Product Manager Interview Experience
Interview process
What went well was the collaborative discussion around the product case. I identified the importance of exports as the core success metric, connected it to activation and monetization, and proposed sensible ways to diagnose a drop, including checking product changes, funnel performance, experiments, model outages, and user segments. The conversation about AI, autonomy, and product culture also felt natural and engaging. On the technical interview they asked me to prototype using an ai tool such as lovable or claude. They offered an account and I ran out of credits after a couple of chat messages but managed to get a first draft to present. Since they left the room while I was prototyping and ran into the issue, I could not recover quickly. I tried to start over in my own AI accounts but time was extremely limited. I had never really done product interviews (I've been working on the same company for a long time) so I struggled a bit with structuring my answers, which I believe is what got me eliminated, although their feedback mentioned my prototype was not enough to support my solution, even though they knew about the hiccups with the credit limit.
- Recruiter screen
- Technical interview
- Take-home project
Interview tips
I’d tell them to use the product extensively before the interview and form a few specific opinions about what works well and what could improve. For the case study, practise defining a clear north-star metric, separating goals from supporting metrics, diagnosing problems systematically, and explaining prioritization decisions. I’d also recommend answering with a clear structure before diving into details: state the approach, explain the reasoning, then give the recommendation. Finally, be ready to discuss a real product failure or ambiguous project with honest self-reflection, because the interview evaluates how you think and collaborate as much as the final answer.
Company culture
What stood out was the combination of high autonomy, strong product craft, and low ego. PMs are expected to set direction and understand users and metrics, while engineers have real ownership over what they build and test.
Questions asked
Question types asked
Specific questions asked
Do you prefer core product or growth product management?
How did you reduce ambiguity when building the AI functionality from scratch?
Was that the metric you had in mind when you started building?
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