Product guide

Building LLM Powered Applications: Practical Guide to LLM Apps and Agents

Practical Guide Apps: Building LLM Powered Applications is a hands-on book about applying large language models to software, covering model choices, prompt engineering, LangChain, and intelligent agents. Its scope also includes retrieval from unstructured data, structured-data workflows, fine-tuning, multimodal applications, and responsible AI. The listing expects readers to have core machine-learning or software-engineering fundamentals, though prior LLM experience is not assumed.

At a glance

Covers LLM architecture and models including GPT-3.5/4, Llama 2, and Falcon LLM.
Applies LangChain and Streamlit to building LLM-based applications.
Topics include prompts, memory, tools, vector databases, and retrieval from unstructured information.
Also covers structured data, fine-tuning, multimodal applications, and responsible AI.

Price

$36.97Save 26%

Reference price: ~~$49.99~~

Price checked: Nov 14, 2026

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Pros and cons

Pros

Bridges LLM concepts with application-building topics, including agents, retrieval, conversational apps, and search.
The broad contents span practical tooling as well as fine-tuning, multimodal systems, and ethical considerations.
The listing states that specific prior LLM experience is not assumed.

Cons

Readers are expected to bring core machine-learning or software-engineering fundamentals, so this is not positioned as a fundamentals-free introduction.

Technical specifications

8 specifications

Publication details
Publisher	Packt Publishing
Publication date	May 22, 2024
Language	English
Print length	342 pages
ISBN-10	1835462316
ISBN-13	978-1835462317

Dimensions and installation
Weight listed	1.39 pounds
Dimensions	7.5 x 0.78 x 9.25 inches

What to know before buying

Listing details to confirm

The book covers named model families and frameworks, but the listing does not establish that examples or instructions have been updated beyond its May 2024 publication date. Check whether its covered tools and models suit your current project.

Who is it for?

A good fit for

Software engineers and data scientists seeking applied guidance for building LLM-powered applications.
Technical leaders, students, and researchers interested in applied LLM topics who have core ML or software-engineering fundamentals.

Less suited to

Readers seeking a book that assumes no technical background or teaches core software-engineering and machine-learning fundamentals from scratch.
Readers who need coverage guaranteed to reflect the latest changes to LLM tools and models.

Customer reviews on Amazon

4.1 / 5 · 47 ratings

5 stars58%58%
4 stars20%20%
3 stars10%10%
2 stars2%2%
1 star10%10%

Aggregate customer ratings lean positive, with a majority in the five-star category, but the distribution also includes a notable one-star share. That spread suggests opinions are not uniform. Ratings alone do not reveal which topics readers liked or what prompted lower scores, so use the contents and stated technical prerequisites to judge fit.

Frequently asked questions

Does the book assume previous LLM experience?

The listing says previous LLM experience is not assumed, but readers should have core machine-learning or software-engineering fundamentals.

What development topics does it cover?

Listed topics include LangChain, Streamlit, prompt engineering, conversational applications, search and recommendation, structured data, retrieval, and agents.

Does it cover more than text-based LLM applications?

Yes. The listing includes multimodal applications involving tasks and modalities such as vision and audio, alongside fine-tuning and responsible AI.

What are the listed print details?

The listing gives a print length of 342 pages, English language, and publication date of May 22, 2024.