Claude Certified Architect Professional Exam Mock Tests

The Claude Certified Architect – Professional (CCA-P / CCAR-P) certification exam is built around 7 core competency domains.

Because the exam evaluates senior solution architects across end-to-end production AI deployments, the domain weights are intentionally balanced to ensure both broad architectural vision and deep technical rigor.

CCA-P Blueprint & Exam Domains

1. Integration (19% weight)

• Core Focus: Connecting Claude to existing enterprise systems, API mechanisms, and external tools.

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• Key Topics: Model Context Protocol (MCP) design, API and CLI integration patterns, tool/agent configuration management, authentication/authorization security gaps, latency vs. accuracy trade-offs, and Retrieval-Augmented Generation (RAG) pipeline architecture.

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2. Solution Design & Architecture (17% weight)

• Core Focus: Translating high-level enterprise requirements into robust AI system architectures.

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• Key Topics: Choosing between agentic, workflow, or augmented-LLM architectural patterns; multi-agent orchestration; complex problem decomposition; aligning designs with business SLAs, cost controls, and system efficiency.

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3. Evaluation, Testing & Optimization (16% weight)

• Core Focus: Measuring model performance, quality control, and ongoing production refinement.

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• Key Topics: Designing evaluation frameworks, defining custom LLM metrics, executing A/B tests, diagnosing edge-case failures, and implementing production telemetry/monitoring.

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4. Governance, Safety & Risk Management (14% weight)

• Core Focus: Securing production models against malicious inputs and compliance risks.

• Key Topics: Guardrails implementation, prompt injection/jailbreak defenses, data privacy and regulatory compliance, bias mitigation, and human-in-the-loop (HITL) oversight strategies.

5. Stakeholder Communication & Lifecycle Management (14% weight)

• Core Focus: Managing long-term AI deployments and cross-functional alignment.

• Key Topics: Solution lifecycle management, cost model forecasting, demonstrating ROI/business-value pillars, managing model updates/deprecations, and executive reporting.

6. Claude Models, Prompting & Context Engineering (13% weight)

• Core Focus: Selecting models and optimizing input/context utilization.

• Key Topics: Model capability sizing (Haiku vs. Sonnet vs. Opus), advanced system prompting techniques, dynamic context window management, structured output enforcement (JSON/schema), and token usage optimization.

7. Developer Productivity & Operational Enablement (7% weight)

• Core Focus: Enabling internal engineering teams to build efficiently.

• Key Topics: Configuring Claude workspace tools, AI-assisted developer workflows, CI/CD pipelines for prompts/evals, and operational debugging support.

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Exam Logistics Overview

• Format: 63 questions | 120 minutes | Passing score: 720 / 1000.

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• Delivery: Pearson VUE online-proctored.

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• Validity: 12 months.

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