01
Profile
Topic, goal, level, learning style, and weekly commitment become the first signal.
Adaptive learning, mapped
Coordinate turns a topic into a guided learning workspace with planned chapters, generated lessons, quizzes, a course-aware tutor, and private document context.
5
MVP workflows
1
course-aware workspace
0
generic lessons
Draft lesson
Quiz
Next step
Tutor prompt
"Show me why attention matters, then quiz me with one practical example."
The method
The page stays simple because the product does the organization underneath.
01
Topic, goal, level, learning style, and weekly commitment become the first signal.
02
Coordinate drafts chapters, milestones, quizzes, and a final project as one coherent path.
03
Lessons, tutor answers, and document references stay tied to the course you are taking.
Agent trace
Coordinate is designed around visible AI workflows: each planning step can become something you inspect, not a hidden prompt behind a spinner.
Generate a structured path from a topic and learner profile, with an inspectable run trace.
Turn chapters into study-ready explanations, checkpoint quizzes, and project-oriented next steps.
Ask questions inside the course and get answers that understand chapters, progress, and context.
Attach private documents so lessons and tutor answers can retrieve relevant source material.
Document context
Upload documents once, then let lessons and tutor responses retrieve the relevant pieces when they matter. It keeps the workspace personal without adding clutter.
Coordinate is not another folder of AI outputs. It is a structured learning workspace where each answer knows the course, each lesson has a place, and each document can be traced back.