I learned a hard lesson after building my website with AI.
At first, it felt like a win. I used ChatGPT to create the page structure, write frontend code, fix styling, and help with basic backend logic. The site loaded. The forms worked. The design looked decent. From the outside, it felt like I had saved time.
Then I looked closer and realized something uncomfortable.
I had built fast, but I had not built safely.
That was the moment I thought: I probably should have worked with an experienced team instead of treating AI-generated code like production-ready software.
AI was not the problem. My trust in unreviewed AI code was.
For my next project, I am still using AI for ideas, drafts, and prototyping. But for the actual build, I would rather work with a team like Quokka Labs because custom development is not just about getting something live. It is about making sure the product is secure, scalable, and maintainable from day one.
The Website Worked, But That Was Not Enough
This was my first mistake.
I assumed “working” meant “safe.”
The AI-generated code passed the basic checks:
- Pages rendered
- Buttons worked
- Forms submitted
- Layout looked clean
- Deployment was quick
But I had not properly checked:
- Exposed config files
- Weak form validation
- Public repo visibility
- Dependency risks
- Poor access control
- Messy backend assumptions
That is the trap with vibe coding.
It gives you speed before it gives you understanding.
The Real Issue Was Ownership
The code going public was not just an AI problem.
It was an ownership problem.
I had copied, adjusted, and deployed code I did not fully understand. Some files should have been reviewed more carefully. Some values should never have been anywhere near the codebase. Some logic looked fine locally but was not ready for the real world.
That is where AI-generated code becomes risky.
ChatGPT can write code quickly, but it does not automatically understand your business risk, deployment environment, private data, or security requirements. It will not stop you from making a bad release decision.
Once you ship the code, it is yours.
What I Should Have Checked Before Launch
Looking back, I should have slowed down before publishing anything.
Here is what I would check now before deploying AI-generated code:
- Review every file before pushing: Not just the main files. Config files, logs, test files, and unused drafts can expose more than you expect.
- Keep secrets out of the codebase: API keys, database URLs, tokens, and private credentials should never be placed directly in code.
- Validate every input: A form that submits is not the same as a form that is safe.
- Check dependencies: AI may suggest packages that work, but that does not mean they are secure, maintained, or necessary.
- Review access control: If your app has user accounts, dashboards, payments, or private data, access logic cannot be casual.
Why I Would Involve An Agency Next Time
For experiments, AI is great.
For anything serious, I would not rely on raw AI-generated code alone.
A good custom AI app development company does more than write code. It helps answer the questions AI often skips:
- Is this secure?
- Is this scalable?
- Can another developer maintain it?
- Are we protecting user data?
- Can this handle real users?
- Are the architecture choices right?
That is the difference between building fast and building responsibly.
How I Will Use AI Differently Now
I am not done with AI.
I will still use it for:
- Brainstorming
- Rough prototypes
- Documentation
- Test case ideas
- Early UI drafts
But I will not let it own:
- Architecture
- Security decisions
- Backend logic
- Production deployment
- Scalability planning
- User data protection
Those need real engineering judgment.
Final Thought
I do not regret using ChatGPT to build.
I regret treating the output like it was ready.
AI-generated code can speed up early work, but once something goes public, the standard changes. You need review, structure, security, and accountability.
Next time, I will still use AI.
But I will not ship without real engineering review.
Have you ever shipped AI-generated code and later found something risky in it?
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