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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Claude Models, Prompting & Context Engineering | 13% | - Mitigate prompt injection, leaks, and jailbreak risks - Apply context engineering and context management techniques - Select appropriate Claude models based on trade-offs - Design system prompts, templates, and guardrails |
| Topic 2: Governance, Safety & Risk Management | 14% | - Manage data privacy and security compliance - Ensure regulatory compliance (GDPR, HIPAA, etc.) - Address ethical AI considerations and bias mitigation - Implement guardrails and safety controls |
| Topic 3: Evaluation, Testing & Optimization | 16% | - Define evaluation metrics and success criteria - Implement iterative improvement pipelines - Optimize performance, prompting, and model selection - Test accuracy, reliability, latency, and cost |
| Topic 4: Stakeholder Communication & Lifecycle Management | 14% | - Communicate architectural decisions and trade-offs - Document architectures and support full lifecycle phases - Conduct structured discovery and requirement gathering - Manage stakeholder feedback and expectation alignment |
| Topic 5: Solution Design & Architecture | 17% | - Design multi-agent systems and orchestration strategies - Select architectural patterns: workflow, agentic, augmented LLM - Design end-to-end architectures and feedback loops - Translate business problems into Claude-based AI solutions - Align solutions to business value pillars |
| Topic 6: Developer Productivity & Operational Enablement | 7% | - Improve developer workflows with AI-assisted tooling - Configure Claude tools and environments for teams - Support debugging, monitoring, and operational resolution |
| Topic 7: Integration | 19% | - Implement Model Context Protocol (MCP) integrations - Design authentication, authorization, and observability - Integrate Claude with enterprise systems, APIs, and tools - Integrate with data pipelines and RAG systems |
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NEW QUESTION # 88
A security audit uncovers two issues: (1) all end users share a single API key, and (2) tool calls are executed without logging the initiating user.
Which two mitigations directly address these specific findings? (Select two.)
Answer: A,C
Explanation:
Per-user, scope-restricted OAuth tokens directly eliminate the shared-credential weakness. Each token represents a distinct user or delegated identity, carries only the permissions required for that user's role, and can be revoked independently. This supports least privilege, limits the blast radius of credential compromise, and enables authorization decisions to be tied to a specific principal instead of an undifferentiated shared API key.
Actor attribution in tool-call logs directly resolves the second finding. Each audit event should record the authenticated user, delegated service identity, session or request identifier, tool name, authorization decision, relevant resource, timestamp, and outcome. This establishes accountability and permits incident investigators to reconstruct who initiated a consequential action.
Moving credentials into a server-side secret store is sound secret-management practice, but it does not by itself correct the shared-identity problem: a centrally stored key can still represent every user as the same principal. Schema validation protects downstream processing, while retrieval-layer RBAC protects information access; neither addresses the two specific audit findings.
These controls should be reinforced by short-lived tokens, server-side authorization enforcement, sensitive- field redaction, and tamper-resistant audit-log retention.
Study Guide references/topics: [Claude Code security](https://docs.anthropic.com/en/docs/claude-code
/security); [MCP authentication and OAuth] (https://docs.anthropic.com/en/docs/claude-code/mcp); least privilege; identity propagation; auditable tool execution.
NEW QUESTION # 89
You must present an architectural recommendation to deploy a Claude-based contract review assistant to a steering committee that includes the CFO, the general counsel, and the CIO. Each stakeholder cares about different aspects of the decision.
How should you structure the recommendation document?
Answer: B
Explanation:
A steering committee needs an answer-first recommendation that states the proposed architectural decision, the business outcome it supports, and the approval or action required. After establishing that common decision frame, the document should address each stakeholder's concerns separately.
The CFO requires implementation and operating costs, expected savings, consumption assumptions, financial exposure, and cost-control mechanisms. General counsel needs evidence concerning confidentiality, privilege, data handling, human legal review, explainability, retention, and regulatory risk. The CIO needs integration architecture, security boundaries, availability, scalability, operational ownership, technical dependencies, and lifecycle support.
Option A begins at an implementation depth unsuitable for the entire committee. Option B overweights the CFO's concerns and delays the rationale required by the other decision-makers. Option C ignores audience- specific responsibilities and forces every stakeholder to extract relevant information from an undifferentiated narrative.
The recommended structure is: decision and executive rationale, expected outcomes, accepted trade-offs, stakeholder-specific impact sections, major risks and controls, implementation implications, success metrics, and the requested governance decision. Technical appendices can preserve component-level detail without overwhelming the principal recommendation.
