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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
59 practiced
Design a requirement-driven incident response playbook for post-release model behavior regressions. Include detection triggers, stakeholders/roles to notify, decision criteria for rollback vs hotfix, runbook steps, post-mortem requirements, and a sample customer communication template for an externally visible issue.
EasyTechnical
74 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.
EasyTechnical
74 practiced
Explain the difference between functional and non-functional requirements specifically for an AI product. Then provide three concrete functional requirements and three concrete non-functional requirements for an AI-based recommendation system on an e-commerce website. For each requirement make it measurable and include one example acceptance criterion that would allow QA to verify the requirement.
EasyTechnical
68 practiced
You are asked to build a medical NLP system. Describe the types of regulatory and compliance constraints (e.g., GDPR, HIPAA) you would elicit and how you would translate each into measurable technical requirements or checks. Provide two sample testable controls per regulation.
EasyTechnical
72 practiced
Explain KPIs, SLOs, and SLAs in the context of deploying an AI model to production. For an image classification API used internally (not customer-facing), give one example KPI, one example SLO, and one example SLA, and explain how they differ in ownership, enforcement, and monitoring.

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