When results fail to push — whether from the AI engine or from the app itself — the system does not surface any meaningful error details to the user. As a result, users have no way to identify what failed, where in the process it failed, or why, making troubleshooting and resolution difficult.

This lack of visibility affects the user's ability to self-diagnose issues (e.g., network failure vs. data validation error vs. server-side rejection) and increases dependency on backend/dev teams to investigate every failure manually, even minor or recurring ones.

Steps to Reproduce:

1. Trigger a result push from the AI engine [specify screen/flow] or from the app [specify screen/flow]
2. Simulate or encounter a failure condition (e.g., network drop, invalid payload, server timeout — specify if known)
3. Observe the response/UI after the failure