Vibecoding looks easy. You describe what you want, AI writes it, and you ship. Except your first project usually crashes before it sees a user.
At Inithouse, a studio shipping a growing portfolio of products in parallel, we've reviewed hundreds of vibecoded projects through our audit tool at auditvibecoding.com. The same five mistakes show up in roughly 90% of them.
Here's what goes wrong, and how to fix it.
1. Starting with a complex app instead of a simple MVP
Your first vibecoded project should not be a SaaS with auth, payments, and a dashboard. AI tools like Lovable and Cursor are powerful, but they produce fragile code when the scope is too wide.
Fix: First project = one screen, one feature, no auth. Build a calculator, a landing page, a single-purpose tool. Ship it. Then go bigger.
We learned this building Vibe Coderi, our Czech vibecoding platform. Most learners who start simple end up shipping. Those who start with "my dream app" end up debugging for weeks.
2. Not reading the generated code
AI wrote it. You pasted it. It works. Why read it?
Because it will break. And when it does, you'll need to understand what happened. Vibecoding sits between no-code and traditional development: AI writes it, but you own it.
Fix: After every generation, spend 5 minutes reading the output. You don't need to understand every line. Follow the structure, the data flow, the dependencies.
3. Ignoring error messages and just re-prompting
This one is universal. The build fails, the console screams red, and the vibecoder's instinct is to paste the same prompt again, maybe with "fix the error" appended.
Fix: Copy the full error message. Read it. Then provide it to the AI with context: what you were trying to do, what happened, and the exact error text. This triples the chance of a correct fix on the first try.
4. No version control from day one
We've seen projects where the developer built for three days without a single commit. Then one bad prompt wiped a working feature, and there was no way back.
Fix: git init before your first prompt. Commit after every working state. It takes 30 seconds per commit and saves hours of pain.
5. Building without a clear spec
"Make me an app that does X" is not a spec. AI tools perform dramatically better when they receive structured input: what the app does, who uses it, what the screens look like, what data it stores.
Fix: Write a one-page brief before you start prompting. We use simple briefs for every product in our portfolio, and the output quality difference is measurable.
These patterns repeat across everything we build at Inithouse, a studio running a growing portfolio of AI-powered products. Whether we're building Audit Vibe Coding, a professional audit tool for AI-generated projects, or running courses at Vibe Coderi, the lesson is the same: vibecoding rewards preparation, not speed.
Start small. Read the code. Commit often. Spec before you prompt.
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