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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Governance, Safety & Risk Management | 14% | - Address ethical AI considerations and bias mitigation - Manage data privacy and security compliance - Ensure regulatory compliance (GDPR, HIPAA, etc.) - Implement guardrails and safety controls |
| Topic 2: Developer Productivity & Operational Enablement | 7% | - Configure Claude tools and environments for teams - Improve developer workflows with AI-assisted tooling - Support debugging, monitoring, and operational resolution |
| Topic 3: Evaluation, Testing & Optimization | 16% | - Define evaluation metrics and success criteria - Implement iterative improvement pipelines - Test accuracy, reliability, latency, and cost - Optimize performance, prompting, and model selection |
| Topic 4: Claude Models, Prompting & Context Engineering | 13% | - Select appropriate Claude models based on trade-offs - Mitigate prompt injection, leaks, and jailbreak risks - Design system prompts, templates, and guardrails - Apply context engineering and context management techniques |
| Topic 5: Solution Design & Architecture | 17% | - Design end-to-end architectures and feedback loops - Select architectural patterns: workflow, agentic, augmented LLM - Design multi-agent systems and orchestration strategies - Align solutions to business value pillars - Translate business problems into Claude-based AI solutions |
| Topic 6: Integration | 19% | - Design authentication, authorization, and observability - Implement Model Context Protocol (MCP) integrations - Integrate Claude with enterprise systems, APIs, and tools - Integrate with data pipelines and RAG systems |
| Topic 7: Stakeholder Communication & Lifecycle Management | 14% | - Manage stakeholder feedback and expectation alignment - Conduct structured discovery and requirement gathering - Document architectures and support full lifecycle phases - Communicate architectural decisions and trade-offs |
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NEW QUESTION # 120
A Claude architect observes that after a recent model-version upgrade, grounded responses began including claims not supported by the retrieved source documents.
Which mitigation is most directly targeted at this failure mode?
Answer: A
Explanation:
The observed failure is a groundedness defect: the response contains claims that cannot be traced to retrieved evidence. Option A directly constrains generation to the supplied sources, requires visible attribution, and verifies that each material claim has supporting text. Unsupported claims should be removed, qualified, or replaced with an explicit statement that the available sources are insufficient. Regression evaluation in Option B may detect the failure but does not itself prevent unsupported claims. OAuth addresses identity and authorization, while input classifiers address malicious or unsafe retrieved content; neither verifies factual support. Anthropic recommends citations, supporting quotations, and post-generation claim verification to reduce hallucinations in document-grounded applications. Reducing hallucinations
NEW QUESTION # 121
You are integrating Claude Code into a workflow that runs against a production database.
Which guardrail design most directly preserves safety on data-modifying operations?
Answer: B
Explanation:
Option D applies three complementary controls. First, a read-only database credential creates an authorization boundary outside the model; prompt instructions alone cannot convert that credential into write access.
Second, restricting the subagent's tool list reduces capability exposure by preventing the agent from selecting unrelated or unnecessarily privileged operations. Third, explicit human confirmation creates a deliberate approval gate before any exceptional data-changing action is executed.
This is defense in depth. If Claude misinterprets a request or processes malicious instructions from untrusted content, the restricted credential and tool configuration limit the available action surface. Human review then protects operations with potentially irreversible production consequences. Logging and audit trails should remain enabled to record the actor, request, tool call, approval, affected records, and outcome.
Anthropic documents that Claude Code begins with read-only permissions in Manual mode and requests approval for actions that modify the environment. Its permission system also supports granular allow, ask, and deny controls for MCP tools and subagents. Claude Code Security , Configure Permissions Options A and B eliminate least privilege and approval boundaries. Option C removes essential detection and forensic evidence.
Study Guide references/topics: Production database safety; least privilege; read-only defaults; MCP permissions; subagent scoping; human confirmation; auditability.
NEW QUESTION # 122
You are comparing two configurations for an internal compliance Q & A assistant. Configuration X reduces top-k retrieval and uses a lighter model, lowering p95 latency by 38 percent while producing a measured 2 percent reduction in the accuracy benchmark. Configuration Y retains the existing top-k retrieval setting and heavier model, with unchanged p95 latency and no measurable change in accuracy. The deployment's stated priorities are accuracy first and latency second.
