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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Evaluation, Testing & Optimization | 16% | - Implement iterative improvement pipelines - Define evaluation metrics and success criteria - Test accuracy, reliability, latency, and cost - Optimize performance, prompting, and model selection |
| Topic 2: Solution Design & Architecture | 17% | - Align solutions to business value pillars - Design multi-agent systems and orchestration strategies - Translate business problems into Claude-based AI solutions - Select architectural patterns: workflow, agentic, augmented LLM - Design end-to-end architectures and feedback loops |
| Topic 3: Stakeholder Communication & Lifecycle Management | 14% | - Communicate architectural decisions and trade-offs - Document architectures and support full lifecycle phases - Manage stakeholder feedback and expectation alignment - Conduct structured discovery and requirement gathering |
| Topic 4: Claude Models, Prompting & Context Engineering | 13% | - Apply context engineering and context management techniques - Design system prompts, templates, and guardrails - Mitigate prompt injection, leaks, and jailbreak risks - Select appropriate Claude models based on trade-offs |
| Topic 5: Integration | 19% | - Integrate with data pipelines and RAG systems - Design authentication, authorization, and observability - Implement Model Context Protocol (MCP) integrations - Integrate Claude with enterprise systems, APIs, and tools |
| Topic 6: Governance, Safety & Risk Management | 14% | - Implement guardrails and safety controls - Address ethical AI considerations and bias mitigation - Manage data privacy and security compliance - Ensure regulatory compliance (GDPR, HIPAA, etc.) |
| Topic 7: 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 |
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NEW QUESTION # 14
You are evaluating model-selection claims used by a peer team.
For each statement, select yes if the statement is generally true. Otherwise, select no.
Answer:
Explanation:
Explanation:
Yes, Yes, No, Yes, No
More capable reasoning configurations generally require greater computation, produce higher latency, and may consume larger token or rate-limit allocations than lighter alternatives. This makes the first statement generally accurate, although actual performance must be measured under the organization's specific provider and service tier.
Representative workload testing is essential because generic benchmark rankings do not establish performance on the organization's prompts, data, edge cases, tools, or required output format. Anthropic recommends benchmark tests specific to the use case, using actual prompts and data, followed by comparison of accuracy, quality, edge-case behavior, and cost. Choosing the Right Model The strongest model is not automatically the correct production choice. Model selection must balance capability, speed, cost, throughput, and operational constraints. Tiered routing implements this principle by serving predictable requests with an efficient model and escalating difficult cases to a more capable model.
Anthropic documents multi-model strategies in which lower-cost workers handle most traffic while harder decisions are escalated.
Recency is also not a valid selection criterion. A newly announced model must pass the workload's existing evaluation, security, latency, and cost gates before replacing a validated production model.
Study Guide references/topics: Model trade-offs; representative evaluations; tiered routing; escalation architectures; cost-capability optimization; model migration validation.
NEW QUESTION # 15
You are identifying the highest-impact optimization for a deployment whose token cost is dominated by a long, repeated system prompt and a large retrieved context per request.
Which optimization most directly targets the dominant cost driver?
Answer: A
NEW QUESTION # 16
You are compiling factors that should drive the choice between Model Context Protocol (MCP), direct API integration, and agent-to-agent handoff.
Which two factors belong on the list? (Select two.)
Each correct answer presents a complete solution.
Answer: D,E
Explanation:
The interaction model and portability requirement are architectural decision drivers. MCP is appropriate when tools or data sources must be exposed through a standardized interface reusable across compatible AI clients.
Direct API integration is often preferable for a narrow, stateless, latency-sensitive call where the application already owns the integration logic. Agent-to-agent handoff is better suited to stateful or longer-running delegation between independently responsible agents. Documentation quality and team familiarity influence implementation effort but do not determine the correct integration pattern. Encryption in transit is a mandatory security property for production integration rather than a differentiating architectural requirement; each viable approach must provide it. Anthropic distinguishes direct Messages access from stateful managed- agent infrastructure, while MCP supplies a standardized tool integration layer. Claude Platform documentation
NEW QUESTION # 17
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 # 18
You are building a feedback-and-alignment routine for a multi-stakeholder deployment.
Which two practices belong in the routine? (Select two.)
Each correct answer presents a complete solution.
Answer: D,E
Explanation:
Alignment is an ongoing governance process rather than a one-time approval. Option D creates a predictable cadence for reassessing objectives, constraints, assumptions, risks, service levels, and success measures as business and technical conditions change. Option E requires disagreements to be surfaced and reconciled explicitly, preserving decision traceability and preventing unresolved conflicts from reappearing during implementation or operation. The routine should document decisions, owners, accepted trade-offs, action items, and conditions that trigger reconsideration. Recording meetings may improve accessibility but does not itself produce alignment. Rotating facilitation is optional and may weaken accountability. Automatically escalating every disagreement to an executive sponsor bypasses normal architectural negotiation and should be reserved for material deadlocks.
Study Guide references/topics: Stakeholder alignment; feedback cadence; assumption management; conflict reconciliation; decision records; lifecycle governance.
NEW QUESTION # 19
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