In this project you will design a personal AI study assistant — a custom-prompted tutor that explains, quizzes, and tracks what you have learned across any subject. The deliverable is a single system prompt plus a small set of "lesson templates" you can reuse for every new topic you want to learn.
A free chat window is the worst classroom you can imagine. There is no syllabus, no quizzes, no spaced repetition, no record of what you covered yesterday. Most people lose 70% of what an AI tutor explained simply because they never had to retrieve it again.
This project fixes that. We will build a study assistant that turns any chat session into a structured learning loop: explain, check understanding, quiz, summarise, schedule a review. The whole system runs on prompts — no app required.
A study assistant is just a chat with a strong system prompt, plus a discipline around how each session ends. The system prompt sets the persona and rules. The session structure makes sure the learning sticks.
The clever part is the notes log. It is just a Markdown file or a Google Doc. Each lesson ends with the assistant generating a five-line summary, a small quiz, and a recommended review date. You paste that into your notes log. Next time you start a session you paste the previous summary back in as context. The "memory" of the system is your file, not the model.
Here is what most people type when they want to learn something with AI:
No structure
explain probability to me, I'm a beginner
The AI dumps a wall of text. You read 30%. You ask a follow-up. Two days later you remember almost nothing. There was no check on whether you understood, no quiz, no record. The session evaporates the moment you close the tab.
The system prompt (paste once at the top of every chat)
You are my personal study assistant. Your job is to help me learn,
not to dump information.
Rules:
- Calibrate to my current level. Ask 1 short question before explaining
anything new, to gauge what I already know.
- Explain concepts using simple language and one concrete analogy.
- Never give me more than 4 short paragraphs in a single message.
- After each explanation, ask one "check-understanding" question and
wait for my answer before continuing.
- At the end of a lesson, generate:
(a) a 5-line summary I can paste into my notes
(b) a 3-question quiz (mix recall + application)
(c) a "next review" date using spaced repetition
(1 day, 3 days, 7 days, 21 days)
- If you don't know something, say so. Do not invent facts.
- Track open questions I raised but we didn't fully resolve.
Subject: {paste your subject here, e.g. "introductory probability"}
My current level: {beginner / intermediate / advanced}
My goal: {paste your concrete goal, e.g. "pass the data science
mid-term in 4 weeks"}
Starting a session
Last lesson summary (paste from notes):
"""
Topic: conditional probability basics.
Covered: P(A|B), tree diagrams, simple Bayes' rule example.
Quiz score last time: 2/3.
Open questions: when is independence safe to assume?
"""
Today I want to learn: Bayes' theorem in plain language and one
worked example involving medical testing.
Begin with a check-in question. Don't dump theory at me.
Sample first response from the model: "Quick check before we dive in — when you see the formula P(A|B) = P(B|A) · P(A) / P(B), which symbol do you find the most confusing? I want to know whether to start from the formula or from a story."
Notice what just happened. The assistant did not lecture. It asked a calibration question. That single design choice — forced by the system prompt — is what separates studying from scrolling.
Ending a session — the wrap-up prompt
End the lesson now. Output exactly this structure:
### Summary (5 lines, no fluff)
- ...
### Quiz (3 questions)
1. (recall)
2. (recall)
3. (application — give me a tiny scenario, not a definition)
### Open questions to revisit
- ...
### Next review
Suggested date: {today + N days} where N follows my spaced-repetition
schedule. Justify the choice in one line.
Sample wrap-up output (abbreviated): "Summary — Bayes flips conditional probabilities, base rates dominate small effects, tree diagrams unlock the intuition… Quiz — Q1 define P(A|B) in your own words; Q2 calculate P(disease | positive test) given priors X, Y; Q3 in a fraud-detection setting, what changes if the base rate doubles? Open questions — when do we use Bayes vs simple frequencies? Next review — Wednesday (3-day step on the spaced schedule). Reason: you scored 3/3 today; if you score below 2 next time, drop the interval."
Pick a topic you have wanted to learn for months — a programming concept, a language, a school subject. Run one full lesson with the system prompt above. End with the wrap-up. Save the summary in a file. The "study system" exists the moment you save that first summary.
Add one extra rule to the system prompt that fits your learning style. Examples: "After explaining anything, ask me to teach it back to you in 3 sentences", or "Quiz me on the previous lesson before starting the new one". Notice how a one-line rule changes the entire feel of the session.
Run two parallel "subjects" with the same system prompt — for example, a technical one and a creative one. Track which subject the assistant handles better and which one needs more rules. The mismatches teach you how to harden the system prompt over time.
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