---
title: "Claude Certified Architect (Professional) — CCAR-P Exam Guide & Prep | Claude Certification Guide"
url: https://stacklist.com/card/a298430f-9623-4922-9004-ccf4f764bc3d
source_url: "https://claudecertificationguide.com/ccar-p"
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summary: "Claude Certified Architect (Professional) is an exam for mid- to senior-level practitioners testing production Claude system ownership across discovery, architecture, integration, and governance. The CCAR-P exam contains 63 items, lasts 120 minutes, costs $175 USD, and requires a scaled score of 720 to pass."
tags: "claude, certification, exam, architecture, professional, ai-systems, anthropic"
key_entities: "Anthropic (organization), Pearson VUE (organization), Brevo (organization), Claude (technology), Solution Architecture (concept), Prompt Engineering (concept), RAG Pipeline (concept), Multi-agent Systems (concept)"
classification: "reference"
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---

# Claude Certified Architect (Professional) — CCAR-P Exam Guide & Prep | Claude Certification Guide

Coming soon · Prep track planned Version 1.0 · Effective July 2026 · Exam code: CCAR-P Claude Certified Architect (Professional) The Professional tier of the Architect track goes beyond foundations. It tests whether you can own a production Claude system end to end: discovery, architecture, integration with enterprise systems, evaluation, governance, and the stakeholder conversations that surround all of it. Launch_Waitlist Get notified when this launches Leave your email and we'll send a single message when the Claude Certified Architect (Professional) prep track goes live here. Leave this field empty Notify me One email when this track goes live, and nothing else. Submitting adds you straight to the list (no confirmation step). Your address is held by Brevo, the email platform we use, and every email we send includes an unsubscribe link. More in our privacy policy . Who the exam is for Anthropic aims this exam at mid- to senior-level practitioners: solution architects, AI/ML engineers, technical leads, and senior software engineers who translate business problems into scalable Claude-based systems. The guide recommends three or more years of systems-architecture or platform-engineering experience, and at least six months of hands-on production work with Claude or comparable LLM systems. Recommended, not required — the credential is awarded on exam performance alone. Exam facts at a glance Exam code CCAR-P Number of items 63 Item format Multiple-choice and multiple-response; each item states how many responses to select Time limit 120 minutes Delivery Through Pearson VUE, online proctored or at a test centre Passing score Scaled score of 720 on a scale of 100–1,000 Anthropic's exam fee $175 USD per attempt Validity 12 months from the date the credential is awarded Result reporting Pass/fail with scaled score, plus percent-correct by domain on the score report Retakes waiting periods of 14, 30, and 90 days after failed attempts, up to four attempts in a rolling twelve months, fee per attempt Renewal free on-time renewal via a non-proctored assessment on the Anthropic Partner Academy; a lapsed credential requires the full exam at the full fee All figures from Anthropic's Exam Guide v1.0 (July 2026). The exam fee is Anthropic's charge for the official exam, not a price of this site; nothing here requires payment today. Exam blueprint Domain weights are the guide's own figures. They set how much of the exam each area carries, and how we size lessons and practice questions. Domain 1: Solution Design & Architecture 17% Translate business problems into Claude-based AI solutions Design end-to-end architectures (input → processing → output → feedback loops) Select appropriate architectural patterns (workflow, agentic, augmented LLM) Design multi-agent systems and orchestration strategies Apply decomposition techniques for complex problem solving Align solutions to business value pillars (efficiency, transformation, productivity, cost, performance SLAs) Domain 2: Claude Models, Prompting & Context Engineering 13% Select appropriate Claude models based on trade-offs Design system prompts, templates, and guardrails Apply prompt engineering techniques (zero-shot, few-shot, chain-of-thought) Optimise context windows and manage token usage Implement prompt reuse strategies (caching, modular prompts, Skills) Domain 3: Integration 19% Evaluate tool/agent configuration for capability bloat Analyse authentication and authorisation requirements to identify security gaps Evaluate accuracy-latency trade-offs and justify configuration decisions Analyse observability challenges and select monitoring strategies at scale Design a RAG pipeline with appropriate chunking and indexing strategies Apply retrieval strategies matched to data shape and query pattern Evaluate connection protocols and select the appropriate integration mechanism (MCP, API/CLI, agent-to-agent) Evaluate progressive discovery vs. monolithic context strategy Domain 4: Evaluation, Testing & Optimisation 16% Define evaluation metrics (accuracy, latency, cost, safety, security) Design evaluation datasets and test frameworks using mixed methodologies Conduct A/B testing and iterative improvements Diagnose system issues (prompt failure, hallucinations, model mismatch) Optimise token usage, latency, and cost-performance trade-offs Monitor system performance using logging and observability tools Domain 5: Governance, Safety & Risk Management 14% Implement guardrails and safety controls Identify risks, limitations, and failure modes of LLM systems Apply human-in-the-loop validation strategies Ensure compliance with regulations (e.g., GDPR, HIPAA, FedRAMP) Address ethical AI considerations (bias, fairness, transparency) Domain 6: Stakeholder Communication & Lifecycle Management 14% Conduct structured discovery and requirement gathering Communicate architectural decisions and trade-offs Manage stakeholder feedback loops and expectation alignment (including SLAs) Document architectures and provide implementation guidance Support lifecycle phases (discovery, design, handoff, monitoring, iteration) Domain 7: Developer Productivity & Operational Enablement 7% Configure Claude tools and environments for teams (e.g., Claude Code) Improve developer workflows using AI-assisted tooling Support debugging and operational issue resolution Available_Now Study free while this track is built While the Professional track lands, Architect (Foundations) is free and fully open here, and it overlaps most with this exam's agentic-architecture and integration material. It's the best free place to start. Start Claude Certified Architect (Foundations) free Frequently asked questions When does the Claude Certified Architect (Professional) prep track launch? It's on the build plan now — the site's free Architect (Foundations) track shipped first, and each new track follows the same recipe: a lesson for every point in the blueprint, a weight-proportional practice bank in the real exam's multiple-choice and multiple-response format, and a full mock exam. This page becomes the track's hub when it ships, so the URL you're on is the one to bookmark. If you'd rather be told than keep checking, the waitlist on this page sends one email when the track goes live. Who is the CCAR-P exam for? Mid- to senior-level solution architects, AI/ML engineers, technical leads, and senior software engineers who design, build, and deliver production-grade Claude solutions. That's Anthropic's target audience for the exam; the full profile is in section 3 of the official exam guide. What does the CCAR-P exam cover? 63 items in 120 minutes across 7 domains: Solution Design & Architecture (17%), Claude Models, Prompting & Context Engineering (13%), Integration (19%), Evaluation, Testing & Optimisation (16%), Governance, Safety & Risk Management (14%), Stakeholder Communication & Lifecycle Management (14%), Developer Productivity & Operational Enablement (7%). Scoring is scaled from 100 to 1,000, with 720 needed to pass. How do I register for the official exam? Registration runs through Anthropic's Partner Academy, which is currently open to Anthropic partner organisations. That gap is exactly why this site exists: complete preparation for people without partner access. Is this site affiliated with Anthropic? No. This is an independent community resource. It is not affiliated with, endorsed by, or sponsored by Anthropic. Exam facts on this page come from Anthropic's published exam guide.