Your Vibe Coded App Worked on the Demo.
Now It's Breaking in Production.
Every technology wave creates a build-fast-fix-later cycle. A few years ago, it was low-cost delivery models. Ship it fast, figure out quality later. Many teams spent more fixing what was delivered than it cost to build in the first place.
Today, AI and vibe coding are creating the same cycle. Faster.
Ideas that once took months can be validated in days. The code compiles. The tests pass. The demo works. Founders close early customers. Investors get excited.
Then real users show up, real data flows in, and the engineering bills come due.
What AI Slop Actually Looks Like in the Codebase
I have reviewed dozens of AI-generated and vibe coded repos recently. They all share the same recognizable shape: every individual file looks fine, but the system doesn't hold together at the seams.
Overly abstracted code where simple solutions would do. Basic building blocks missing that actually matter: proper error handling, input validation, connection pooling. Database as an afterthought rather than a design decision. State management that works with one test account and falls apart the moment two real users show up. AI comments scattered everywhere explaining what the code does (why do you need comments when AI itself is reading the code?).
This is POC-grade code that got shipped as a product. The typing got faster, but that was never the expensive part.
The cost of software was never the typing. It's the thinking, the architecture, the assurance, and the support. Who are you going to call on a Friday evening when it all stops working?
The AI Code Quality Crisis Is Real
81%
of enterprise tech leaders report increased production issues from AI-generated code
43%
of AI code changes need manual debugging in production even after passing QA
1.7x
more issues introduced by AI-generated code compared to human-written code in production
Sounds Familiar?
Every file looks fine on its own, but the system doesn't hold together
Nobody on the team fully understands the code because nobody actually wrote it
State management is a house of cards that breaks when real users show up
Any user can access another user's data because data isolation was never designed
The database is an afterthought: no proper schema, no foreign keys, no indexing strategy
Production incidents are impossible to diagnose because there's no real observability
Adding features takes longer every sprint because the architecture fights you
You've made promises to investors or customers that the current codebase can't deliver on
These are not AI problems. They are software engineering problems. Whether code is written by humans, agencies, or AI agents, the same principles apply. Systems must be reliable. Data must be trustworthy. Operations must be observable. The architecture must make sense to the people who have to maintain it.
How I Help Teams Move Forward
You don't need someone to tell you what went wrong. You need someone who can help you move forward without losing momentum.
Your app found product-market fit but the code underneath is AI slop. I audit what you have, figure out what's actually broken vs what's fine, and build a plan that doesn't require throwing everything away.
AI loves over-engineering: unnecessary abstractions, layers that add complexity without value, spaghetti code backends with no clear ownership. I untangle the mess and simplify to what actually matters.
The scariest AI code problem: every function works in isolation, but access control, data boundaries, and permission enforcement live at the seams between files. Those seams are usually missing entirely.
When AI-built systems break in production, the debugging is brutal because nobody understands the code. I dig into root causes and fix things so they stay fixed, not just patch the symptom.
Logging everywhere but observability nowhere. AI-generated code almost never ships with proper metrics, structured logging, or alerting. I set up foundations so your team can see what the system is doing.
The app is already in production and worse than anything you've seen. The hardest part is maintaining business continuity long enough to actually fix things. I plan the migration so nothing breaks for your users.
The AI Slop Refactoring Wave Is Here
Right now, a generation of products is getting shipped by skipping the part where you understand what you're building. Many of today's vibe coded apps are effectively becoming tomorrow's modernization projects.
The companies that benefit most from AI won't be the ones generating the most code. They'll be the ones that can distinguish between “fast to build” and “cheap to own.”
AI will keep accelerating software development. That's not changing. What will continue to create value is the ability to combine speed with engineering judgment, business understanding, and system thinking.
Every product starts as an idea. Many become prototypes. Only a few become dependable platforms that businesses can confidently build upon. Helping teams make that transition is where I create the most impact.
Stuck with a Vibe Coded App?
Don't wait until you're in a panic. At the very least, get an architecture review before the problems compound. I can help you figure out what's actually broken, what's salvageable, and what needs to be rebuilt. I also mentor engineers on building the judgment that AI can't replace.