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The Augmented Developer: Code Smarter, Not Harder
The Augmented Developer is a comprehensive guide to AI-assisted coding. It covers everything from the use of AI in code completion, generation, refactoring, security, and bug detection, to the creation of custom model chains and AI assistants.
The guide dives into advanced prompt engineering techniques and best practices used to maximize the potential of AI in coding. It also explores the ethical and technical implications of using generative AI in coding. Moreover, it looks into the future impacts of AI in coding and its potential to change the developer role as we know it.
Across the chapters of The Augmented Developer, you
Explore AI-assisted coding's impact on pair programming and remote work, enhancing the coding experience.Unpack GitHub Dive into the specifics of GitHub Copilot, from its foundational AI training to its real-world application in coding. This section breaks down its features, pricing, and setup, making it practical for you to start using it in your projects right away.Learn How to Use GitHub Copilot Master the art of using GitHub Copilot to boost your productivity. From writing code, debugging, refactoring, security hardening, unit testing, documentation, code reviews, pull requests, context-aware prompting, and more. You'll gain a deep understanding of how to leverage GitHub Copilot to its full potential.Explore a Spectrum of AI Coding Assistants and Get acquainted with the broad landscape of AI coding tools available Tabnine, DeepCode, fauxpilot, privy, aider, Devin, SWE-Agent, Codeium, Tabby, CodeGeeX, Amazon CodeWhisperer, AskCodi, Blackbox AI, Bito, and many more.Master prompt engineering to boost developer productivity with AI tools like GitHub Copilot and Learn to create effective prompts for optimal outputs including topics like Few-Shot Learning, Chain of Thoughts, Tree of Thoughts, and more.Understand the Best Practices of Prompt Acknowledge the best practices of prompt engineering and how you can apply them with the techniques you've learned. This section will provide you with a clear roadmap to follow when writing prompts for AI coding assistants.Build Your In-house Developer Productivity Learn how to use tools like OpenAI APIs, LangChain, Chroma, and others to code your own AI-powered developer productivity tools. This section will guide you through the process of coding your custom AI assistants, step by step.Understand Advanced Concepts in Generative Gain a clear understanding of useful concepts such as RAG, vector databases, embeddings, tokens, and more.Explore Advanced LLM Orchestration Dive into advanced LLM orchestration and workflow tools like DiFy, Flowise AI, and LLMStack.
The guide dives into advanced prompt engineering techniques and best practices used to maximize the potential of AI in coding. It also explores the ethical and technical implications of using generative AI in coding. Moreover, it looks into the future impacts of AI in coding and its potential to change the developer role as we know it.
Across the chapters of The Augmented Developer, you
Explore AI-assisted coding's impact on pair programming and remote work, enhancing the coding experience.Unpack GitHub Dive into the specifics of GitHub Copilot, from its foundational AI training to its real-world application in coding. This section breaks down its features, pricing, and setup, making it practical for you to start using it in your projects right away.Learn How to Use GitHub Copilot Master the art of using GitHub Copilot to boost your productivity. From writing code, debugging, refactoring, security hardening, unit testing, documentation, code reviews, pull requests, context-aware prompting, and more. You'll gain a deep understanding of how to leverage GitHub Copilot to its full potential.Explore a Spectrum of AI Coding Assistants and Get acquainted with the broad landscape of AI coding tools available Tabnine, DeepCode, fauxpilot, privy, aider, Devin, SWE-Agent, Codeium, Tabby, CodeGeeX, Amazon CodeWhisperer, AskCodi, Blackbox AI, Bito, and many more.Master prompt engineering to boost developer productivity with AI tools like GitHub Copilot and Learn to create effective prompts for optimal outputs including topics like Few-Shot Learning, Chain of Thoughts, Tree of Thoughts, and more.Understand the Best Practices of Prompt Acknowledge the best practices of prompt engineering and how you can apply them with the techniques you've learned. This section will provide you with a clear roadmap to follow when writing prompts for AI coding assistants.Build Your In-house Developer Productivity Learn how to use tools like OpenAI APIs, LangChain, Chroma, and others to code your own AI-powered developer productivity tools. This section will guide you through the process of coding your custom AI assistants, step by step.Understand Advanced Concepts in Generative Gain a clear understanding of useful concepts such as RAG, vector databases, embeddings, tokens, and more.Explore Advanced LLM Orchestration Dive into advanced LLM orchestration and workflow tools like DiFy, Flowise AI, and LLMStack.
238 pages, Paperback
Published May 2, 2024
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