Three out of four AI-generated code snippets contain at least one security vulnerability that could compromise your entire application. That's the reality facing developers who jump headfirst into vibe coding without understanding the risks. While AI-powered development tools promise faster builds and smoother workflows, they're creating a dangerous blind spot for app creators who don't know what to look for.
Vibe coding—the practice of using AI to generate large portions of your app's codebase—has exploded in popularity recently. And honestly, I can see why. Who wouldn't want to cut development time in half? But here's what most people don't realise: that speed comes with hidden costs that can destroy your app's future.
The biggest mistake I see is developers treating AI-generated code like it's been written by a senior developer with years of experience, when in reality it's more like having an intern who's read every programming book but never worked on a real project
The problems aren't just technical—they're business-threatening. Security vulnerabilities, maintenance nightmares, performance issues, and team collaboration problems are just the beginning. This guide will walk you through the real risks of vibe coding, so you can make informed decisions about your app's development approach.
Understanding Vibe Coding and Its Appeal
Vibe coding—sometimes called prompt-driven development or AI-assisted coding—has become incredibly popular with developers and businesses alike. The concept is simple: you describe what you want your app to do using natural language, and AI tools generate the code for you. No need to spend months learning programming languages or hiring expensive developers.
I've watched clients' eyes light up when they discover they can build an app by simply typing "create a fitness tracker that counts steps and shows calories burned" into an AI tool. The appeal is obvious. You get working code in minutes rather than weeks, and the barrier to entry has never been lower.
Why Everyone's Talking About It
The main reasons people are drawn to vibe coding include:
- Speed of development—prototypes can be built in hours
- Lower upfront costs compared to hiring developers
- No technical knowledge required to get started
- Ability to iterate quickly on ideas
- Democratisation of app development
But here's the thing—what looks like a shortcut to success can actually lead you down a path filled with unexpected problems. The code might work initially, but that doesn't mean it's ready for real users or capable of growing with your business.
Security Vulnerabilities in AI-Generated Code
When I first started seeing developers use AI tools to write code, I'll admit I was impressed by the speed. But then I started looking closer at what was actually being produced—and that's where the problems begin. AI-generated code often contains security holes that could put your entire app at risk.
The biggest issue is that AI doesn't understand context the way humans do. It might generate code that looks perfectly fine on the surface but includes outdated security practices or leaves sensitive data exposed. I've seen AI create database connections without proper encryption, generate authentication systems with weak password requirements, and even produce code that's vulnerable to common attacks like SQL injection.
Common Security Risks in AI Code
AI tools frequently produce code that handles user input without proper validation—this is a hacker's dream. They might also generate API endpoints that don't check user permissions properly, or create data storage solutions that don't follow current security standards. The scary part is that these vulnerabilities aren't obvious; they're hidden beneath code that appears to work correctly.
Always have a security expert review any AI-generated code before it goes into production. What seems functional might be dangerously insecure.
Your app's security isn't something to gamble with. One breach could destroy user trust and your reputation forever.
Code Quality and Maintenance Problems
I'll be honest with you—one of the biggest headaches I see with AI-generated code is the quality. Sure, it might work when you first run it, but that's only half the battle. The real problems start showing up weeks or months later when you need to fix bugs or add new features.
AI tools like vibe coding often produce code that looks fine on the surface but lacks the structure and clarity that human developers rely on. Variables get confusing names, functions do too many things at once, and there's rarely any helpful comments explaining what's happening. It's like getting a recipe that works but has no instructions—you can follow it once, but good luck modifying it later.
When Things Go Wrong
The maintenance nightmare really kicks in when bugs appear. And they will appear—every app has them. With human-written code, you can usually trace through the logic and understand what went wrong. But AI-generated code? It's often a tangled mess that's difficult to debug. You end up spending more time trying to understand what the AI was thinking than actually fixing the problem.
Plus, if you want to add new features or make changes, you're basically starting from scratch because the existing code is so hard to work with.
Performance and Efficiency Concerns
When I'm working with clients who've experimented with vibe coding, one of the biggest red flags I see is the performance issues that crop up later. AI-generated code often takes the safest, most generic approach to solving problems—which sounds good in theory, but can lead to some serious performance headaches down the line.
