[ Level 01 ]
Fundamentals
What AI models are, what they can and cannot do, and the anatomy of an AI-automated system.
What is an AI model and how it “thinks”
What a language model is, how it predicts text one token at a time, and why that makes it flexible and powerful — yet sometimes confidently wrong.
Updated 2026-10-05
Capabilities and limits: what is worth automating
A four-question test for deciding which tasks to hand to AI, where the human stays irreplaceable, and when automation does more harm than good.
Updated 2026-10-05
Prompt fundamentals
What a prompt is and how to build reliable ones from five parts — task, context, role, output format, and examples — while avoiding five common mistakes.
Updated 2026-10-05
Where AI automation already works: use cases
Five areas where organizations already automate with AI — support, sales, admin, internal knowledge, and software — plus a simple formula for the real savings.
Updated 2026-10-05
Anatomy of an AI-automated system
The seven parts of every AI-automated system, from trigger to data storage, and the three shapes it can take: a single prompt, a workflow, or an agent.
Updated 2026-10-05
Roles and responsibility in a project
The five roles every AI automation project needs — sponsor, builder, content designer, reviewer, maintainer — and why humans stay responsible when AI errs.
Updated 2026-10-05