Pass CCAF — and ship to production
Certification prep guides, exam-domain breakdowns, scenario training, and engineering coaching for developers, architects, and AI engineering teams.
Why This Exists
[?]Official material is all in English, raising the cost of study
The official docs are sprawling and English-only, with no systematic Chinese interpretation — making prep inefficient and core points hard to grasp.
Little real engineering-scenario training
Theory is disconnected from real engineering practice, leaving you stuck on the exam's complex real-world scenario questions.
No one to ask; you can't see your weak spots
Without community discussion and expert feedback, mock-test scores don't turn into a score-raising strategy, and blind drilling works poorly.
The Five Exam Domains, Decomposed
[DOMAINS]Agentic Architecture
AI Code Assistant 配置
Prompt Engineering
Tool / MCP
Context Management
Core Scenarios
[SCENARIOS]Practice Topic A
CCAF101 PRACTICE · Knowledge
Build a RAG-based internal enterprise Q&A system; tests context recall and accuracy.
Practice Topic B
CCAF101 PRACTICE · Code Review
Use Claude Code to analyze PRs, detect latent defects, and suggest improvements.
Practice Topic C
CCAF101 PRACTICE · Multi-Agent
Design a multi-agent collaboration flow to plan and execute complex tasks.
Practice Topic D
CCAF101 PRACTICE · MCP
Develop and integrate external tools to extend an agent's environment interaction.
Practice Topic E
CCAF101 PRACTICE · Prompt
Optimize prompts for a specific vertical to improve model output quality.
Practice Topic F
CCAF101 PRACTICE · Reliability
Implement security controls in agent architectures to prevent prompt injection and data leakage.
Latest Updates
[CONTENT]CCAF exam format: question count, duration, and scenario structure
The five domain weights and study order
Enrollment, fees, and the boundaries of an independent learning community
Multi-agent, MCP, and context-reliability practice
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