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| Section | Objectives |
|---|---|
| Solution Design | - Claude platform and solution architecture - Model, architecture, context, and deployment strategy selection |
| Enterprise Integration and Production | - Cost, latency, reliability, and operational design - Enterprise integration architecture and production readiness |
| Governance, Safety, and Risk | - Safety controls and fail-closed system design - Security, compliance, risk management, and governance |
| Stakeholder Engagement and Solution Lifecycle | - Stakeholder discovery and architectural trade-off communication - Solution lifecycle, handoff, adoption, and operational enablement |
| Evaluation and Optimization | - Evaluation design and acceptance criteria - Model and architecture optimization |
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NEW QUESTION # 116
You are an architect supporting the iteration phase of a deployed Claude-based system.
Which activity most directly fits this phase?
Answer: B
Explanation:
Iteration is an evidence-driven lifecycle phase. Option D combines three essential inputs: production telemetry, sampled output evaluation, and stakeholder feedback. Telemetry exposes latency, cost, errors, tool failures, retrieval behavior, and operational anomalies. Output sampling identifies quality, safety, grounding, or consistency failures that infrastructure metrics may not reveal. Stakeholder feedback establishes whether the system continues to satisfy real business and user needs.
The architect should prioritize the highest-impact validated problem, define the intended improvement, and test the proposed change against the existing evaluation framework and reference set. Anthropic emphasizes that evaluations make behavioral changes visible before they affect users and that their value compounds throughout an agent's lifecycle. Demystifying Evals for AI Agents Option A replaces targeted iteration with unnecessary redesign. Option B incorrectly treats deployment as the end of measurement. Option C removes the baseline needed to distinguish genuine improvement from regression or noise.
A mature iteration cycle preserves evaluation continuity, adds production failures as new test cases, validates changes offline, conducts controlled rollout, monitors results, and updates documentation and known limitations.
Study Guide references/topics: Production iteration; telemetry; sampled evaluation; stakeholder feedback; regression testing; evaluation continuity; change prioritization.
NEW QUESTION # 117
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: D
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 # 118
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 # 119
You are defining an SLA for a Claude-based assistant.
Which SLA definition is most operationally meaningful?
Answer: D
Explanation:
An operational SLA must be objectively measurable and enforceable. Option B defines the metric, percentile, threshold, and observation window, allowing both parties to determine whether service performance complied with the agreement. A complete SLA also defines what follows a breach, such as escalation, remediation, service credits, capacity changes, or architectural review. Percentile latency is preferable to an average because it exposes degraded tail performance experienced by a meaningful portion of users. Anthropic provides usage, cost, and operational data that can support monitoring and alerting through the Usage and Cost API . Options A and C are subjective. Option D remains incomplete because neither assessment periods nor breach handling can be applied consistently.
Study Guide references/topics: SLA construction; p95 latency; thresholds; evaluation windows; breach consequences; operational measurement.
NEW QUESTION # 120
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: A,D
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 # 121
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