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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
2. Chapter 1: Recognizing the Power of Design in ChatGPT FREE CHAPTER 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

Designing chat experiences

An LLM-powered chat experience comes in a few flavors: a straight chat-only experience, such as OpenAI’s chat UI, or a chat window that is part of a more extensive GUI experience. Each has unique issues, and both have a collection of issues to address. A traditional chat-only experience is an excellent place to start.

Chat-only experiences

Many, if not most, readers will have this use case: a conversational experience backed with a ChatGPT solution. It might support a traditional conversational AI platform (Salesforce, Oracle’s Digital Assistant, Alexa, Google Assistant, or one of the dozens of other vendors) or eventually replace them. However, the primary interaction is via a chat window with chat responses. This means the channel SMS (text messaging), WhatsApp, WeChat, Facebook, LinkedIn, a web experience, Slack, Teams, or other services depend on the technology those channels support for integrations, backend services, security, and...

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