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| Section | Weight | Objectives |
|---|---|---|
| Solution Design & Architecture | 17% | - Design end-to-end architectures and feedback loops - Select architectural patterns: workflow, agentic, augmented LLM - Design multi-agent systems and orchestration strategies - Translate business problems into Claude-based AI solutions - Align solutions to business value pillars |
| Developer Productivity & Operational Enablement | 7% | - Support debugging, monitoring, and operational resolution - Configure Claude tools and environments for teams - Improve developer workflows with AI-assisted tooling |
| Claude Models, Prompting & Context Engineering | 13% | - Mitigate prompt injection, leaks, and jailbreak risks - Design system prompts, templates, and guardrails - Apply context engineering and context management techniques - Select appropriate Claude models based on trade-offs |
| Evaluation, Testing & Optimization | 16% | - Test accuracy, reliability, latency, and cost - Optimize performance, prompting, and model selection - Implement iterative improvement pipelines - Define evaluation metrics and success criteria |
| Stakeholder Communication & Lifecycle Management | 14% | - Conduct structured discovery and requirement gathering - Document architectures and support full lifecycle phases - Communicate architectural decisions and trade-offs - Manage stakeholder feedback and expectation alignment |
| Integration | 19% | - Design authentication, authorization, and observability - Integrate Claude with enterprise systems, APIs, and tools - Integrate with data pipelines and RAG systems - Implement Model Context Protocol (MCP) integrations |
| Governance, Safety & Risk Management | 14% | - Ensure regulatory compliance (GDPR, HIPAA, etc.) - Manage data privacy and security compliance - Implement guardrails and safety controls - Address ethical AI considerations and bias mitigation |
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NEW QUESTION # 25
You are distinguishing functional from non-functional requirements during discovery.
Which item is a non-functional requirement?
Answer: C
Explanation:
Option D defines a measurable performance characteristic rather than a business capability. The requirement specifies a percentile-based latency threshold-under 800 milliseconds at the 95th percentile-and ties that threshold to the expected workload volume. It therefore describes how well the system must operate under defined conditions.
Options A, B, and C are functional requirements. They describe actions the solution must perform: extracting fields and creating a downstream record, producing an editable draft, and assigning tickets to categories.
Functional requirements define observable system behaviors or outputs.
A strong non-functional requirement must include a metric, threshold, measurement method, and operating condition. For Option D, the architect should further define whether latency is measured end-to-end or only at the model API, the test duration, concurrency, input-size distribution, cache state, timeout behavior, geographic region, and treatment of failed requests. Without those details, teams may report incompatible results while claiming to satisfy the same requirement.
Non-functional requirements for Claude solutions commonly address latency, availability, throughput, cost, privacy, security, recoverability, observability, scalability, and regulatory compliance.
Study Guide references/topics: Structured discovery; functional requirements; non-functional requirements; p95 latency; workload conditions; measurable acceptance criteria.
NEW QUESTION # 26
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: C,E
NEW QUESTION # 27
You are classifying token-management tactics by where in the request lifecycle each tactic applies.
For each tactic, select where in the request lifecycle it applies: Input Preparation , Prompt Construction , or Output Handling .
Answer:
Explanation:
Explanation:
Input Preparation reduces the amount of unnecessary information before the request is assembled.
Summarizing older conversation history and trimming retrieved passages preserve relevant context while reducing token consumption. Prompt Construction determines how prepared content is organized for the model. Stable instructions and repeated reference material should appear in a cacheable prefix, while variable per-request content follows afterward, improving prompt-cache reuse and lowering processing cost. Output Handling begins after Claude generates the response. Structured output must be validated against the required schema before downstream systems consume it. Once validated, the result can be persisted for later processing, audit, or compliance purposes. Correctly separating these tactics prevents validation and persistence from being confused with input optimization while ensuring that caching decisions are implemented during prompt assembly rather than during retrieval or post-processing.
NEW QUESTION # 28
You are integrating Claude Code into a workflow that runs against a production database.
Which guardrail design most directly preserves safety on data-modifying operations?
Answer: D
Explanation:
Option D applies three complementary controls. First, a read-only database credential creates an authorization boundary outside the model; prompt instructions alone cannot convert that credential into write access.
Second, restricting the subagent's tool list reduces capability exposure by preventing the agent from selecting unrelated or unnecessarily privileged operations. Third, explicit human confirmation creates a deliberate approval gate before any exceptional data-changing action is executed.
This is defense in depth. If Claude misinterprets a request or processes malicious instructions from untrusted content, the restricted credential and tool configuration limit the available action surface. Human review then protects operations with potentially irreversible production consequences. Logging and audit trails should remain enabled to record the actor, request, tool call, approval, affected records, and outcome.
Anthropic documents that Claude Code begins with read-only permissions in Manual mode and requests approval for actions that modify the environment. Its permission system also supports granular allow, ask, and deny controls for MCP tools and subagents. Claude Code Security , Configure Permissions Options A and B eliminate least privilege and approval boundaries. Option C removes essential detection and forensic evidence.
Study Guide references/topics: Production database safety; least privilege; read-only defaults; MCP permissions; subagent scoping; human confirmation; auditability.
NEW QUESTION # 29
You are compiling guardrail tactics for a customer-facing assistant.
Which two tactics belong on the guardrail list?
Each correct answer presents a complete solution.
Answer: A,B
Explanation:
Option C introduces a deterministic validation boundary between probabilistic model output and downstream execution. Structured validation can reject missing fields, invalid types, unauthorized actions, malformed arguments, and values outside approved enumerations before any tool or business process acts on the response. Anthropic recommends Structured Outputs when guaranteed schema conformance is required.
Increase Output Consistency
Option D implements defense in depth. Prompt-level instructions establish intended behavior, while runtime classifiers, content filters, policy engines, output validators, tool permissions, and human confirmation gates provide controls outside the model. Anthropic's guardrail guidance recommends combining safeguards rather than depending on one mechanism. Mitigate Jailbreaks and Prompt Injections Option A creates a bypass mechanism that adversaries may discover or imitate. Option B may alter output variability but is not a security boundary and cannot guarantee policy compliance. Option E places complete reliance on a system prompt, which remains vulnerable to ambiguity, conflicting inputs, model errors, and indirect prompt injection.
Guardrails should be risk-based, independently enforceable where possible, observable, tested against adversarial cases, and proportional to the consequences of downstream actions.
Study Guide references/topics: Layered guardrails; structured validation; runtime content checks; prompt injection; deterministic enforcement; defense in depth.
NEW QUESTION # 30
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