Everyone vibe coding their product idea needs to seriously consider adding some sort of actual developer consultation to the budget.
Not a giant engineering team or six months of architecture meetings.
Just someone who can look at the repo, the dependencies, the auth flow, the deployment setup, and the blast radius before you start putting real users into the thing.
AI makes it very easy to build something that looks like a product before it is ready to operate like one.
The Prototype Is Not the Product
This is the part people keep collapsing together.
A prototype proves that an idea might work. It helps you test a workflow, show the demo, learn what users care about, and decide whether the product is worth taking seriously.
A product has users. It stores data. It handles accounts. It processes payments. It sends emails. It accepts uploads. It runs in production. It needs logs, backups, permissions, dependency hygiene, and some idea of what happens when something breaks.
Those are not the same thing.
Vibe coding is genuinely useful for the prototype side of that equation. It gives more people a way to explore ideas without waiting on a technical co-founder, an agency proposal, or a pile of investor money. That part rules.
The danger starts when a prototype gets treated like a finished system because the UI looks convincing and the happy path works.
"Only the Good Guys" Is Not a Security Model
A lot of the AI tooling conversation still circles around this comforting idea that the dangerous capabilities will only be handed to responsible people. We've seen that already with Anthropic's Mythos System Card.
Cool.
Less than two months later, we're seeing a shit load more of this:
- GitHub security incident — source control is part of the attack surface.
- AntV Supply Chain Attack — popular packages can become delivery mechanisms. (Socket’s original X thread)
- TanStack Supply Chain Attack — even serious projects with serious maintainers can get caught in the blast radius.
- CopyFail CVE — “copy/paste this command” is a security boundary now.
- YellowKey Windows 11 Zero-Day — exploit chains are getting weirder and more accessible.
- Canvas, a popular LMS used in schools, hacked — real user data is always the prize.
- And a lot more — this is not an edge case.
This is the world your AI-built prototype gets deployed into.
The pattern is not one specific company getting owned. The pattern is the giant pile of systems modern software is connected to: GitHub, npm, CI pipelines, cloud credentials, browser sessions, environment variables, package scripts, build caches, deployment hooks, and every third-party service your app quietly depends on.
Most founders are not thinking about that surface area when they ask an AI tool to build their product...they are thinking about the feature.
Can users sign up?
Can they upload the file?
Can they pay?
Can the dashboard load?
Can I show this to someone next week?
And honestly, that is reasonable. That is how you validate an idea.
It is just not enough to safely run a product.
AI Makes the Surface Feel Finished
This is what AI hides really well.
- The button clicks.
- The checkout fires.
- The upload form accepts files.
- The dashboard loads.
- The demo looks great.
But under the hood?
- Maybe auth is duct-taped together.
- Maybe authorization barely exists.
- Maybe admin routes are exposed.
- Maybe secrets are sitting in the wrong place.
- Maybe every dependency was blindly accepted.
- Maybe the upload path is terrifying.
- Maybe the app has no logs.
- Maybe database permissions are too broad.
- Maybe the backup plan is "hope."
The product surface can feel done while the system underneath is still a liability. This is not a knock on the founder, but most of this stuff is invisible until you know what to look for.
It is also not a knock on AI. It did exactly what it was asked to do: make the thing work enough to keep moving.
The problem is when nobody steps back and asks whether the thing is safe enough to put in front of users. That is a judgment call, and it is not one an AI tool can make.
What a Developer Review Should Actually Cover
This does not need to be some giant formal audit for every tiny prototype. It just needs to be someone who knows what they are looking at to answer a few uncomfortable questions.
If you are still testing a fake-door landing page, a local demo, or an internal throwaway workflow, keep moving.
But if the thing touches real users, accounts, money, customer data, files, internal business operations, or anything someone would be upset to see leaked or broken, budget for a practical engineering review.
At minimum, someone should review:
- authentication and session handling
- authorization and role boundaries
- environment variables and secrets
- dependency risk and package scripts
- CI/CD configuration and deploy permissions
- database access rules
- file upload paths and storage permissions
- payment and webhook handling
- logging and error reporting
- backup and restore paths
- admin access
- obvious abuse cases
- what happens if the thing gets popular or attacked
That list is not glamorous.
It is also the difference between "AI helped me build this" and "this is safe enough to operate."
You'll Pay for This One Way Or Another
You do not need a committee.
You do not need a 90-page architecture document.
You do not need to turn your scrappy product into a procurement exercise.
You need someone who knows what they are looking at to answer a few uncomfortable questions:
- What can this app access?
- What can users do that they should not be able to do?
- Where are the secrets?
- What happens when a dependency gets compromised?
- What happens when an upload is malicious?
- What happens when a webhook is replayed?
- What happens when a user should lose access?
- What happens when the app goes down?
- What happens when you need to recover data?
Those questions are boring until they are expensive.
And they get expensive fast.
Vibe Coding Is Not the Problem
We are not anti-vibe-coding.
We think founders should absolutely use AI to prototype, explore, test ideas, and get unstuck. More people being able to make software is a good thing.
The problem is shipping something you do not understand just because the demo works.
AI lowers the cost of getting from idea to prototype. It does not remove the need for engineering judgment when that prototype becomes a product.
So if you are building with AI and getting ready to put real users, customer data, payments, file uploads, or internal operations on top of it, add a developer review to the budget.
Not a rebuild or a six-month architecture meeting. Just a practical engineering pass on the parts that can hurt you later.
"Works on my machine" and "safe enough to ship" are not the same thing.
If you built something with AI and are getting ready to put real users, customer data, payments, or internal operations on it, House of Giants can help review the system before you ship. No bullshit. Just a practical engineering pass on the parts that can hurt you later.