Prompting Generative AI for Intelligent Applications

From Prompt to Production — Build the Future with Generative AI.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 Applications shows 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.

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

Jit Sinha is an accomplished Enterprise Architect with 15 years of experience, specializing in cloud platforms and cybersecurity. He designs scalable solutions across banking, telecom, and healthcare. A Splunk expert and AI enthusiast, he also shares knowledge as a speaker and instructor, simplifying complex

About the Technical Reviewer
Mainak Saha is a technology leader with more than 20 years of experience architecting large-scale platforms across wealth management, trading, data, cloud, and artificial intelligence. He currently serves as a Principal Architect at Morgan Stanley, where he has led major initiatives in Generative AI adoption, enterprise AI platforms, and modernization across wealth management technology.

Over the course of his career, Mainak has worked at the intersection of business transformation and deep engineering, with expertise spanning AI/ML, large language models, cloud-native architecture, and high-volume, low-latency financial systems. Before his recent AI-focused work, he built and modernized trading and advisory platforms across equities, mutual funds, and FX, giving him a rare combination of hands-on market-technology depth and enterprise AI leadership.

Mainak’s works include enabling practical adoption of AI in regulated financial environments, advancing developer productivity, and helping firms apply emerging technologies to real business problems. His public activity also reflects participation in industry-facing AI and open-source finance forums.

Mainak is especially passionate about turning frontier AI capabilities into scalable enterprise outcomes and helping organizations navigate into the next generation of transformation in financial services.

Shruti Mishra is a Senior Product Manager at Microsoft, where she leads enterprise platform initiatives within the Microsoft 365 ecosystem. Her work focuses on large-scale change management systems, AI-enabled user experiences, and customer-facing features used by hundreds of millions of monthly active users worldwide.

At Microsoft, Shruti has driven high-impact product strategies, including integrating Service Health AI capabilities into Microsoft Copilot to deliver intelligent product health experiences for enterprise administrators managing complex cloud environments. She also launched a centralized internal workflow platform now adopted by more than 50 product teams, streamlining the end-to-end lifecycle of feature release communications. Known for her cross-functional leadership, she collaborates with engineering, design, and business teams to deliver scalable experiences used by thousands of enterprise customers globally.

Beyond her corporate responsibilities, Shruti serves as a judge and coach for innovation and technology competitions, mentoring and encouraging emerging young entrepreneurs. She holds a B.S. in Computer Science with a specialization in Artificial Intelligence from Georgia Tech, which enables her to combine deep technical knowledge with strategic product vision to build solutions that solve meaningful customer problems.