Pearson CCAR-P New Attempt

The required control is best implemented through layered prevention. The system prompt should explicitly classify personalized investment recommendations as out of scope, instruct Claude not to recommend particular securities or transactions, and provide standardized refusal language. Fixed refusal behavior reduces ambiguity and gives the model a clear alternative response when users request prohibited advice or attempt to reframe it indirectly.

An output classifier supplies an independent enforcement layer after generation but before delivery. It should detect prohibited recommendation language, individualized buy-or-sell instructions, portfolio allocations, and equivalent regulated content. A detected violation must block or replace the response rather than merely record it. This protects against prompt circumvention, unexpected phrasing, and occasional model noncompliance.

Increasing temperature makes responses less predictable and weakens control reliability. Session-length limits regulate volume, not content. SIEM logging is valuable for monitoring, investigation, and compliance evidence, but it is detective rather than preventative: the prohibited recommendation may already have reached the customer.

The completed design should evaluate both layers using adversarial prompts, paraphrases, multi-turn escalation, and classifier false-negative testing.

Study Guide references/topics: [Mitigating jailbreaks and prompt layered guardrails; explicit scope boundaries; standardized refusals; output classification; pre-delivery enforcement.

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A dedicated subagent is justified when specialization is recurring and operationally valuable. Option A allows the team to encode a database-review role once, including its system prompt, triggering description, permitted tools, model, and review criteria. This improves consistency across sessions, isolates specialized context, and applies least privilege by withholding unrelated capabilities. Anthropic’s custom subagent documentation supports task-specific prompts, model selection, tool allowlists, permission modes, hooks, skills, and persistent memory. A one-time question does not justify the maintenance overhead of a reusable agent definition, while Options C and D explicitly provide no specialization requirement. The subagent should also have clear invocation conditions, evaluation cases, ownership, and lifecycle review.

Study Guide references/topics: Claude Code subagents; task specialization; context isolation; model routing; scoped permissions; reusable automation.

A delivery team needs implementation-level direction rather than an executive architecture summary. Component responsibilities establish ownership and boundaries, while interface contracts define schemas, accepted inputs, outputs, errors, and behavioral expectations. Sequence diagrams show how components interact across dominant and failure flows. Configuration tables with defaults prevent inconsistent assumptions between environments. Operational runbooks ensure that deployment, recovery, monitoring, and routine maintenance are addressed during implementation rather than improvised after release. Options B, C, and D omit one or more elements required to translate architectural intent into a buildable and supportable system. The guide should enable normal delivery work without continuous dependence on undocumented knowledge held by the architect.

Study Guide references/topics: Implementation documentation; component contracts; sequence diagrams; configuration management; operational readiness.

An actionable runbook must connect detection, diagnosis, containment, recovery, and escalation. Option B supplies that complete operational chain: alerts identify abnormal conditions; triage procedures guide initial investigation; dashboards and logs provide evidence; escalation paths assign authority; and rollback procedures restore a known-safe state. The runbook should cover model errors, latency degradation, rate limits, tool failures, prompt regressions, cost anomalies, data-governance events, and dependency outages. Anthropic’s operational materials demonstrate incident workflows in which alerts lead responders to logs and runbooks before corrective action. Options A, C, and D each omit information required for an on-call engineer to progress from notification to controlled resolution. Procedures should be tested through exercises and updated after incidents.

Study Guide references/topics: Claude operational and observability patterns; incident response; triage; escalation; rollback; operational readiness.