The course

Everything, in one place.

8 interactive modules · about 1 hour total. Your progress saves on this device as you go — sign in any time to keep it across devices.

0 of 8 complete
  1. 01
    The foundation

    What is an LLM (Large Language Model)

    Run four steps and watch the model predict text one word at a time. The keystone idea everything else builds on: it isn't thinking, it's autocomplete.

    6 min Open
  2. 02
    Orientation

    Getting Around the Interface

    A guided tour of every control in a modern chat app — model picker, thinking effort, files, voice, projects, history and temporary chat — then three worked examples through the same mock UI.

    8 min Open
  3. 03
    What it can see

    Context — What the Model Can See

    Ask for a client email with no context and get “Dear [Client Name]”. Attach a client list, a product one-pager and a voice guide in the chat, ask again — and watch a generic reply become a specific one.

    7 min Open
  4. 04
    Working memory

    The Context Window

    A live token meter is the hero. Attach one novel to a 128k model and it answers; attach a second and the window overflows — the first book silently drops out of view; switch to a 1M model and both fit.

    7 min Open
  5. 05
    The payoff

    Projects — Set Context Once

    Create a five-a-side coaching project yourself — name it, add the instruction and sources — then run three brand-new chats — website, break-even, marketing — each auto-loading the same context. Fresh never means from scratch.

    8 min Open
  6. 06
    Automation

    Skills & Schedules

    Package a repeated procedure once so it runs the same way every time, fires with one line, and can be put on a schedule. Build a /morning-summary skill and set it for 8am.

    8 min Open
  7. 07
    Make things

    HTML — The Presentation Layer

    Describe a dashboard in plain English and watch the AI write HTML, then render a rich interactive artifact — KPI cards, charts and a data table. The whole course is AI-generated HTML.

    7 min Open
  8. 08
    Use it safely

    Risks & Issues

    Where these tools go wrong and how to stay in control — confident-but-wrong answers, privacy and security, and the habits that keep AI useful without trusting it blindly.

    7 min Open
For teams

Want your team to learn this too?

These are the lessons Riz runs with client teams, made hands-on. Bring the interactive version to yours — or book a session tailored to what your team actually does.

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