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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Stakeholder Communication & Lifecycle Management | 14% | - Communicate architectural decisions and trade-offs - Conduct structured discovery and requirement gathering - Manage stakeholder feedback and expectation alignment - Document architectures and support full lifecycle phases |
| Topic 2: Evaluation, Testing & Optimization | 16% | - Optimize performance, prompting, and model selection - Implement iterative improvement pipelines - Test accuracy, reliability, latency, and cost - Define evaluation metrics and success criteria |
| Topic 3: 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 4: Solution Design & Architecture | 17% | - Select architectural patterns: workflow, agentic, augmented LLM - Align solutions to business value pillars - Design end-to-end architectures and feedback loops - Translate business problems into Claude-based AI solutions - Design multi-agent systems and orchestration strategies |
| Topic 5: Claude Models, Prompting & Context Engineering | 13% | - Select appropriate Claude models based on trade-offs - Design system prompts, templates, and guardrails - Mitigate prompt injection, leaks, and jailbreak risks - Apply context engineering and context management techniques |
| Topic 6: Integration | 19% | - Integrate with data pipelines and RAG systems - Design authentication, authorization, and observability - Integrate Claude with enterprise systems, APIs, and tools - Implement Model Context Protocol (MCP) integrations |
| Topic 7: Developer Productivity & Operational Enablement | 7% | - Configure Claude tools and environments for teams - Improve developer workflows with AI-assisted tooling - Support debugging, monitoring, and operational resolution |
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NEW QUESTION # 59
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: B
Explanation:
Progressive tool discovery preserves the complete capability catalog while limiting initial context to a curated set of common common 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 implements this pattern through deferred loading. The context initially contains the search search 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. ToolTool Search Tool Option B adds a model call and still repeatedly processes all definitions, increasing latency latency 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 server server descriptions, define which high-frequency tools remain immediately available, and evaluate discovery recall, selection accuracy
NEW QUESTION # 60
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: D
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 # 61
You are transitioning a Claude-based deployment from design into implementation.
Which handoff package most directly supports a clean transition?
Answer: A
Explanation:
Option C provides the minimum coherent package required to move from architectural intent to implementable and supportable delivery. The architecture overview establishes system boundaries and component relationships. Architecture Decision Records preserve the context and trade-offs behind key choices. Component contracts define interfaces, schemas, responsibilities, failure behavior, and integration assumptions.
The evaluation framework and reference set allow the implementation team to confirm that prompts, models, retrieval components, and tool integrations continue to meet the defined quality, safety, latency, and cost thresholds. Runbooks translate operational knowledge into repeatable procedures, while the on-call playbook defines detection, escalation, containment, and recovery actions. The known-limitations register prevents unsupported behavior from being mistaken for an implementation defect and helps stakeholders manage residual risk.
Options A and B depend excessively on slides or undocumented verbal knowledge. Option D provides implementation material without explaining the system-level decisions, operating model, acceptance criteria, or limitations. Source code cannot substitute for architectural and operational documentation.
A clean transition does not mean the architect can never be consulted. It means routine implementation and support do not depend on undocumented knowledge held by a single individual.
Study Guide references/topics: Design-to-implementation handoff; ADRs; component contracts; reference evaluations; runbooks; operational playbooks; limitations management.
NEW QUESTION # 62
You are designing a test strategy for a Claude-based pipeline that handles sensitive financial data.
Which two test types should be prioritized to cover both safety under attack and cross-component correctness? (Select two.)
Answer: B,C
Explanation:
Adversarial tests directly evaluate behavior under attack, including prompt injection, malformed records, malicious document content, credential-extraction attempts, and unauthorized tool requests. Integration tests provide the complementary coverage required by the question: they verify authentication, retrieval, prompt construction, model invocation, validation, logging, and downstream actions as one end-to-end system.
Regression, smoke, and unit testing remain valuable, but they do not jointly satisfy the two stated objectives.
A stable regression set measures previously established behavior; smoke tests provide shallow availability confirmation; and prompt-rendering unit tests cover only one component. Anthropic recommends explicit prompt-injection defenses and task-specific evaluations that represent both normal and edge-case traffic.
Prompt-injection mitigation
NEW QUESTION # 63
Engineering leadership wants to roll out Claude Skills to 280 developers across 14 teams. Skills will encode internal coding standards, code-review checklists, and incident-postmortem templates. Leadership has asked how to govern Skill authorship so that Skills remain trustworthy without bottlenecking on a single central team.
Which governance model should you recommend?
Answer: B
Explanation:
Federated authorship allows each domain team to maintain the procedural knowledge it understands while preserving organization-wide trust through a central publication gate. Team authors can update coding standards, review practices, and postmortem procedures without waiting for a single platform group to write every change. Central reviewers can validate ownership, security, tool permissions, duplication, versioning, testing evidence, and compliance before publication. Per-developer or fully decentralized publication creates inconsistent and potentially unsafe Skills. Fully centralized authorship becomes a scalability bottleneck and separates content maintenance from domain expertise. Anthropic describes Skills as packages of instructions, scripts, and resources and warns that repository Skills may grant broad tool access, making formal review essential. Claude Code Skills
NEW QUESTION # 64
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