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Anthropic CCAR-P Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Evaluation, Testing & Optimization | 16% | - Test accuracy, reliability, latency, and cost - Optimize performance, prompting, and model selection - Define evaluation metrics and success criteria - Implement iterative improvement pipelines |
| Topic 2: Stakeholder Communication & Lifecycle Management | 14% | - Conduct structured discovery and requirement gathering - Manage stakeholder feedback and expectation alignment - Document architectures and support full lifecycle phases - Communicate architectural decisions and trade-offs |
| Topic 3: Developer Productivity & Operational Enablement | 7% | - Support debugging, monitoring, and operational resolution - Configure Claude tools and environments for teams - Improve developer workflows with AI-assisted tooling |
| Topic 4: Governance, Safety & Risk Management | 14% | - Implement guardrails and safety controls - Address ethical AI considerations and bias mitigation - Manage data privacy and security compliance - Ensure regulatory compliance (GDPR, HIPAA, etc.) |
| Topic 5: Integration | 19% | - Integrate with data pipelines and RAG systems - Integrate Claude with enterprise systems, APIs, and tools - Design authentication, authorization, and observability - Implement Model Context Protocol (MCP) integrations |
| Topic 6: Claude Models, Prompting & Context Engineering | 13% | - Design system prompts, templates, and guardrails - Select appropriate Claude models based on trade-offs - Apply context engineering and context management techniques - Mitigate prompt injection, leaks, and jailbreak risks |
| Topic 7: Solution Design & Architecture | 17% | - Design end-to-end architectures and feedback loops - Translate business problems into Claude-based AI solutions - Design multi-agent systems and orchestration strategies - Align solutions to business value pillars - Select architectural patterns: workflow, agentic, augmented LLM |
Anthropic Claude Certified Architect - Professional Sample Questions:
1. You are a solution architect evaluating candidate use cases for a Claude-based program.
For each scenario, select Yes if Claude is appropriate as the primary solution at the architectural level.
Otherwise, select No.
2. A revenue projection assistant has missed its monthly cost target by 38 percent. Profiling shows three contributors: a 6,000-token policy preamble repeated on every call (45 percent of cost), retrieval of historical sales chunks averaging 3,000 tokens per call (30 percent), and inference on a flagship-tier model (25 percent).
Stakeholders require that projection accuracy remain unchanged.
Which two optimizations should you sequence first to reduce cost without affecting accuracy? (Select two.) Each correct answer presents part of the solution.
A) Reduce the number of historical sales chunks retrieved across each query run.
B) Switch the workload to a smaller, faster Claude model tier across all queries.
C) Cache common retrieved sales chunks accessed across many of the daily queries.
D) Enable prompt caching on the static policy preamble across the recurring calls.
E) Truncate the policy preamble to remove non-essential clauses from the prompt.
3. You are operating an interactive assistant whose dominant performance constraint is per-turn latency. Quality on routine turns is already acceptable.
Which configuration adjustment most directly improves latency without disproportionately damaging quality?
A) Increase retrieval depth to the corpus maximum to improve recall regardless of latency.
B) Reduce retrieval depth to the top-k passages that historically cover the answer, and cache stable system- prompt content.
C) Disable prompt caching entirely to ensure fresh context processing on every request, preventing stale prefix content from affecting latency-sensitive interactions.
D) Switch every turn to the heaviest available model to maximize output quality, accepting that the increased model latency will worsen the per-turn SLO rather than improve it.
4. After a prompt-template update, several previously passing test cases now produce unexpected outputs.
Which test type is specifically designed to detect this category of failure?
A) Integration tests that validate cross-component pipeline behavior.
B) Adversarial tests that probe for prompt-injection vulnerabilities.
C) Regression tests scored against a stable reference set of known-good behavior.
D) Smoke tests that confirm high-level system availability after the change.
5. You are explaining the precedence of Claude Code configuration scopes to the team.
Which precedence ordering, from highest to lowest, is correct?
A) Local # managed # user # command-line arguments # project
B) Managed # command-line arguments # local # project # user
C) Project # user # managed # local # command-line arguments
D) User # project # local # command-line arguments # managed
Solutions:
| Question # 1 Answer: Only visible for members | Question # 2 Answer: C,D | Question # 3 Answer: B | Question # 4 Answer: C | Question # 5 Answer: B |
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