The best way to learn AI is to stop learning about AI and start using it in your actual work.
Every module follows the same structure: a short concept section, an interactive Socratic prompt you paste into your AI, a concrete artifact you keep, and a mastery gate before you can move on. Nothing theoretical. Nothing you won't use.
Start with Module 00 and work sequentially through Part 1 (Modules 0-5). After Module 5, Parts 2 and 3 can be done in any order based on what's most relevant to your work.
All modules
Part 0 - Setup
The Discovery
Build your three personalization files - the infrastructure that makes every future module work for you specifically.
Rules of Engagement
Three rules experienced through controlled experiments. The operating system for the entire course.
Part 1 - How AI Actually Works (Modules 2-5)
What's Actually Happening When You Prompt
Token prediction, tokenization, probability distributions, temperature. See the mechanics in action.
Attention, Structure & Prompt Architecture
Attention mechanics, "lost in the middle," XML tags as structural signals, few-shot examples as attention anchors.
Context Engineering
Context hierarchy, hallucination as a context problem, what to include, exclude, and where to place it.
From Conversations to Systems
System prompts, configured workspaces, reusable skills. Never start from a blank chat again.
Part 2 - The Domains (Modules 6-10)
AI for Writing & Content
Voice extraction, human+AI workflow, style guides. Produce content that sounds like you.
AI for Images & Visual Content
Diffusion model basics, consistency techniques, image prompt templates.
AI for Video & Audio
The 6-step production workflow. Node-based pipelines, voiceover, and sound design.
AI for Research & Analysis
Question decomposition, tool matching, source evaluation, and the three-layer research stack.
AI for Code & Building
Specification writing, iterative building workflow, building a working tool without being a developer.
Part 3 - The Systems (Modules 11-15)
MCPs - Giving AI Hands
MCP architecture, connecting AI to your actual tools. Before and after workflow value.
AI Agents - When and When Not
The agent spectrum. When to agent vs. when to prompt. Build a chain or document why you didn't.
Automations & Workflows
Trigger → AI → action pattern. Platform comparison (n8n/Zapier/Make). Deploy a working automation.
Building Your AI Stack
Stack audit methodology. Lean 3-tool stack. Cut unnecessary subscriptions.
Open Source & Running Your Own Models
Ollama setup, honest local vs cloud comparison, hybrid usage plan.