3 things I wish I understood before building an AI real estate product

After spending months building FixerFlip, there are a few things I wish I understood before starting:

1. More data doesn't automatically mean better decisions.

2. Users care about assumptions almost as much as the final number.

3. A simple workflow is harder to build than a complicated dashboard.

The third one surprised me the most.

It's easy to keep adding features. It's much harder to remove everything that isn't helping the user get from question → decision.

For other makers: what's something you learned only after actually building your product?