10 AI Mistakes Every Teacher Makes

Eleven pages on why AI gives you flat, generic material — and what to change.

Most AI guides are about the technology. This one is about the teaching. It is in two parts.

The foundation: understanding the tool. Why treating AI as an answer key rather than a synthesis engine turns you into a full-time fact-checker. Why you work with principles rather than named students, and where that crosses from pedagogy into GDPR. When a general-purpose tool is the wrong choice for a specialist job.

The method: steering the output. Giving a task without a teaching method. Editing the result instead of the instruction. Letting AI imitate a textbook instead of your own voice. Building one resource where the class needs three levels. Using AI to plan but never to give feedback.

Each mistake comes with the rewritten prompt that fixes it.