Before AI, the industry sold speed under an older name: rapid e-learning. I wrote about it, and I built under its promises — faster, more, cheaper per hour. AI is that promise’s second act, with the volume turned up.
Speed is not the enemy. Pretending speed is design is. A machine that can produce a course in an afternoon has automated production, which was never the scarce part. It has not automated judgment, which always was.
What speed buys, and what it deletes
Faster production buys reach and lowers cost. What it silently deletes is the friction where design decisions used to get made: the pause where you noticed the task did not match the goal, cut the duplicate reading, or realised the assessment tested recall when you wanted transfer. Studies of AI assistance love to report how much more content people produced; that is an output measure, not a measure of learning, and the two are easily confused.
AI can build the course faster. Faster course production is not the same as better learning design.
Judgment frames, not model walkthroughs
This is where the old models earn their keep — not as steps to follow but as questions to ask. TPACK asks whether the technology, the content, and the teaching actually fit each other. SAMR asks whether the tool changed the task or just digitised it (Mishra & Koehler, 2006; Hamilton et al., 2016). Point either at an AI-built module and the seams show quickly.
Why AI raises the stakes
The honest workload question is not whether AI saves time but where the saved time goes. Drafting gets cheaper; judging what was drafted does not, and if the saved hour is spent producing more instead of designing better, the learner is worse off with a fuller course.
The move
Let AI draft. Then spend the time it saved on the four failures — path, practice, feedback, transfer — not on generating more. Production is the cheap part now. Protect the judgment.