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| Section | Weight | Objectives |
|---|---|---|
| Solution Design & Architecture | 17% | - Multi-agent systems and orchestration - Architectural patterns
- Translating business problems into Claude-based AI solutions - Alignment with business value, cost, performance, and SLAs - End-to-end architecture design |
| Evaluation, Testing & Optimization | 16% | - Cost and performance optimization - Production monitoring and optimization - Evaluation framework design - A/B testing - Evaluation metrics and datasets - System issue diagnosis |
| 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% | - Context window optimization - Claude model selection and trade-offs - System prompts and prompt templates - Guardrails - Prompt reuse and context engineering strategies |
| Integration | 19% | - Authentication and authorization analysis - Claude integration mechanisms
|
| Governance, Safety & Risk Management | 14% | - AI safety and guardrails - Security and risk management - Regulatory and compliance requirements - Ethical AI considerations - Human-in-the-loop validation |
| Stakeholder Communication & Lifecycle Management | 14% | - Solution lifecycle management - Discovery and requirements gathering - Architecture documentation - Communicating architectural decisions - Stakeholder management - Service-level agreements |
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NEW QUESTION # 115
You are responding to a stakeholder request that adds significant scope to a deployment already in flight.
Which response best aligns expectations while respecting the stakeholder's underlying need?
Answer: C
Explanation:
Option C preserves both transparency and stakeholder agency. The architect acknowledges the underlying business need while making the delivery consequences explicit. Presenting controlled alternatives converts an unbounded request into a governed decision: defer the capability, exchange it for existing scope, or accept a later release date. The selected option should be documented with revised success criteria, dependencies, risk, cost, ownership, and approval. Concealing the request prevents accurate planning and creates unmanaged delivery risk. Rejecting it without exploring alternatives ignores legitimate stakeholder value. Quietly absorbing additional work produces scope creep and makes later delays appear unexpected. Effective lifecycle communication does not promise every requested capability; it presents the trade-offs necessary for an informed decision.
Study Guide references/topics: Scope governance; expectation alignment; transparent trade-offs; change control; stakeholder decision rights.
NEW QUESTION # 116
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: B,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 # 117
The compliance team has authored a regulatory disclosure procedure that must be applied identically across customer service, sales, and onboarding workflows. The procedure changes when regulators issue updates, currently four to six times per year. You are designing how the procedure will be packaged for use by Claude across all three workflows.
Which two design decisions should you include? (Select two.)
Each correct answer presents part of the solution.
Answer: C,D
Explanation:
The procedure should have one authoritative implementation and one accountable owner. Packaging it as a compliance-owned Skill allows the instructions, examples, templates, and prohibited patterns to be maintained together. Referencing that same Skill from all three workflows ensures that updates propagate consistently without requiring separate prompt changes. Embedding copies in multiple system prompts or allowing workflow teams to rewrite the procedure creates configuration drift and inconsistent regulatory behavior. A retrieval corpus is appropriate for searchable reference material, but the requirement concerns a fixed operational procedure that Claude must follow, making a Skill the stronger abstraction. The Skill should be versioned, reviewed, tested, and released through a controlled publication process. Claude Code Skills
NEW QUESTION # 118
You are classifying token-management tactics by where each tactic applies in the request lifecycle: "Input Preparation," "Prompt Construction," or "Output Handling."
Answer:
Explanation:
Explanation:
* Persist the validated output for downstream consumption and audit - Output Handling
* Order prompt sections so cacheable content appears before per-request content - Prompt Construction
* Summarize prior conversation history when full history is no longer needed - Input Preparation
* Validate the model's structured output against the expected schema - Output Handling
* Move stable repeated content into a cacheable prefix at the beginning of the prompt - Prompt Construction
* Trim retrieved passages to spans relevant to the user's question - Input Preparation Input preparation determines what evidence and history should enter the request, so summarization and retrieval trimming belong there. Prompt construction determines ordering and cache boundaries; stable repeated instructions must precede dynamic per-request content to maximize cache reuse. Output handling begins after generation and includes schema validation, persistence, auditing, and downstream delivery.
Mixing these responsibilities creates inefficient prompts and weak validation boundaries. Anthropic's context guidance emphasizes curating the smallest useful context because unnecessary tokens can reduce recall and accuracy. Prompt caching similarly depends on a stable reusable prefix, while structured outputs or schema validation protect downstream systems from malformed responses. Context windows ; prompt caching
NEW QUESTION # 119
You are reviewing a peer's end-to-end design for a Claude-based platform expected to scale to thousands of concurrent users.
For each statement, indicate Yes if it reflects sound architectural practice. Otherwise, select No.
Answer:
Explanation:
Explanation:
* Authentication and authorization run before retrieval so retrieval can filter by identity - Yes
* An asynchronous queue absorbs bursty traffic between intake and the model-invocation layer - Yes
* Tax computation is encoded directly in the system prompt rather than in code - No
* Conversation logs include unredacted government identifiers to maximize tuning signal - No Authentication and authorization must precede retrieval so unauthorized information never enters model context. An asynchronous queue is appropriate for burst absorption, backpressure, controlled concurrency, and retry management at scale. Deterministic tax computation should be implemented in validated code or a controlled calculation tool, not delegated to probabilistic prompt interpretation. Including unredacted government identifiers in conversation logs violates data-minimization principles and creates unnecessary privacy, security, and regulatory exposure. Sensitive fields should be removed, tokenized, or redacted before logging or model use unless specifically required and authorized. The resulting design separates deterministic computation, access control, scalable orchestration, and language reasoning into appropriate architectural layers.
NEW QUESTION # 120
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