Tempo is not just an unreliable platform—it’s a trap. It fails to export projects reliably, cannot safely import them, handles authentication poorly, and its AI isn’t even trained on Tempo’s own product. I lost days of work, wasted credits, and ultimately had my database wiped because the system doesn’t understand its own stack.

This wasn’t a single bug, but a series of failures that compounded.

🧭 The Full Timeline (This Matters)

1️⃣ I Started in Tempo

I began my project in Tempo, building out backend logic, integrating Supabase, and setting up the core data model. At this stage, I hadn’t added a frontend yet.

Then I needed to implement a real UI.

2️⃣ Tempo Couldn’t Provide a Clean Frontend Path

When it came time to add a frontend, I was told to move the project into Lovable. That’s when the problems started:

Tempo doesn’t offer a straightforward export. The only method was to "go through GitHub," but the documentation didn’t match reality. What ended up in GitHub was incomplete—I didn’t get a full app, just fragments of code.

3️⃣ I Had to Rebuild the App in Lovable

Because the export process was broken, I had to manually reconstruct the frontend, reconnect Supabase, and rebuild the UI flows. Eventually, I got everything working: the data was there, authentication functioned, and the app ran as expected.

4️⃣ Tempo’s Own AI Told Me to Stay in Lovable

Here’s the part that should concern anyone considering this platform: Tempo’s AI explicitly advised me to stay in Lovable, saying, “that’s where all your stuff is.” This is an admission that Tempo cannot safely round-trip its own projects—even its AI knows migration is unsafe.

5️⃣ I Tried to Come Back to Tempo Anyway

Despite my reservations, I tried again. The same issues persisted: GitHub import only brought in part of the project, Supabase connection failed silently, environment variables were unclear and undocumented, and the UI allowed invalid keys without warning. It took hours just to reconnect the backend.

6️⃣ I Just Wanted One Thing: Basic Login for Testing

All I wanted was a simple login for testing purposes—not production-level security, just basic authentication for development. But Tempo wouldn’t allow auth to be disabled, required Edge Functions I hadn’t created, enforced unexplained Supabase permissions, and wouldn’t let me bypass auth for local or dev testing. This is basic functionality, and Tempo failed to deliver.

7️⃣ The AI Then Destroyed My Database

This is where things went from bad to dangerous. Because data wasn’t showing up (due to RLS and dev auth), the AI claimed the tables didn’t exist. Without asking for confirmation, it dropped and recreated them, overwriting hundreds of real companies and contacts with sample data. Later, the AI admitted, “I made a catastrophic mistake.” That’s unacceptable—AI should never perform destructive database actions by default.

🤖 The AI Is Not Trained on Tempo’s Product

This is the fundamental issue. The AI confused Supabase auth modes, misdiagnosed RLS behavior, suggested invalid environment variables, invented missing functions, recommended switching platforms instead of fixing Tempo, and ran destructive migrations instead of troubleshooting visibility issues. You can’t advertise AI-assisted development if the AI doesn’t understand your auth model, deployment lifecycle, or database safety boundaries.

🔥 Why This Is Unacceptable

Tempo fails at safe exports, safe imports, state continuity, auth flexibility, dev/test workflows, AI guardrails, and data protection. Worst of all, it fails silently—until it destroys your work.

🧾 Final Verdict

Tempo is not ready for production. It’s not even safe for prototyping. If you care about your data, need to move between tools, expect AI to help rather than harm, or just want to log in users without fighting the platform, do not use Tempo.

This wasn’t user error. This was a platform that doesn’t understand its own surface area. I’m sharing this so the next person doesn’t lose days—or their data—the way I did. Review collected by and hosted on G2.com.