Dusting off the room because it has been a minute or two since I was in here last!
Through last year, I ran a lot of vibe-coded projects. Most...
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I don't trust AI. It once destroyed my entire codebase/.
I think the idea is to gently guide the AI/agent you're using, and not just giving them direct, unmonitored access to an entire code base.
I didn't give it access but it was just uncommitted files where the agents added a hell lot of files, and my initial code broke!
Oh my. That must have been a lot to fix.
yes!
use CLI tools like Codex -- it won't run without a git repo (so you can always go back)
codex is shit. 🙂
lol i know that -- but it's good for a couple of use cases (maybe not vibe coding)
which cases?
anything local. personally I use it to understand complex codebases .. very accurate and works well
Why did it fail in my case? It just provides a superficial overview, which, as a developer, you're not interested in.
it might need detailed prompts and what things you want .. otherwise it would give you an ultra trimmed version (which is so bad)
indeed!
I think vibe coding works as long as you approach in the right way -- like system prompts, in-depth guidelines and verifying everything. for most of my projects, I have used AI to figure out the best architecture/project structure before starting (at the very least, it gives me a direction).
for 90% of use cases (which are not hardcore engineering projects), vibe coding works tbh. I trust perplexity cuz I have pro version and can see the sources clearly :)
(finally found time to read this -- I have a habit of opening in a tab and forgetting lol)
Thank you for taking the time to read it.
I am not really a core software dev/engineer, so a lot of the best practices to expect are lost on me.
But this is the most seamless vibe coding experience I have had so far.
I used Gemini. 3 (pro) to achieve this.
I vibe coded my current portfolio, and it looks great. Https://eunit.me
Broooo, this is so cool!
Thank you @dumebii . Here is a technical piece detailing how I built it: eunit.me/blog/building-a-modern-di...
Woah. This is really cool. I enjoyed reading it.
I still got a lot to learn. 😅
I don't know if this makes me excited or anxious 😅
Fantastic piece btw
😅😅 It's giving "AI is coming for your job."
Fr 🥲😅
Very interesting. Commenting here to get notifications for other people's opinions.
I'm waiting too! 🤞
I would have liked to get a look at your code base, to sufficiently verify the grade of the code written.
I'd share the GitHub Repo link when I'm done with the entire project.
Good post, but for "professional" software engineering practices, I would have expected even more, including static code analysis beyond linters, unit tests, continuous builds with some integration test, and emotional discussions about clean code patterns during merge requests. Because that's what you do with juniors. And that's what I do with AI code generators.
I'm not a software engineer. And all the times I tried to be one, I failed so badly at it; especially when it came to testing.
It's something that I'm learning is a necessary part of building anything.
I used to believe that "once it works, then it's okay."
But, I will share these updates with you in coming articles.
What made me understand better what good code is was reading and watching what Uncle Bob (Robert C. Martin) has produced. It is full of wisdom. And currently I come to the conclusion that it still holds even in the ages of code generation.
I am curious about your upcoming articles - keep them coming :)
Thank you!
I'd also check out Robert C. Martin.
I find that AI is very good at achieving fancy things with very simple ingredients. I have been a pro developer for over 15 years. When I specify a new AI project, I use Django, HTML, Bootstrap and vanilla JavaScript. I once vibe-coded a huge React mess that had to be rewritten. TO be fair, I am not good with react and did not know how to get the project back on track.
What I found:
No "build" processes (no node, C#)
No dependencies unless very specifically required (like for writing .pdfs)
All styling done within Bootstrap.
Django is an opinionated framework, but AI loves Python and "knows" how to use Django well.
Use text data files as long as possible. Instead of a database of "categories," just make a plain text file and tell AI to use it as an array.
Then transition to SQLITE if necessary.
Use tech that you understand as much as possible. (don't use Firebase for the first time in an AI project)
Remind AI to use "best practices."
Ask AI to summarize what it did in a documentation.md file.
With plain JavaScript and HTML, you can do anything on the front end. React, TypeScript, jQuery and Vue are essentially wrappers for JavaScript. They are also far slower than native JS. I am consistently amazed by how quickly JS can sort, move, build, etc.