Course Overview

Working Well With AI

Format: Mini course — 4 modules, 10 lessons
Target time: Approximately 3–5 hours total, self-paced
Level: Accessible to all roles; no technical background required

What this course is about

Most people who use AI regularly hit a ceiling. The output is technically fine but somehow wrong — too generic, too stiff, too padded, or not quite right for the situation. They hit the ceiling not because of anything broken in the tool, but because of how they are using it.

This course addresses that ceiling directly.

Working Well With AI is a practical course that teaches people how to get stronger output from AI by improving the inputs: the context they give, the goals they define, the audience they name, the constraints they set, and the way they refine what comes back.

This is not a course about advanced hacks or clever phrasing. It is about the fundamentals that separate average AI use from high-value AI use — and those fundamentals are available to everyone who is willing to think a bit more deliberately about how they communicate.

What learners will walk away with

By the end of the course, learners will be able to:

1. Explain why vague prompts produce vague output
2. Give AI the context it needs to produce relevant, useful work
3. Define audience clearly before asking for any content
4. Guide tone, structure, and quality more precisely
5. Ask for outcomes rather than just deliverables
6. Use constraints to keep output on-target
7. Refine AI output with editorial judgment instead of accepting the first draft
8. Build reusable prompt frameworks for recurring work
9. Apply AI more effectively to their specific role

Course philosophy

The course is built on a few core ideas:

• Weak output is usually caused by weak input
• AI works best when treated as a collaborator, not a shortcut
• Better prompting is really better briefing, thinking, and editing
• Context is usually the difference between generic and useful
• Iteration is a feature, not a sign something went wrong

Modules at a glance

Module 1 — The Mindset Shift

Reframes how learners think about AI output and their role in shaping it.

Module 2 — Giving AI Better Direction

Teaches the practical inputs that change output quality: context, audience, tone, structure.

Module 3 — Getting Better Results Through Process

Covers goal clarity, constraints, and editorial judgment as tools for stronger results.

Module 4 — Turning Better Prompting Into Better Work

Makes the course practical across departments with reusable patterns and role-based examples.

Capstone

The course closes with a 5-step practical AI workflow — Frame, Aim, Guide, Refine, Reuse — that learners can use as their daily mental model going forward.