use this filter before building an AI tutoring product
A field note on why AI tutoring products need teacher workflows, student goals, tutor notes, and clear next actions.
The workflow is the product. An AI tutoring session should connect to a real teacher workflow, the student’s goal, tutor notes, and a next action.
what should an AI tutoring session connect to?
Tie the session to a real teacher workflow. That connection gives the conversation a place inside the work teachers already do.
A tutoring session should exist within that workflow instead of standing alone as another conversation.
whose goal should shape the session?
Anchor the session to the student’s goal. The goal gives the tutoring interaction a clear direction and keeps the session connected to what the student is trying to achieve.
what should happen after the tutoring conversation ends?
Capture tutor notes and the next action. Those details carry the session forward and connect it to the surrounding teacher workflow.
A generic chatbot creates another untracked conversation. The workflow is the product.
How should an AI tutoring product be designed?
Tie each session to a real teacher workflow and anchor it to the student’s goal. Capture tutor notes and the next action.
Why does a generic tutoring chatbot create a problem?
A generic chatbot creates another untracked conversation. The session needs to connect to a teacher workflow so it can carry forward.
What makes the workflow the product?
The workflow connects the teacher’s work, the student’s goal, the tutor’s notes, and the next action. Those connections define the tutoring product.