# Building Agent-Powered Applications: Generative AI, RAG, Fine-Tuning, and Agents

Agents: Building Agent-Powered Applications is a Packt book on engineering generative AI systems from initial model concepts through production-oriented workflows. It covers prompting, RAG, fine-tuning, agent design, evaluation, and deployment, with practical trade-offs for readers who already have programming and software engineering fundamentals.

- [Original product page](https://best-deals.pro/product/building-agent-powered-applications-generative-ai-rag)
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- Market: US
- Language: en-US
- Currency: USD
- Category: Books, Music & Hobbies > Books, Music & Movies > Books & Comics
- Price: 33.99 USD
- Previous price: 49.99 USD
- Discount: 32%
- Price checked: 2026-11-14T05:51:13.766Z
- Rating: 4.4 / 5
- Reviews: 10

Prices and deal status are the latest recorded data, not a guarantee of availability. Confirm the price and availability with the store.

## At a glance

- Moves from AI, NLP, embeddings, transformers, and LLM behavior into prompting, RAG, fine-tuning, and agent workflows.
- Covers agent tools, memory, planning, orchestration, and human-in-the-loop controls.
- Includes evaluation topics such as offline and online testing, task-specific metrics, LLM-as-a-judge methods, and responsible AI checks.
- The listing says print or Kindle purchases include a free PDF eBook. Access requires email sign-up and proof of purchase.

## Pros

- Combines model fundamentals, application techniques, agent design, and evaluation in one end-to-end engineering-focused book.
- Includes guidance on choosing between prompting, retrieval-augmented generation, and fine-tuning rather than treating them as unrelated methods.
- The stated audience includes engineers transitioning from traditional software or classical machine learning, and says deep learning or LLM training experience is not required.

## Specifications

### Book details
- Publisher: Packt Publishing
- Publication date: April 30, 2026
- Language: English
- Print length: 490 pages
- ISBN-10: 1807605175
- ISBN-13: 978-1807605179
### Dimensions and installation
- Weight listed: 1.84 pounds
- Dimensions: 7.5 x 1.11 x 9.25 inches

## Before you buy

- The listing describes a free PDF and access to Packt's Reader, but the PDF and Reader access require email sign-up and proof of purchase.

## A good fit for

- Software engineers, AI engineers, data scientists, applied AI practitioners, and technical leads building LLM applications.
- Engineering-focused product managers who want an overview of production-oriented generative AI architectures and trade-offs.
- Programmers comfortable with Python or a similar language, APIs, data structures, and integration who are moving into generative AI.

## Less suited to

- Readers seeking a programming-free introduction, since the listing expects programming and core software engineering familiarity.
- Readers looking specifically for deep learning or LLM training instruction, which is not presented as a required background or central focus.

## Customer feedback

Aggregate ratings lean positive, with most ratings in the five-star category, but a smaller two-star share means the overall picture is not uniformly favorable. The sample is limited, and no written feedback is supplied here to explain either the positive or critical ratings. These figures cannot establish how useful the book's coverage of RAG, agents, and production evaluation will be for a particular reader.

## Frequently asked questions

### What topics does Building Agent-Powered Applications cover?
The listed topics span AI and NLP fundamentals, LLMs, prompting, language tasks, RAG, fine-tuning, agent architecture and construction, and evaluation of LLM applications and agents.
### Who is this book intended for?
The listing targets engineers, data scientists, applied AI practitioners, technical leads, and engineering-focused product managers. It expects programming ability and familiarity with software engineering concepts such as APIs, data structures, and integration.
### Does the book include a digital version?
The listing says purchase of the print or Kindle book includes a free PDF eBook. It requires email sign-up and proof of purchase, and also mentions access to Packt's Reader.
### Is prior deep learning experience required?
The listing says prior deep learning or LLM training experience is not required, while programming and core software engineering concepts are expected.

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## Images

![Building Agent-Powered Applications: Generative AI, RAG, Fine-Tuning, and Agents — 1](https://best-deals.pro/i/yRTY42-ql7hsOGTeukVOfiP5Syxc3UPheyn6erGxRPhI52Yhh0ufORNn7oEZUvS4znX-wWmpmj0T75Z8f5cfOZlPJQRiPe0L87Uas8xnfofmLlZNg-3V.jpg)