Claude Certified Architect: Foundations
An independent study guide for the CCAR-F exam blueprint: agentic architecture, tool and MCP design, Claude Code configuration, prompt engineering for structured output, and context management. Written from scratch and not affiliated with, endorsed by or sponsored by Anthropic. It reproduces no exam questions.
6 modules · 34 lessons · 8 hr 54 min · prepares for CCAR-F
4 of 34 lessons are open to read without an account, and a free account opens the other 30. Creating one costs nothing.
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Starts with: What the CCAR-F exam measures
Modules
- Orientation: what CCAR-F measuresWhat the Claude Certified Architect Foundations exam is, the blueprint it is built on, the six production scenarios it frames questions inside, and how to prepare. Read this first: it also sets out what this guide is and is not.4 lessons54 min
- Domain 1: Agentic architecture and orchestrationFree accountThe largest domain at 27%. Agentic loops driven by stop_reason, coordinator and subagent systems, context passing, programmatic enforcement, hooks, task decomposition, and session lifecycle.7 lessons1 hr 53 min
- Domain 2: Tool design and MCP integrationFree account18% of the exam. Tool descriptions as the selection mechanism, structured error responses, distributing tools across agents, tool_choice, MCP server scoping, and the built-in tools.5 lessons1 hr 18 min
- Domain 3: Claude Code configuration and workflowsFree account20% of the exam. The CLAUDE.md hierarchy, slash commands and skills, path-scoped rules, plan mode versus direct execution, iterative refinement, and non-interactive use in CI.6 lessons1 hr 36 min
- Domain 4: Prompt engineering and structured outputFree account20% of the exam. Explicit criteria over vague instruction, few-shot examples, tool use with JSON schemas for guaranteed structure, validation and retry, batch processing, and multi-pass review.6 lessons1 hr 36 min
- Domain 5: Context management and reliabilityFree account15% of the exam. Preserving facts across long conversations, escalation and ambiguity, error propagation between agents, exploring large codebases, human review and confidence calibration, and provenance in synthesis.6 lessons1 hr 37 min