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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Evaluation, Testing & Optimization | 16% | - Evaluation metrics and datasets - Cost and performance optimization - A/B testing - System issue diagnosis - Evaluation framework design - Production monitoring and optimization |
| Topic 2: Governance, Safety & Risk Management | 14% | - AI safety and guardrails - Regulatory and compliance requirements - Security and risk management - Human-in-the-loop validation - Ethical AI considerations |
| Topic 3: Claude Models, Prompting & Context Engineering | 13% | - Claude model selection and trade-offs - Guardrails - Context window optimization - System prompts and prompt templates - Prompt reuse and context engineering strategies |
| Topic 4: Solution Design & Architecture | 17% | - Alignment with business value, cost, performance, and SLAs - Multi-agent systems and orchestration - End-to-end architecture design - Architectural patterns
- Decomposition techniques for complex problem solving |
| Topic 5: Developer Productivity & Operational Enablement | 7% | - Debugging and operational issue resolution - Claude tooling configuration for teams - Developer enablement - AI-assisted developer workflows |
| Topic 6: Stakeholder Communication & Lifecycle Management | 14% | - Communicating architectural decisions - Service-level agreements - Solution lifecycle management - Architecture documentation - Stakeholder management - Discovery and requirements gathering |
| Topic 7: Integration | 19% | - Claude integration mechanisms
- RAG pipeline design
|
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NEW QUESTION # 51
You are auditing a procurement-assistant agent whose defined responsibility is to draft purchase requests for review.
For each tool currently configured on the agent, select yes if the tool should remain after a least-privilege audit. Otherwise, select no if it should be removed.
Answer:
Explanation:
Explanation:
Yes, No, Yes, No, Yes
Least privilege requires each retained tool to be necessary for the agent's assigned responsibility and restricted to the minimum action level needed. Catalog lookup is appropriate because vendor and SKU information is needed to prepare an accurate request. The policy-document tool is similarly justified because the agent must ground the draft in applicable procurement rules. The draft-write tool is also aligned because it writes only to a review queue, preserving the required human approval boundary.
The inbox-send tool exceeds the stated responsibility. Sending a request directly to a vendor converts a drafting assistant into an externally acting purchasing agent and bypasses the review stage. The production- database administrator tool is unrelated to procurement and introduces unnecessary destructive capability, privilege-escalation exposure, and potential data-access risk.
Anthropic's prompt-injection guidance recommends limiting access to sensitive data and actions and applying least privilege so that a compromised agent can cause minimal damage. Claude Code also supports tool- specific allow, ask, and deny rules that are enforced outside the model. Prompt-Injection Mitigation, Claude Code Permissions Study Guide references/topics: Capability-bloat auditing; least privilege; tool scoping; human review gates; separation of drafting and execution authority.
NEW QUESTION # 52
You are responding to an adversarial input pattern in which users include text claiming admin authority and instructing the model to bypass safety restrictions.
Which combination of controls most effectively mitigates this attack pattern?
Answer: D
Explanation:
Self-declared administrative authority inside a prompt is untrusted data, not authenticated identity or authorization evidence. Option B correctly combines independent controls across the model, runtime, authorization, and monitoring layers.
Prompt instructions establish that user content cannot override system policy. Runtime classifiers detect known and generalized attempts to bypass controls. Tool permissions are enforced outside the model and must derive from authenticated identity, role, and approved scope-not statements contained in the conversation. Audit logging records the actor, attempted override, classifier result, tool requests, and final disposition for investigation and control improvement.
Anthropic recommends input screening, hardened system prompts, safe handling of untrusted content, narrowly scoped permissions, red-team testing, and continuous monitoring. Mitigate Jailbreaks and Prompt Injections Option A depends entirely on model behavior and provides no containment if the model fails. Option C removes the protections the attacker is attempting to defeat. Option D commits a fundamental authorization error by accepting an unverified claim as privilege elevation.
The strongest design also rate-limits repeated attempts, escalates suspicious activity, validates outputs, and requires human confirmation for consequential actions.
Study Guide references/topics: Direct prompt injection; untrusted user content; runtime classifiers; non-model authorization; scoped tools; audit logging; defense in depth.
NEW QUESTION # 53
A Claude architect is leading the discovery phase for a new AI-powered customer service solution.
Which two activities are characteristic of structured discovery and requirement gathering for a Claude-based deployment? (Select two.)
Answer: D,E
Explanation:
Structured discovery begins by eliciting constraints from the people who own the business outcome, operate the process, manage risk, and will use or support the deployed system. Stakeholder workshops in Option A identify measurable expectations concerning accuracy, latency, throughput, cost, privacy, compliance, escalation, and acceptable failure behavior before the solution is scoped.
Option D converts those expectations into production gates. Success criteria must be explicit enough to evaluate empirically, while failure thresholds must determine when the design requires remediation, human review, or rejection. Anthropic's evaluation guidance states that successful LLM applications begin with defined success criteria and evaluations that measure performance against them. It characterizes strong criteria as specific, measurable, achievable, and relevant. Define Success Criteria and Build Evaluations Option B prematurely selects a model before the workload profile is known. Option C can supplement discovery, but reaction-driven prototyping cannot replace documented requirements and acceptance criteria.
Option E postpones essential constraints until architectural commitments may already have been made.
The discovery output should create traceability from stakeholder objectives to requirements, evaluation metrics, architecture decisions, and deployment gates.
Study Guide references/topics: Structured discovery; stakeholder workshops; nonfunctional requirements; success criteria; failure thresholds; production readiness gates.
NEW QUESTION # 54
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: C
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 # 55
You must present an architectural recommendation to deploy a Claude-based contract review assistant to a steering committee that includes the CFO, the general counsel, and the CIO. Each stakeholder cares about different aspects of the decision.
How should you structure the recommendation document?
Answer: D
Explanation:
A steering committee needs an answer-first recommendation that states the proposed architectural decision, the business outcome it supports, and the approval or action required. After establishing that common decision frame, the document should address each stakeholder's concerns separately.
The CFO requires implementation and operating costs, expected savings, consumption assumptions, financial exposure, and cost-control mechanisms. General counsel needs evidence concerning confidentiality, privilege, data handling, human legal review, explainability, retention, and regulatory risk. The CIO needs integration architecture, security boundaries, availability, scalability, operational ownership, technical dependencies, and lifecycle support.
Option A begins at an implementation depth unsuitable for the entire committee. Option B overweights the CFO's concerns and delays the rationale required by the other decision-makers. Option C ignores audience- specific responsibilities and forces every stakeholder to extract relevant information from an undifferentiated narrative.
The recommended structure is: decision and executive rationale, expected outcomes, accepted trade-offs, stakeholder-specific impact sections, major risks and controls, implementation implications, success metrics, and the requested governance decision. Technical appendices can preserve component-level detail without overwhelming the principal recommendation.
Study Guide references/topics: Executive communication; stakeholder differentiation; decision-first structure; financial, legal, and technology concerns; architectural recommendations.
NEW QUESTION # 56
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