The Call That Started It All

It started with a casual message from a friend:

“Hey, we have a client who has an AI-powered app which is in production, used by end users, and he wants to now upgrade his code and get to next level. Would you like to be part of the team that helps him?”

Always been enthusiastic about software in general, I said, “Yes, let’s talk and see what do we need to solve.”
Especially in today’s world, I’m always looking forward to seeing use cases where people are using AI to solve real-world problems.

So we got on a call, and for the first 20 minutes, I heard things that explained the whole situation.

• Client loves building startups

• Client loves AI

• Client is a vibe coder and has successfully launched a product and is generating revenue

• He only has one stage, and every time he wants to deploy a new version, he is sending messages to all his clients that there can be downtime.

In all honesty, I was impressed. Because well, I’ve seen a lot of vibe coders who try to build a nice product but fail to get it to production, kudos to the guy, he actually set up everything and was serving the needs of the customers.

But pain points were there, like:
“How can I improve my token usage?”
(It was an AI wrapper, prompt engineering and stuff there was no RAG pipeline or agents.)

I got access to the repository, cloned it expecting a typical early stage setup something scrappy but serviceable.

BUT

What I saw instead stopped me cold.

800 Lines of Chaos

The first file I opened had over 800 lines of code.
A single component was doing everything UI rendering, API calls, data transformations, even business logic, all bundled in one place.

Two folders: Backend and Frontend.

Everywhere I looked, there were:

• Functions repeating the same logic over and over

• Conditional chains stretching dozens of lines long.

• State changes and API requests all wired together with no separation.

It wasn’t careless work.
It was passionate, fast-paced “get it done” coding, what I call vibe coding.
When you’re deep in that flow, everything feels possible. You’re building features at light speed, and it works… until it doesn’t.

There Are Times When Impressive Leads to Impractical

On the surface, the app was amazing underneath, it was an over-engineered monster eating up resources.

I did a quick check to see how well the app would scale.
Did some load testing, and I could tell that this wasn’t going to scale.
AI calls would start blocking soon, and bucket size would keep increasing with each call.

Full disclosure on every call, the backend was uploading a new “cache file.”
Not sure how it was a cache file if it was recached on every call.
Imagine writing something so you can use a cached version but instead of using the cache, you use the real version and keep updating the cache.
And no, if there was an error, it wasn’t using the cached version either.

But enough ranting.
We looked at the problem, and our job was to provide a solution while making sure that end customers were not affected.

We Made a Plan

We wrote a report out for the client:

• Environment Separation: Dev, Staging, Production

• CI/CD Pipelines: Automated testing and deploys (we used Bitbucket actions)

• Refactoring: Breaking down those 800-line monsters into small, reusable modules

• Caching and API Optimization: Reducing redundant calls

• Security: Yes, there were hard-coded keys in the codebase. Yes, anyone could access cloud functions

• Monitoring: To track cost spikes and performance drops in real-time

We did not rewrite things we stabilized.
We made sure that the customer spent less money on infrastructure, spent more time on creating real business value, could scale up easily, and most importantly, had a pipeline of work he could trust and a product his customers could rely upon.

What did We Learn?

This actually changed the way I looked at MVPs.

Yes, you can prototype easily.
Yes, you can generate good ARR.
Yes, you can create an impact.

But the real challenge begins after that, and if you’re not ready for it, you only have a recipe for disaster in your bucket.

Key Takeaways

• Speed is good, but structure is important.

• Complexity and capability are two different things.

• Always think of your codebase like a plug-and-play item. Your product will outgrow the platform, and you will have to port out of that platform always plan for that.

• Every line of code is a cost that will pile up.

• Last but not least, documenting your solution isn’t optional.

Final Thoughts

Vibe coding is not bad it actually helps you test your idea real quick, see product-market fit, and move fast.
But once it validates, you need to stay alive as well and you need to scale.
There has to be security in place.
Customer is always first, and you need to protect your customer data at all costs.

The real challenge begins when you want to have more customers without exposing your data online, without breaking stuff.

Your MVP is your foundation, don’t let it break.

⚡ Want to Avoid These Pitfalls?

Fortunately, this is exactly what we do at ProdifyTech. helping indie founders and teams scale their products without chaos or technical debt.
Get in touch today.