When providing feedback on an AI feature, I focus on the balance between capability and user control. I would approach it in three steps:

​Identify the Friction: I look for where the AI’s output doesn't match the user's intent or where the workflow feels clunky. For example, if the AI hallucinates or gives a vague answer, is there an easy way for the user to correct it?

​Proposed Solution: Instead of just saying 'it's broken,' I suggest specific UI/UX improvements—like adding 'regenerate' buttons, providing confidence scores, or allowing users to edit the input context more easily.

​Data/Impact: I would explain why this change matters, such as 'improving this specific interaction will likely reduce user drop-off rates and build trust in the model's accuracy.

The way it responds to well defined and detailed prompts

Yes