How do you review AI output before trusting it?

Something we’ve noticed is that AI answers aren’t usually wrong, they’re just uneven. Parts are solid, parts are hand-wavy, and it’s not always obvious which is which.

We’ve been experimenting with a workflow where multiple models answer the same prompt, review and score each other’s responses, and then we combine the strongest parts into a single result.

What surprised me is how often this feels more like an editorial process than a debate — less “which model is right” and more “which parts are actually good.”

We’re testing this approach in a tool we’re building @creayo, but I’m curious how others here handle this:

• Do you manually review outputs?

• Rewrite sections yourself?

• Switch models mid-task?

• Or just accept “good enough” and move on?

We would love to hear how people approach this.