Git commits should be focused on one small thing at a time, doing small changes or additions. Then using descriptive commit messages like “add webook notifications” or “fix webhook triggering twice”.

This makes the history of the project easier to see what changes were made and for what purpose. If something breaks webhook functionality then you can have an easier time finding what broke that feature. It also has the added benefit of someone showing their work progress. It’s like you can be a math genius but if you don’t show your work, your professor is going to think you cheated. In this case, it’s a pretty dead giveaway that AI was involved. Since you are using AI then smaller commits also let you see what the AI to changing between iterations since even if you give it a copy of a file, it may change other parts of that file that you didn’t ask for, and those changes could be good or bad.

And just because you are making these commits doesn’t mean you have to “git push” them to your public repo right away. Since you’re working alone and don’t have any community contributors then you can just keep that work locally and push when you’re ready for the next public release. Over time you could start using a development branch in git and push to that, so other developers can see your progress and when you’re ready for a public release your merge the changes to your main branch. That’s some more advanced git stuff but it’s a core skill of any developer to be able to use branches.

Also there’s nothing wrong with being new. I only mentioned the new account because when combined with the other things, this was a dead giveaway of AI use.

For what it’s worth, good job putting together something that is useful for you. I would just encourage you to make sure you are trying to understand what you are doing and be willing to challenge yourself instead of using AI as a mental crutch like many people do. AI can only get you so far and you’ll need to learn enough to call its bullshit and point out its mistakes.

I see.
As a poc it certainly works.

Side remark: I usually see the term “dashboard” usally being used for a sort of compilation about services individual status (like you do) but also links to the actual service to use said service.
So yours is a sort of hybrid of (I believe they are called) Yacht and homarr

It’s not a bad idea at all to have a label so we could set expectations right. But don’t be too harsh on me ;) Just being able to pull a functional app without much of experience is already a reasonable accomplishment is it?

I appreciate you being honest in your response here.

I’d recommend adding this disclaimer to the post text and repo readme for complete transparency, and so anyone who doesn’t want to use AI-generated projects can move on without creating arguments in the comments.

There are many genuine reasons to not trust code generated by LLMs, especially with anything network-connected or handling important data, so it’s important to be upfront about it.

EDIT: removing this comment because I don’t think you will use this feedback responsibly

If you want to learn to develop web applications, try to understand everything you do. Don’t let the entire thing be generated by AI. Do small changes and commit those one at a time. Understand the programming language, your application’s architecture, internet security, and so forth. Not understanding and then releasing it publicly and later asking for advice on how to improve it, isn’t the way. You’re still the maintainer of the project now, and will have to understand and approve any PR’s people may send your way.

I mean, it can be addictive to just let AI throw everything together in a week without learning anything consequentual. But I wouldn’t throw it on my server with root access to Docker. What’s your real interest here? Learning or telling AI to make stuff for you?

An issue with your statement “know what you’re doing by doing it” is that without an actually educated teacher to provide trustworthy feedback, you are going to struggle the learn from your mistakes. The LLMs can only provide so much, and they will lie out their ass to you. Unless explicitly prompted to provide critical feedback, they will find any way to provide positive feedback even to your actual detriment. They will happily skirt their sandboxes, and fight your every attempt to make them actually safe.

At a quick glance, nothing in the project indicates that you are not an expert and that an AI Agent provided the code. The quality of the code is also quite poor, even by Claude standards. I’m actually kinda mind blown you got it to built this without any tests… Something we’ve recently been talking about at my job in terms of AI agents is “cognitive debt” that is incurred in the project. LLMs are fundamentally a statistical next-word generator. If they are given something of poor quality, they will tend to produce more and more poor quality work. And without intervention, it just snowballs.

I’ll never tell someone to stop trying to learn. But, your hubris is going to negatively impact your learning outcomes. And to be clear, YOU are not writing the code and the code is what runs on the server and people interact with. What you are doing is using an AI Agent. If you want to get feedback on that, then be honest about it.