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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Solution Design & Architecture | 17% | - Design end-to-end architectures and feedback loops - Align solutions to business value pillars - Translate business problems into Claude-based AI solutions - Design multi-agent systems and orchestration strategies - Select architectural patterns: workflow, agentic, augmented LLM |
| 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: Stakeholder Communication & Lifecycle Management | 14% | - Manage stakeholder feedback and expectation alignment - Document architectures and support full lifecycle phases - Conduct structured discovery and requirement gathering - Communicate architectural decisions and trade-offs |
| Topic 4: Evaluation, Testing & Optimization | 16% | - Test accuracy, reliability, latency, and cost - Implement iterative improvement pipelines - Optimize performance, prompting, and model selection - Define evaluation metrics and success criteria |
| Topic 5: Integration | 19% | - Integrate Claude with enterprise systems, APIs, and tools - Design authentication, authorization, and observability - Implement Model Context Protocol (MCP) integrations - Integrate with data pipelines and RAG systems |
| Topic 6: 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 7: Claude Models, Prompting & Context Engineering | 13% | - Apply context engineering and context management techniques - Select appropriate Claude models based on trade-offs - Design system prompts, templates, and guardrails - Mitigate prompt injection, leaks, and jailbreak risks |
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NEW QUESTION # 100
You are integrating Claude Code into a team workflow and must complete the design and configuration steps before piloting the integrated workflow with a small group.
Which two steps must be completed BEFORE piloting the integrated workflow? (Select two.) Each correct answer presents part of the solution.
Answer: B,D
Explanation:
The pilot must test a deliberately designed workflow, not technology added without role boundaries. Option B identifies where Claude provides measurable value and where approval, accountability, or consequential decisions must remain human responsibilities. Option E establishes the technical environment required for consistent pilot execution: repository-shared MCP servers, scoped permissions, specialized subagents, and persistent project instructions. Iteration in Option D necessarily follows observed pilot findings. Formal approval from every manager is unnecessarily broad unless required by organizational governance. Complete runbooks and final handoff documentation mature after the workflow has been validated, although essential pilot procedures must exist. Anthropic documents project-level instructions, permissions, MCP servers, and subagents as complementary mechanisms for team workflows. Claude Code extension overview
NEW QUESTION # 101
You are selecting a pattern for a compliance Q & A assistant that must answer policy questions with citations to the authoritative internal source set. Latency, cost, and audit predictability are prioritized.
Which pattern is the best fit?
Answer: B
Explanation:
A constrained retrieval-augmented generation architecture best satisfies the grounding, citation, latency, cost, and audit requirements. The system first indexes the approved internal policy corpus. At request time, it retrieves a small set of relevant passages, supplies those passages to Claude with stable source identifiers, and requires the answer to cite the supporting material. Anthropic's search-result content blocks are specifically designed for this pattern: they allow custom RAG systems to provide source-attributed internal content and enable Claude to render citations against those results.
The retrieval boundary is critical. Only approved and version-controlled policy sources should be searchable, with document identifiers, effective dates, access controls, retrieval scores, and cited passages retained for audit reconstruction. This produces substantially more predictable evidence than unconstrained web research.
A planner-researcher-writer system introduces unnecessary model calls, orchestration complexity, cost, latency, and behavioral variance for routine policy lookup. Open-web browsing violates the authoritative- source requirement and increases prompt-injection and provenance risk. Concatenating the complete corpus into every prompt wastes tokens, increases latency, and can reduce retrieval precision as the corpus expands.
Study Guide references/topics: Search-result blocks for cited RAG ; Claude citations ; authoritative-corpus retrieval; source attribution; auditable context engineering.
NEW QUESTION # 102
You are supporting an EU-based deployment with GDPR obligations.
Which combination of measures best supports the deployment's GDPR posture?
Answer: D
Explanation:
Option A combines the contractual, technical, and operational measures relevant to a defensible GDPR posture. For commercial services, the Data Processing Addendum defines processor obligations and incorporates safeguards such as Standard Contractual Clauses where applicable. Anthropic states that its DPA is incorporated into its Commercial Terms, while the customer remains responsible for determining lawful purposes, issuing processing instructions, and fulfilling controller obligations.
A defined retention configuration ensures personal data is not retained indefinitely without a documented purpose. Redacting personal information that is unnecessary for the task implements data minimization and reduces exposure in prompts, logs, retrieval stores, and model outputs. Documented data-subject-rights procedures support access, correction, deletion, restriction, and other applicable requests by ensuring the organization can locate and act on relevant records.
Enterprise deployment alone does not establish compliance; the organization must configure and govern the service consistently with its processing activities, risk assessment, lawful basis, and contractual commitments.
Options B, C, and D intentionally remove those controls or promote excessive collection.
Study Guide references/topics: [Anthropic Data Processing Addendum guidance](https://privacy.anthropic.
com/en/articles/7996862-how-do-i-view-and-sign-your-data-processing-addendum-dpa); [commercial data- retention practices] (https://privacy.anthropic.com/en/articles/7996866-how-long-do-you-store-my- organization-s-data); GDPR data minimization; retention governance; data-subject-rights procedures.
NEW QUESTION # 103
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: A,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 # 104
A customer support team has proposed delegating customer refund decisions to a Claude-driven workflow with no human review for refunds under 50 USD. The team's reasoning is that small refunds are low-risk and human review would erase the efficiency gain.
Which Delegation-competency principle should guide your response?
Answer: A
Explanation:
Transaction value is only one component of risk. Even a small refund can create fraud exposure, discriminatory outcomes, contractual violations, account compromise, policy inconsistency, or cumulative financial loss. Delegation should therefore depend on the nature, detectability, reversibility, and aggregate impact of failure-not a monetary threshold alone. Option B supports risk-stratified automation: routine, well- evidenced cases may proceed automatically, while anomalous, identity-sensitive, disputed, or policy-edge cases require review or escalation. Anthropic's trustworthy-agent principles emphasize maintaining meaningful human control rather than imposing universal review or unrestricted autonomy. Option A is unnecessarily absolute; Option C prioritizes efficiency over governance; and Option D prohibits potentially safe, controlled automation without risk analysis.
Study Guide references/topics: Delegation competency; human control; risk classification; reversibility; cumulative exposure; escalation design.
NEW QUESTION # 105
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