Building AI Agent for SQL from Scratch

"Building AI Agent for SQL from Scratch" is written from a fundamental educational philosophy: the most profound way to understand a complex system is to build it. While many texts explore the theoretical underpinnings of Large Language Models (LLMs) or the high-level applications of AI, a critical gap exists for a practical, step-by-step guide that empowers a student or developer to construct a functional, real-world AI agent from its foundational components. This book is engineered to fill that gap.


Philosophy

The core philosophy of this book is "learning by doing." I believe that true mastery in a technical field like AI engineering comes from building, not just reading. Every concept is introduced with the immediate goal of applying it. I demystify the "magic" of AI by breaking it down into logical, understandable, and implementable components. The emphasis is squarely on developing a functional solution, encouraging the reader to think like an engineer—focusing on architecture, component interaction, security, and deployment.


Key Features

1. From-Scratch Approach: Learn the fundamental principles by building the agent's core logic yourself before moving on to industry-standard frameworks.

2. Practical Focus: More than 80% of the content is dedicated to practical implementation, code walkthroughs, and hands-on exercises.

3. Comprehensive Coverage: The book covers the entire lifecycle of an AI agent: ideation, design, architecture, implementation, testing, deployment, and future scope.

4. Globally Relevant: Uses industry-standard tools and techniques (Python, LLMs, APIs, Docker) that are in high demand across the international tech landscape.

5. Beginner to Advanced: Starts with foundational concepts for beginners and progressively introduces advanced topics like self-correction, security, and framework integration for intermediate and advanced learners.

6. Complete Working Code: Provides full, tested code for all major examples and the final capstone project.


To Whom This Book Is For

This book is written for a diverse audience, including:

1. B.Tech and M.Tech Computer Science Students: An ideal textbook or supplementary resource for courses in Artificial Intelligence, Machine Learning, Natural Language Processing, and Database Management Systems.

2. Aspiring AI/ML Engineers: A perfect starting point for those who want to build practical AI applications and develop a strong portfolio.

3. Software Developers: A clear guide for professionals who wish to upskill and integrate AI-powered features into their existing software products.

4. Data Analysts and Scientists: For those looking to build tools that democratize data access for non-technical stakeholders within their organizations.

Note: A prerequisite of basic Python programming and a foundational understanding of SQL and relational databases is assumed. No prior experience with AI or LLMs is necessary.

Disclaimer: Earnest request from the Author.

Kindly go through the table of contents and refer kindle edition for a glance on the related contents.

Thank you for your kind consideration!