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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Stakeholder Communication & Lifecycle Management | 14% | - Document architectures and support full lifecycle phases - Communicate architectural decisions and trade-offs - Manage stakeholder feedback and expectation alignment - Conduct structured discovery and requirement gathering |
| Topic 2: Integration | 19% | - Integrate with data pipelines and RAG systems - Integrate Claude with enterprise systems, APIs, and tools - Design authentication, authorization, and observability - Implement Model Context Protocol (MCP) integrations |
| Topic 3: Solution Design & Architecture | 17% | - Align solutions to business value pillars - Design multi-agent systems and orchestration strategies - Select architectural patterns: workflow, agentic, augmented LLM - Translate business problems into Claude-based AI solutions - Design end-to-end architectures and feedback loops |
| Topic 4: Governance, Safety & Risk Management | 14% | - Implement guardrails and safety controls - Manage data privacy and security compliance - Address ethical AI considerations and bias mitigation - Ensure regulatory compliance (GDPR, HIPAA, etc.) |
| Topic 5: Claude Models, Prompting & Context Engineering | 13% | - Mitigate prompt injection, leaks, and jailbreak risks - Select appropriate Claude models based on trade-offs - Apply context engineering and context management techniques - Design system prompts, templates, and guardrails |
| Topic 6: Developer Productivity & Operational Enablement | 7% | - Support debugging, monitoring, and operational resolution - Improve developer workflows with AI-assisted tooling - Configure Claude tools and environments for teams |
| Topic 7: Evaluation, Testing & Optimization | 16% | - Optimize performance, prompting, and model selection - Test accuracy, reliability, latency, and cost - Define evaluation metrics and success criteria - Implement iterative improvement pipelines |
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NEW QUESTION # 92
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 # 93
You are configuring Claude Code for a team that needs every engineer to share the same MCP server set, permission rules, and project context across the engineering monorepo.
Which configuration scope best supports this requirement?
Answer: A
Explanation:
Project scope is designed for configuration that must be shared by everyone working in a repository.
Committing the approved configuration provides versioning, review history, repeatable onboarding, and consistent MCP and permission behavior across the monorepo. User scope is intended primarily for individual preferences and personal rules, so independently maintained user files create configuration drift. Local scope affects only one person in one project and is therefore unsuitable for team-wide distribution. A lead architect's local configuration cannot establish a shared environment. Claude Code documentation specifically describes .
claude/settings.json as the shared project settings file that teams check into source control. Security-critical policies that must not be overridden should additionally be enforced through managed organizational settings rather than relying exclusively on repository configuration. Claude Code: Settings files and precedence
NEW QUESTION # 94
You are supporting a team whose Claude Code sessions consistently load 60 or more MCP tools from many servers, exhausting context budget before the session begins.
Which adjustment most directly addresses this issue without removing capability?
Answer: C
Explanation:
Tool Search applies progressive discovery to a large tool catalog. Instead of inserting every MCP tool's complete JSON schema and description into the initial context, Claude receives limited discovery information and loads the full definitions only when a task requires them. This preserves the available context for instructions, repository content, conversation history, and tool results without removing the underlying capabilities.
Anthropic's Claude Code documentation states that Tool Search keeps MCP context usage low by deferring tool definitions until Claude needs them. Only the tools actually selected enter the working context. Claude Code MCP Tool Search Anthropic's advanced-tool-use guidance also describes conventional multi-server configurations consuming tens of thousands of tokens before work begins, while on-demand discovery substantially reduces that overhead. Advanced Tool Use Option B solves context pressure by destroying required functionality. Option C worsens the constraint by adding more prompt tokens. Option D expands the exact source of context bloat.
The team should also improve server and tool descriptions so discovery returns the correct tools, monitor tool- selection quality, and keep frequently required foundational tools non-deferred only when evaluations justify the additional context cost.
Study Guide references/topics: MCP scaling; Tool Search; progressive discovery; deferred schemas; context- budget management; tool-selection accuracy.
NEW QUESTION # 95
You are integrating human review into a high-volume classification pipeline where reviewing every output is infeasible.
Which sampling strategy best balances throughput with quality oversight?
Answer: C
Explanation:
Risk-stratified sampling concentrates limited reviewer capacity where error consequences and uncertainty are greatest. All low-confidence and high-impact cases should receive mandatory review, while random sampling of routine high-confidence outputs provides an unbiased signal for drift, unexpected failure modes, and overconfident errors. Complaint-only monitoring discovers defects after harm occurs. Reviewing only high- confidence cases systematically ignores the most dangerous outputs. Universal review provides maximum coverage but contradicts the stated throughput constraint and may create queues that undermine service objectives. The sampling policy should define confidence calibration, impact categories, escalation thresholds, review SLAs, and periodic adjustment based on observed error rates. Reviewer decisions should feed the evaluation dataset so monitoring quality improves over time.
NEW QUESTION # 96
You are identifying inefficiency in a Claude Code workflow where each engineer manually re-explains the project's conventions and architecture in every session.
Which adjustment most directly removes this inefficiency?
Answer: A
Explanation:
A project-scoped CLAUDE.md converts repeatedly supplied information into persistent, version-controlled context. Claude Code loads applicable CLAUDE.md instructions at session initialization, allowing architecture principles, coding conventions, build commands, repository structure, and verification requirements to be shared consistently across engineers. Anthropic explicitly recommends using CLAUDE.
md for information that developers would otherwise explain repeatedly; concise and specific instructions provide stronger adherence. Committing the file also enables normal review and change-control practices.
Option C reduces typing speed but preserves the underlying waste and inconsistency. Options A and D remove useful capability or governance rather than correcting the workflow. The implementation should periodically review the file for obsolete, conflicting, or unnecessarily verbose instructions.
Study Guide references/topics: Claude Code project memory ; CLAUDE.md; persistent context; repository conventions; workflow standardization.
NEW QUESTION # 97
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