You shipped an AI feature. Users found it, tried it, and did not come back. The reason is usually visible in the interface, not the model.

In moderated sessions on one AI assist panel, 5 of 8 users read the AI's suggestions as static help content. The feature was working. The interface was not showing its work. One sentence explaining why each suggestion appeared fixed both the trust failure and the comprehension failure.

This diagnostic reviews one AI feature that closely. No calls, no meetings, no waiting.

The findings name what is breaking trust or comprehension in that feature, ranked by what each issue costs you, with a specific fix for every one. No broad audit, no padding.

Prioritized findings report. Every issue ranked by severity, with a specific fix.

Annotated screens. The feature reviewed screen by screen with specific callouts.

Recorded walkthrough. A narrated pass through the findings, ready to share with your team.

72-hour turnaround. Fixed price, no scope creep, no surprise invoices.

One AI feature, named at booking. Its entry point, first use, error states, and the moments where trust is won or lost.

One feature. If the feature spans more than one flow, the review follows it across those flows. A second unrelated feature is a second engagement, or the AI UX Snapshot.

The clock starts when product access and the intake answers are both in hand, not at purchase. Access details arrive by email within one business day of booking.

You already know which feature is underperforming and want a fast, precise answer.

You would rather fix one thing well than commission a broad audit.

You need findings your team can act on this sprint.

Every diagnostic is run personally by Frank Rodriguez. 20 years of product design experience shipping AI features at Intuit (QuickBooks, TurboTax) and Workday.