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| Section | Weight | Objectives |
|---|---|---|
| Integration | 19% | - Enterprise system integration - RAG pipeline design
- Claude integration mechanisms
|
| Governance, Safety & Risk Management | 14% | - AI safety and guardrails - Ethical AI considerations - Regulatory and compliance requirements - Human-in-the-loop validation - Security and risk management |
| Stakeholder Communication & Lifecycle Management | 14% | - Solution lifecycle management - Architecture documentation - Communicating architectural decisions - Stakeholder management - Discovery and requirements gathering - Service-level agreements |
| Solution Design & Architecture | 17% | - Translating business problems into Claude-based AI solutions - Alignment with business value, cost, performance, and SLAs - Architectural patterns
- Decomposition techniques for complex problem solving - End-to-end architecture design |
| Developer Productivity & Operational Enablement | 7% | - Debugging and operational issue resolution - AI-assisted developer workflows - Developer enablement - Claude tooling configuration for teams |
| Claude Models, Prompting & Context Engineering | 13% | - Guardrails - Context window optimization - Prompt reuse and context engineering strategies - Claude model selection and trade-offs - System prompts and prompt templates |
| Evaluation, Testing & Optimization | 16% | - Evaluation framework design - System issue diagnosis - Production monitoring and optimization - Cost and performance optimization - A/B testing - Evaluation metrics and datasets |
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NEW QUESTION # 125
You are compiling continuity practices that span the deployment lifecycle.
Which two practices belong on the list? (Select two.)
Each correct answer presents a complete solution.
Answer: A,E
Explanation:
Lifecycle continuity depends on preserving validated knowledge and feeding operational learning back into subsequent phases. Carrying the evaluation framework and reference set forward, as stated in Option B, creates a stable baseline across prompt changes, model migrations, retrieval adjustments, and architectural revisions. Rebuilding the evaluation system each time would undermine longitudinal comparison because changes in the test framework could be mistaken for changes in solution performance.
Option D establishes the second essential continuity mechanism: lessons from discovery, design, implementation, deployment, and production monitoring become explicit inputs to the next phase. This closes the feedback loop and prevents recurring defects, invalid assumptions, and operational findings from being lost at organizational handoffs.
Option A is overly mechanical. Stakeholders should receive communications relevant to their responsibilities and decision rights, not indiscriminate notifications at every transition. Option C confuses comprehensive archival with lifecycle continuity; retention must follow business, regulatory, security, and records- management requirements rather than an unconditional "archive everything" policy. Option E is directly contrary to iterative architecture. Decisions should be documented and governed, but material evidence or changed requirements must be allowed to reopen them.
Study Guide references/topics: Lifecycle phases; evaluation continuity; reference datasets; feedback loops; lessons learned; decision records; iterative architecture governance.
NEW QUESTION # 126
You are sequencing decomposed components in an invoice-processing pipeline.
For each of the decomposed components, select the execution layer it belongs to: "Pre-Processing," "Model Stage," or "Post-Processing."
Answer:
Explanation:
Explanation:
Model Stage, Post-Processing, Post-Processing, Model Stage, Pre-Processing, Pre-Processing Pre-processing prepares source material before Claude receives it. Optical character recognition converts scanned invoice images into machine-readable text. Because PII redaction is explicitly performed before model invocation, it also belongs in pre-processing. Additional activities at this layer can include file validation, malware scanning, normalization, page separation, and metadata extraction.
The model stage contains tasks requiring Claude's language-understanding capability. Classifying the invoice type involves interpreting textual and contextual features, while extracting structured invoice fields requires mapping unstructured content into defined business attributes.
Post-processing verifies and commits the model's result. Schema validation confirms that required fields exist, data types are correct, enumerated values are permitted, and structural constraints are satisfied.
Persistence must occur only after validation and any required human review because the system of record should not receive malformed or unapproved model output.
This decomposition separates probabilistic inference from deterministic processing. OCR, redaction, validation, and persistence do not need to be delegated to Claude when conventional components can execute them more predictably. The resulting architecture reduces model workload, strengthens privacy controls, improves auditability, and prevents unvalidated output from directly changing authoritative records.
Study Guide references/topics: Task decomposition; pre-processing; model inference; post-processing; deterministic validation; privacy-by-design; system-of-record protection.
NEW QUESTION # 127
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: A,B
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 # 128
A Claude architect is designing a HIPAA-compliant pipeline that processes patient records.
Which two design decisions directly support HIPAA compliance requirements? (Select two.)
Answer: C,D
Explanation:
Role-based access control directly supports HIPAA's access-control and minimum-necessary principles. The retrieval and orchestration layers must verify the authenticated user's role before protected health information enters the model context. Authorization should be applied to individual records, data sources, tools, and actions, with audit events recording the requesting identity, accessed resource, purpose, and result. Model instructions alone are not a security boundary.
Patient information must also remain within services and processing activities covered by the organization's Business Associate Agreement. Anthropic states that PHI processing requires a HIPAA-ready organization and an accepted BAA, and that only specified eligible services and configurations are covered. Patient data must not be submitted through training, feedback, beta, third-party, or integration pathways that fall outside the applicable agreement. A BAA is not blanket authorization; architects must verify feature eligibility and disable inappropriate data-sharing mechanisms.
Reducing max_tokens, selecting a more capable model, and enabling streaming affect output length, quality, or latency. They do not establish authorization, contractual coverage, minimum-necessary access, or compliant PHI handling.
Study Guide references/topics: Anthropic Business Associate Agreement requirements ; HIPAA-ready services; PHI access control; minimum necessary; eligible-service boundaries; auditability.
NEW QUESTION # 129
A healthcare organization is evaluating two Claude-powered AI architectures for a clinical documentation assistant. Architecture X produces higher output quality scores but costs $0.18 per documentation session and averages 4.2 seconds per response. Architecture Y scores slightly lower on quality metrics but costs $0.09 per session and averages 2.1 seconds per response. The stated SLA requires responses under 3 seconds, and the annual volume is projected at 2 million documentation sessions.
Which evaluation approach correctly applies business value pillar analysis to this decision?
Answer: A
Explanation:
Architecture X fails a stated production gate: its 4.2-second average exceeds the required three-second response SLA. It should therefore not remain a qualifying architecture unless it is redesigned and retested before selection. A promise to optimize after deployment is not evidence of compliance.
Architecture Y meets the latency requirement at 2.1 seconds. Its annual inference cost is $180,000 at two million sessions, compared with $360,000 for Architecture X-a difference of $180,000 annually. However, cost alone does not establish suitability. The organization must determine whether Y's lower quality score causes material omissions, correction effort, clinician dissatisfaction, documentation risk, or reduced workflow productivity.
Option C correctly treats the SLA as a threshold and then analyzes the remaining architecture across cost, efficiency, quality, and productivity. Option A ignores clinical quality. Option B disregards an explicit SLA failure. Option D may eventually be viable, but it introduces routing complexity and leaves unanswered how complex cases are detected, whether X's latency becomes acceptable for them, and how both paths are evaluated.
The final choice should be gated by clinical-quality evaluation, human review requirements, safety metrics, operational latency, and total annual cost.
Study Guide references/topics: Business-value pillars; performance gates; solution cost; workflow efficiency; quality trade-offs; healthcare architecture evaluation.
NEW QUESTION # 130
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