Large language models can produce impressive demos, but turning them into reliable products takes more than better prompts. You need to understand model behavior, know when to use retrieval or fine-tuning, structure agents correctly, and evaluate systems before deployment.
Building Agent-Powered Applications gives an end-to-end engineering perspective on creating production-ready generative AI solutions. Written by Microsoft Principal AI Engineer Vasyl Zvarydchuk, it helps software engineers, data scientists, and applied AI practitioners move from concept to implementation. You’ll begin with AI, NLP, embeddings, transformers, and LLM behavior, then progress to prompt engineering, summarization, classification, extraction, reasoning, RAG, and fine-tuning.
The book shows how to design agentic workflows with tools, memory, planning, orchestration, and human-in-the-loop controls. You’ll learn to evaluate quality with offline and online testing, task-specific metrics, LLM-as-a-judge methods, and responsible AI checks. Rather than treating prompting, RAG, fine-tuning, and agents as separate topics, this book shows how they work together in practice. By the end, you’ll be able to make better architectural trade-offs, reduce failure modes, and build scalable, trustworthy AI applications.
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Spis treści

Building Agent-Powered Applications. Your guide to generative AI, RAG, fine-tuning, and orchestration for production use eBook -- spis treści

• 1. Artificial Intelligence and Natural Language Processing Fundamentals
• 2. Understanding Large Language Models
• 3. Prompt Engineering
• 4. Understanding Language Tasks
• 5. Generation, Question Answering, and Reasoning
• 6. Retrieval-Augmented Generation
• 7. LLM Fine-Tuning
• 8. Exploring the Architecture of AI Agents
• 9. Building AI Agents
• 10. Evaluating LLM Applications and Agents