This page describes a structured approach to assessing FDE candidates: link each job responsibility to observable evidence and score it against anchored rubrics. Before making a hiring decision, interviewers must distinguish three cases: missing evidence, performance achieved only through coaching, and critical failures. The page also lists related course lessons and premium practice questions covering behavioral and customer scenarios (conflicting interviewer recommendations, prospects without an operating owner, missed engagement start dates, ROI disputes with finance) and system design (assessing whether a customer is ready to run AI coding agents in their codebase). Full access requires a paid subscription (₹2,000 / $25 for six months).

Key points

• Structured FDE assessment maps responsibilities to observable evidence and anchored scoring.
• Interviewers must separate missing evidence, coached performance, and critical failures.
• Practice scenarios include conflicting interviewer verdicts and ROI reconciliation with finance.
• A system design question covers customer readiness for AI coding agents in their codebase.
• Full question bank and materials are behind a paid subscription.

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