Practise real FAANG interview rounds with an AI interviewer that adapts to your answers — 2 mock interviews across 2 roles, modelled on real candidate reports from 2024 to 2026. Each ends with a published rubric and a transcript-backed scorecard, so you know exactly what to fix before the real thing.
An AI product strategy round where you must prove an LLM chatbot is measurably better and defensible while rival models ship weekly. Priya Nair, a Group Product Manager building a support assistant, interrogates your evaluation harness, unit economics, and moat at the mid-level FAANG bar. You leave with a transcript-backed scorecard naming the exact claim you could not quantify.
A GenAI feature design round where every model choice gets pushed on hallucination tolerance, p95 latency, and cost per resolved query. Priya, a hiring manager for an AI assistant team, presses you to define the user, set a measurable quality bar, and sequence mitigations by what each one adds in latency and dollars. You leave with a transcript-backed scorecard naming the trade-off you could not ground in a number.