The main issue is that AI doesn't understand your specific use case or user patterns. It might generate code that works perfectly for a handful of users but completely falls apart when you hit 10,000 concurrent users. I've seen apps that were lightning fast during development suddenly become sluggish beasts once they went live.
Memory Management Problems
Vibe coding tools aren't great at optimising memory usage. They tend to create more objects than necessary, keep references longer than needed, and generally write code that's wasteful with system resources. This is particularly problematic on mobile devices where memory is limited.
The AI might solve your immediate problem, but it's not thinking about how that solution will scale or perform under real-world conditions
Battery drain is another major concern. AI-generated code often lacks the nuanced optimisations that experienced developers would naturally include—things like reducing unnecessary network calls, optimising loops, or implementing proper caching strategies. Your users will notice when their battery starts dying faster after installing your app.
Team Collaboration and Knowledge Transfer Issues
Here's something that keeps me up at night—and I'm not being dramatic here. When your team uses vibe coding to build parts of your app, you're creating a knowledge gap that can seriously hurt your project down the line. Think about it: if an AI writes chunks of your code, who on your team actually understands how it works?
I've seen this happen more times than I'd like to admit. A developer uses an AI tool to generate some complex functionality, it works brilliantly, and everyone moves on. But then six months later when you need to modify that feature or fix a bug, nobody can figure out what the code is actually doing. The original developer has moved on to another project, and the new person is left scratching their head.
The Documentation Problem
AI-generated code often comes with minimal or confusing comments. This makes it really hard for team members to understand the logic behind the code. When you're working in a team, clear documentation isn't just nice to have—it's absolutely necessary for long-term success.
Skills Development Concerns
There's another issue here that's worth mentioning. When junior developers rely too heavily on AI-generated code, they miss out on learning opportunities. They might not develop the problem-solving skills they need to become truly skilled developers.
- Code reviews become more difficult when reviewers don't understand AI-generated logic
- Debugging sessions take longer because the code structure might be unfamiliar
- Knowledge transfer between team members becomes nearly impossible
- New team members struggle to get up to speed on existing codebases
Long-term Support and Scalability Risks
Here's something that keeps me up at night when I think about AI-generated code—what happens when your app needs to grow? I've watched plenty of projects start small and suddenly need to handle ten times more users, or require completely new features that weren't part of the original plan. This is where vibe coding can really bite you.
The problem isn't just about making your app bigger; it's about making it bigger without breaking everything. AI-generated code often creates solutions that work perfectly for the specific problem it was asked to solve, but it doesn't think about what might happen six months down the line. When your startup suddenly gets featured in a major publication and your user base explodes overnight, you need code that can handle that pressure.
The Hidden Costs of AI Development
From my experience, the real costs of using AI for app development show up much later than you'd expect. Here's what typically happens:
- Code becomes harder to modify as requirements change
- Performance issues emerge under heavy load
- Integration with new technologies becomes complicated
- Bug fixes take longer because the code structure isn't intuitive
- Finding developers who can work with AI-generated code proves difficult
The scariest part? These scalability risks compound over time. What starts as a small performance hiccup can turn into a complete system overhaul when your app reaches a certain size. I've seen companies spend more money fixing AI-generated code than they would have spent building it properly from scratch.
Always plan for your app to be at least 10 times bigger than you think it needs to be—AI-generated code rarely makes this kind of forward-thinking easy.
Conclusion
After working with countless development teams over the years, I've seen what happens when shortcuts seem too good to be true—and vibe coding is no exception. The risks we've covered aren't just theoretical problems; they're real challenges that can seriously impact your app's success.
Security vulnerabilities in AI-generated code can leave your users' data exposed. Poor code quality makes your app harder to maintain and more expensive to fix. Performance issues frustrate users and hurt your app store ratings. When your team can't understand or work with the code, you're stuck depending on AI tools that might not always be available or reliable.
Look, I'm not saying vibe coding is always wrong—there are situations where it might work for quick prototypes or simple features. But for anything you're planning to scale, maintain long-term, or trust with user data, you need to be very careful. The money you save upfront often costs much more down the line.
My advice? If you're serious about building a quality app that'll grow with your business, invest in proper development practices. Work with experienced developers who understand your code inside and out. Your future self will thank you when you're not dealing with security breaches or trying to untangle mysterious code nobody understands.