Which configuration is the better recommendation?
Answer: A
Explanation:
Configuration Y is the appropriate recommendation because architectural optimization must follow the deployment's explicitly defined priorities and acceptance criteria. Accuracy is the primary requirement for this compliance assistant, and Configuration X introduces a measured two-percent accuracy regression. That reduction cannot be dismissed as ordinary benchmark variation unless repeated evaluation establishes that it is statistically insignificant. In a compliance workload, even a small accuracy decline can increase incorrect guidance, missed policy requirements, human-review effort, and regulatory exposure. Configuration Y preserves the established accuracy level while maintaining the current latency profile. Although its latency does not improve, latency is explicitly the secondary objective. Configuration X could be reconsidered only if further testing eliminates the accuracy regression or stakeholders formally approve a revised trade-off.
Options C and D incorrectly impose a general preference for latency over the documented deployment priorities.
NEW QUESTION # 123
A solutions architect is analyzing stakeholder feedback collected after the first quarter of a Claude-powered procurement automation deployment. The feedback includes four statements: (1) "Our procurement team is processing 3x more purchase orders per analyst per day." (2) "We have eliminated the manual data entry role entirely and redeployed those staff to vendor relationship management." (3) "The API integration costs are running 40% over the projected per-transaction budget." (4) "Response latency during end-of-month batch runs is averaging 11 seconds, against our committed 5-second SLA." Which of the following correctly identifies the primary business value pillar each stakeholder statement represents?
Answer: A
Explanation:
Statement 1 measures efficiency because the same operating unit-one procurement analyst-now processes three times as many purchase orders per day. It reflects increased throughput and reduced effort per transaction within the existing procurement process.
Statement 2 represents transformation. The organization has not merely accelerated manual data entry; it has eliminated that role from the workflow and redirected employees toward higher-value vendor relationship management. This is a structural redesign of responsibilities and operating practices.
Statement 3 is a solution-cost issue because the measured API integration expense exceeds the approved per- transaction financial model by 40%. The architect must investigate token consumption, model routing, caching, retrieval overhead, tool calls, and integration charges while protecting the required quality level.
Statement 4 directly concerns the performance SLA. The observed 11-second latency is compared with an explicit contractual or operational target of five seconds. This is not simply an efficiency complaint; it is a measurable breach of a defined service-level commitment.
The architect should map each stakeholder statement to its dominant value pillar before recommending remediation because throughput, organizational transformation, cost control, and SLA compliance require different architectural responses.
Study Guide references/topics: Business-value pillars; efficiency; transformation; solution cost; performance SLAs; stakeholder-outcome classification.
NEW QUESTION # 124
You are selecting a model for a new production workload and must complete the upstream steps before testing candidate models empirically.
Which two steps must be completed BEFORE running a representative sample on a candidate model? (Select two.) Each correct answer presents part of the solution.
Answer: A,C
Explanation:
Empirical model testing requires a defined decision frame. Option D must occur first because the quality threshold, acceptable latency, expected request volume, and associated cost envelope determine what constitutes a successful result. Without these criteria, a representative-sample test can produce measurements but cannot support a defensible selection.
Option C is the next upstream step. Known model capabilities and the workload profile are used to identify a plausible candidate rather than testing models arbitrarily. Anthropic's model-selection guidance recommends evaluating capability, speed, cost, and effort requirements before narrowing the candidate set. Choosing the Right Model Option A occurs after empirical testing because the architect cannot know which lightest model consistently meets the quality bar until sample results have been evaluated. Option B belongs to ongoing lifecycle management after a new version becomes available. Option E is a deployment-governance activity that follows successful model selection, security review, and readiness validation.
The correct sequence is: define workload criteria, shortlist candidate models, run a representative evaluation, compare quality and operational metrics, select the least costly model that reliably satisfies all gates, and periodically retest the decision.
Study Guide references/topics: Requirements-driven model selection; representative sampling; quality thresholds; latency and volume requirements; capability-cost trade-offs; model lifecycle reassessment.
NEW QUESTION # 125
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