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GitHub Copilot Automation and AI Development: A Practical Guide to AI-Powered Automation, Agentic Coding, Intelligent Workflows, Codebase Management,
Paperback
Series: Github Copilot AI Development, Book 2
Please select the version of book you would like to purchase.
ISBN13: 9798175272889
Publisher: Independently Published
Published: Sep 18 2026
Pages: 234
Weight: 0.91
Height: 0.49 Width: 7.00 Depth: 10.00
Language: English
Publisher: Independently Published
Published: Sep 18 2026
Pages: 234
Weight: 0.91
Height: 0.49 Width: 7.00 Depth: 10.00
Language: English
GitHub Copilot Automation and AI Development explores the next stage of AI-assisted software engineering: using GitHub Copilot to support intelligent development workflows, automate repetitive tasks, work with complex codebases, and build more efficient software development processes.
As AI coding tools evolve beyond simple code completion, developers can use them for increasingly sophisticated tasks across the development lifecycle. This book examines how to approach AI-powered development as a workflow rather than a collection of isolated coding suggestions. You will learn how to combine Copilot's capabilities with structured instructions, project context, development tools, and automation techniques to create more productive and repeatable workflows.
As AI coding tools evolve beyond simple code completion, developers can use them for increasingly sophisticated tasks across the development lifecycle. This book examines how to approach AI-powered development as a workflow rather than a collection of isolated coding suggestions. You will learn how to combine Copilot's capabilities with structured instructions, project context, development tools, and automation techniques to create more productive and repeatable workflows.
The book covers AI-assisted automation, coding agents, intelligent development workflows, codebase analysis, code generation, refactoring, testing, documentation, and project maintenance. You will learn how to break complex programming tasks into manageable steps, provide effective context, review AI-generated changes, and maintain appropriate control over automated development processes.
You will also explore practical techniques for working with larger projects and existing repositories. These include understanding unfamiliar codebases, locating relevant files and components, analyzing dependencies, improving implementations, generating tests, updating documentation, and handling repetitive engineering tasks with AI assistance.
A major focus of the book is responsible automation. Greater automation does not eliminate the need for developers to understand and evaluate the resulting code. You will learn how to establish review practices, validate AI-generated changes, consider security and reliability concerns, protect sensitive information, and maintain human oversight when applying AI to software engineering tasks.
From individual development workflows to broader engineering processes, this playbook shows how GitHub Copilot can become part of a more intelligent and automated approach to building software. It is designed for developers who want to move beyond basic AI code completion and explore practical ways to integrate AI assistance into real-world development and automation.
By the end of this book, you will understand how to design more capable AI-assisted development workflows, automate repetitive programming tasks, work more effectively with complex codebases, and use GitHub Copilot as a practical component of modern AI-powered software engineering.
You will also explore practical techniques for working with larger projects and existing repositories. These include understanding unfamiliar codebases, locating relevant files and components, analyzing dependencies, improving implementations, generating tests, updating documentation, and handling repetitive engineering tasks with AI assistance.
A major focus of the book is responsible automation. Greater automation does not eliminate the need for developers to understand and evaluate the resulting code. You will learn how to establish review practices, validate AI-generated changes, consider security and reliability concerns, protect sensitive information, and maintain human oversight when applying AI to software engineering tasks.
From individual development workflows to broader engineering processes, this playbook shows how GitHub Copilot can become part of a more intelligent and automated approach to building software. It is designed for developers who want to move beyond basic AI code completion and explore practical ways to integrate AI assistance into real-world development and automation.
By the end of this book, you will understand how to design more capable AI-assisted development workflows, automate repetitive programming tasks, work more effectively with complex codebases, and use GitHub Copilot as a practical component of modern AI-powered software engineering.
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