Ben Erez shows how to use AI to simulate candidates in big tech product sense interviews, helping PMs see what good performance looks like and practice their own approaches.
Ben explains the context: âWhen youâre interviewing at series A, B, C companies, itâs about fit, behavioral questions, and chemistry. As you get to bigger companies, the people interviewing you probably wonât even work with you. I joined Facebook as the 2000th PM - what theyâre looking for is standardized signals that eliminate bias and look for specific evaluation criteria.â
Hereâs Benâs demonstration using Claude as a candidate answering âYou are a PM at Uber. Design a product for kidsâ:
First, Claude starts with assumptions: âIâm assuming weâre talking about children under 18, that this would be a new product line for Uber, and that safety is the primary concern.â This models what Ben coaches - always state assumptions upfront.
Second, Claude outlines a structured approach: âI want to describe the product experience, break down the target audience, identify key problems, pick one, brainstorm solutions, pick one, and describe a V1.â Ben responds with terse âYesâ answers - exactly how real interviewers respond.
Third, Claude works through each section methodically:
- Sets a mission statement connecting to Uberâs broader mission
- Identifies ecosystem players and chooses to focus on parents
- Creates three mutually exclusive segments with scoring
- Maps user journey to identify problems
- Develops solutions and evaluates on impact/effort
- Describes V1 implementation with risk mitigation
