What is the Claude Certified Architect certification?

The Claude Certified Architect (CCA) certification, offered by Anthropic, validates expertise in designing, building, and deploying AI applications using Claude. The Foundations (CCA-F) level covers 5 official domains: Agentic Architecture, Claude Code, Prompt Engineering & Structured Output, Tools & MCP, and Context Management & Reliability.

How do I prepare for the CCA-F exam?

This free study platform offers 116 lessons across the 5 official exam domains, 800+ practice questions, unlimited weighted mock exams, and spaced-repetition flashcards to prepare for the CCA-F exam. It features interactive quizzes, diagnostics, and progress tracking.

What are the 5 official CCA-F exam domains?

The CCA-F exam covers 5 official domains weighted as follows: Agentic Architecture & Orchestration (27%), Claude Code Configuration & Workflows (20%), Prompt Engineering & Structured Output (20%), Tool Design & MCP Integration (18%), and Context Management & Reliability (15%). A solid background in Claude fundamentals is assumed.

How many questions are on the CCA-F exam?

The CCAR-F (Claude Certified Architect - Foundations, formerly CCA-F) exam has 60 items in 120 minutes, mixing multiple-choice and multiple-response questions. It is scored on a 1000-point scale with 720 required to pass. It is proctored (online via Pearson OnVUE or at a Pearson test center), closed-book, and valid for 12 months, renewed via a free non-proctored assessment on the Anthropic Partner Academy.

How long does the CCA-F exam take?

The CCA-F exam allows 120 minutes (2 hours) to complete 60 questions. Candidates average roughly 2 minutes per question. Good time management means reading each scenario carefully and flagging uncertain answers for review rather than lingering.

What is the passing score for the CCA exam?

The CCA-F exam requires a passing score of 720 out of 1000 points. The exam mixes multiple-choice and multiple-response items, is closed-book and proctored (Pearson OnVUE online or a Pearson test center). It is designed to be difficult, only well-prepared candidates should expect to pass.

Is the Claude Certified Architect certification worth it?

The Claude Certified Architect certification demonstrates verified expertise in building AI applications with Claude. As organizations increasingly adopt AI agents and Claude-powered workflows, certified architects are positioned to lead architecture decisions, optimize production deployments, and implement best practices across multi-agent systems.

Claude Code is a CLI tool developed by Anthropic that brings Claude's coding capabilities directly into the development environment. It supports edit mode and plan mode, keyboard shortcuts, slash commands, and a skills directory. Claude Code accounts for approximately 20% of the CCA-F exam content.

How do Claude agents work?

Claude agents operate using an agentic loop: send a request to the Messages API, process Claude's response, execute any tool calls Claude requests, append the results, and repeat. The stop_reason field signals when the task is done. Agentic architecture accounts for approximately 27% of the CCA-F exam.

What is the Model Context Protocol (MCP)?

The Model Context Protocol (MCP) is an open standard developed by Anthropic and governed by the Linux Foundation's Agentic AI Foundation. It provides a three-layer architecture (Host, Client, Server) with three primitives: Resources (application-controlled), Tools (model-controlled), and Prompts (user-controlled), built on JSON-RPC 2.0.

What domains are tested on the CCA exam?

The CCA-F exam tests 5 official domains weighted as follows: Agentic Architecture & Orchestration (27%), Claude Code (20%), Prompt Engineering & Structured Output (20%), Tools & MCP (18%), and Context Management & Reliability (15%).

Can I take the CCA practice exam for free?

Yes. This platform provides unlimited free mock exams (60 questions, 120 minutes, weighted to the official domain split), domain-specific practice, and flashcards. No registration or payment is required.

How do I get started with Claude AI development?

Start with the Fundamentals: learn what Claude is, understand the Messages API, manage tokens, write system prompts, and configure sampling parameters. Claude offers three model tiers: Sonnet (general-purpose), Opus (complex reasoning), and Haiku (fast and cost-effective for simple tasks).

What is the Claude Certified Architect certification?

The Claude Certified Architect (CCA) certification, offered by Anthropic, validates expertise in designing, building, and deploying AI applications using Claude. The Foundations (CCA-F) level covers 5 official domains: Agentic Architecture, Claude Code, Prompt Engineering & Structured Output, Tools & MCP, and Context Management & Reliability.

How do I prepare for the CCA-F exam?

This free study platform offers 116 lessons across the 5 official exam domains, 800+ practice questions, unlimited weighted mock exams, and spaced-repetition flashcards. All content is free and open-source.

What are the 5 official CCA-F exam domains?

The exam covers 5 official domains weighted as follows: Agentic Architecture & Orchestration (27%), Claude Code Configuration & Workflows (20%), Prompt Engineering & Structured Output (20%), Tool Design & MCP Integration (18%), and Context Management & Reliability (15%).

