Vibe coding feels almost magical, and that is exactly the appeal.
There is a certain romance around vibe coding right now: 'just talk to an AI and ship a SaaS'. Landing page, database, deploy, done. And honestly, that is impressive.
It has never been easier to turn an idea into a working MVP in just a few days. For prototypes, internal tools, or quick validation, this is a real game changer.
The risk starts when you deploy what you do not fully understand.
But that is also where the problem starts. More and more people deploy software they do not fully understand, and sometimes you only notice that when the bill arrives.
We found a Reddit post from someone who accidentally generated 16 billion Cloudflare Durable Object writes. No hack. No attack. Just a mistake in an AI-generated flow. The outcome was a massive cloud bill and a system spiraling out of control.
Read the Reddit post here: Reddit
AI can generate code that works, but it often misses production constraints.
That is exactly why vibe coding can get risky. AI is extremely good at producing code that works, but it is far less reliable at producing code that is scalable, secure, and cost-efficient. You do not feel that difference in a demo with ten users. You feel it when your application is live.
Suddenly there is an infinite loop hammering your database, an API call gets executed thousands of times per minute, or worse: sensitive user data is exposed because security was postponed for later.
Usage-based billing makes small architectural mistakes expensive.
The danger is not AI itself. The danger is skipping fundamentals. If you do not understand what you deploy, you cannot realistically estimate the impact on privacy, security, scalability, cloud cost, and performance. Cloud cost is often the most underestimated factor.
Many modern SaaS stacks bill by usage: every write, every function call, every database operation, every AI request. A small architectural mistake can literally cost thousands of euros per day without you noticing immediately.
AI accelerates development, but responsibility remains human.
Does that mean vibe coding is bad? No. We actually think it is one of the most interesting developments right now. The speed at which you can test ideas is absurdly valuable. Building MVPs becomes cheaper. Experimentation becomes easier. Small teams can move much faster.
But there is a big difference between building a working demo and building and operating a production-grade SaaS.
The latter still requires experience, architecture choices, security knowledge, and control over your infrastructure. AI accelerates development, but it does not replace responsibility. That is probably the most important lesson of vibe coding.
Luckily, situations like this are often preventable. Not by using less AI, but by developing smarter. Think rate limiting, budget alerts, monitoring, logging, usage caps, and clear limits on API calls or database writes.
Most importantly: keep a critical eye on what AI generates before you ship it. AI can accelerate development massively, but production-grade software still requires human oversight, technical knowledge, and responsibility. That combination ultimately determines whether you build a smart SaaS or learn an expensive lesson.