Prompting Generative AI for Intelligent Applications: Build LLM Applications, RAG Pipelines, AI Agents, Chatbots, and Vector Database Workflows Faster with Prompt Engineering

Book Description
From Natural Language to Intelligent Systems at Production Scale

Generative AI is reshaping how software gets built, how businesses operate, and how professionals deliver value — and the ability to move from a natural language idea to a working AI application is the defining skill of the next decade. Prompting Generative AI for Intelligent Applicationsshows you how to translate plain language intent directly into LLM applications, RAG pipelines, and intelligent agents using AI, accelerating every stage of development from first prompt to production deployment.

Rather than teaching AI theory from scratch, this book puts prompt-driven execution at the centre. You use prompt engineering techniques to build chatbots, chain AI actions, design knowledge bases with vector databases, and orchestrate multi-agent systems, then deploy them across cloud and private infrastructure with confidence. Every chapter is oriented around getting working AI output faster, not theory.

By the end of the book, you will use prompts as a core part of your AI development workflow, building and deploying intelligent applications with greater speed, clarity, and production confidence than traditional development approaches allow.

What you will learn
● Translate natural language intent into working LLM applications using prompt engineering techniques.
● Build AI workflows by chaining prompts, actions, and tools into logical multi-step pipelines.
● Design and deploy RAG systems using embeddings, vector databases, and knowledge retrieval architectures.
● Orchestrate intelligent multi-agent systems for complex reasoning and collaborative AI task execution.
● Deploy AI applications across cloud platforms and private infrastructure with production-ready confidence.
● Build responsible AI solutions with ethics, safety, and governance frameworks embedded from day one.

Table of Contents
1. Discover the GenAI Revolution from Hype to Real Impact
2. How Large Language Models Understand and Generate Text
3. Build Your AI Vocabulary with Tokens, Prompts, and Embeddings
4. Choose Your AI Partner by Exploring GPT, Claude, and Gemini
5. Create AI Solutions without Code Using No-Code Platforms
6. Master Prompt Engineering to Make AI Work for You
7. Build Your First AI App by Turning Ideas into Code
8. Create Smart Workflows by Chaining AI Actions Together
9. Design Beautiful AI Apps with Professional User Interfaces
10. Teach AI to Understand Meaning with Semantic Search
11. Build Knowledge Bases with Vector Databases
12. Create AI with Memory Using RAG Systems that Remember
13. Build Reasoning Agents with Design Thinking
14. Orchestrate AI Teams with Collaborative Multi-Agent Systems
15. Deploy AI Privately on Your Own Hardware
16. Launch AI Apps on Cloud
17. Accelerate Development with AI-Powered Coding Assistants
18. Build Responsible AI with Ethics and Safety Best Practices
19. Building a Sustainable Career in Generative AI
20. Capstone Projects Using Generative AI
Index