The Developer's Guide to AI: A Field Guide for the Working Developer
Orshalick, Jacob; Reghunadh, Jerry M.; Thompson, Danny
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Language: English
Published by No Starch Press, 2026
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- Title
- The Developer's Guide to AI: A Field Guide for the Working Developer
- Author
- Orshalick, Jacob; Reghunadh, Jerry M.; Thompson, Danny
- Publisher
- No Starch Press
- Publication year
- 2026
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1718504764
- ISBN 13
- 9781718504769
Build intelligent applications—no data science degree required.
Your boss is pitching new AI features. Your team is buzzing about MCP servers. Job postings are asking for AI experience with RAG, vector databases, fine-tuning, and agents. You can feel the excitement. You see the potential. You may be wondering how to get started in AI without a data science degree. You’re in the right place.
The Developer’s Guide to AI gives working developers a practical path through the terminology, tools, and implementation patterns that matter. It shows you how to build with AI using the tools you already know: JavaScript, Python, APIs, SDKs, and databases.
By the end of this book, you’ll know how to:
LLMs, RAG, LoRA, MCP, embeddings, and agents are not just intimidating buzzwords. They are the building blocks for the next generation of software.
Grab your code editor, bring your engineering instincts, and let’s build what’s next!
Your boss is pitching new AI features. Your team is buzzing about MCP servers. Job postings are asking for AI experience with RAG, vector databases, fine-tuning, and agents. You can feel the excitement. You see the potential. You may be wondering how to get started in AI without a data science degree. You’re in the right place.
The Developer’s Guide to AI gives working developers a practical path through the terminology, tools, and implementation patterns that matter. It shows you how to build with AI using the tools you already know: JavaScript, Python, APIs, SDKs, and databases.
By the end of this book, you’ll know how to:
- Call LLM APIs and stream intelligent responses directly to your UI.
- Engineer prompts that produce reliable, production-ready results.
- Build RAG pipelines using vector databases to give AI access to your private data.
- Fine-tune models with LoRA for specialized tasks like classification.
- Deploy AI agents using tool-calling and the Model Context Protocol (MCP) to reason and act inside real workflows.
LLMs, RAG, LoRA, MCP, embeddings, and agents are not just intimidating buzzwords. They are the building blocks for the next generation of software.
Grab your code editor, bring your engineering instincts, and let’s build what’s next!
"Synopsis" may belong to another edition of this title.
About the Author
Jacob Orshalick has over 20 years in software development as an independent consultant for startups and Fortune 500 companies, leading high-impact projects and speaking regularly at conferences.
Jerry Mannel Reghunadh is a senior director with over 20 years in tech, spanning QA, product innovation, and solution architecture. He is known for mastering complex concepts and making them accessible.
Danny Thompson is a director of technology who works with Fortune 500 companies, teaches software developers worldwide, and hosts The Programming Podcast.
Jerry Mannel Reghunadh is a senior director with over 20 years in tech, spanning QA, product innovation, and solution architecture. He is known for mastering complex concepts and making them accessible.
Danny Thompson is a director of technology who works with Fortune 500 companies, teaches software developers worldwide, and hosts The Programming Podcast.
"About the title" may belong to another edition of this title.
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