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  • Book Overview & Buying Generative AI-Powered Assistant for Developers
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Generative AI-Powered Assistant for Developers

Generative AI-Powered Assistant for Developers

By : Behram Irani, Rahul Sonawane
5 (4)
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Generative AI-Powered Assistant for Developers

Generative AI-Powered Assistant for Developers

5 (4)
By: Behram Irani, Rahul Sonawane

Overview of this book

Many developers face the challenge of managing repetitive tasks and maintaining productivity. This book will help you tackle both these challenges with Amazon Q Developer, a generative AI-powered assistant designed to optimize coding and streamline workflows. This book takes you through the setup and customization of Amazon Q Developer, demonstrating how to leverage its capabilities for auto-code generation, code explanation, and transformation across multiple IDEs and programming languages. You'll learn to use Amazon Q Developer to enhance coding experiences, generate accurate code references, and ensure security by scanning for vulnerabilities. The book also shows you how to use Amazon Q Developer for AWS-related tasks, including solution building, applying architecture best practices, and troubleshooting errors. Each chapter provides practical insights and step-by-step guidance to help you fully integrate this powerful tool into your development process. You’ll get to grips with effortless code implementation, explanation, transformation, and documentation, helping you create applications faster and improve your development experience. By the end of this book, you’ll have mastered Amazon Q Developer to accelerate your software development lifecycle, improve code quality, and build applications faster and more efficiently.
Table of Contents (23 chapters)
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1
Part 1:Generative AI-Powered Assistant
4
Part 2:Generate Code Recommendations
12
Part 3:Advanced Assistant Features
17
Part 4:Accelerate Build on AWS

Understanding Auto-Code Generation Techniques

In this chapter, we will look at the following key topics:

  • What is a prompt?
  • Single-line prompts for auto-code generation
  • Multi-line prompts for auto-code generation
  • Chain-of-thought prompts for auto-code generation
  • Chat with code assistant for auto-code generation
  • Common building methods of auto-code generation

With the growth in large language model (LLM) applications, one of the interesting use cases, auto-code generation based on user comments, has become popular. The last few years have given rise to multiple code assistants for developers, such as GitHub Copilot, Codex, Pythia, and Amazon Q Developer, among many others. These code assistants can be used to get code recommendations and, in many cases, generate error-free code from scratch, just by passing a few plain text comments that describe what the user requires from the code.

Many of these code assistants are now backed by LLMs. LLMs are...

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Generative AI-Powered Assistant for Developers
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