We Audited 12 Vibe-Coded Apps. Here's What We Found

Over the last 3 months, 12 founders booked calls with us. Different stories, same root cause.

Some had paying users and a quiet panic about how flimsy the product felt. Some had launched and gotten almost no signups. Some had users sign up, click around for a minute, and never come back. A few were losing money on Stripe in ways they did not fully understand.

All of them had built their first version with AI: Lovable, Bolt, Cursor, v0, or Replit. The products looked good. The screens were polished. Nothing was on fire in the way you would expect.

When we looked closer, the same 6 issues kept showing up. Some are about the product itself. Some are about the user. Some are about the technology underneath. None of them are obvious until they cost you a customer.

They Built Something Nobody Asked For

The most painful version of this. The product works. The screens look great. Nobody wants to use it.

What we keep seeing

Founders fall in love with their idea. AI tools make it real before the idea has been tested with anyone. By the time the product is live, the founder has spent 2 months and a few thousand dollars on something that solves a problem nobody else recognizes.

The signal is usually launch day. The post goes out on social. A few friends sign up. After that, silence. The founder concludes they need better marketing. They do not. They built something nobody was waiting for.

Why AI tools made this worse

The thing that used to be slow about building products has changed. Coding once took months. AI compressed that to days. But finding the people who want to pay for what you build, getting them to commit money, learning what they would actually use, none of that got faster. AI tools have not replaced market research. They have just made it easier to skip.

The fix

Talk to 20 people in your target market before you build anything. Not "show them a demo." Ask them about their problem in their own words. If you keep hearing the same complaint described in specific terms, you have something worth building. If they are polite but vague, you do not.

Real Users Cannot Figure Out How to Use It

The second most common issue, and the one founders are most surprised by.

What we keep seeing

Apps with 12 buttons on the dashboard, 4 of which do almost the same thing. Sign-up flows that take 8 steps when they could take 3. Important actions buried 2 clicks deep in menus. No clear "this is the thing you do next" anywhere on the screen.

When we put real users in front of these products, the same scene plays out every time. The user opens the app. They look around for 30 seconds. They click 2 things, get confused, and quit. The founder watches and says, "wait, you did not see the [feature they spent a week building]?" The user did not. It was on the second page of a settings menu.

Why AI tools generate this

AI tools optimize for screens that look polished in a screenshot. They do not optimize for screens a stranger can use without help. The output looks good. The product is hard to use. There is very little overlap between "looks good" and "is intuitive," and AI tools have only solved the first one.

The fix

Once a week, sit with someone who has never used your product. Watch them try to do the main thing your product is for. Do not help them. Do not explain anything. Write down everywhere they get stuck. Fix those things first, before the next feature. The product will stay simple for longer than feels comfortable. It will also stay usable.

Anyone Could Become an Admin in 5 Minutes

11 of 12 products had login systems that looked legitimate and were not.

What we keep seeing

"Admin" access controlled by checking whether a user's email matches a single specific address. Anyone who guesses the address gets admin access. Login systems that do not lock out an attacker after 1,000 failed attempts. Password resets that email the new password in plain text. Database security rules that are either turned off or written wrong, so any logged-in user can see every other user's data with 2 minutes and a browser.

One founder found out about this when a customer emailed asking why they could see someone else's billing information. Another founder discovered it when their entire user list ended up posted on Reddit.

Why this happens

AI tools generate the shape of security. A login form. A signup flow. A password reset endpoint. They do not, by default, generate the boring parts that make security actually work. The product looks like it has authentication. It does not have authentication.

What this costs you

A data leak from a small startup is not a small story when the customer involved is upset enough to post about it. It is also not a small invoice from your insurance company. It is the kind of thing that ends a startup before it has the chance to grow.

You Are Losing Money You Do Not Know About

8 of 12 had Stripe integrated. 6 of those 8 had at least one bug in the integration the founder did not know about.

What we keep seeing

Customers charged twice when they refresh at the wrong moment. "Successful" payments that never made it to the founder's account because something failed silently between Stripe and the app. Subscription cancellations that update the database but not Stripe, so customers keep getting billed for months and eventually file chargebacks. Payment confirmations the app accepts without verifying they actually came from Stripe, which means anyone who knows what to send can mark themselves as paid.

One founder had been paying Stripe fees on $4,000 of "successful" transactions that had actually failed. He thought his sales were soft. They were not. The receipts were lying to him.

Why this happens

Stripe is one of the most well-documented services on the internet. AI tools can wire up the basics in 2 minutes. The difference between "Stripe code that runs" and "Stripe code that handles real money in production" is a level of detail that only shows up after you have shipped payments before. AI has not shipped payments before. It has read about it.

What this costs you

Money you would swear you earned. Customer trust when refunds get messy. Hours on the phone with Stripe support and unhappy customers. Most founders find out about it when their bank balance does not match their dashboard.

