Get Insanely Good at AI
How to Work Smarter, Build Faster, and Think Better with AI
by Ebenezer Don · 180 pages · 8 chapters
What this book is about
Most AI books fall into two camps: academic texts that explain the math but don't help you build anything, and tip collections that tell you what to do but not why it works.
This book is neither. It starts with the mechanics: how models actually process your input, from tokenization through transformer attention to next-token prediction. Then it builds on that foundation with practical skills: structured prompting, AI-assisted coding workflows, production architecture, and agent systems.
The goal isn't to make you an AI researcher. It's to give you the understanding that makes every AI tool you touch more effective, today and five years from now, regardless of which models or platforms exist.
From Chapter 2
How your text becomes AI output
Every interaction with an AI model follows this pipeline. Understanding it changes how you write prompts.
Your Text
"How do I make this function faster?"
Tokenization
Embedding + Transformer Processing
Attention patterns across token positions
Next-Token Prediction
"Consider using memoization or..."
From Chapter 3
The prompting framework
Every effective prompt has three components. Most people only use one.
Context
Who you are, what you're building, what's already been done. Without this, the model guesses generically.
Instruction
The specific task. The clearer and more specific, the less the model has to guess.
Constraints
Format, length, tone, what to avoid. Without boundaries, the model defaults to generic output.
Try the prompt analyzer → to see this framework in action.
Chapter by chapter
The Shift
The way we write software has changed. Not incrementally. The core workflow, how code gets written, reviewed, and shipped, is different now. This chapter explains what changed, why it matters, and what it means for you.
How AI Actually Works
Tokenization, transformers, next-token prediction, embeddings, context windows, RAG. Not the math, the mechanics. Once you see how models actually process your input, you can't unsee it. It changes everything.
Prompting Is Thinking
Prompting isn't a bag of tricks or a template collection. It's structured thinking: context, instruction, constraints. This chapter teaches the framework that makes prompts work, and why most prompting advice is backwards.
AI-Assisted Coding
The workflow that matters: what to generate, what to keep, what to fix, and what to throw away. How to use AI as a coding partner without losing control of your codebase.
Building With AI
From API calls to production systems. How to build products that use AI as a core capability, and how to make sure they actually work outside the demo.
Agents and Automation
When AI tools use other tools. How agent architectures work, where they're headed, and how to build automations that handle complexity a simple script never could.
The Craft Still Matters
AI amplifies what you already know. Your deep, hard-won experience is now the most valuable asset in the room. This chapter explains why, and how to use that advantage.
What Comes Next
What's actually coming in AI, with the hype stripped away. The patterns that hold, the trends that matter, and the ones you can safely ignore.