The LLM Engineer's Handbook 👷 'Super proud to announce my new book'

Posted Jul 20, 2024 Updated Nov 15, 2025

By Fodev JEO 2 min read

The LLM Engineer’s Handbook: Building Production-Ready LLM Applications

Curiosity: How do we bridge the gap between LLM research and production deployment? What engineering practices enable us to build reliable, scalable LLM applications?

The LLM Engineer’s Handbook represents a comprehensive guide to building production-ready LLM applications, focusing on best engineering practices, reproducible pipelines, and end-to-end deployment—everything currently lacking in the ecosystem.

Book Overview

Goal: Provide everything you need to know to build LLM applications, all in one comprehensive resource.

Focus Areas:

Best engineering practices
Reproducible pipelines
End-to-end deployment
Production-ready systems

LLM Twin Course

LLM Twin Course - A practical learning resource
GitHub: https://github.com/decodingml/llm-twin-course
Focus: LLMs, vector DBs, and LLMOps good practices

LLM Twin Architecture

graph TB
    A[User Query] --> B[LLM Twin System]
    B --> C[Vector Database]
    B --> D[LLM Service]
    B --> E[LLMOps Pipeline]
    
    C --> C1[Embeddings]
    C --> C2[Retrieval]
    
    D --> D1[Model Inference]
    D --> D2[Response Generation]
    
    E --> E1[Monitoring]
    E --> E2[Logging]
    E --> E3[Evaluation]
    
    style A fill:#e1f5ff
    style B fill:#fff3cd
    style C fill:#d4edda
    style D fill:#f8d7da
    style E fill:#e7d4f8

Key Contributors

Contributor	Role	Contribution
Paul Iusztin	Co-author	LLM Twin Course creator
Alex Vesa	Co-author	Engineering practices expert

Collaboration: The team has created the excellent LLM Twin Course on GitHub, an amazing resource for learning about LLMOps.

What’s Covered

Topic	Description	Importance
Engineering Practices	Best practices for LLM development	⭐⭐⭐ Critical
Reproducible Pipelines	Version control, testing, CI/CD	⭐⭐⭐ Critical
End-to-End Deployment	Production deployment strategies	⭐⭐⭐ Critical
Vector Databases	Embedding storage and retrieval	⭐⭐ High
LLMOps	MLOps for LLM applications	⭐⭐ High

Why This Book Matters

Retrieve: The LLM ecosystem currently lacks comprehensive engineering guidance. This book fills that gap by providing:

Practical Examples: Real-world implementations
Best Practices: Industry-proven patterns
Complete Workflows: From development to deployment
Production Focus: Scalable, maintainable systems

Innovate: By following the practices in this handbook, you can build LLM applications that are:

Reliable and maintainable
Scalable and efficient
Production-ready from day one

Pre-order Information

📙 Pre-order on Amazon: https://www.amazon.com/dp/1836200072

Note: Everything online is free, but pre-ordering helps support the work and increases visibility on Amazon.

Key Takeaways

Retrieve: This handbook provides comprehensive guidance on building production-ready LLM applications, covering everything from development practices to deployment strategies.

Innovate: Apply these engineering practices to create reliable, scalable LLM systems that can handle real-world production workloads.

Curiosity → Retrieve → Innovation: Start with curiosity about production LLM systems, retrieve knowledge from this handbook, and innovate by building robust applications that solve real problems.

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