You're reading from Generative AI-Powered Assistant for Developers Accelerate software development with Amazon Q Developer

Product type Paperback

Published in Aug 2024

Publisher Packt

ISBN-13 9781835089149

Length 416 pages

Edition 1st Edition

Tools

AWS

Concepts

GPT/LLMs

Authors (2):

Behram Irani

Rahul Sonawane

Preface

1. Part 1:Generative AI-Powered Assistant

2. Chapter 1: Introduction to Generative AI-Powered Assistants FREE CHAPTER

3. Chapter 2: Introducing and Setting Up Amazon Q Developer

4. Part 2:Generate Code Recommendations

5. Chapter 3: Understanding Auto-Code Generation Techniques

6. Chapter 4: Boost Coding Efficiency for Python and Java with Auto-Code Generation

7. Chapter 5: Boost Coding Efficiency for C and C++ with Auto-Code Generation

8. Chapter 6: Boost Coding Efficiency for JavaScript and PHP with Auto-Code Generation

9. Chapter 7: Boost Coding Efficiency for SQL with Auto-Code Generation

10. Chapter 8: Boost Coding Efficiency for Command-Line and Shell Script with Auto-Code Generation

11. Chapter 9: Boost Coding Efficiency for JSON, YAML, and HCL with Auto-Code Generation

12. Part 3:Advanced Assistant Features

13. Chapter 10: Customizing Code Recommendations

14. Chapter 11: Understanding Code References

15. Chapter 12: Simplifying Code Explanation, Optimization, Transformation, and Feature Development

16. Chapter 13: Simplifying Scanning and Fixing Security Vulnerabilities in Code

17. Part 4:Accelerate Build on AWS

18. Chapter 14: Accelerate Data Engineering on AWS

19. Chapter 15: Accelerate Building Solutions on AWS

20. Chapter 16: Accelerate the DevOps Process on AWS

21. Index

22. Other Books You May Enjoy

How developers/builders benefit from assistants

Generative AI assistants for developers are useful for several key reasons:

Improved productivity: They automate repetitive coding tasks and workflows, allowing developers to get more done in less time. Things such as autocomplete, code generation, and debugging assistance directly save developers time and effort.
Reduce cognitive load: By handling rote tasks and providing context-aware recommendations, AI assistants reduce the burden on a developer’s working memory. This frees up mental bandwidth for more complex problem-solving.
Code discoverability: Features such as natural language code search and summaries improve the discoverability of code bases. Developers can more easily find and understand relevant code examples.
Knowledge sharing: AI models can encode programming best practices and patterns. This makes it easier to share knowledge across developer teams.
Consistency: Code generated or optimized...