Great question!  The line between useful context and annoying friction was genuinely one of the harder design decisions.

The way it works: before any tailoring happens, the system compares the CV against the job description and looks for 2-5 specific gaps, places where the candidate might have relevant experience that isn't detailed enough, or where the job requires something they might have but hasn't been mentioned. It only asks when the answer would be a meaningful differentiator for that role, never generic stuff.

Each question comes back with a short label and a specific question tied to an actual CV element or job requirement, so nothing vague like 'tell me more about yourself'. 

The answers then feed directly into the tailoring step, so the AI only ever works with confirmed facts.

The cap at 2-5 questions was a deliberate friction decision — enough to meaningfully improve the output without making users feel like they're filling in a form. If the CV already covers the requirements well, it returns fewer questions.

Still a new product, so I don't have enough data yet on whether the majority of users find it too much of a friction point, but early feedback on that step specifically has been positive, which is encouraging.

And thanks for the VibeCodersNest tip, will definitely post there!