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UX for Enterprise ChatGPT Solutions

You're reading from   UX for Enterprise ChatGPT Solutions A practical guide to designing enterprise-grade LLMs

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Product type Paperback
Published in Sep 2024
Publisher Packt
ISBN-13 9781835461198
Length 446 pages
Edition 1st Edition
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Author (1):
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Richard H. Miller Richard H. Miller
Author Profile Icon Richard H. Miller
Richard H. Miller
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Table of Contents (18) Chapters Close

Preface 1. Part 1:UX Foundation for Enterprise ChatGPT FREE CHAPTER
2. Chapter 1: Recognizing the Power of Design in ChatGPT 3. Chapter 2: Conducting Effective User Research 4. Chapter 3: Identifying Optimal Use Cases for ChatGPT 5. Chapter 4: Scoring Stories 6. Chapter 5: Defining the Desired Experience 7. Part 2: Designing
8. Chapter 6: Gathering Data – Content is King 9. Chapter 7: Prompt Engineering 10. Chapter 8: Fine-Tuning 11. Part 3: Care and Feeding
12. Chapter 9: Guidelines and Heuristics 13. Chapter 10: Monitoring and Evaluation 14. Chapter 11: Process 15. Chapter 12: Conclusion 16. Index 17. Other Books You May Enjoy

Giving context through prompt engineering

To be clear, when building a RAG solution, customers prompt the enterprise system for answers to questions, fill out forms, and interact through prompting. Additional prompts, called instructions, wrap these prompts to ensure they are constrained or managed within a context defined by the business. These instructions give the customer guardrails. Time for prompt engineering 101.

Prompt 101

Prompt engineering instructs the chat instance to respond. It frames or puts structure around the answer, defines what to include or exclude from responses, and provides any safety rails to implement.

Instructions can be tested and iterated. Hundreds of changes will be made before settling on better instructions. Multiple models will be doing pieces of the enterprise puzzle, each with its instructions. We will take a few minutes to clarify that we are focused on instructions, a form of prompts that a user needs to control how the model will respond...

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