AI did not break your course. It exposed a handful of assignments.

Teaching Day thought for the faculty in here. The most useful reframe I can offer about AI and your classroom is this: it is not a discipline problem, it is a design problem. A discipline problem means you police every student all semester. A design problem means you fix a few assignments once. The second one is a much better life.

Here is the four move redesign, SeedStacking style.

Seed, audit. List every graded task and rate each one green, yellow, or red against one question: could a student get a passing version from AI in under ten minutes, undetected? Most of your course is green. The reds cluster.

Sprout, reframe. Lift the outcome above what the model fakes. Turn summarize into critique and defend. Turn describe into diagnose and fix. Same content, higher altitude.

Grow, rebuild. Make the reds AI resilient (oral defense, live application, show the process) or AI integrated (grade students on out reasoning the AI). Rebuild one this week, not all of them.

Harvest, share. Pilot in one unit, measure whether it got harder to fake and whether students actually learned more, then hand your one page to a colleague.

The full kit with the audit grid, reframe verbs, and rebuild templates is here: https://www.harvestkernel.com/the-ai-ready-course-redesign-kit/

Tell me in the comments: what is your reddest assignment, and which rebuild path fits it?