When AI Makes You Feel Like a Genius (But Builds You a Time Bomb)
“I built and shipped a working SaaS MVP in 72 hours with zero dev experience. AI is insane.” 👀
I’ve seen that exact sentiment more times than I can count. In so many fields, design, programming, legal…
The real problem? People believe it.
Founders are spinning up full app prototypes using ChatGPT, Replit, Figma plugins, and low-code tools. They look slick. They demo well. Investors get excited. The illusion is complete.
Until it breaks. Or scales. Or hits real users. And then the wheels come off.
AI Makes Shipping Fast. That’s the Problem.
AI is lowering the bar to creation, but it’s also making people think they are experts when they are absolutely not.
Shipping something that “works” is easy. But creating something that works WELL, that scales, that doesn’t cost you three rewrites and a lawsuit? That still takes expertise.
The Dunning-Kruger Effect is in full swing. People with no real dev background are suddenly confident they’ve built something meaningful. But confidence isn’t competence.
Apps aren’t just a front-end. They’re systems. Systems that need to account for:
- Security
- Data integrity
- Scalability
- Error handling
- Codebase maintainability
AI doesn’t do this for you. And if you don’t know to ask, you won’t know it’s missing.
The Dunning-Kruger Stack
Here’s what most of these AI-fueled MVPs actually look like:
- Frontend: Copied from ChatGPT with no component reusability
- Backend: Jammed into Firebase or Replit with no structure
- Auth: Plugged in from a Discord thread
- Data Model: Nonexistent or brittle
- DevOps: huh?
- Testing: “It worked when I clicked it”
- Security: Cross your fingers
It’s a house of cards. And yet people are treating it like a product launch.
The Real Cost Comes Later
Early success masks future disaster.
Founders build fast, raise on a shiny demo, and then hit the wall when they try to scale. Or fix bugs. Or integrate anything.
That’s when they call someone like me. And that’s when they find out:
- The data model is unfixable without starting over
- The MVP has security holes big enough to drive a truck through
- None of it can be tested or deployed in production
- It will cost more to fix than rebuild
You didn’t build an MVP. You built a demo.
Why Non-Technical Founders Are the Most at Risk
You can’t see the problem because it looks finished. But the rot is under the surface.
Ask yourself:
- Do I actually understand what this app is doing behind the scenes?
- Is there anyone on my team who can evaluate the quality of what AI gave us?
- What will this cost to maintain, secure, or scale?
If you can’t answer confidently, you’re gambling with your product.
How to Use AI Without Getting Burned
AI is a phenomenal tool for velocity. But only in the right hands.
Here’s how to use it responsibly:
- Treat AI as a co-pilot, not a substitute
- Pair output with experienced dev review
- Always build in validation, testing, and basic security from day one
- Know what you don’t know… and hire for it
Fast is fine. Reckless is not.
AI Is Fuel. But What Are You Driving?
Give AI to a skilled builder, and you get leverage. Give it to someone clueless, and you get overconfident garbage with a UI.
The Dunning-Kruger wave is peaking. Founders riding it will learn the hard way that software doesn’t care how confident you are.
Want a second opinion on your AI-built app before you raise, scale, or ship? Let’s talk. One conversation now could save six figures later.
