How AI models actually write
What an LLM does when it answers you, and why that explains its strengths and failures.
About this course
AI conversations move fast, and the vocabulary moves faster. This course gives you a working understanding of how AI tools actually work, from tokens and context windows to agents, retrieval, and evals.
Each lesson takes one idea from plain-English definition to hands-on practice. You will see it in action with an animated walkthrough, experiment with a real AI model to watch how it behaves, and lock it in with quick checks and an explain-it-back exercise graded by AI.
By the end you will write sharper prompts, know why an answer went wrong and what to do about it, and ask better questions when you evaluate AI tools for your team.
What you'll learn
6 outcomesPrompts that get usable results
The parts of a good brief, and how system prompts shape every reply.
The limits behind the pricing
Tokens and context windows, so costs, caps, and forgetting stop being a mystery.
When to trust the output
Temperature, hallucinations, and embeddings, and how each changes what you should check.
How AI takes action
Tools, retrieval, and agents, and where each one needs a human checkpoint.
Using AI safely at work
Evals to judge quality and the safeguards that stop prompt injection.
Course curriculum
6 parts · 17 chapters