Short version: a Reddit user shared a long system prompt that turns an AI into a software-building mentor. It assigns projects at your level, coaches you with graded hints, reviews your code, and quizzes you. You write the code and the AI guides.
The author said they weren’t sure if it was good or bad and wanted feedback. Here’s my read.
What the prompt does
Most AI tutors fail the same way. You get stuck, the AI pastes the answer, and you learn nothing. This prompt is built to prevent that. It sets the AI up as a mentor whose job is to produce evidence that you can do the work alone, not just finished projects.
The prompt is split into labeled blocks, which is why it holds together over a long chat: role, about me, languages, session flow, project assignment, coaching, verification, code review, quizzing, guardrails, style, and progress tracking.
The parts worth stealing
The hint ladder. When you’re stuck, the AI climbs four rungs, one at a time:
- A guiding question
- A pointer to the concept or docs
- Pseudocode or the structure of the solution
- A snippet of about 10 lines, each line explained
If you fail twice on a step, the AI climbs a rung without being asked. That keeps you from spinning on endless questions. A full solution only comes if you literally say “show me the full solution”.
Hypothesis before help. You state your guess about the cause before any hint arrives. Pasting an error and asking “what’s wrong?” is banned. Forming the guess is the skill being trained.
Predict before you run. Before running anything non-trivial, you write a one-line prediction of the output. The gap between prediction and result is where the learning happens.
Ship at 70%. A finished imperfect project teaches more than a perfect unfinished one. If you start polishing past the Done checklist, the AI points it out and moves you on. New ideas go on a parked list instead of derailing the current project.
Evidence labels. Every concept gets a label: independent, hinted, guided, or copied. Only independent evidence counts toward “solid”, and the prompt says you can’t talk the AI into a higher status. That blocks the usual trap where the AI flatters you into thinking you’ve mastered something.
You run the code, not the AI. You paste the real output and the AI reasons from it. This saves tokens, and it stops the AI from saying “this works” when it only read the code.
How to set it up
The prompt has bracketed blanks: your schedule, learning style, tendencies to guard against (perfectionism, over-preparing), and your toolchain. Fill those in honestly, because the AI uses them to size sessions and pick projects. It also expects a roadmap file (it mentions LADDER.md or ROADMAP.md) that defines levels and promotion rules, plus some form of memory so it can save state between sessions. A Claude Project or a custom GPT with a memory file fits well.
A few honest caveats
- It’s long, and the project reference file is doing a lot of work. Without a roadmap, the promotion rules have nothing to stand on.
- It relies on the AI actually tracking state across sessions. If your tool has no memory, you’ll be pasting state blocks by hand. The prompt does cover that case.
- One commenter liked the structure, especially the hint ladder and the 70% rule, and said it’s the kind of thing that keeps people out of tutorial hell. I agree. They also suggested a tweak to the verification section, but the comment got cut off, so I can’t tell you what it was.
Use cases
- ✅ Self-taught beginners who keep starting tutorials and never finishing projects
- ✅ Career switchers who need a portfolio of small tools they can explain line by line
- ✅ Anyone learning a second language who wants only the syntax differences taught
Prompt of the Day
Want to test the idea before adopting the whole thing? Paste this at the start of a new chat:
“Act as my software-building mentor. I write the code, you guide. Give me one useful project above my level, with a 3 to 5 item Done checklist and test inputs. When I’m stuck, make me state a hypothesis first, then hint one rung at a time: question, concept pointer, pseudocode, then a snippet of 10 lines max. Before I run anything, make me predict the output. Ship at 70%.”
If the short version sticks, graduate to the full prompt.
Your move
Try it on one small project this week, like a CLI tool you’d actually use. Pay attention to how it feels to state a hypothesis before getting help. That friction is the point. Then tell us what you’d tweak.
Frequently Asked Questions
Q: Can the AI tutor actually run my code?
No. The tutor can’t execute anything, so it only sees what you paste. Run the code yourself and paste the full output or error message back. If the tutor says something works before you’ve shown the output, ask it to point to the evidence before you move on.
Q: How do I use the hint ladder without getting stuck?
Ask for help one step at a time instead of jumping straight to the answer. Start with a nudge, then ask for the concept behind it, then a pseudocode outline, and only then a near-solution. Each step asks you to do more of the thinking yourself, and that’s where the learning happens.
Q: What does the 70% ship rule mean in practice?
Ship the project once it works for its main job and is about 70 percent done. The last 30 percent of polish can go into a later version. The goal is to get something real in your hands instead of looping through tutorials forever.
Q: How does the warm-up question help me remember things?
Each session opens with a quick question about an earlier concept, so the review happens inside the lesson instead of in a separate flashcard routine. Answer it before the new work starts, even on a short day. Recalling something right before you need it is what makes it stick.
Project based AI tutor project instruction
by u/Me_Luden in PromptEngineering