Yesterday a free prompt catalog dropped on r/PromptEngineering, and step two is the twist. u/Cuatuza built a catalog that turns your AI assistant into a Python tutor, one structured lesson at a time. It covers 28 learning blocks, from installing Python and writing your first program to testing, databases, APIs, and deployment. That is a full path from “what is a variable” to “my app is live,” and it costs nothing.
The twist
The prompts are not “explain this topic” requests. Each block has learning objectives plus a prompt that tells the AI how to teach. It’s told to quiz you with open-ended questions, hand you practical exercises, review your work, and loop back to whatever you struggled with. On harder exercises it guides you through the problem without solving it for you. So the curriculum lives in the catalog, and the teaching behavior lives in the prompt.
That split matters more than it sounds. Most people use AI as an answer machine. You ask, it tells you, you feel smart for ten minutes, and then you can’t reproduce any of it. A tutor prompt flips the direction of effort. The AI asks, you think, and the thinking is where the learning sticks. Because the behavior is baked into the prompt, you also don’t have to remember to say “don’t just give me the answer” every single time. It’s already set up for you.
One early tester said it’s weirdly good at catching you when you’re just nodding along without really understanding. They also flagged one block (functions) as a weak spot, which is exactly the kind of feedback the author is asking for. Functions are a classic stumbling point, so it’s a useful place to watch if you try it. Parameters, return values, and scope trip up a lot of beginners, and a tutor that rushes through them can leave you with shaky foundations for everything that follows.
Mini-workflow 🛠️
- Open the catalog and pick your starting block. Total beginner? Start at installing Python. Filling gaps? Jump straight to the block you need, like testing or APIs, instead of grinding through material you already know.
- Read the learning objectives so you know what “done” looks like. Treat them as a checklist. If you can’t explain each one in plain words at the end, you’re not finished with the block.
- Paste that block’s prompt into your AI assistant of choice. Start a fresh chat per block so earlier context doesn’t muddy the lesson.
- Answer the open-ended questions in your own words. Skip the one-word replies. A sentence like “a list is an ordered collection I can change after creating it” gives the tutor far more to work with than “yes.”
- Do the exercise, send your work back for review, and let the tutor revisit the shaky parts. Actually type the code yourself, run it, and paste in any error messages you hit. ✅
Pro tips
- Be honest when you’re lost. The adaptive part only works if your answers show where the gaps are. Saying “I guessed on that one” is a gift to the tutor, because it knows where to dig.
- Resist asking for the solution on harder exercises. The prompt is built to guide you, and that is where the learning happens. If you’re truly stuck, ask for a smaller hint rather than the full answer.
- If a block feels confusing or flat, note exactly where. The author wants to hear what helped, what confused you, and what could be better. Specific notes like “the explanation of return values skipped an example” are far more useful than “it was okay.”
- Keep a small notes file as you go. Write down one thing you learned per block and one thing you still find fuzzy. Revisit the fuzzy list a week later and ask the tutor to quiz you on it.
- Try the same block with two different AI assistants. Teaching style varies a lot between models, and you may find one explains things in a way that clicks better for you.
The goal is a thorough Python path that’s free, and a real test of whether AI tutoring can come close to paid courses. It’s an experiment in public, and your usage is part of how it improves. Feedback is optional, so you’re also welcome to just use it and learn.
Catalog: https://catalogo-tutores-production.up.railway.app/
If you’re learning Python, grab a block and give it a spin. Then tell the author how it went! 🚀
Frequently Asked Questions
Q: Will the tutor notice if I’m just nodding along?
Yes. One early tester said it’s surprisingly good at catching that. The prompts ask open-ended questions instead of simple yes-or-no checks, so a vague answer gets a follow-up. Try explaining each concept in your own words, even when it feels obvious, because that’s where the gaps show up.
Q: What should I do if a block moves too fast?
One tester found that Block 7 (functions) moved past scope too quickly and didn’t include enough practice exercises. They fixed it by asking the tutor to slow down and give more practice before moving on. If a block feels rushed, say so directly and ask for extra exercises, since the tutor adjusts once you tell it what you need.
Q: Can this replace a paid course?
One tester thinks it could, as long as you have the discipline to keep going. The structure is clean, and the 28 blocks run from installing Python all the way to deployment. A paid course gives you a schedule and some accountability, so you’ll need to build that routine yourself. Treat it like a daily practice session rather than something you binge.
I built a free catalog of Python tutoring prompts across 28 learning blocks. Looking for testers and feedback
by u/Cuatuza in PromptEngineering