The Product Is Broken on Mobile

About 65% of traffic to early-stage products comes from mobile in 2026. 8 of 12 apps we audited were unusable on a phone.

What we keep seeing

Pop-ups that fall off the bottom of the screen with no way to scroll. Buttons hidden behind the iOS Safari address bar. Forms where the keyboard covers the input you are typing into. Tables that simply run off the side of the screen. Touch targets so small that hitting the right one is luck.

The funny part: the founder always knows their app exists on mobile. They have checked. They opened it on their phone, the homepage loaded, and they assumed the rest worked. Most of the time, the rest does not.

Why this happens

AI tools generate desktop-first because that is what the founder is staring at all day. The founder builds on a laptop, demos on a laptop, and tests on a laptop. Mobile gets a cursory check, usually of the homepage. The actual workflow, the part where the user is supposed to convert, almost never gets tested on a real phone with real fingers.

The fix

Pick up your phone. Sign up to your own product as if you have never seen it. Get all the way through to the most important action. Note every place something looked broken or hard. Fix those before the next feature.

Every Time You Change Something, Something Else Breaks

12 of 12 products had the same problem. The product had become fragile. Every change was a gamble.

What we keep seeing

The founder asks the AI to add a small feature. The AI writes new code. Everything looks fine. 3 days later, an unrelated part of the product stops working. The founder asks the AI to fix it. The AI generates a fix. Now something else is broken.

By month 3, the founder is afraid to ship anything. New features take a week of fighting the product. Every change has a 30% chance of breaking something that worked yesterday.

Why this happens

AI tools generate code that works in isolation. They do not always check that the new code plays nicely with the rest of the product. There is no automated check running to catch breakage. There is no system in place to alert you when something silently breaks in front of customers. By the time you notice, a real customer has already noticed first.

What this costs you

The most expensive thing is not the bugs. It is the fear. A product that punishes the founder for shipping is a product that stops getting better. You stop iterating. Customers stop seeing improvements. The product slowly loses ground to anyone willing to ship.

What This Costs to Fix

The honest answer: between $20,000 and $60,000, depending on how far the product has drifted.

A typical rebuild for a vibe-coded app at the "I have users and something is wrong" stage takes us 4 to 6 weeks. We work through the full list of issues. We talk to your actual users to understand what is working and what is not. We rebuild the parts of the product that confuse people. We replace the security and payment plumbing. We make sure the product works on a phone. We add the systems that catch problems before customers do.

The original product features stay. The design usually survives. The brand stays the same. What changes is everything underneath that you, the founder, cannot see.

That number is more than what most founders spent on the original build. It is also less than the cost of refunding 3 months of double-charged subscriptions, or losing your customer list in a data leak, or watching the product drift while you are afraid to touch it.

The "rebuild tax" is real. It is also predictable. Plan for it.

When Vibe Coding Is The Right Tool

We are not against AI tools. We use them ourselves, every day.

What they are good for

Validating a rough idea in front of real users in 2 days. Building a clickable prototype to show investors. Replacing a Figma mockup with something interactive. Testing a landing page hypothesis. Building internal tools that 10 employees will use and that will be replaced when the company grows.

For all of these, Lovable, Bolt, Cursor, and v0 are extraordinary. They compress months of work into hours.

Where they break

The moment your product handles money, personal data, regulated information, or more than a few hundred users, the gap between "demo-ready" and "production-ready" widens fast. That gap is where most apps go to die.

The founders we audit who are happiest are the ones who used AI to validate, then brought in real engineering before they took the first dollar. The ones who are unhappiest are the ones who took dollars first, then discovered what they had built.

A Self-Audit You Can Run This Weekend

Before you take your 10th paying customer, run this on your own product. None of it requires technical skills.

The market check. How many people who signed up last month still use the product a week later? If the answer is fewer than half, your problem is not the product. It is that the product solves something people did not actually want.

The stranger test. Find someone who has never seen your product. A friend, a partner, anyone outside the build. Sit them down for 2 minutes and ask them to do the main thing the product is for. Do not help. Do not explain. Watch what happens. If they get stuck, your product is harder to use than you think.

The mobile test. Open your product on your phone. Sign up as a brand new user. Try to complete the most important action. If anything looks broken, scrolls strangely, or makes you want to switch back to your laptop, fix it before tomorrow.

The "where did the money go" check. Pull up your Stripe dashboard. Pick 3 customers from the last month. Match each of them to a real entry in your own user list. Are they marked as paid? Are they being billed correctly? If you cannot tell, you have a payment problem.

The "what would I do if it broke" question. Imagine a customer emails you tonight saying their account is gone, or their data looks wrong. Could you find out what happened? If not, you have no visibility into your own product. That is a problem before it is a crisis.

If 2 or more of these turn up something, talk to someone before it gets worse. Not necessarily us. But someone who has shipped products to real customers before.