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Requirements Elicitation and Scoping Questions

This topic covers the end to end practice of clarifying ambiguous problem statements, eliciting and defining functional and non functional requirements, and scoping solutions before design and implementation. Candidates should demonstrate the ability to identify target users and user journeys, conduct stakeholder interviews, ask targeted and probing clarifying questions, surface hidden assumptions and root causes, and convert vague business language into measurable technical and business requirements. They should capture acceptance criteria and success metrics, define key performance indicators, and translate requirements into testable statements and test strategies that map unit, integration, and system tests to requirement risk and priority. The topic includes assessing technical constraints and operational context such as expected scale, throughput and latency requirements, data volume and read write ratios, consistency expectations, real time versus batch processing trade offs, geographic distribution, uptime and availability expectations, security and compliance obligations, and existing system state or migration considerations. It also requires evaluation of non technical constraints including timelines, team capacity, budget, regulatory and operational concerns, and stakeholder priorities. Candidates are expected to synthesize inputs into clear artifacts such as product requirement documents, user stories, prioritized backlogs, acceptance criteria, and concise requirement checklists to guide architecture, estimation, and implementation. Emphasis is placed on scoping and prioritization techniques, distinguishing must have from nice to have features, conducting trade off analysis, proposing incremental or phased approaches, identifying risks and mitigations, and aligning cross functional teams on scope and success measures. Expectations vary by seniority: entry level candidates should reliably ask core clarifying questions and avoid solving the wrong problem, while senior and staff candidates should rapidly prioritize requirements, anticipate critical non functional needs, align solutions to business impact, and communicate trade offs and timelines to stakeholders.

HardTechnical
0 practiced
A product goal is 'reduce customer support average resolution time by 20%.' Decompose this goal into measurable AI project requirements. Map requirements to user journeys and data sources, estimate a high-level timeline and milestones, and propose phased deliverables with acceptance criteria that show incremental value.
HardTechnical
0 practiced
Design a requirement checklist and acceptance criteria for launching an AI system that must comply with HIPAA. Cover data flows, encryption at rest and in transit, audit logging, de-identification, access control, third-party processing controls, incident detection and breach response, and how you would technically validate each item before go-live.
HardSystem Design
0 practiced
You must serve 10,000 model inferences per second for a 2B parameter model. Propose scoping decisions to achieve cost-effective low-latency serving: discuss model quantization, distillation, batching strategies, hardware selection, horizontal scaling, caching, and an outline of how these constraints and choices will appear in a PRD and acceptance criteria.
EasyTechnical
0 practiced
List five common hidden assumptions that cause AI projects to fail (for example: IID data, static user behavior). For each assumption propose one practical technique you would use during elicitation or early discovery to surface and validate that assumption.
EasyTechnical
0 practiced
Define 'acceptance criteria' in the context of an AI feature. Then write a concise set of acceptance criteria (3-6 items) for an MVP that automatically summarizes customer support emails into a one-paragraph summary suitable for an agent. Make each criterion measurable and indicate the primary test that would validate it.

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