial intelligence. Daniel’s academic background forms the bedrock of his technical expertise.

Divit Gupta, a seasoned IT professional with 20 years of industry expertise, excels in driving strategic architecture initiatives and providing leadership in multi-pillar sales cycles. With a global impact, he spearheads technical partnerships, defines team vision, and champions new strategic endeavors.

As the host of popular podcasts such as Tech Talk with Divit, Live Labs with Divit, and Cloud Bites with Divit, he showcases Oracle’s technological initiatives and leadership. In 2022–23, he served as Oracle TV’s correspondent for Cloud World. His passion for knowledge sharing extends to international conference talks, technical blogs, and multiple books on emerging technologies.

A recognized expert, Divit presented on Oracle Database technology at Oracle CloudWorld FY 2023. Holding over 40 certifications from Microsoft, Oracle, AWS, and Databricks, he remains at the forefront of technology.

David Santiago Castillo, with an extensive tenure of over a decade at Twnel, is a seasoned software developer who has played a pivotal role in the evolution of the company’s communication platform. Twnel, initially founded as a messaging platform, has since transformed into a cutting-edge solution that automates business processes through conversational user interfaces. In the rapidly evolving landscape of AI and natural language processing, David has been at the forefront of harnessing the power of large language models to enhance and expand Twnel’s automation capabilities.

Table of Contents

Preface

Part 1: Introduction to Prompt Engineering

1

Understanding Prompting and Prompt Techniques

Technical requirements

Introducing LLM prompts

How LLM prompts work

Architecture

LLM training

A journey from prompt to reply – how inference helps LLMs fill in the blanks

Types of LLM prompts

Components of an LLM prompt

Adopt any persona – role prompting for tailored interactions

Few-shot learning – training models with example prompts

Finding your voice – defining personality in prompts

Using patterns to enhance prompt effectiveness

Mix and match – strategic combinations for enhanced prompts

Exploring LLM parameters

How to approach prompt engineering (experimentation)

The challenges and limitations of using LLM prompts

Summary

2

Generating Text with AI for Content Creation

Using AI for copywriting

Creating social media posts

Writing a Twitter thread

Writing an Instagram post

Producing high-converting sales copy

Writing video scripts

Generating blog posts, articles and news

Creating engaging content with AI

How to use AI for personalized messaging

Creating tailored content with AI

Summary

Part 2: Basic Prompt Engineering Techniques

3

Creating and Promoting a Podcast Using ChatGPT and Other Practical Examples

Crafting podcast questions for celebrity guests

Preparing podcast questions with everyday guests

Identify topics, ideas, and potential guest speakers for your podcast

Using AI to promote a podcast

Writing a summary of the podcast episode

Crafting engaging quotes for social media promotion

Conceptualizing podcast highlight reels

Repurposing podcasts into shareable blog content

Identifying insightful interview questions

Sharpening interview skills with AI-generated responses

Generating strategic questions for client engagements with AI

Summary

4

LLMs for Creative Writing

Using AI for creative writing

Using AI to generate fiction

Using AI to write poetry

Summary

5

Unlocking Insights from Unstructured Text – AI Techniques for Text Analysis

Sentiment analysis – AI techniques for emotion detection in text

Organizing unstructured data – using AI for automated text categorization and data classification

Cleaning up dirty data – how AI identifies and resolves issues in datasets

Making sense of unstructured data – pattern matching for information extraction

Summary

Part 3: Advanced Use Cases for Different Industries

6

Applications of LLMs in Education and Law

Creating course materials with ChatGPT

Creating handouts and other materials

Creating handouts for the unit

Creating solved examples

Word problems

Creating quizzes

Creating rubrics

Creating cloze comprehension tests

AI for legal research

Reviewing legal documents using an LLM

Drafting legal documents with an LLM

AI for legal education and training

LLMs for eDiscovery and litigation support

AI for intellectual property (IP) management

Other applications of LLMs for lawyers

Summary

7

The Rise of AI Pair Programmers – Teaming Up with Intelligent Assistants for Better Code

Code generation with coding assistants

From confusion to clarity – AI explains what code does in plain English

Commenting, formatting, and optimizing code

Fixing faulty code – how AI transforms the debugging process

Translating code from one language to another

Case study 1 – developing a website code using AI

Case study 2 – creating a Chrome extension using AI

Summary

8

AI for Chatbots

Technical requirements

How to use GPT-4 APIs and other LLM APIs to create chatbots

Building conversational interfaces with LLM APIs

How to use AI for customer support

Case study – a chatbot using AI to assist users in ordering products

Case study – creating interactive quizzes/assessments and deploying them as chatbot flows

Summary

9

Building Smarter Systems – Advanced LLM Integrations

Automating bulk prompting with spreadsheets

Integrating LLMs into your tech stack using Zapier and Make

Creating and translating product descriptions

Moving beyond APIs – building custom LLM pipelines with LangChain

LangChain’s building blocks

LangChain's no-code tools – Langflow and Flowise

LangSmith – debug, test, and monitor your LLM workflows

The future of LLM integration – plugins, agents, assistants, GPTs, and multimodal models

Summary

Part 4: Ethics, Limitations, and Future Developments

10

Generative AI – Emerging Issues at the Intersection of Ethics and Innovation

Exploring the ethical challenges of generative AI

Trust and accountability challenges of generative AI

Economic impact considerations

Environmental sustainability issues

Societal risks and reflections

Broader societal impacts

What machine creativity reveals about cognition

Concerns in defense and healthcare

The path forward – solutions and safeguards

Summary

11

Conclusion

Recap of the book’s content

Expanding possibilities – innovative prompt engineering applications

Achieving intended outcomes – prompt engineering goals

Understanding limitations and maintaining oversight

Summary

Index

Other Books You May Enjoy

Part 1:Introduction to Prompt Engineering

Part 1 establishes a comprehensive foundation in the world of prompt engineering for language AIs. Chapter 1 offers an expansive exploration of AI prompts, elucidating their composition, categories, real-world applications, underlying concepts, and techniques to shape desired model outputs.

Equipped with insights into prompt architecture and the inner workings of language models, you can systematically craft precise prompts to achieve your intended results. Building on these core concepts, Chapter 2 demonstrates leveraging tools such as ChatGPT for automated content creation.

Practical use cases such as developing viral social posts or high-converting sales copy are examined. Additionally, personalization and engagement strategies are covered to ensure that your content resonates with target audiences.

With proven prompt engineering best practices, Part 1 empowers you to tap the phenomenal potential of language AIs to enhance content development workflows. The stage is set to apply these skills and explore innovative applications across manifold domains in subsequent chapters.

This part has the following chapters:

Chapter 1, Understanding Prompting and Prompt TechniquesChapter 2, Generating Text with AI for Content Creation