Product Sense

Behavioral for Full-Stack Engineers

Full-stack behavioral rounds grade for a contested signal: the credibility of a single engineer who can ship a feature from data model to pixel without dropping any of the layers. The skeptical interviewer's silent question is whether the candidate is a real full-stack engineer with depth on multiple layers or a generalist who is shallow on every layer. This lesson defines the cross-cutting full-stack signals interviewers grade, walks through how the loop probes for breadth-with-depth rather than breadth-instead-of-depth, maps the signals to the questions interviewers ask, and shows two model answers tailored to the vertical-slice ownership and breadth-versus-depth navigation story shapes.

Define a user outcome and baseline

Explain why longer sessions do not justify shipping AI hints, then use a fictional pilot's per-arm figures to propose an evaluation with a real baseline, an independent learning outcome, and guardrails.

Design an A/B test with cost guardrails

Write the experiment contract and sample-size plan for a staged-hints A/B test, implement a validated per-arm summary of outcomes and costs, and explain which checks and guardrails must pass before a lift can justify shipping.