How many questions are on the CCA-F exam?

The CCAR-F (formerly CCA-F) exam has 60 items mixing multiple-choice and multiple-response questions with a 120-minute time limit. The passing score is 720 out of 1000. The exam is proctored (Pearson OnVUE online or a Pearson test center) and closed-book.

Is the CCA-F exam free?

The study platform is completely free and open-source. The CCA-F certification exam itself is administered by Anthropic and requires payment. This platform provides all the preparation materials you need at no cost.

How long does it take to get Claude Certified Architect certified?

Most learners complete the 116 lessons and pass the certification in 4 to 8 weeks with consistent study. The platform tracks your progress across all 5 domains with spaced repetition and learning analytics to optimize your study time.

What is the passing score for the CCA-F exam?

The passing score for the CCAR-F (Claude Certified Architect - Foundations) exam is 720 out of 1000 possible points. The exam has 60 items mixing multiple-choice and multiple-response questions and a 120-minute time limit. Credentials are valid 12 months with free non-proctored renewal on the Partner Academy.

What is Model Context Protocol (MCP)?

Model Context Protocol (MCP) is an open protocol developed by Anthropic that standardizes how AI applications connect to external systems. It uses a three-layer architecture (Host, Client, Server) with three primitives: Resources, Tools, and Prompts.

How do practice exams help with the CCA-F certification?

Practice exams simulate the real CCA-F testing experience with unlimited mocks weighted to the official 27/20/20/18/15 split, 60 questions, 120 minutes, and 720/1000 scoring. Each exam includes detailed explanations and performance analytics.

What is Claude Code and how is it used?

Claude Code is a CLI tool that brings Claude's coding capabilities directly into your terminal with file system access, command execution, and project context. It features edit mode for making changes and plan mode for safe exploration and analysis.

What is the Agents SDK in Claude?

The Claude Agents SDK is a framework for building stateful, long-running AI agents. It provides agent lifecycle management, state persistence, tool binding, inter-agent communication, and observability.

What are the three Claude model tiers?

Claude offers three model tiers: Sonnet for general-purpose tasks (fast, high intelligence, moderate cost), Opus for complex reasoning (highest intelligence, slower, adaptive thinking), and Haiku for simple high-throughput tasks (fastest, lowest cost). All share the same Messages API.

All Lessons

In FieldDesk, a technician queries for torque specifications for Model X-840 Revision D. If the retrieval pipeline applies naive post-filtering (retrieving the top-20 most semantically similar chunks across the entire database, then discarding any chunk not tagged with revision == 'Rev-D'), what failure mode frequently occurs?

AThe vector index deadlocks because post-filters mutate the underlying HNSW graph edges during query execution.BCatastrophic recall collapse occurs because identical passages from older revisions consume all 20 candidate slots and are subsequently discarded, returning zero results.CThe embedding model confuses the revision tag with the torque measurement, causing an out-of-range numerical hallucination.DThe search engine automatically falls back to full-table scans that exhaust the client-side memory buffer.

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intermediate 45 min

Day 12: Apply Metadata Filters Without Losing Relevant Evidence

Apply Metadata Filters Without Losing Relevant Evidence

Based on Anthropic Claude documentation and the CCA-F exam blueprint. Updated August 2026.

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In PolicyDesk's metadata filtering architecture, what security principle is upheld by deriving tenant_id and clearance_level directly from userToken rather than accepting them from queryFilters?

ADynamic schema migration, allowing user roles to override database index structures at runtime.BAsymmetric payload compression, minimizing the byte size of outgoing Elasticsearch filter payloads.CDeterministic token caching, ensuring that all users within a company share identical vector search responses.DTrust boundary isolation, preventing client-side parameter tampering or prompt injection from breaching multi-tenant access controls.

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An enterprise vector database contains 2,000,000 document chunks. A search query specifies a highly selective tenant filter that matches only 0.2 percent of the corpus (4,000 chunks). Why is single-stage in-index filtering (such as bitmask-guided HNSW traversal) superior to both pre-filtering and post-filtering in this scenario?

AIt evaluates candidate graph neighbors against precomputed bitmasks during traversal, avoiding recall collapse without abandoning vector index acceleration.BIt eliminates vector distance calculations by performing exact string hashing across all 4,000 candidate metadata tags.CIt duplicates the vector index into 500 isolated physical shards to guarantee constant O(1) retrieval time.DIt automatically widens the user filter to include non-matching tenant documents whenever candidate density falls below 10 percent.

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Day 12: Apply Metadata Filters Without Losing Relevant Evidence

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