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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.

EasyTechnical
75 practiced
A product manager says: 'Build an AI assistant for sales.' List at least 15 clarifying questions (grouped by category: users, data, model behavior, metrics, integrations, constraints) you would ask during the first stakeholder interview to avoid solving the wrong problem.
EasyTechnical
54 practiced
Compare real-time inference versus batch inference for a recommendation system. List the clarifying questions and constraints you would elicit to decide between them (consider latency, throughput, data staleness, engineering complexity, cost, and business value). Provide one example scenario where batch is preferable and one where real-time is required.
HardTechnical
73 practiced
Design a requirement checklist for detecting and mitigating hallucinations in an LLM-powered product. Include a definition for hallucination, detection metrics, acceptance criteria, remediation strategies (e.g., grounding, citations, human review), deployment gates, and monitoring signals to catch regressions after release.
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.
MediumTechnical
65 practiced
You have 6 weeks and one engineer to deliver an MVP: automatic summarization of incoming customer emails into bullet points for agents. Propose an MVP scope, success metrics (quantitative and qualitative), a three-phase roadmap (weeks 0-6 and post-MVP), and at least three mitigations for the top risks you see.

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