# The Vibe Coding Doom Loop: Why Your Lovable or Replit App Breaks Every Time You Fix It

> Fix one bug in your Lovable or Replit app and ten more appear? Why the vibe coding doom loop happens, the prompts that prevent it, and when to call an engineer.

Source: https://eaquirstech.com/en/blog/vibe-coding-doom-loop · Eaquirs Tech, AI-native software engineering partner · Updated 2026-11-09

By Muhammad Safdar Iqbal · Published 2026-10-31 · Tags: Vibe Coding, App Rescue, AI Agents, Software Rescue

You type one sentence: *"The save button on the profile page doesn't work, please fix it."*

The AI thinks for a few seconds, edits six files, and proudly tells you it's done. The save button works now. The login page doesn't. You ask it to fix the login. Login works, but the dashboard is blank. You fix the dashboard, and somehow the save button is broken again.

If that sounds familiar, you're in what developers call the **vibe coding doom loop**. You're not bad at prompting, and the tool isn't broken. It's a predictable result of how most vibe-coded apps are built, and once you see why it happens, most of it can be avoided.

I'm writing this because a big part of our work at Eaquirs Tech now is pulling people out of exactly this loop. Below is what causes it, a real rescue story, and the prompts I'd give anyone building with Lovable, Replit, Bolt or Cursor so they never need someone like me.

### What is the vibe coding doom loop?

The vibe coding doom loop is when every fix you ask an AI coding tool for breaks something else, so you keep prompting, keep spending credits, and the app gets worse instead of better. Each change solves the problem in front of the AI but quietly damages parts of the app it can't see or doesn't understand.

The name comes from [vibe coding](https://en.wikipedia.org/wiki/Vibe_coding) itself: building software by describing what you want in plain language and accepting whatever the AI writes, without reading the code. For a weekend demo, that's wonderful. For a product with real users, payments and data, it's where the loop starts.

### Why it happens: five causes we see on every rescue

#### 1. The AI only sees part of your app

AI tools work inside a limited context window. On a small app, the whole project fits. As the app grows, the tool only sees the files it decides are relevant to your latest prompt. It fixes the save button using what it can see, and has no idea that the login page depends on the same function it just rewrote.

#### 2. Everything is tightly coupled

Ask a vibe coding tool for "a profile page that saves to the database" and it will often put the screen, the business rules and the database calls in one place. Do that across twenty screens and every part of the app is tangled with every other part. Engineers call this tight coupling. In practice, it means you can't touch one thing without touching ten.

#### 3. Nothing checks that old features still work

Professional software has tests: small automatic checks that run after every change and shout when yesterday's feature breaks. Most vibe-coded apps have none. So the only "test" is you clicking around, and you only click on the thing you just fixed.

#### 4. The conversation forgets its own decisions

Long chats drift. In message five you agreed that users log in with email. By message eighty, the AI has lost that detail and adds a phone number login that half-replaces the first one. Nobody wrote the decisions down, so nobody, including the AI, can keep them.

#### 5. Patches pile on patches

When a fix fails, the natural move is to ask for another fix on top. After a few rounds, the code is layers of half-solutions, each written to work around the last. The AI is now reading its own confused patches and making more of them. This is the actual loop.

### A real rescue: "80% done, just needs fixing"

One of our clients, a [US startup](/en/software-development/usa), found us on Upwork. He had a hiring platform, now live as [OpenInterview.me](/work/openinterview-hiring-platform), and he told us it was about 80% done. The remaining 20% was "mostly fixing."

I've heard that sentence many times, so before agreeing to anything, I audited the code.

There wasn't one codebase. There were **more than four**. Some of it was Python, some React, some PHP and some plain JavaScript. Different freelancers and different AI sessions had each started their own version, and none of them worked properly. The only thing that actually ran was a basic HTML, CSS and Node version, and even that was broken. Most of the features he'd been promised existed as screens: they looked right, but behind them there was little or nothing doing the real work.

This is very common, and it's not the client's fault. The pattern usually goes like this. To save money, the project goes to someone without much experience, often leaning heavily on AI tools. At the start, the vendor and the client are both happy, because screens appear fast and the demos look great. Then the app grows, the loop starts, every fix breaks something, and progress slows to a stop. That's usually the point when someone calls us.

What I didn't do was scare him. Telling a founder "everything you paid for is worthless" helps nobody. Instead, I took responsibility for the mess as it was. I explained what we had, picked the one direction that could be saved, cleaned up the structure so the app had a single, clear shape, and told him plainly: *I'll get this fixed for you.*

Then I showed rather than told. Within the first stretch of work, he could see a real database running on Neon and a working sample of the payment flow. Those two things changed the whole conversation. He extended the first contract, added a bonus on top, and later hired us again for a second phase to finish the core properly and add new features.

Only once the platform was stable did we talk tech stack in detail: what he had, why it had failed, and what a long-term version should be built on. He agreed, and he's committed to building the next major version properly on NestJS and Next.js. He's a very happy client today, and the platform is live.

The point of the story isn't that the first developers were bad people. It's that **the loop is a structural problem**, and more prompts can't fix a structural problem.

### Signs you're already in the loop

You're in the doom loop if three or more of these are true:

- A fix for one screen regularly breaks a different screen.
- You've asked for the same fix more than three times.
- The AI says "fixed" and it isn't.
- You're scared to change anything that currently works.
- There are features you've stopped mentioning because asking about them breaks things.
- You can't say where your data is actually stored.
- Your credits or tokens go faster every week, while visible progress goes slower.

If that's you, read on. Some of it you can fix yourself.

### How to vibe code without falling into the loop

Most of this comes down to giving the AI the instructions an experienced engineer would give a junior developer. You don't need to write code. You need to write rules.

#### Start with a plan, not a feature

Before the first screen, ask the AI to design the app on paper. Something like:

> Before writing any code, write a short architecture plan for this app: the main parts, which part owns which data, how the parts talk to each other, and the folder structure. Keep it to one page. Don't write code until I approve it.

Read it, ask questions, and save it. That plan is now the map you'll point the AI back to every time.

#### Ask for loose coupling, out loud

AI tools take the shortest path unless you tell them otherwise. Ask for separation from the start:

> Keep the app loosely coupled. Separate it into three layers: screens (UI only), business logic (rules and calculations), and data access (the only code that talks to the database). Screens must never call the database directly. Each feature lives in its own folder. Shared code goes in one shared folder, not copied between features.

This one prompt prevents a large share of the problems we see on rescues, because a change in one feature can no longer reach into every other feature.

#### Keep a rules file the AI reads every time

Most AI coding tools have somewhere to keep standing instructions: a project knowledge section, a rules file, or a file like `CLAUDE.md` in Claude Code. Use it. Put your architecture plan, your key decisions ("users log in with email only") and your coding rules there, so they survive long conversations.

Even better, keep a short **pitfalls** list. Every time the AI makes a mistake you had to fix, add one line: what went wrong and the rule that prevents it. The AI reads it before every change, so the same mistake stops coming back. We run our own builds this way, and we've written up the full setup in [Claude vs ChatGPT for developers](/en/blog/claude-vs-chatgpt).

#### One feature per conversation

Don't build your whole app in one endless chat. Start a fresh conversation for each feature, and open it with a short summary: what the app is, the relevant part of the plan, and the task. A clean, focused context gives better results than a huge, drifting one, and it costs fewer tokens too.

#### Make every change small and fenced in

Vague prompts produce wide edits. Narrow prompts produce narrow ones:

> Fix only the save button on the profile page. Change the smallest amount of code possible. Do not refactor, rename or touch any other file. Before changing anything, tell me which files you plan to edit and why.

That last line matters. If the AI wants to edit eight files to fix one button, you've caught the problem before it happens.

#### Prove the bug before fixing it

> Before fixing this, write a small test that reproduces the bug and fails. Then fix the code until the test passes. Keep the test.

Over time, those kept tests become a safety net that tells you, automatically, when an old feature breaks.

#### Save a checkpoint after everything that works

Use your tool's version history, checkpoints or Git. Every time something works, save it. When a fix goes wrong, **roll back instead of fixing the fix.** Reverting to the last good version and trying again with a clearer prompt is almost always cheaper than asking for patch number six.

#### Set a stop rule

If three fixes in a row fail, or each one breaks something new, stop prompting. Roll back to the last checkpoint, re-read the plan, and either rewrite the prompt from scratch or ask someone who can read the code. The loop feeds on "just one more try."

### How to save tokens and credits

The doom loop is also why vibe coding bills grow faster than the app. A few habits help a lot:

- **Name the file.** "Fix the total in `cart-summary`" is cheaper than "the cart is wrong somewhere."
- **Paste the relevant error, not the whole log.** The first error is usually the real one.
- **Don't re-explain the app every time.** Point to the plan and rules file instead.
- **Roll back rather than repair.** Failed fixes on top of failed fixes are the most expensive tokens you'll ever spend.
- **Plan before building.** Ten minutes of planning saves hours of rework, and the AI reads less confused code afterwards.

### Prompts that push the AI toward scalable code

Here's a block you can paste into your rules file or the start of a project. It won't make the AI a senior engineer, but it pushes it toward choices that scale:

> - Keep UI, business logic and data access in separate layers.
> - One feature per folder. No copy-pasting code between features.
> - Validate every input on the server, not only in the browser.
> - Never trust user IDs, prices or permissions sent from the browser.
> - All database changes go through migrations.
> - Payments must be safe to retry: the same request must never charge twice.
> - Keep secrets and keys in environment variables, never in the code.
> - Use one language and one framework for the whole backend.
> - Add a test for every bug you fix.
> - If a change needs more than three files, explain the plan first and wait.

That rule about one language and one framework sounds obvious. On the hiring platform above, ignoring it is exactly how one product ended up as four half-finished codebases.

### When to stop prompting and call an engineer

Some problems are past what prompts can fix:

- **Real users and real money.** Once people pay or store personal data, security and data integrity need someone who reads the code.
- **Multiple codebases or stacks** for one product.
- **Data you can't trust:** missing records, double charges, numbers that don't add up.
- **Everyone is scared to touch it,** including the AI.

At that point, the right move is an audit, not another prompt. A good engineer will tell you what's worth keeping, what needs rebuilding, and in what order, without making you start from zero if you don't have to. We walk through that decision in detail in [vibe-coded app rescue](/en/blog/vibe-coded-app-rescue), and if your developer has disappeared entirely, see [how to take over a failed software project](/en/blog/take-over-failed-software-project).

### Common questions

**What is the vibe coding doom loop?** It's when every fix an AI coding tool makes breaks something else, so you keep prompting and the app gets worse. It's usually caused by tightly coupled code, no tests, and an AI that only sees part of the project at a time.

**Why does Lovable or Replit break my app when I ask for a fix?** As the app grows, the tool can't keep the whole project in view, so it changes shared code without knowing what else depends on it. Without tests, nothing catches the damage until you find it yourself.

**How do I stop the AI from breaking working features?** Ask for small, fenced-in changes, make it list the files it will edit before it starts, keep a rules file with your decisions, save a checkpoint after everything that works, and roll back instead of stacking fixes.

**Can a vibe-coded app be saved, or does it need a rewrite?** Often it can be saved. Many apps have a usable core under the mess. An audit tells you which parts to keep, which to rebuild, and in what order. A full rewrite is only the answer when nothing underneath is sound.

**Is vibe coding bad?** No. It's an excellent way to test an idea, build a demo or show investors something real. The trouble starts when a prototype is treated as a finished product. Use it to learn what to build, then build the version that will carry real users properly.

### Stuck in the loop?

If your app has reached the point where every prompt makes it worse, you don't need to throw it away, and you don't need to feel bad about it. Almost every product we've rescued started exactly like yours.

We audit the code, tell you honestly what's worth keeping, and get it back to a state where changes are safe again. See how we approach [rescue and modernization](/services/rescue-modernization), how we build [web and mobile products](/services/product-engineering) properly from the start, or [book a free 30-minute call](/book) and show us what you've got.

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