Within 48 hours of launching Plant Finder on Google Play , we checked our backend telemetry to see what users were scanning.

We expected to see monsteras, tomatoes, rose bushes, and succulents.

Instead, we saw:

A worn-out leather sneaker.

A user’s sleeping cat.

A slice of pepperoni pizza.

A car dashboard.

Dozens of dark, blurry selfies.

When you hand people an app that uses multimodal AI vision to diagnose leaves, human nature takes over: people immediately try to break it.

While this curiosity is completely natural, it creates two major headaches for any mobile developer:

The Hallucination Problem: The AI tries way too hard to find a plant where none exists.

The Financial Drain: Every photo of a coffee mug or a carpet burns real money in visual AI tokens.

Here is how we tackled adversarial non-plant uploads, protected our bills, and stopped our app from diagnosing shoes.

The Sneaker That Had "Severe Root Rot"

General-purpose vision models are trained to be helpful and answer prompts…