Study Guide references/topics: Executive communication; stakeholder differentiation; decision-first structure; financial, legal, and technology concerns; architectural recommendations.
NEW QUESTION # 90
You are classifying chunking strategies by the corpus type each is best suited to.
For each chunking strategy, select the appropriate corpus type: "Long Structured Documents,"
"Heterogeneous Short Records," or "Code or Hierarchical Specifications."
Answer:
Explanation:
Explanation:
* Function-level or section-level chunking for code modules - Code or Hierarchical Specifications
* Tree-aware chunking that follows code or specification hierarchy - Code or Hierarchical Specifications
* Per-record chunking where each record is one chunk - Heterogeneous Short Records
* Semantic chunking along clause or paragraph boundaries - Long Structured Documents
* Fixed-size chunking with overlap for short records of similar length - Heterogeneous Short Records
* Hierarchical chunking that mirrors document section structure - Long Structured Documents Chunking must preserve the structural unit that carries meaning in the source corpus. Code and hierarchical specifications are best divided at function, module, class, or tree boundaries because arbitrary token cuts can separate definitions from their implementation or parent context. Heterogeneous short-record collections should generally preserve each record as an independent chunk. Fixed-size overlapping chunks are also effective when records have broadly similar lengths and lack meaningful internal hierarchy. Long structured documents benefit from semantic boundaries such as clauses and paragraphs, while hierarchical chunking preserves relationships among sections, subsections, and parent headings. Anthropic notes that chunk size, boundaries, and overlap materially affect retrieval performance; therefore, one universal chunking method is inappropriate. Anthropic Contextual Retrieval
NEW QUESTION # 91
A Claude architect at a health services organization is defining evaluation metrics for a clinical-summary pipeline. The pipeline must remain within a per-query cost ceiling and must never surface patient data to unauthorized roles.
Which two metrics directly address these requirements? (Select two.)
Answer: A,E
Explanation:
The evaluation metrics must map directly to the two stated requirements. Role-based access-control enforcement rate, tested against a red-team dataset, measures whether requests from unauthorized identities, roles, or access paths are consistently denied. It converts the privacy and authorization requirement into an observable security metric and exposes bypass conditions that ordinary functional tests may miss. Because the requirement says patient data must never reach unauthorized roles, the acceptance threshold should be effectively 100% enforcement across representative and adversarial cases.
Per-query token cost directly measures compliance with the financial constraint. The metric should include uncached input, cache reads and writes where applicable, output tokens, thinking tokens, and any other billable components attributed to the request. Results can then be compared with the defined ceiling across normal, boundary, and worst-case inputs.
Anthropic's evaluation guidance identifies privacy preservation and price as distinct success criteria and emphasizes that criteria must be specific, measurable, and relevant to the application. Define Success Criteria and Build Evaluations BLEU may assess textual similarity but does not test authorization or cost. Throughput and percentile latency are valuable operational metrics, yet neither directly answers the two requirements in the scenario.
Study Guide references/topics: Multidimensional evaluation; privacy preservation; authorization testing; red- team datasets; token-cost measurement; requirement-to-metric traceability.
NEW QUESTION # 92
A senior architect is managing stakeholder expectations for a Claude-based reporting assistant midway through development. Stakeholders have escalating concerns about response latency.
Which two actions most directly address stakeholder expectation alignment in this situation? (Select two.)
Answer: C,E
Explanation:
Expectation alignment begins with measured evidence. Option A gives stakeholders the median experience through p50 latency and the slower-tail experience through p95, then compares both with the agreed SLA.
The measurements should reflect representative input sizes, concurrency, retrieval activity, tool calls, geographic routing, and cache conditions.
If the target remains infeasible after reasonable optimization, Option E establishes the correct governance response. The architect should collaboratively revise the SLA, scope, cost envelope, model choice, or user- experience design rather than silently accepting a breach or making unilateral changes. Any revision should document the business impact and accepted trade-offs.
Option B commits all resources before the problem's severity, causes, and business priority have been established. Option C wrongly treats latency as uncontrollable; model selection, prompt length, retrieval depth, caching, streaming, and architecture can materially affect it. Option D introduces an unvalidated provider and could create quality, security, compliance, and integration regressions.
Expectation management is not merely communicating bad news. It requires transparent measurements, credible optimization options, explicit trade-offs, and jointly approved commitments that the production architecture can actually satisfy.
Study Guide references/topics: SLA alignment; p50 and p95 latency; stakeholder negotiation; evidence-based communication; architectural trade-offs; production constraints.
NEW QUESTION # 93
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