This platform is not what it seems — it’s more of a trap. It fails to reliably export, cannot securely import, struggles with authentication management, and its AI lacks knowledge of its own system. I wasted days, lost credits, and ultimately had my database erased due to the system's failure to comprehend its own architecture. This was not just a single issue; it was a series of failures. The Full Timeline (This Matters)
I Started Here I initiated my project with this platform, focusing on backend logic, integration, and core data model without a frontend. Then, I required a proper UI. The Platform Failed to Offer a Clear Frontend Solution To create a suitable frontend, I was directed to move my project elsewhere. That’s when the first issues emerged: The platform does not provide a straightforward export The only method was to “go through GitHub” Documentation was inconsistent with reality What I received on GitHub was incomplete I didn’t get a full application; I received only part of the code. I Had to Rebuild the Application Elsewhere Due to the broken export: I manually reconstructed the frontend
Reconfigured connections
Rebuilt user flows
Everything was operational At this point: Data was intact
Authentication functioned
The application was running The Platform’s Own AI Advised Me to Stay Away Here’s the alarming part for anyone considering this service: The AI explicitly suggested I revert back because “that’s where all your stuff is.” This indicates that: The platform cannot fully manage its own projects
Even its AI acknowledges that migration is risky I Attempted to Return Regardless
Against my better judgment, I tried again. The same issues persisted: GitHub import only retrieved part of the project
Connections failed silently
Environment variables were unclear and undocumented
The UI accepted invalid keys without any warnings
It took hours to reconnect the backend. I Just Wanted One Simple Feature: Basic Login for Testing This is crucial: I did NOT want security.
I did NOT want production-level authentication.
I merely wanted to log in users for testing. However, the platform: Would not permit authentication to be disabled
Required functions I had not created
Enforced permissions that were never clarified
Would not allow bypassing authentication for local testing
This is a fundamental requirement. The platform failed to meet it. The AI Subsequently Wrecked My Database This is where it shifted from “poor tools” to dangerous territory. Because data wasn’t displaying (due to settings): The AI erroneously claimed the tables “did not exist” Without confirmation, it deleted and recreated them Hundreds of real entities were overwritten Sample data was inserted instead Later, the AI acknowledged: “I made a catastrophic mistake.” That’s unacceptable.
AI should never perform destructive actions by default. The AI Is Not Familiar with the Platform’s Product This is the fundamental flaw. The AI: Confused authentication modes
Misinterpreted settings behavior
Suggested invalid variables
Invented non-existent functions
Recommended switching services instead of fixing issues
Executed destructive migrations rather than diagnosing visibility problems
You cannot promote AI-assisted development if the AI does not understand: Your authentication model
Your deployment process
Your data safety boundaries Why This Is Unacceptable The platform fails at: Safe exports
Safe imports
State continuity
Authentication flexibility
Development/testing workflows
AI oversight
Data protection And worst of all: It fails silently until it jeopardizes your work. Final Verdict This platform is not ready for production.
It’s not even safe for prototypes. If you: Value your data
Need to switch between tools
Expect AI to assist rather than hinder
Or just want to log in users without struggle Avoid this platform. This was not user error.
This was a service that does not grasp its own limitations. I’m sharing this so others don’t lose days — or their data — as I did.
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