I wrote a free, open-source book on LLMs. No fluff, just practical code and concepts. Looking for feedback! [P]

About the Book

Hi everyone, I’ve spent the last few months compiling everything I know about Large Language Models into a structured, open-source book. My goal was to create the resource I wish I had when I started: something that bridges the gap between high-level tutorials and complex academic papers.

The book is available on GitHub at:
https://github.com/Drobiazkin/ai-agent-architecture

What’s Inside

The content focuses on practical code and core concepts, with no fluff. It covers:

• Foundational LLM architecture and transformer mechanics
• Tokenization, embeddings, and attention mechanisms
• Fine-tuning strategies and prompt engineering
• Deployment and inference optimization
• Building agents and tool-use systems

Looking for Feedback

I’m actively seeking feedback from the developer community. Whether you’re new to LLMs or experienced, your input on clarity, depth, or missing topics would be invaluable. Feel free to open issues or pull requests on the repository.