How QuickLaunch made $120k+ fixing vibe-coded apps in 2025
We made $120k+ in 2025 fixing vibe-coded apps. Here's what was actually broken.
QuickLaunch started as an idea-to-MVP platform. We built it, launched it, got 100+ users in the first week.
Then founders started asking us to fix their existing apps instead of building new ones.
Same story every time: "I built this with Cursor/Lovable/v0, it worked great for the demo, now it's breaking and I don't know why."
We said yes to a few. Then a few more. By the end of 2025, fixing vibe-coded applications had become a significant part of our business.
Here's what we found under the hood.
Problem 1: The God Component
Nearly every React/Next app we opened had massive components doing everything. Login logic, API calls, state management, UI rendering - all crammed into single files.
We're not talking about slightly messy code. We're talking 600-800 line components with 30-40+ useState hooks each.
Why does this happen? AI tools optimize for "make it work." When you ask for a new feature, the AI adds it to whatever file is already open. It doesn't stop to refactor. It doesn't create new modules. It just keeps stacking.
One founder's dashboard had grown to 47 useState hooks in a single component. Every small change risked breaking three other things.
Problem 2: Memory Leaks
This one shows up after the app has been running for a while.
We had a client whose trading dashboard crashed after 2-3 hours of use. Their users were furious. They assumed it was a server problem.
It wasn't.
The app created new WebSocket subscriptions every time users navigated between pages. Old subscriptions never got cleaned up. The useEffect hooks had no cleanup functions. After a few hours, browsers were holding 2GB+ of dead references.
We've seen this pattern repeatedly: timers that keep running after unmount, event listeners that stack up, closures holding onto components that no longer exist.
AI generates the happy path. It rarely generates the cleanup.
Problem 3: Security Holes
This is the one that actually scared us.
Veracode's 2025 report found 45% of AI-generated code fails security tests. We've seen why.
Apps with Supabase service keys sitting in the frontend bundle. Anyone could open DevTools and grab them.
Login forms that store passwords in plain text because the founder asked for "a login system" and the AI delivered exactly that - minus the hashing, salting, and secure session management.
No input validation. No rate limiting. Auth flows you could bypass by changing a URL parameter.
One app let any logged-in user access any other user's data. The AI had set up authentication but forgot about authorization. No row-level security. No permission checks. Just vibes.
Escape's research team analyzed 5,600 vibe-coded apps and found 2000+ vulnerabilities and 400+ exposed secrets. We're not surprised.
Problem 4: Copy-Paste Everywhere
AI doesn't refactor existing code when you ask for something new. It just adds more.
We've found the same API call implemented five different ways across a single codebase. Three separate date formatting utilities, none of which handled timezones correctly. Validation logic copy-pasted with slight variations in a dozen places.
When something needs to change, it needs to change everywhere. But nobody knows where "everywhere" is.
What We Actually Do
We built a service called Rescue Sprint specifically for this.
7 days. Fixed scope. We go in, audit everything, and rebuild the foundation while keeping the UI intact.
The process:
Day 1-2: Full audit. Security scan, memory profiling, architecture review, duplication mapping.
Day 3-7: Fix in order of severity:
- Security vulnerabilities (auth, exposed keys, injection risks)
- Memory leaks and performance killers
- God component decomposition
- Code consolidation and cleanup
We don't rewrite the whole app. That's almost never the right move. We fix what's broken and leave what's working.
The Business Reality
This turned into $120k+ in revenue for 2025. We didn't run ads. Didn't do cold outreach. Founders just kept finding us through word of mouth because they all hit the same wall.
Y Combinator's Winter 2025 batch was 25% AI-generated codebases. Those startups needed to scale. Many couldn't without fixing their foundations first.
70% of investors now require technical validation before funding vibe-coded MVPs. Due diligence has caught up to the tooling.
The demand is real. Founders who moved fast with AI tools suddenly need someone to make the code production-ready before their next fundraise, their next 1000 users, or their first enterprise customer.
Why We Work US Hours
Most founders building with vibe-coding tools are US-based. We work full US timezone overlap from India.
Real-time Slack. No waiting 12 hours for a response. When production is breaking, you need someone who can jump on it now.
We've worked this way with US clients for years. It's not a workaround. It's how we operate.
What We Tell Founders Now
Vibe-coding tools are genuinely incredible for validation. Ship fast, test the idea, get users. We're not anti-AI. We use these tools ourselves.
But there's a predictable gap between "demo ready" and "production ready."
If you're planning to scale, raise money, or handle real user data, budget for a technical cleanup. The problems compound fast. Technical debt in AI-generated code grows at roughly 23% per month according to recent studies. A small fix today becomes a massive rewrite in six months.
We'd love to hear from other teams working in this space. What patterns are you seeing?
