Everyone is using AI to write course content faster.
Almost nobody is using it to design courses better.
There's a difference, and it's costing learners a lot.
Here's what "faster" looks like:
→ Feed ChatGPT a topic
→ Get 10 modules of generic text
→ Wrap it in slides
→ Ship it
The result? Content that reads fine and teaches nothing. The learner watches, nods, forgets.
Here's what "better" looks like:
1. Design the learning architecture first — by hand.
Define the behavioral outcome of every unit: what will the learner be able to DO after this that they couldn't do before? No AI involved yet. This is the thinking machines can't do for you.
2. Turn that architecture into constraints.
Outcome, audience, prior knowledge, one practice activity per unit, one checkpoint per unit. Now it's a spec, not a vibe.
3. THEN let AI produce inside those constraints.
Drafting explanations, generating scenario variations, adapting examples to different industries — AI is genuinely excellent at this. Because now it's filling a designed structure, not inventing one.
In my work building course production pipelines, this order is the single thing that separates AI-assisted courses people finish from AI-generated courses people abandon.
AI is a brilliant bricklayer.
It's a terrible architect.
Don't hand it the blueprint.
→ Read the full breakdown: The Course Production Pipeline — 5 stages, with the exact boundary between human and AI work