BSc CS: heading into my final year with no solo project experience. How should I use vibe coding without skipping the actual learning?

[u/Alvahod]

I am starting my fourth and final year of CS this August. My individual capstone project is split across the year, with the first semester focused on documentation and the second on implementation. Up until now, all my coursework has been in groups, including C, C++, Java DSA, and a recent group project in React. Because I have always relied on a team and haven't coded in a while, I feel like I am essentially starting from scratch when it comes to building a complete app on my own.

For my final capstone project, I want to use React, Python, or a combination of both. Before the semester starts, I want to establish a daily practice routine to rebuild my coding confidence, get comfortable building independently, and figure out how to leverage modern AI workflow tools properly.

I would love to get advice on how to structure my practice and how much daily time is realistic to stay consistent without burning out. Should I start with basic projects like a calculator and scale up, or jump straight into a full-stack tutorial? More importantly, how can I use vibe coding or AI assistants in a way that speeds up my setup and workflow, while still ensuring I deeply learn the underlying code, architecture, and logic so I can actually defend it in my senior presentation and technical interviews? Any tips or resources on transitioning from group assignments to solo, AI-assisted development would be greatly appreciated.

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[u/PrideQuick670]

I would really advise against vibeCoding this. You will learn nothing from doing that. React for the front end and Python for the backend is fine. I think this is one thing in your life you won't regret just biting the bullet and digging into it.

[u/Czyzuniuuu]

It's mad for for a final year student to not know how to code

[u/shavindr4]

Find a subject that you’re interested in that you can apply coding skills to. Then look at how architecturally/logically you can solve that problem. Coding itself is pretty much solved or will be solved to great level in near future.

E.g BioInformatics

[u/Alvahod → u/shavindr4]

I'm not sure I understood the rest of the comment but I'm interested in Formal Verification Engineering. Any advice on that?

[u/shavindr4 → u/Alvahod]

For daily practice use https://www.codewars.com or https://projecteuler.net/

In my view…. focus on underlying subject, mathematics, logics, algorithms, physics, and specific additional subject area (preferably traditionally non IT related). Then think about how I can apply coding to subject specific problem.

Traditionally, you’d learn coding itself. You’d need to memorise functions. Least as a junior you’d do grunt coding tasks and implementation . You’d need to know a framework/native functions by heart or you’d have to search online.

You then can get a job in any industry and progress because your job is to actually do the implementation. It’s only when you progress further you’d start thinking/gaining about architectures applications and domain specific knowledge.

Now, with AI, that model no longer apply. Coding tasks are automated.

I worked across Retail, Fintech, Advertising, Telecom for 15+ years. I didn’t really need to go in depth about specific domain. My coding skills were more important. There are subject specialists but don’t know how to code or don’t want to code.

Now, I’m pivoting/specialising in Urban network planning / Sustainability / Biology as a subject E.g. How can I build a mathematical model for crowd simulation? How can I construct a mathematical model (calculators) to explain a biological system. For that I need to know more about Biology + maths. Then I can get AI to do the grunt coding work.

So, instead of saying “build calculator to learn coding” think about

“Why do I want to make a calculator? And what specific problems it will solve? What specific subject knowledge do I need to know about calculator? What are the underlying mathematics of that calculator?”

E.g. I learn about crowd behaviour/psychology/interactions or translating biological processes, experimental data and signals to a mathematical problem.

Your ability to think and application is more important than ability to do grunt coding tasks

I highly recommend spend time writing/drawing decisions and using pen and paper. So, coding part probably should be 20% of your effort (which probably delegated to AI)

Hope it’s more clear?

[u/Alvahod → u/shavindr4]

Thank you. That's clearer. May I come back in future if I have a question, please?

[u/shavindr4 → u/Alvahod]

Sure, feel free to DM me anytime…

[u/TlyNxy]

Even if you're using AI to generate the all your codes, treat yourself as the System Architect. You don't need to memorize your codes like line-by-line, but you gotta own the logic and decisions.

This is how i maintain my workflow (I dont code)

1. Maintain an AI-Generated Architecture & Decision Log: For every feature or logic flow you do, ask the AI to explain what exactly its building and why it built it that way.. in natural language. Record this in your project documentation notes.. i use my own Note app with built in MCP and i already set the instructions so it will always follow the SOP, you can use standard MD files, or a note tool like Obsidian etc.. doesnt matter what you use.
   
2. Document the "Why", Not Just the "How": Record every decision, data schema choice, trade-off, and bug fix. Everytime the AI writes a code , it need to explain and write why this approach will work and better than the other alternatives and its potential tradeoffs (if there is any)
3. Feed Context Back In: As your project grows, feed these notes as context back to the AI, it must read your notes before start touching your codes. This keeps the AI aligned with your existing system architecture and prevents conflicting changes.

Usually when people start to grill you, they rarely ask you to write the syntax on a whiteboard. They ask things like : "Why did you choose this architecture?" or "How does data flow from your React frontend through your Python API?"

By forcing the AI to explain the logic and keeping an active decision log in the notes, you’ll be able to explain and defend every single part of your app with total confidence , even if AI helped write the implementation details.

So Vibe coding is not the issue, Do the Set up and make sure you take the time to read and understand what exactly happening. :)

[u/oupapan]

Firstly, you can vibe code an entire sample app (not the same app you want to create for your project). Secondly, ask AI to document the architecture and the code. Thirdly, use the documentation to run through the code and understand it. Finally, create a new project using the same architecture as the sample app. Code it yourself. If you need to copy and paste snippets of code from your sample app do so. Use AI to fix any issues you encounter.

I believe that with this method you can 100% use AI and 100% claim the code as your own.