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| Section | Weight | Objectives |
|---|---|---|
| Evaluation, Testing & Optimization | 16% | - Evaluation metrics and datasets - Cost and performance optimization - Production monitoring and optimization - A/B testing - Evaluation framework design - System issue diagnosis |
| Developer Productivity & Operational Enablement | 7% | - Developer enablement - Claude tooling configuration for teams - Debugging and operational issue resolution - AI-assisted developer workflows |
| Stakeholder Communication & Lifecycle Management | 14% | - Solution lifecycle management - Stakeholder management - Architecture documentation - Service-level agreements - Communicating architectural decisions - Discovery and requirements gathering |
| Governance, Safety & Risk Management | 14% | - Security and risk management - Ethical AI considerations - Human-in-the-loop validation - AI safety and guardrails - Regulatory and compliance requirements |
| Solution Design & Architecture | 17% | - End-to-end architecture design - Alignment with business value, cost, performance, and SLAs - Decomposition techniques for complex problem solving - Multi-agent systems and orchestration - Translating business problems into Claude-based AI solutions - Architectural patterns
|
| Integration | 19% | - Claude integration mechanisms
- Authentication and authorization analysis - RAG pipeline design
|
| Claude Models, Prompting & Context Engineering | 13% | - System prompts and prompt templates - Guardrails - Claude model selection and trade-offs - Prompt reuse and context engineering strategies - Context window optimization |
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NEW QUESTION # 110
An architect at Trenova Systems, Inc. is reviewing two draft communication packages for the same architectural decision. Package 1 contains a threat model, residual-risk register, and control-mapping table.
Package 2 contains a list of capabilities delivered and feature-level roadmap dependencies.
Which two audiences are correctly matched to these packages? (Select two.)
Answer: B,E
Explanation:
Package 1 is designed for security and compliance review because its threat model identifies relevant threats and attack paths, its residual-risk register documents the risks remaining after controls, and its control- mapping table connects safeguards to organizational or regulatory requirements. Package 2 is designed for the product manager because delivered capabilities and roadmap dependencies directly support prioritization, release planning, sequencing, and lifecycle ownership. An engineering implementation team would ordinarily need component diagrams, interface contracts, configuration schemas, deployment instructions, and operational runbooks rather than primarily risk-governance artifacts. An executive sponsor generally needs a concise outcome, cost, risk, and decision summary instead of feature-level dependency details. Effective architecture communication must therefore adapt the content and level of detail to each audience's responsibilities and decision rights.
NEW QUESTION # 111
You are evaluating prompting claims in a peer's design document.
For each claim, select yes if the claim reflects sound practice. Otherwise, select no.
Answer:
Explanation:
Explanation:
Yes, Yes, No, Yes, No
Zero-shot prompting is a reasonable baseline for a clearly defined closed-set classifier because the model receives both the permissible labels and their meanings. Performance should then be measured against an evaluation set before additional prompt complexity is introduced. Few-shot examples are also sound for extraction because examples containing the exact field names demonstrate the required schema and reduce formatting ambiguity. Anthropic identifies examples as one of the most reliable methods for steering output format, structure, and consistency. Prompting Best Practices Chain-of-thought is not an unconditional default. Additional reasoning is appropriate when the task requires substantive decomposition or complex judgment, but routine classification and extraction may gain little while consuming more tokens and increasing latency. The technique should be selected according to evaluated task requirements.
An even-handed comparison governed by explicit criteria mitigates leading-question bias by requiring symmetrical treatment of alternatives rather than presupposing a preferred conclusion. Finally, prompt validation is model-specific. New model versions may follow instructions differently, change formatting behavior, alter tool selection, or produce different latency and cost characteristics. Anthropic's migration guidance consequently recommends reevaluating prompts and workloads against the new baseline. Model Migration Guide Study Guide references/topics: Zero-shot prompting; few-shot examples; reasoning techniques; neutral framing; model migration and regression evaluation.
NEW QUESTION # 112
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: B,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 # 113
You are assessing a Claude-based system whose dominant risk is silent quality drift on safety-relevant outputs after a model-version upgrade.
Which assessment activity most directly addresses this risk?
Answer: B
Explanation:
A stable adversarial regression set provides a controlled basis for detecting behavioral change between model versions. Version-attributed results show whether the proposed upgrade improves, preserves, or degrades performance on the same safety-relevant cases. The evaluation must run before promotion so a regression can block deployment rather than becoming a production incident. Randomly replacing the test inputs removes comparability and makes score changes difficult to attribute. Disabling evaluation or relying on complaints converts a preventable release-control failure into reactive incident handling. Anthropic characterizes regression evaluations as tests of whether an agent still handles tasks it previously completed and recommends maintaining them continuously to detect backsliding. Demystifying evals for AI agents
NEW QUESTION # 114
You are a solution architect designing a Claude-based assistant with access to 60 internal tools across multiple business domains. Loading every tool definition on every request increases token usage and time to first response.
Which design pattern best addresses this issue without sacrificing capability breadth?
Answer: C
Explanation:
Progressive tool discovery preserves the complete capability catalog while limiting initial context to a curated set of common tools and a discovery mechanism. When the task requires an additional capability, Claude searches the catalog and loads only the relevant tool definitions.
Anthropic's Tool Search mechanism implements this pattern through deferred loading. The context initially contains the search tool and any deliberately non-deferred tools; relevant definitions are expanded only when discovered. This reduces token consumption and helps maintain tool-selection accuracy in large catalogs.
Tool Search Tool
Option B adds a model call and still repeatedly processes all definitions, increasing latency and cost while potentially losing important schema details. Option C treats a larger context window as permission to waste context and does not address time-to-first-response overhead. Option D reduces capability breadth because the fixed five tools may be irrelevant to a given task.
The architect should provide clear tool and server descriptions, define which high-frequency tools remain immediately available, and evaluate discovery recall, selection accuracy, latency, and context savings across representative workflows.
Study Guide references/topics: Progressive discovery; deferred tool loading; MCP scaling; context optimization; tool-selection accuracy; on-demand capability loading.
NEW QUESTION # 115
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