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| Section | Weight | Objectives |
|---|---|---|
| Claude Models, Prompting & Context Engineering | 13% | - Select appropriate Claude models based on trade-offs - Design system prompts, templates, and guardrails - Apply context engineering and context management techniques - Mitigate prompt injection, leaks, and jailbreak risks |
| Integration | 19% | - Design authentication, authorization, and observability - Integrate with data pipelines and RAG systems - Implement Model Context Protocol (MCP) integrations - Integrate Claude with enterprise systems, APIs, and tools |
| Governance, Safety & Risk Management | 14% | - Address ethical AI considerations and bias mitigation - Manage data privacy and security compliance - Ensure regulatory compliance (GDPR, HIPAA, etc.) - Implement guardrails and safety controls |
| Evaluation, Testing & Optimization | 16% | - Implement iterative improvement pipelines - Test accuracy, reliability, latency, and cost - Define evaluation metrics and success criteria - Optimize performance, prompting, and model selection |
| Developer Productivity & Operational Enablement | 7% | - Improve developer workflows with AI-assisted tooling - Configure Claude tools and environments for teams - Support debugging, monitoring, and operational resolution |
| Stakeholder Communication & Lifecycle Management | 14% | - Conduct structured discovery and requirement gathering - Manage stakeholder feedback and expectation alignment - Communicate architectural decisions and trade-offs - Document architectures and support full lifecycle phases |
| Solution Design & Architecture | 17% | - Align solutions to business value pillars - Translate business problems into Claude-based AI solutions - Design multi-agent systems and orchestration strategies - Select architectural patterns: workflow, agentic, augmented LLM - Design end-to-end architectures and feedback loops |
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NEW QUESTION # 89
You are rolling out monitoring for a Claude-based deployment and must complete the specification steps before instrumenting the deployment.
Which two steps must be completed BEFORE instrumenting the deployment to emit metrics and traces?
(Select two.)
Each correct answer presents part of the solution.
Answer: A,B
NEW QUESTION # 90
You are reviewing instrumentation in a multi-agent system.
Which two findings constitute valid observability gaps in the instrumentation? (Select two.) Each correct answer presents a complete solution.
Answer: C,E
Explanation:
Model identity and version are essential diagnostic dimensions. Without them, operators cannot correlate a behavioral change with a model migration, reproduce the conditions of a failed turn, compare performance among model versions, or distinguish model drift from prompt, retrieval, and application defects. Therefore, the omission described in Option D is a genuine observability gap.
Option E is equally significant. A multi-agent execution normally crosses orchestration, model, agent, MCP, and tool boundaries. If the request-scoped correlation identifier or distributed trace context is lost at any boundary, the resulting spans cannot reliably be reconstructed into one end-to-end transaction. Anthropic's monitoring guidance explains that distributed tracing links a user prompt to the API requests and tool executions it initiates; it also documents propagation of W3C trace context to supported subprocesses and outbound MCP requests. Claude Code Monitoring Options A and B describe healthy telemetry coverage rather than gaps. Option C is also appropriate because recording tool interactions supports investigation, while redaction reduces the risk of exposing sensitive data in logs.
Study Guide references/topics: Integration-observability challenges at scale; distributed tracing; correlation identifiers; model-version attribution; privacy-aware tool telemetry.
NEW QUESTION # 91
You are defining an SLA for a Claude-based assistant.
Which SLA definition is most operationally meaningful?
Answer: A
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 # 92
You are designing a content moderation classifier that processes high volumes of user-generated comments under a tight per-message latency budget using well-defined classification labels.
Which model selection best aligns with the workload?
Answer: B
Explanation:
Haiku is the appropriate starting point because the workload is high-volume, latency-sensitive, and based on a stable closed set of moderation labels. These characteristics favor a fast, cost-efficient model capable of consistent classification without incurring the additional inference time and expense associated with deeper reasoning.
Anthropic's model-selection guidance requires architects to balance capability, speed, and cost rather than automatically selecting the most capable model. Its content-moderation guidance specifically identifies Haiku as a cost-effective option for processing moderation workloads at substantial scale. Choosing the Right Model, Content Moderation Opus is disproportionate to a routine closed-set classification problem. Sonnet may become justified if evaluation demonstrates that Haiku fails materially on complex policy distinctions, multilingual ambiguity, or adversarial edge cases, but it should not be selected merely because it is larger. Enabling extended thinking on every request would further increase latency and token consumption without evidence that the additional reasoning improves the defined success metrics. The correct architectural practice is to establish a representative moderation evaluation set, validate Haiku against accuracy and safety thresholds, and escalate only the cases that genuinely need deeper reasoning.
Study Guide references/topics: Model selection; capability-latency-cost trade-offs; classification workloads; evaluation-driven routing; moderation architecture.
NEW QUESTION # 93
You are rolling out a standardized Claude Code configuration to an engineering team and must complete the planning steps before piloting the configuration.
Which two steps must be completed BEFORE piloting the configuration with a small group of engineers?
(Select two.)
Each correct answer presents part of the solution.
Answer: C,E
Explanation:
Before a pilot begins, the architect must understand the workflows being enabled, the associated security boundaries, and the correct ownership of each configuration decision. Option D establishes this foundation.
Organization-wide, non-overridable controls belong in managed configuration, whereas repository-specific MCP servers, shared permissions, and team subagents generally belong in project scope.
Option A then converts those decisions into an initial project baseline that the pilot group can use. The baseline should identify approved MCP endpoints, minimum permission rules, denied operations, subagent responsibilities, configuration ownership, and observable success criteria. Anthropic distinguishes managed, user, project, and local scopes according to who they affect and whether they are shared with the team. Claude Code Configuration Scopes Options B and C are broad-rollout activities and should not occur before pilot evidence is available. Option E is explicitly post-pilot: findings must first be collected before the configuration can be iterated and stabilized.
The correct lifecycle is discovery, boundary definition, baseline design, limited pilot, evidence review, baseline refinement, documentation and training, followed by controlled expansion with a support and rollback process.
Study Guide references/topics: Claude Code rollout planning; scope ownership; MCP baselines; permission design; pilot strategy; operational enablement.
NEW QUESTION # 94
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