How to Build Your Own LLM

(A Complete Guide on Building LLMs)

Stop consuming AI content.

Start building with it.

This book takes you from:

• Understanding how LLMs work
• To building real-world AI systems using RAG, agents, memory, tool calling, pipelines, and production workflows.

Built for:

• AI beginners
• developers
• AI founders
• prompt engineers
• creators
• future AI engineers

What You’ll Get Inside

• 6 Structured Levels
• 24 Deep-Dive Chapters
• 100+ Hands-On Exercises
• Practical Challenges After Every Chapter
• MCQs & Validation Tests
• Action Checklists
• Real AI System Design Thinking
• End-to-End LLM Product Building

This is not passive learning.

Every chapter forces you to:

• implement
• test
• optimize
• validate
• build

You’ll learn by doing.

The 6 Levels

Level 1 — Foundations

LLMs, tokens, prompts, hallucinations, context windows

Level 2 — Control

Prompt engineering, system prompts, structured outputs, evaluation

Level 3 — Real Power

RAG, embeddings, vector databases, chunking, indexing

Level 4 — Building Systems

Agents, pipelines, tool use, memory systems

Level 5 — Optimization & Scale

Latency, cost optimization, fine-tuning vs RAG, deployment

Level 6 — Advanced Thinking

AI product design, multi-model systems, failure handling, end-to-end builds

Every Chapter Includes

Action Checklists

• Concrete things to complete before moving on.

Hands-On Exercises

• 100+ exercises designed to expose real gaps in understanding.

Validation Tests & MCQs

• Know whether you actually learned the concept.

Mini Challenges

• Small focused builds after every chapter.

Advanced Reflection

• For deeper system and architecture thinking.

By The End Of This Book

You’ll be able to:

• Build RAG pipelines
• Design prompt systems
• Create AI agents
• Structure AI outputs
• Optimize cost & latency
• Build scalable LLM workflows
• Think like an AI engineer instead of an AI user

🎁 Bonus Included

“50 AI Project Ideas to Build After This Book”

Not random ideas.

Projects categorized by difficulty:

• Beginner
• Intermediate
• Advanced

And each project includes:

• what to build
• core concepts involved
• recommended stack
• difficulty level
• expansion ideas
• monetization potential
• optional challenges 

Kernex.AI Presents — How to Build Your Own LLM