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3 reasons your Lovable app breaks in production (and how to fix each)
Debugging loops, the AI keeps "fixing" the same bug differently each time. Stop prompting for more fixes; pull up the actual error trace and fix the root cause manually.
Supabase auth is misconfigured, most non-technical builds skip Row Level Security. Your app looks fine until a user sees someone else's data.
Deployment/domain issues, works on the preview URL, breaks on your custom domain. Usually a DNS or environment variable mismatch, not a code problem.
If your app is stuck on one of these, happy to take a look.
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From QA to QFixing: Expanding the Role of Quality Assurance
by Hiba Al Fayssal, Quality Assurance Manager, InfiniteUp
Quality assurance bug fixing is evolving. At InfiniteUp, we call our approach QFixing – a practical way for QA professionals to safely fix small issues while reducing unnecessary developer handoffs.
As a Manual Quality Assurance Manager at InfiniteUp, the role has traditionally focused on finding issues before they reach the user, testing different journeys, exploring edge cases, and documenting anything that does not behave as expected.
Recently, that process started to evolve.
Instead of only reporting smaller FlutterFlow issues, there was an opportunity to investigate them and try fixing them directly.
That experience revealed something unexpected:
Fixing bugs is just as rewarding as finding them – and it creates new ways to bring value to the whole team.
Starting with Small, Clear Issues
Many issues found during testing are not complex development problems. They may involve:
A button opening the wrong page
A widget appearing when it should be hidden
Text overflowing outside the screen
An uploaded image connected to the wrong field
An action running in the wrong order
A typo, color, or translation that needs correcting
These issues may only require a small change to a condition, widget setting, variable, or action flow.
This became the starting point for QFixing: using a QA mindset to investigate small, clear issues, apply a safe fix, and test the result.
The QA Mindset Behind the Fix
Quality assurance already provides a strong foundation for problem-solving.
The investigation usually begins with familiar questions:
What triggers the issue?
What should happen?
What happens instead?
Which widget, condition, action, or variable controls the behavior?
Is there a similar working flow that can be used for comparison?
The difference is that the process does not always end after identifying the cause.
In those cases, the QA tester who already found and understood the issue may also be the fastest person to fix it.
A Win for the Entire Team
The biggest benefit of QFixing is not only that a small bug gets resolved.
It can also remove unnecessary back-and-forth.
Even a small bug can create a long workflow.
QA reproduces the issue, captures screenshots, writes detailed steps, explains the expected result, assigns it to a developer, answers follow-up questions, waits for the fix, and then retests it.
For complex issues, this process is essential.
But for a typo, an incorrect color, a missing visibility condition, or a simple navigation mistake, the process can sometimes take longer than the fix itself.
If the QA tester who already understands the issue can safely correct it, the team gains several benefits:
The issue is resolved faster.
Developers spend less time switching context for small tasks.
Unnecessary explanations and follow-up questions are reduced.
QA can verify the result immediately.
The busiest team members can focus on more complex and valuable work.
This makes QFixing a practical team capability, not only an individual skill.
Expanding the Team’s Capabilities
QFixing does not mean replacing developers or moving away from quality assurance.
It represents a hybridization of skills, where team members gradually become capable of handling a wider range of tasks.
The question becomes:
Who is the right person to handle this issue?
Rather than:
Who is the only person able to handle it?
Complex logic, APIs, architecture, security, performance, and custom code still require the right technical expertise.
QFixing focuses on small, obvious improvements and knowing when something should be escalated.
The value comes from having more than one option.
As the team’s skills become broader, work can be distributed more intelligently and efficiently.
Learning Through Fixing
There is also a long-term team benefit.
Every small fix builds more practical knowledge of FlutterFlow, including state management, Firestore references, responsive layouts, localization, authentication, and navigation.
That knowledge improves future testing, makes bug reports more accurate, and helps the team identify root causes faster.
It also creates career growth by expanding the range of tasks that can be handled confidently over time.
From QA to QFixing
QFixing turns quality assurance into an even more active part of the product-building process.
It reduces unnecessary back-and-forth, protects developer focus, speeds up small fixes, and strengthens the team’s overall capabilities.
The result is not only better use of time.
It is a more flexible, collaborative, and efficient team.
That is the real value of QFixing: more people able to contribute, fewer unnecessary handovers, and faster progress for everyone.
Want to bring AI to your business? Have an idea for an app? Setup an exploratory call with InfiniteUp CEO Barrett Nash here or reach out at nash@infiniteup.dev
Just sharing a digital coffee is a pleasure in and of itself. We love hearing your ideas…. and happy to sign NDAs.
aievaluationqaqualityassuranceFlutterflow Development Quality Assurance EngineeringQuality Assurance TestingChatGPTClickUpFlutterFlow
QFixing seems like a logical evolution of QA right!
1: “Integrate RevenueCat for payments.”
And it’s done?
Without App Store / Play Store setup?
Without product configuration?
Without entitlement mapping?
Without receipt validation?
Do you think any AI agent just figures that out?
2: “Integrate Stripe so I can receive payments in my app.”
Cool.
But you missed something.
Webhook is not set.
And then what happens?
User cancels payment
system, never gets the event
paid features still active
Revenue leak. Silent.
3: “Add login system.”
without session invalidation?
without refresh token rotation?
without secure storage?
Stolen token = permanent access.
4: “Secure APIs”
without backend authorization?
without object-level checks?
So, any user can simply change an ID…
and sees another user’s data?
5: “System is stable.”
without retry limits?
without circuit breakers?
One failing API -> infinite retry loop -> self-inflicted outage.
6: “AI feature works.”
without token caps?
without prompt injection protection?
One input -> cost explosion -> unpredictable billing.
7: “Save user data.”
without backend confirmation?
UI shows success… but nothing saved.
refresh -> everything gone.
8: “File upload works.”
without file type validation?
without size limits?
Someone uploads a massive file…
and kills your storage or crashes processing.
9: “Database is optimized.”
without indexing?
without query batching?
one page load -> 100+ queries -> silent slowdown.
10: “Notifications are working.”
without event deduplication?
Same event fires twice -> user gets duplicate emails.
11: “Payments are safe.”
without idempotency keys?
user clicks twice -> gets charged twice.
12: “System is scalable.”
without stateless design?
One server -> one bottleneck -> everything breaks under load.
13: “Deploy is safe.”
without feature flags?
one push -> full production break -> no rollback path.
14: “Logs are available.”
without structured logging?
Debugging becomes guesswork in production.
15: “Everything is connected.”
without failure isolation?
One third-party API goes down → entire app breaks.
16: “Vibe coder says: test end-to-end.”
But he means:
login works -> ship it.
No real devices.
No cancellation flows.
No failure scenarios.
No edge cases.
…only 16 points, hundreds more to address as an engineer.
Lately, I audited a few vibe-coded SaaS projects.
And what shocked me wasn’t the bugs.
It was how confidently incomplete the systems were.
The clients genuinely thought the product was “production-ready.”
Until I started showing what happens outside the happy path.
That was the moment the room changed.
Because this wasn’t debugging anymore.
-This was an engineering reality showing up.
So instead of manually reviewing random files, I built something structured:
The 24_Phase_Agentic_Software_Due_Diligence_and_Audit_Framework.
Each acts like a different senior engineer.
Engineering optimizes for survival in real-world production.
This isn’t hacking.
This is engineering thinking at the system scale.
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