AI Product Manager

The map connects user need, workflow, data, probabilistic or deterministic component, interface, human decision, operations, feedback, and fallback with clear ownership.

The brief uses a sourced baseline, names a specific user outcome and owner, defines in- and out-of-scope behavior, and compares a credible non-AI option.

Data dependence, output variability, uncertainty, evaluation needs, failure modes, human authority, and update effects are stated without anthropomorphic or deterministic claims.

Measures cover user task, model behavior, safety, service, adoption, cost, and harm, with baseline, direction, owner, and an initial stop guardrail.

Arabic and English summaries describe the same user outcome, AI role, limitations, measures, and ownership using precise product language.

Evidence combines suitable users, workflow and service sources, documents selection and method, and is sufficient to challenge rather than confirm the initial idea.

The synthesis distinguishes needs, behaviors, workarounds, causes, exceptions, segments, and feature requests, and traces each material finding to evidence.

The problem statement names user, context, task, obstacle, consequence, baseline, and desired outcome without embedding AI or a chosen feature.

Consent or notification, data minimization, de-identification, access, retention, vulnerable participants, accessibility, and unequal impacts are addressed.

The bilingual decision states continue, reframe, investigate, or stop, with evidence strength, contradictory findings, assumptions, owner, and next question.

The inventory traces each required input and outcome to provenance, owner, permission, quality, coverage, representativeness, freshness, retention, and unresolved gaps.

Capabilities and limits are supported by technical evidence and cover variability, uncertainty, language, context, latency, cost, updates, and known failure patterns.

Each material constraint produces an explicit requirement, exclusion, fallback, dependency, test, or no-go decision rather than remaining a background note.

The prototype gives users meaningful disclosure, evidence, review, correction, override, refusal, fallback, feedback, and recourse at the right decision points.

Arabic RTL and English LTR controls preserve meaning, prominence, sequence, warning strength, and access to fallback and appeal.

The PRD defines users, service outcome, baseline, task, in- and out-of-scope behavior, human authority, fallback, success, and exclusions without solution ambiguity.

Requirements specify measurable contracts for provenance, permission, quality, timing, variability, language, performance, latency, cost, updates, and failure.

Scenario-based criteria are observable and cover normal, boundary, uncertain, unsupported, unsafe, unavailable, inaccessible, appealed, and recovery states with named owners.

Each requirement traces to discovery evidence or a constraint and onward to an owner and planned verification; dependencies and unresolved decisions are visible.

User-facing Arabic and English requirements, examples, acceptance criteria, warnings, and escalation preserve equivalent behavior and priority.

The assessment covers intended benefit and foreseeable harm across representative and vulnerable groups, including access, error, exclusion, contestability, and cumulative effects.

Material scenarios have causes, consequences, likelihood, severity, prevention, detection, response, evidence, owner, and residual-risk assessment.

Qualified people have timely context and authority to review, correct, override, pause, explain, handle complaints and appeals, and avoid automation bias.

The final decision follows evidence and authority, records conditions and dissent, names prohibited use and residual uncertainty, and defines review and stop triggers.

Arabic and English decision summaries accurately communicate product purpose, AI role, human responsibility, main risks, controls, recourse, and owner.

Dimensions map to user, model, safety, service, cost, and human outcomes; scoring anchors are observable, non-overlapping, and reliable enough for reviewers.

The set reflects real task frequency and material risks, covers languages and affected groups, has traceable labels, and reserves a protected final portion.

Baseline, hypothesis, unit, comparison, assignment or selection, sample size, duration, denominators, analysis, uncertainty, and missing data are technically coherent.

The plan preserves prior controls, defines harm and operational guardrails, human review, complaints, pause, rollback, stop, and limits causal and generalization claims.

Arabic and English quality, RTL and LTR behavior, language switching, assistive use, errors, fallback, and feedback are evaluated with equivalent criteria.

Work, dependencies, decisions, evidence, owners, capacity, dates, and escalation align across functions with no hidden critical path or unowned gate.

Readiness covers people, process, technology, data, controls, support, monitoring, capacity, continuity, incidents, complaints, changes, rollback, and retirement with verifiable evidence.

Stages have entry, quality, safety, adoption, pause, stop, and rollback criteria, and the exercise demonstrates restoration of a safe service state.

The plan addresses workload, training, resistance, support, feedback, complaints, accessibility, non-digital alternatives, known limits, and accountable contacts.

Arabic and English materials accurately explain scope, AI role, human responsibility, data use, limitations, recourse, support, and change timing for each audience.

User outcome, evidence, constraints, requirements, controls, evaluations, operating model, roadmap, and decision align, and material claims trace in both directions.

The PRD defines a feasible bounded product with precise data, model, UX, human, operational, accessibility, and failure requirements and observable acceptance.

Representative evaluation, quantitative baselines and thresholds, experiments, guardrails, affected-group analysis, monitoring, and feedback support the stated decision without selective evidence.

Human authority, controls, residual risk, complaints, appeal, operations, staged gates, pause, rollback, stop, unsupported use, and review ownership are complete.

Arabic and English materials request and justify the same decision with consistent evidence, figures, limitations, user controls, responsibility, and next action.