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| Section | Objectives |
|---|---|
| Topic 1: Stakeholder Engagement and Solution Lifecycle | - Stakeholder discovery and architectural trade-off communication - Solution lifecycle, handoff, adoption, and operational enablement |
| Topic 2: Governance, Safety, and Risk | - Safety controls and fail-closed system design - Security, compliance, risk management, and governance |
| Topic 3: Solution Design | - Claude platform and solution architecture - Model, architecture, context, and deployment strategy selection |
| Topic 4: Evaluation and Optimization | - Model and architecture optimization - Evaluation design and acceptance criteria |
| Topic 5: Enterprise Integration and Production | - Enterprise integration architecture and production readiness - Cost, latency, reliability, and operational design |
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NEW QUESTION # 10
You are integrating AI-assisted tooling into the team's documentation workflow. The team wants generated documentation that stays grounded in the actual code.
Which integration approach best fits this requirement?
Answer: A
Explanation:
Documentation remains grounded only when the generating agent can inspect the authoritative implementation. A purpose-built subagent should receive scoped filesystem and code-search capabilities, identify the relevant modules, interfaces, configuration files, tests, and call sites, and generate documentation from that evidence. This approach minimizes reliance on training-data recall, which cannot represent the repository's current private code or recent changes.
Subagents are useful because repository exploration occurs in their own context, allowing them to return focused findings or proposed edits without filling the main conversation with every file read. Their tool access should follow least privilege: read access to required paths, narrowly controlled write access, and explicit exclusions for secrets or unrelated repositories.
Generated documentation should enter the team's established change-control process as a patch, branch, or pull request. Normal review, automated checks, link validation, example execution, and human approval provide accountability and prevent unverified material from being published. Direct publication bypasses these safeguards, while disabling repository tools makes factual grounding impossible.
Study Guide references/topics: [Claude Code custom subagents](https://docs.anthropic.com/en/docs/claude- code/sub-agents); [codebase exploration workflows] (https://docs.anthropic.com/en/docs/claude-code
/common-workflows); source-grounded generation; least-privilege tools; human review and lifecycle controls.
NEW QUESTION # 11
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: B,C
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 # 12
You are classifying chunking strategies by the corpus type each is best suited to.
For each chunking strategy, select the appropriate corpus type: "Long Structured Documents,"
"Heterogeneous Short Records," or "Code or Hierarchical Specifications."
Answer:
Explanation:
Explanation:
Function-level or section-level chunking for code modules - Code or Hierarchical Specifications Tree-aware chunking that follows code or specification hierarchy - Code or Hierarchical Specifications Per-record chunking where each record is one chunk - Heterogeneous Short Records Semantic chunking along clause or paragraph boundaries - Long Structured Documents Fixed-size chunking with overlap for short records of similar length - Heterogeneous Short Records Hierarchical chunking that mirrors document section structure - Long Structured Documents Chunking must preserve the structural unit that carries meaning in the source corpus. Code and hierarchical specifications are best divided at function, module, class, or tree boundaries because arbitrary token cuts can separate definitions from their implementation or parent context. Heterogeneous short-record collections should generally preserve each record as an independent chunk. Fixed-size overlapping chunks are also effective when records have broadly similar lengths and lack meaningful internal hierarchy. Long structured documents benefit from semantic boundaries such as clauses and paragraphs, while hierarchical chunking preserves relationships among sections, subsections, and parent headings. Anthropic notes that chunk size, boundaries, and overlap materially affect retrieval performance; therefore, one universal chunking method is inappropriate. Anthropic Contextual Retrieval
NEW QUESTION # 13
You are selecting a model for a new production workload and must complete the upstream steps before testing candidate models empirically.
Which two steps must be completed BEFORE running a representative sample on a candidate model? (Select two.) Each correct answer presents part of the solution.
Answer: A,D
NEW QUESTION # 14
You are reviewing a customer-support agent's configuration. Each candidate tool falls into one of four categories: (1) required to complete defined tasks, (2) frequently used and reduces hand-offs, (3) occasionally useful for unrelated work, (4) speculative future utility.
Which categories should typically remain in the agent configuration?
Answer: C
Explanation:
Category 1 tools are necessary for the agent to complete its approved responsibilities and must remain.
Category 2 tools are also justified when they are regularly used and eliminate predictable hand-offs without expanding the agent beyond its defined operating role.
Categories 3 and 4 create capability bloat. A tool that is occasionally useful only for unrelated work does not belong to this agent's responsibility boundary. A speculative tool has no validated requirement and adds attack surface, context consumption, authorization complexity, evaluation burden, and operational dependencies without demonstrated value.
Tool inclusion should be based on task traceability: every configured capability should map to a documented user journey, responsibility, permission scope, and evaluation case. Anthropic recommends least privilege so that a successful injection or model error can cause minimal damage. Mitigate Jailbreaks and Prompt Injections The architect should periodically review tool-call telemetry and remove unused capabilities. New tools can be added when a validated workflow requires them, after security review and evaluation. The objective is not the smallest possible catalog regardless of usefulness; it is the smallest catalog that reliably completes the agent's approved tasks.
Study Guide references/topics: Capability-bloat analysis; tool necessity; hand-off reduction; least privilege; attack-surface management; tool lifecycle review.
NEW QUESTION # 15
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