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| Section | Objectives |
|---|---|
| Solution Design | - Model, architecture, context, and deployment strategy selection - Claude platform and solution architecture |
| Governance, Safety, and Risk | - Security, compliance, risk management, and governance - Safety controls and fail-closed system design |
| Enterprise Integration and Production | - Enterprise integration architecture and production readiness - Cost, latency, reliability, and operational design |
| Stakeholder Engagement and Solution Lifecycle | - Solution lifecycle, handoff, adoption, and operational enablement - Stakeholder discovery and architectural trade-off communication |
| Evaluation and Optimization | - Model and architecture optimization - Evaluation design and acceptance criteria |
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NEW QUESTION # 111
You are building an evaluation pipeline for a Claude-based deployment and must complete the specification steps before running the deployment against the dataset.
Which two steps must be completed BEFORE running the deployment against the evaluation dataset? (Select two.) Each correct answer presents part of the solution.
Answer: A,C
Explanation:
The evaluation specification must exist before inference begins. Option D defines what the evaluation will measure and how results will be segmented. Representative cases measure normal workload performance, edge cases test boundary behavior, and adversarial cases examine safety, security, or robustness under hostile inputs.
Option B then supplies the correctly curated and labeled dataset corresponding to those slices. Labels, expected outcomes, grading rubrics, provenance, and dataset versions must be established before the deployment generates outputs. Otherwise, evaluators risk modifying criteria after seeing results and introducing confirmation bias.
Anthropic defines an evaluation as an input combined with grading logic used to measure success. Its evaluation guidance distinguishes tasks, trials, graders, traces, outcomes, and the harness that runs and aggregates them. Demystifying Evals for AI Agents Option E occurs after model execution because outputs must exist before they can be scored. Option A follows scoring and aggregation. Option C is an iterative improvement step performed after failure cases become available, although rubric calibration may also be conducted on separate development data.
Study Guide references/topics: Evaluation specification; metrics and slices; representative and adversarial datasets; labeling; scoring; aggregation; release gates.
NEW QUESTION # 112
You are selecting the documentation set that should accompany a Claude-based deployment at handoff.
Which set is most complete?
Answer: A
Explanation:
A complete handoff package must help different stakeholders understand, operate, troubleshoot, and evolve the Claude-based solution. An architecture overview explains the system's structure and responsibilities, while Architecture Decision Records document important decisions, alternatives, and trade-offs. Component- level diagrams provide implementation context without forcing maintainers to reconstruct dependencies from source code. Operational runbooks and an on-call playbook enable reliable incident detection, diagnosis, escalation, and recovery. Documenting known limitations is particularly important for Claude applications because model behavior can vary with prompts, context, input distribution, and external dependencies.
Options B, C, and D each provide only a partial or temporary understanding of the system. They would create knowledge gaps, increase operational risk, and make future maintenance dependent on individuals rather than durable organizational documentation.
NEW QUESTION # 113
A team manager wants all engineers working on the same repository to share identical MCP server definitions without manual synchronization.
Which configuration approach satisfies this requirement?
Answer: B
Explanation:
Project-scoped configuration is the appropriate mechanism for repository-specific settings that must remain consistent across collaborators. Claude Code recognizes `.claude/settings.json` as the shared project settings file and `.mcp.json` as the project-level MCP server configuration. When these files are committed to source control, every engineer receives the same definitions through the repository's normal clone, pull, review, and versioning workflow.
Anthropic's scope hierarchy distinguishes project configuration from user and local configuration. Files under the user scope apply to one engineer and are not automatically shared. Operating-system environment variables are also workstation-specific and require separate configuration management. Managed settings can be distributed centrally, but they are primarily intended for organization-wide security policies and controls that must be enforced by administrators; they are less appropriate when the configuration belongs specifically to one repository.
Shared configuration should contain server definitions and environment-variable references, but not plaintext credentials. Each engineer can resolve required secrets through an approved local secret mechanism while retaining identical server names, transports, arguments, and non-sensitive settings. Project MCP servers also remain subject to workspace trust and approval controls before execution.
Study Guide references/topics: [Claude Code configuration scopes](https://docs.anthropic.com/en/docs
/claude-code/settings); project-scoped MCP servers; `.mcp.json`; repository-based operational standardization; secure secret separation.
NEW QUESTION # 114
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: D,E
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 # 115
You are designing a human-in-the-loop validation workflow for a new Claude-based deployment and must complete the design steps before piloting the workflow.
Which two steps must be completed BEFORE piloting the workflow with a representative subset of traffic?
(Select two.)
Each correct answer presents part of the solution.
Answer: A,C
Explanation:
The workflow must first identify where human judgment is necessary. Option E applies risk-based oversight by examining each decision's impact and reversibility. High-impact, irreversible, externally binding, privacy- sensitive, or legally consequential actions require stronger review than low-risk draft generation or easily reversible recommendations.
After locating those control points, Option A defines how work reaches reviewers. The sampling strategy should specify whether review is universal, random, risk-triggered, confidence-based, or stratified. Escalation criteria should cover policy violations, uncertain outputs, conflicting evidence, sensitive data, failed validation, and cases exceeding the reviewer's authority.
Anthropic recommends human confirmation for decisions with meaningful real-world consequences and actions requiring affirmative consent. Computer Use Security Considerations Option B necessarily follows the pilot because findings must exist before design iteration. Reviewer onboarding and operational documentation in Options C and D are important readiness activities, but they follow the core design decisions being tested by this item: where oversight is required and how cases are sampled and escalated.
The completed pilot plan should subsequently include trained reviewers, documented procedures, queue capacity, SLAs, audit evidence, and measured inter-reviewer agreement.
Study Guide references/topics: Human-in-the-loop design; impact and reversibility; oversight points; sampling; escalation criteria; consequential decisions.
NEW QUESTION # 116
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