2026Resurfacing · now I teach it
Grad Research & Bibliography(MUSX 5110)
Handed to me this summer, to teach in the fall. Here the arc turns: from survival to innovation, and from running the loop privately to teaching the loop itself. The thesis of this whole talk becomes the curriculum.
What makes it different
A narrower gap — and a status flip
- The gap is smaller. The expertise I bring now includes being an active researcher (research-via-performance — the spine of my promotion case), not just a performer. I’ve also taken this course as a student.
- From catching up to leading.Rather than barely staying a day ahead, I’m adding what the PhD-taught version never had: “it’s time the class is brought into the 21st century by adding a significant AI module.”
What students actually do — the mini-seminar
I don't hand them the machine. I teach them the loop.
The first weeks are a mini-seminar on running the loop on their own work — before AI touches their research:
- The Unit-1 AI failure-mode lab — see where the machine confidently fails, firsthand.
- The AI-use policy + disclosure — an origination line they write to: AI may refine, organize, or critique your thinking, not originate it.
- The THOMAS audit protocol— the habit of checking the machine the way you’d check a colleague’s note.
And the rule for where AI belongs: think & learn = no AI · organize & manage = all in · practice & drill = AI with you.
“I figured it out — now I teach them to.”
The artifact
The built course is the proof
The module, policy, and protocol already exist as working materials in the course spoke: