You know that moment when adding a tiny feature feels like performing open-heart surgery? That’s usually the first warning sign.
“Vibe coding” often happens when teams build fast, sometimes relying on AI-generated code and skip over foundational architectural decisions. While this can accelerate MVP delivery, it often leads to a tangled mix of duplicated logic, missing abstractions, and fragile dependencies.
In this post, we’ll walk through red flags that scream “clean me up” especially in early-stage products where momentum matters and cutting corners can come back to bite.
At ULAM LABS, we often step into projects where teams hit velocity walls because of hidden tech debt. That’s why we offer a Vibe Coding Cleanup service - dedicated to refactoring messy or legacy-heavy systems without slowing down your roadmap. If you’re seeing these symptoms, chances are we’ve already fixed them for someone else.
Now, let’s move on to the red flags. If any of the following situations sound familiar, it might be time to step back and give your codebase the cleanup it deserves.
The Rise and Risks of Vibe Coding
Over the last few years, vibe coding has become an increasingly common phenomenon, especially in teams that build fast, experiment often, or rely on AI-generated code to accelerate delivery. The name comes from the idea of “coding by vibe”: quickly piecing together solutions without fully understanding how they work under the hood. Sometimes this means letting AI assistants write large chunks of your backend; other times it’s developers copy-pasting code just to get things working “for now.”
While vibe coding can feel productive in the moment, the hidden cost is often fragile architectures, duplicated logic, inconsistent patterns, and dependencies nobody really controls. What starts as a shortcut in the early stages can quickly snowball into a system that’s hard to test, painful to debug, and risky to scale.
1. Code Duplication Everywhere
When the same logic appears across multiple modules, services, or functions, it’s usually a sign that early shortcuts are starting to catch up. This often manifests as duplicated serializers, repeated database queries, or copy-pasted business logic. The more duplication accumulates, the harder it becomes to introduce even small changes without chasing bugs across the entire codebase. Consolidating functionality into shared abstractions early prevents your backend from turning into a maintenance trap.
2. File Structure Chaos
As projects grow, they tend to collect scattered scripts, random folder structures, and inconsistent naming conventions. A codebase without a clear structure makes even simple navigation frustrating.
We frequently see teams waste hours searching for functionality instead of building features simply because the project structure hasn’t kept pace with its complexity. At minimum, there should be an agreed layout and naming scheme that scales as features grow.
3. AI-Generated Spaghetti Code
With AI tools becoming part of daily development, many teams move faster than ever but speed has a price. AI-generated snippets often “just work,” but under the surface they introduce hidden dependencies, unnecessary abstractions, and inconsistent patterns. These shortcuts accumulate into spaghetti code: structures that are hard to read, difficult to test, and nearly impossible to extend. Without regular cleanup, developers quickly lose confidence in the system, and what was meant to save time ends up creating more overhead in the long run.
If your MVP is already showing these symptoms, you might want to check out our guide on How To Fix an MVP That Was Built With Vibe Coding — Step by Step. It walks you through practical strategies to restructure your app without rewriting everything from scratch.
4. Feature Paralysis
If adding a small endpoint means touching several unrelated services, modifying old configs, and reviewing distant parts of the code, your architecture is starting to work against you. Poor separation of concerns forces developers to navigate a minefield where every change can trigger unexpected side effects.
In backends, this commonly occurs when business logic, database access, and presentation layers are tightly coupled. Over time, this lack of modularity makes even simple tasks disproportionately expensive and risky.
5. “What Does This Do?” Moments
There comes a point where even the original authors of the code can no longer explain why certain functions exist or how they’re supposed to work. This is a natural symptom of vibe coding - rushing through implementation without documenting intent.
Functions, modules, and classes should tell a clear story, but when naming is inconsistent and logic is overly complex, developers are forced to reconstruct context manually. As teams scale, this leads to an increased risk of introducing subtle bugs.
6. Logging Overload
logs are critical for diagnosing problems, but unmanaged logging quickly becomes its own problem. Overly verbose debug statements, inconsistent formats, and excessive trace dumps often bury the important signals beneath irrelevant noise.
This becomes especially painful when logs from multiple async processes mix together, making real issues difficult to identify. So if you’ve caught yourself scrolling aimlessly through hundreds of messages to find one error - yeah, time to clean up.
6. Comments That Add Nothing
Many codebases are filled with unnecessary, low-value comments explaining the obvious and they often distract from the documentation that actually matters. Explaining that counter += 1 increases the counter doesn’t help anyone; what’s valuable is explaining why the counter is needed at all.
In legacy projects, we often find that useless comments outnumber meaningful ones, making it harder for developers to understand business-critical decisions. Our Vibe Coding Cleanup typically starts with a code walkthrough that helps pinpoint exactly where that noise is coming from and how to replace it with maintainable clarity.
7. Tests Are Fragile or Pointless
Tests that break on small changes or worse, don’t catch regressions, create a false sense of safety. They become a tax instead of a tool. When developers start dreading test suites or skipping tests, you’re in tech debt territory. Tests should assert behavior, not mimic implementation details.
8. Dependency Rot
Every dependency in your project carries maintenance cost, and when left unchecked, outdated packages become security liabilities and upgrade blockers. It’s common to see forgotten libraries, dead imports, and nested dependencies that haven’t been touched in years. These accumulate silently until a build breaks or a security advisory forces an emergency patch. Without regular reviews and updates, dependency rot slowly erodes your project’s stability and makes future improvements harder.
10. Inconsistent Patterns
When every developer uses a different approach, velocity slows dramatically. One endpoint uses Flask, another FastAPI, another Django - each with its own way of handling requests, state, and responses. We often see projects where each feature looks like it was built by a different team entirely. Inconsistency creates hesitation: developers stop building confidently because they’re unsure which conventions to follow. A unified set of patterns speeds up delivery, improves readability, and reduces onboarding time for new engineers.
11. Bug Whack-a-Mole
When fixing one bug spawns three new ones, you’re likely dealing with tight coupling and hidden dependencies. This is common in Python monoliths where cross-module dependencies create fragile chains of behavior. Without proper isolation and contracts between components, seemingly small changes cascade through the system in unexpected ways. Over time, this turns development into a cycle of firefighting instead of building and can bring feature delivery to a halt.
This often goes beyond technical frustration - it impacts your ability to deliver features, retain users, and scale efficiently. We’ve explored this deeper in Why Your Vibe Coding Is Ruining Your Business, where we break down the hidden costs of messy architectures.
Ready to Clean Up Your Code?
Code gets messy and that’s normal. But letting a mess grow unchecked kills speed and confidence. If you're noticing these patterns in your system, it's not too late to fix them and you don’t need a rewrite to do it.
Our Vibe Coding Cleanup service helps teams get back to shipping without the drag of legacy structures or bloated code. We jump in, untangle complexity, and leave your codebase in a place where it’s easy to move fast again.
Curious if your app needs cleanup? Reach out or drop us a message. We'll help you figure out if it's just a rough patch or time for a cleanup sprint.
Frequently asked questions
Isn’t fixing vibe-coded or messy code overkill when you’re just building an MVP?
Not really. Some cleanup is just hygiene - naming things clearly, avoiding duplication, deleting unused files. It doesn’t slow you down; it keeps you fast.
When should I start refactoring my vibe-coded app?
When small features start to feel disproportionately hard. Or when you’re onboarding someone and they struggle. Those are signs you’ve outgrown your original structure.
How much time should I spend cleaning code in my app?
You don’t need a full rewrite. Refactor incrementally. If you're touching a file anyway, clean it up while you're there. If cleaning takes more and more time, contect us, we'll help.
