University

Replace or complement traditional university with AI-powered degree programs, adaptive learning, exam preparation, and progress tracking.

When to Use

User wants to: learn a complete degree/career autodidactically, support their current university studies, prepare for certifications/exams, change careers with structured upskilling, or help someone else study. Agent manages the entire learning lifecycle.

Quick Reference

Area	File
Degree/career setup	degrees.md
Content generation	content.md
Assessment & exams	assessment.md
Planning & calendar	planning.md
Progress tracking	tracking.md
Study formats	formats.md
Learning preferences	feedback.md

Workspace Structure

All learning data lives in ~/university/:

text

~/university/
├── degrees/              # One folder per degree/career/certification
│   ├── index.md          # Active degrees list with status
│   └── [degree-name]/    # Per-degree folder
│       ├── curriculum.md # Full curriculum with modules
│       ├── progress.md   # Module completion, mastery levels
│       ├── calendar.md   # Exam dates, deadlines, milestones
│       └── modules/      # Study materials by module
├── resources/            # Uploaded PDFs, slides, recordings
├── exams/               # Test history, practice exams
├── flashcards/          # Spaced repetition card sets
└── config.md            # Study preferences, schedule, goals

Core Operations

New degree/career: User says what they want to learn → Generate complete curriculum equivalent to university degree → Map prerequisites → Estimate total time → Create study calendar → Store in degrees/[name]/.

Daily study: Check calendar and progress → Generate today's session (reading + exercises + review) → Adapt to available time → Track completion.

Content processing: User uploads PDF/audio/video → Extract key concepts → Generate summary → Create flashcards → Add to relevant module.

Assessment: Generate practice tests from studied material → Simulate real exam conditions → Correct with explanations → Update mastery tracking → Schedule review for weak areas.

Progress review: Show completion %, mastery by topic, time invested → Predict readiness for exams → Alert if falling behind → Suggest plan adjustments.

Critical Rules

• Never generate exam answers without teaching first — explain WHY
• Track what user knows vs doesn't know — don't assume mastery
• Adapt difficulty progressively — start where user actually is
• Spaced repetition is mandatory — schedule reviews automatically
• Distinguish "studied" from "mastered" — require verification
• Support multiple degrees simultaneously — keep them organized
• Learn user's optimal study patterns — times, formats, duration

User Modes

Mode	Focus	Trigger
Autodidact	Full degree replacement	"I want to learn medicine/law/engineering"
Student	Complement existing university	"Help me with my classes/exams"
Career Change	Upskilling with portfolio	"I want to transition to data science"
Exam Prep	Certifications, bar exams, etc.	"Help me pass AWS/PMP/MIR"
Tutor	Help someone else learn	"Help my kid with school"

See degrees.md for setup workflows per mode.

On First Use

1. Ask: What do you want to learn? (degree, skill, certification)
2. Assess: Current knowledge level, available time per week
3. Generate: Curriculum with realistic timeline
4. Configure: Study preferences (formats, schedule, goals)
5. Create: ~/university/ structure