I've seen plenty of solutions that were supposed to exist only for a while. A small script, a simple form, an Excel spreadsheet, a quick integration, a POC. They were usually created for the same reason: to test something quickly, solve a specific problem or prove that an idea could work. And very often, that was the right decision.
The problem started later. Someone began using it. Then someone else. Real data appeared, followed by the first integration, a report and eventually an entire business process. At some point, something that was never meant to become a product became part of the organization's daily operations.
Today, vibe coding can make that happen much faster.
When The Business Can Build The POC
Just a few years ago, building a meaningful proof of concept usually required developers. You needed an environment, frontend, backend, business logic and sometimes integrations. Today, someone without a technical background can use AI to build a working prototype in days or weeks.
I recently saw exactly that happen. A practically non-technical person built an entire application POC on their own. It had a frontend, logic and actual flows you could walk through to understand how the future product might work. Not long ago, something similar would have required at least a small development team. This time, one person did it.
And that's not a problem. Quite the opposite. It's probably one of the best applications of vibe coding I've seen.
A POC Can Say More Than Documentation
One of the recurring problems in software projects has always been translating ideas between people. The business writes requirements, developers try to understand them, mockups and diagrams appear, documents are created, and eventually the implementation reveals that both sides had imagined something slightly different.
A working prototype changes that conversation. Instead of explaining "the user should be able to do X here," you can simply show the screen and say, "I mean something like this." A POC can become a living product specification. You can validate the UX, process, assumptions and logic, and talk to users before the organization invests months of development effort.
That's incredibly valuable.
Then Someone Asks One Dangerous Question
At some point, someone looks at the working prototype and asks: "If it already works, how long can it really take to put it into production?"
This is where two very different things become easy to confuse: something that works and something you can responsibly operate every day. To the user, the difference can be almost invisible. The button works. Data gets saved. The screens look good. The entire process can be completed.
From a product perspective, it can look 80% finished. From an engineering perspective, you may have completed only 20% of the work.
Everything You Don't See In The Demo
A demo doesn't show what happens when the database stops responding. It doesn't show how the system behaves with ten thousand users, who has access to the data or whether lost information can be recovered.
You don't see monitoring, logs, alerts, deployment processes, regression tests, error handling, auditing, security, privacy or ownership. You don't see who gets the call when something breaks on Sunday evening.
Almost none of that is visible during a POC presentation. Yet those things often make up most of the difference between a prototype and a product.
The First Real User Changes Everything
A temporary solution is cheap only as long as it remains temporary. A POC is simple only as long as it remains a POC.
The problem begins when the first real user arrives. Then the second. A customer asks for a report. Someone adds an integration. Someone starts making business decisions based on data from the system.
And then something important appears: dependency. The organization starts relying on the solution. Once the business depends on it, how it was originally created becomes irrelevant.
It could be a system designed by a twenty-person team, a script written over a weekend or a vibe-coded POC. If a business process stops when the system stops, it has become production software — whether anyone formally made that decision or not.
Vibe Coding Didn't Create This Problem
This mechanism existed long before AI. An Excel spreadsheet intended to survive for a month could still be running a critical process five years later. A script written "just for now" became part of monthly financial processing. A temporary API gradually gained more and more consumers.
AI has simply reduced the cost of creating these solutions dramatically. We can build prototypes faster than ever before, which also means we can accidentally turn them into production faster than ever before.
Don't Throw The POC Away
I don't think the right answer is to throw everything away and start again from an empty repository. That would waste a significant part of the value already created.
A working POC contains knowledge. It shows the process, assumptions, UX decisions and how users should move through the product. It can become one of the best sources of truth when building the production version. We just need to stop treating it as the finished product.
So the question isn't: "Can we put this POC into production?"
A more interesting question is: "How can we use what the POC taught us to build the production solution faster and smarter?"
That's a very different conversation.
The Line Is Becoming Harder To See
This is where vibe coding changes something fundamental. Prototypes used to look like prototypes: ugly interfaces, limited functionality and plenty of manual work. Everyone knew they were demonstrations.
Today, an AI-generated prototype can look like a real product. It can have a polished frontend, authentication, a database, integrations and even tests. The visual distinction is disappearing.
The more a POC looks like a product, the harder it becomes to explain why it still isn't one.
Final Thoughts
Vibe coding can fundamentally change how we approach discovery. It allows people who have never programmed before to test ideas themselves and turn them into something others can actually experience.
That's enormously valuable. But it comes with a new responsibility. We need to recognize the moment when an experiment starts becoming a dependency.
Because from that moment, the question is no longer: "Does it work?"
The question becomes: "Are we ready for someone to actually depend on it?"
The most dangerous prototype is the one that works well enough to become production by accident.