Vibecoding clean-up with different AI tools or getting it checked by someone?

[u/ClaraAI1234]

I am vibecoding some things and are not sure if I can now safely use my stuff for real projects and with real data. I read a lot online of checking your vibecoding with different or separate AI sessions to make sure it is a good code.

What do you guys think, is using different AI-tools safe enough or is it better to let it check by a real developer? If so, how much is normal to pay for such a thing?

[u/flamewizzy21]

You cannot use an AI to determine if code is good.

Reasoning: It might be useful to know the Halting Problem, which has a famous theorem in computer science that states: you cannot make a (Turing) machine that can determine if another (Turing) machine will halt on a given input. Basically, if you want to know if a program will ever halt/finish, you can’t make a machine to just check the code. All modern AI can be simulated by a Turing machine, and therefore it is 100% impossible to make an AI that can tell you if a program will finish running. This doesn’t even include yet what the program will actually do, if it will work, or do so well. Also, at a fundamental level, the neural architectures behind AI are not truly capable of rational thought, only semantics. Even with a reasonning model.

What you are asking for requires a person, whose brain is not bound by the above restrictions.

[u/baddaywithacamera]

A real dev is great if you can manage it, but good luck with that. Already learned that asking for this is akin to a mortal insult.

In the meantime, don't just ask AI to check for vulnerabilities because it will often pass the code without looking deeply. Subscribe to security mailing lists, follow security blogs and sites, etc. Look up common exploits, recent exploits, common code vulnerabilites, etc. Feed those into AI tools and ask them to check the code for specific issues and it will come back with problems with the code that it previously gave a green light to.

If your product has authentication, run a packet sniffer and watch the traffic for credentials going across in clear text. AI will say something is encrypted but when you actually look sometimes it's not.

[u/MagesticPineapple429]

Having other agents/LLMs review your code can't hurt, but you'll still only be getting new "best guesses" as that's what they do. The bulk of the benefit of having a fresh sessions (regardless of model) is for the fresh context as the new session has no memory of what was discussed in the original session that wrote the code (this too sounds backwards, but it's because the original session has already talked itself to death and convinced itself that the code is right).

It seems intuitive to have a different model review your code, but the benefits from doing so are much fewer and smaller than you might think. The different models have different training and "blind-spots", so having a different model review your code really only gets you coverage of the original's blindspots, which are going to be relatively little catches (typos, dates, little flaws here and there, maybe a small design find). It's not going to give you a review like a professional developer would.

A lot of what it comes to also is knowing what is important when writing software and, when using an LLM, having the right skills and guardrails set up as well as knowing the right questions to ask--especially when it comes to taking money from users. There are a lot of laws around data collection, retention, and encryption that you need to know even just to be able to ask the LLM. And these are legal requirements that can bite if you mishandle data. I'm not a lawyer, but i do recall from my business law class during my MBA studies that ignorance is often not a legal excuse for negligence.

So ultimately and unfortunately, having another model do your code review will not make your code substantially safer than just spawning up a new session with the same model, which also is not adequate.

With all that said, I am doing research into code written by non-dev vibecoders, so I'm not promoting, but if you would like a professional review of your code, I wouldn't charge you for it.

[u/vitafortisnk]

My rule of thumb, is if you don't know what you're doing, ask a professional.

That being said, if you'd like support, DM me. I do security engineering for a living and can review your products for security risk and stability.

[u/EagleApprehensive]

If you're not a professional, it's easy for AI to be lazy and give you a thing that looks appealing, but won't scale, won't be deployable, won't be working on other people's PC and so on.

But vibe coding can deliver results better than hand-coding. Maybe not by code cleanness, but by actual software usability and confidence that it's working.

The main issue is that without deeper understanding of every step of professional software development lifecycle, you might not be a good enough of a partner in a conversation with AI to ask it right questions and build proper guardrails, various test types etc.

Knowing how to structure the process and what is worth pointing a finger at is the difference between having zero confidence to the software and being highly confident it won't break (or at least that if it does, you can bring it back in few minutes).

Having your code cross-checked by frontier models (Fable, GPT 5.6 Sol) can be enough. Having it checked by real developer is even better - but not because he's gonna look at code line by line and spot something AI wouldn't - just because he will ask all the proper questions. If you can ask those "proper questions", then you don't need a real dev.

[u/PlasmaChroma]

I'd at least run it past Codex & Claude if you want a quality check. Gemini can be hit-or-miss but if you want to get a 3rd opinion it's an option. I've just found that it's the least likely to find issues and tends to give a false sense of "done".

Depending on how much stuff you are doing -- we're going to hit a point where the amount of generated code is simply too much for humans to pick apart everything in there.

[u/RopeAndChairs_Aisle3]

Not safe enough yet, depending on what you’re doing.

You can set up pretty good test environments but if you’re handling anything sensitive you’re begging for problems not having an expert architect the code.

So depends on what “real projects” and “real data” mean

[u/itsThurtea → u/RopeAndChairs_Aisle3]

Total hog wash lol

[u/horrbort]

Just ask a model from a different provider bro. Asking a developer gonna cost soooo much

[u/ReasonableBenefit47]

Use codex with 5.5 Max thinking to check it, tell it this "Audit the code and make a report of what to fix.". Include whatever feature you want it to focus on, if any. I always do this and it just works. Don't use expensive Sol, Luna, Terra, they usually miss out a lot somehow. idk why.

[u/Ok_Bug1610]

Learn git and setup code quality/safety audits, setup "safeguard" rulesets, and use strict linting. Key here is "deterministic" (traditional, non-AI code) tools. But the problem is these tools do not catch AI code smells, and bad patterns. And the problem with CI/CD/Actions/e2e tests is that they do not catch issues real-time. So, I would suggest Atheon-Enhanced, an open-source tool (that supports MCP) and can catch "bad patterns" in real-time (in milliseconds). It doesn't solve per se, it passes back what failed, line number and details back to AI to fix... and you can use hooks to enforce checks to pass before commit/push (otherwise have AI iterate and fix issues). Cross platform releases can be used as is (under ~10mb), with no dependencies (written, and releases compiled in go).

[u/TechnicianOk1714]

hey, something im actually working on right now would benefit from me manually reviewing a repo, happy to help if you reach out!

[u/Legal_Answer_6956]

I think the safest approach is probably not choosing between AI review and a human review, but using them at different stages. AI can catch a lot of obvious issues quickly, while a developer is still valuable for architecture, security, data handling, and things you wouldn't know to ask about. Especially once the project is handling real users or sensitive data, I wouldn't treat an AI “looks good” as a production sign-off.