I just ordered Azure OpenAI Essentials by Amit Mukherjee and Adithya Saladi.
Why this book
I’ve been experimenting with AI agents in my daily work for a while now, but most of what I know about Azure OpenAI has been picked up on the fly — scattered docs, trial and error, the occasional deep dive. I wanted something more structured.
This book caught my eye because it’s written by people at Microsoft who actually build with this stack. It’s not just theory — it covers real-world use cases like building QnA systems, contact center analytics, code generation, and even a multimodal multi-agent framework using the Azure OpenAI Assistant API.
What it covers
The book is 368 pages across 13 chapters:
- Introduction to Large Language Models
- Azure OpenAI Fundamentals
- Azure OpenAI Advanced Topics
- Developing an Enterprise Document Question-Answer Solution
- Building Contact Center Analytics
- Querying from a Structured Database
- Code Generation and Documentation
- Creating a Basic Recommender Solution with Azure OpenAI
- Transforming Text to Video
- Creating a Multimodal Multi-Agent Framework with the Azure OpenAI Assistant API
- Privacy and Security
- Operationalizing Azure OpenAI
- Advanced Prompt Engineering
What stands out is the range — from fundamentals and prompt engineering to enterprise-grade topics like privacy, security, and operationalization. That’s usually the gap: plenty of “getting started” content, not enough on how to actually run this in production.
The plan
I’m going to read through the book chapter by chapter and blog about what I learn here on Ever Near. Not summaries — more like real notes on what clicks, what I try out, and what I’d do differently.
If you’re also exploring Azure OpenAI, follow along. Let’s figure this out together.