Full curriculum
Every area and chapter in CCAF Prep, in the recommended order. On the guided path each area ends in a final quiz that requires a perfect 100% score — with unlimited fresh-draw retries — before the next area opens up. Prefer to explore? Free navigation lets you open any area right away.
Start free1. Orientation
How the exam works: format, scoring, scenarios, and how to use this course.
Final quiz: 8 questions — 100% to advance on the guided path.
- The Exam: Format, Scoring, Scenariosorientation.exam-format
- How to Study with This Courseorientation.study-strategy
2. Claude API Foundations
The request/response contract, tool use, stop_reason handling, the agentic loop, and the Message Batches API.
Final quiz: 12 questions — 100% to advance on the guided path.
- Messages, Roles, and the Request Loopapi.messages
- Tool Use: Definitions, tool_use Blocks, Resultsapi.tool-use
- stop_reason: tool_use vs end_turnapi.stop-reasons
- The Agentic Loop, End to Endapi.agentic-loop
- Message Batches API Fundamentalsapi.batch
3. Prompt Engineering & Structured Output
Explicit criteria and false-positive control, few-shot prompting, tool_use + JSON schemas for guaranteed structure, validation/retry loops, batch processing strategy, and multi-instance review architectures.
Final quiz: 12 questions — 100% to advance on the guided path.
- Explicit Criteria over Vague InstructionsD4.1
- Few-Shot Prompting for ConsistencyD4.2
- Enforcing Structure: tool_use + JSON SchemasD4.3
- Validation, Retry, and Feedback LoopsD4.4
- Batch Processing StrategiesD4.5
- Multi-Instance and Multi-Pass ReviewD4.6
4. Tool Design & MCP Integration
Writing tool descriptions that get selected correctly, structured MCP error responses, scoping tools across agents with tool_choice, MCP server configuration and resources, and choosing the right built-in tool (Read, Write, Edit, Bash, Grep, Glob).
Final quiz: 12 questions — 100% to advance on the guided path.
- Designing Tool Interfaces That Get Selected CorrectlyD2.1
- Structured Error Responses for MCP ToolsD2.2
- Distributing Tools Across Agents & tool_choiceD2.3
- MCP Servers, Scoping, and ResourcesD2.4
- Built-in Tools: Read, Write, Edit, Bash, Grep, GlobD2.5
5. Agentic Architecture & Orchestration
Building reliable agentic loops in production, orchestrating coordinator-subagent systems, configuring subagent invocation and context passing, enforcing multi-step workflows with programmatic gates and handoffs, using Agent SDK hooks for interception and normalization, choosing task decomposition strategies, and managing session resumption and forking.
Final quiz: 12 questions — 100% to advance on the guided path.
- Agentic Loops for Autonomous ExecutionD1.1
- Coordinator–Subagent OrchestrationD1.2
- Subagent Invocation, Context Passing, SpawningD1.3
- Multi-Step Workflows: Enforcement & HandoffsD1.4
- Agent SDK Hooks: Interception & NormalizationD1.5
- Task Decomposition StrategiesD1.6
- Sessions: Resumption and ForkingD1.7
6. Claude Code Configuration & Workflows
Configuring CLAUDE.md hierarchy, @import, and modular .claude/rules/ for team-wide conventions; building custom slash commands and Agent Skills with frontmatter controls; applying path-specific glob rules for conventions spread across a codebase; choosing plan mode versus direct execution; using iterative-refinement techniques (input/output examples, test-driven iteration, the interview pattern); and integrating Claude Code into CI/CD pipelines with non-interactive flags and structured output.
Final quiz: 12 questions — 100% to advance on the guided path.
- CLAUDE.md Hierarchy, @import, and Modular RulesD3.1
- Custom Slash Commands and SkillsD3.2
- Path-Specific Rules with Glob FrontmatterD3.3
- Plan Mode vs Direct ExecutionD3.4
- Iterative Refinement TechniquesD3.5
- Claude Code in CI/CD PipelinesD3.6
7. Context Management & Reliability
Preserving critical facts and figures across long interactions instead of losing them to progressive summarization or the lost-in-the-middle effect; designing escalation and ambiguity-resolution patterns that trigger on explicit requests and policy gaps rather than unreliable sentiment or self-reported confidence; propagating structured error context across multi-agent systems instead of generic failure statuses; managing context in large codebase exploration with scratchpads, subagent delegation, and crash-recovery manifests; calibrating field-level confidence against labeled validation sets to route human review; and preserving provenance, conflicting-source attribution, and temporal metadata through multi-source synthesis.
Final quiz: 12 questions — 100% to advance on the guided path.
- Preserving Critical Information Across Long InteractionsD5.1
- Escalation and Ambiguity ResolutionD5.2
- Error Propagation in Multi-Agent SystemsD5.3
- Context Management in Large Codebase ExplorationD5.4
- Human Review Workflows and Confidence CalibrationD5.5
- Provenance and Uncertainty in Multi-Source SynthesisD5.6
8. Scenario Practice
Applying every domain to the six production contexts the real exam draws its scenarios from: a customer support resolution agent, Claude Code for team code generation, a multi-agent research system, developer-productivity tooling over unfamiliar codebases, Claude Code wired into CI/CD, and a structured data extraction pipeline. Each chapter is a case-study walkthrough of one scenario followed by cross-domain judgment questions in that scenario's voice — the closest rehearsal available for how the real exam actually presents questions.
Final quiz: 12 questions — 100% to advance on the guided path.
- Scenario: Customer Support Resolution Agentscenario.support-agent
- Scenario: Code Generation with Claude Codescenario.code-gen
- Scenario: Multi-Agent Research Systemscenario.research
- Scenario: Developer Productivityscenario.dev-productivity
- Scenario: Claude Code for CIscenario.ci
- Scenario: Structured Data Extractionscenario.extraction