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.

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 codeCCAR-P
Number of items63
Item formatMultiple-choice and multiple-response; each item states how many responses to select
Time limit120 minutes
DeliveryProctored, online or at a test centre, per programme policy
Passing scoreScaled score of 720 on a scale of 100–1,000
Anthropic's exam fee$175 USD per attempt
Validity12 months from the date the credential is awarded
Result reportingPass/fail with scaled score, plus percent-correct by domain on the score report
Retakeswaiting periods of 14, 30, and 90 days after failed attempts, up to four attempts in a rolling twelve months, fee per attempt
Renewalfree 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
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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.

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.