The worst way to use AI for course creation is to type “make me a six-module course about leadership” and publish whatever comes back.
That gives you a course-shaped pile of words. It does not give your students a useful learning experience.
The better use is to start with your real method, real examples and real student questions. AI helps organise and produce. You decide what someone needs to understand first, where they need practice and how they will apply it.
The course work AI is good at
- AI groups source material. You choose the learning outcome.
- AI finds gaps in an outline. You decide what belongs in the course.
- AI drafts worksheets from a lesson. You design useful practice.
- AI retrieves answers from approved lessons. You handle nuance and exceptions.
- AI repurposes a transcript. You protect the meaning and promise.
If AI is making the core teaching decisions, you have crossed the line too early.
Workflow 1: turn your method into a curriculum map
Begin with material you already own: workshop transcripts, client frameworks and recurring questions. Bring in your notes and examples too.
Ask Claude or ChatGPT to identify:
- the transformation you repeatedly help people make
- concepts that must be understood first
- decisions or skills that require practice
- examples you use more than once
- common mistakes and misconceptions
- questions the source material does not answer
Then create the sequence yourself. A neat six-module outline is not automatically the right order. Put prerequisites before advanced work and remove anything that does not help the student reach the stated outcome.
Workflow 2: create lesson assets from the lesson, not instead of it
Record or write the teaching first. Then ask AI to turn that source into support material:
- a one-page lesson summary
- a worksheet with space for the student's own answer
- a checklist for applying the method
- a worked example based on the lesson
- a short knowledge check
Require every answer key to cite the relevant part of your source. If the model needs outside facts, research those separately and link the original source.
This keeps the asset connected to what you taught instead of drifting into generic internet advice.
Workflow 3: build a student question system
Course creators answer the same logistical and conceptual questions repeatedly. Split them into two groups.
Operational questions include access, lesson order, session dates and where to submit work. These can usually be answered from an approved knowledge base.
Teaching questions need context. AI can retrieve the relevant lesson and draft a response, but you should review anything involving judgement, individual circumstances or a promise about results.
Set one important rule: when the source material does not contain the answer, the assistant must say so and route the question to you.
Workflow 4: find where students are getting stuck
Collect de-identified questions, feedback and support requests. Ask AI to group them by lesson and type of confusion.
Look for:
- a term you did not define clearly
- a missing example
- an exercise with vague instructions
- a prerequisite students do not have
- a lesson that asks for too much at once
Do not use the analysis to blame students for not finishing. Use it to improve the teaching path.
Workflow 5: repurpose one lesson without flattening it
Your course already contains more useful content than a blank ChatGPT window.
Take one transcript and ask for a list of self-contained teaching moments with the original quote and timestamp. Choose the ones worth sharing. Then create:
- one practical blog post
- one email built around a specific lesson
- three short videos, each with one idea
- one visual checklist
The selection stays yours. AI handles the production work after the idea has earned its place.
For the broader system, see repurposing one video into social posts with AI.
A focused tool stack for course creators
- Claude or ChatGPT: curriculum analysis, lesson assets and question retrieval
- Fathom, Tella or your existing recorder: capture teaching and demonstrations
- NotebookLM: source-grounded exploration of approved course material
- Your current course platform: delivery, access and student progress
- n8n, Make or Zapier: connect enrolment, reminders and support only when the process is settled
Do not rebuild your course platform because a new AI app has better launch copy. Use the tools you already have until a specific limitation costs you time or student outcomes.
What not to hand to AI
Keep assessment decisions, individual feedback, sensitive student situations and claims about results under human control.
If a student believes a message came from you, you should be comfortable putting your name on every word.
Your first build: transcript to worksheet
Choose one lesson students already find useful. Give the transcript to your assistant and ask for a one-page worksheet using only the concepts and examples in that lesson.
Complete the worksheet yourself. If it feels repetitive, vague or impossible without extra context, fix the teaching instructions before you automate anything else.
That small test tells you more than generating an entire course in an afternoon.
If you want practical support building the workflow, read the guide to the best AI community for women or see inside Wright Mode.