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From zero to expert. Choose your level, learn at your pace. Each article has a quick view (3 min) and a full view to go deeper.
CCA-F Domain 5 : Context Management & Reliability (15%): the complete lesson
The reliability domain: what consumes the context window and how to budget it, compaction and structured summaries, persistent memory across sessions, graceful degradation (timeouts, fallbacks, partial results), error propagation between agents, source attribution and normalization of heterogeneous formats. Diagrams, traps, night-before checklist, corrected scenario questions.
CCA-F Domain 4 : Prompt Engineering & Structured Output (20%): the complete lesson
The prompt domain: explicit criteria over vague instructions, few-shot with reasoning, structured output via tool_use and JSON schema, nullable fields against hallucination, validate-and-retry, extended thinking, Batch API (-50%, 24h, custom_id) and multi-instance review. Diagrams, traps, night-before checklist, corrected scenario questions.
CCA-F Domain 3 : Claude Code Configuration & Workflows (20%): the complete lesson
The most factual domain of the certification: the CLAUDE.md hierarchy, @import, glob-scoped .claude/rules/, commands vs skills (context: fork, allowed-tools, argument-hint), plan mode vs direct execution, iterative refinement, and Claude Code in CI/CD (-p, --output-format json, --json-schema). Diagrams, traps, night-before checklist, corrected scenario questions.
CCA-F Domain 2 : Tool Design & MCP Integration (18%): the complete lesson
The tools domain: how an agent picks the right tool, why it gets it wrong, how a tool should fail, how many tools to give whom, tool_choice, MCP server configuration and Claude Code's built-in tools. Diagrams, traps, night-before checklist and corrected scenario questions.
CCA-F Domain 1 : Agentic Architecture & Orchestration (27%): the complete lesson
The heaviest domain of the Claude Certified Architect exam, broken down point by point: the agentic loop, hub-and-spoke, subagents, programmatic guardrails, hooks, task decomposition and sessions. With diagrams, traps, a night-before checklist and corrected scenario questions.
Securing your MCP servers: the attack surface and the countermeasures
Step 8/9 of the Skills & MCP learning path. The full attack surface of a tool-equipped agent, indirect injection, confused deputy, exfiltration by chaining, and the defense in depth that neutralizes it, from least privilege to supervision. The step your CISOs will read first.
Build your minimal MCP server: the loop closes
Step 7/9 of the Skills & MCP learning path. The two tools of our connecting thread in line-by-line annotated Python: server structure, trigger docstrings, write guardrails, errors designed for the model, and the skill + MCP loop finally complete.
RAG in production: architecture, pipeline and governance
A demo RAG fits in 40 lines. A production RAG is five stages, three cross-cutting layers, and a decision you must make before writing code. Complete guide: decision tree, reference architecture, Python code per stage, continuous evaluation, multi-tenant governance and security.
Passing the Claude Certified Architect (CCA-F): The Complete Guide
The reference guide to earning Anthropic's first official technical certification: the 5 weighted domains, the exact format, SVG schemas, worked sample questions, the traps, a study plan, the free official courses, and a full AI/Claude glossary.
Building a multi-agent system with Claude: practical guide (SDK + MCP)
Complete tutorial to deploy Claude agents that collaborate. Comparison Agent SDK vs API + MCP. Python code, real case, production deployment.
Multi-agent systems: AI agent teams for pros (2026 architecture)
Multi-agent systems are the #1 pro topic of 2026. 4 orchestration patterns, frameworks (LangGraph, CrewAI, AutoGen), 5 fatal mistakes, 4-week roadmap.
Securing an AI project end-to-end: complete 2026 framework
Complete framework to secure your AI in 2026: 5 layers, STRIDE-AI model, 60-point checklist, 90-day program, tooling stack, AI Act/ISO 42001 compliance.
AI red-teaming: attack your own LLMs before others do
Complete 2026 methodology: MITRE ATLAS framework, 6 attack categories, monthly cadence, tools (Garak, PyRIT), AI Act compliance.
Prompt injection: the critical LLM flaw in 2026
Ranked #1 OWASP Top 10 LLM for 3 consecutive years. LLMs cannot distinguish instructions from data, the fundamental flaw. Real cases, 8 attack vectors, defense-in-depth.
AI Agents: the next revolution
Claude Computer Use, OpenAI Operator, Devin... AI agents act in the world, not just answer. We explain how they work, the top 2026 frameworks and the real risks.
RAG explained simply
RAG is the technique that connects an LLM to your documents for grounded, hallucination-free answers. We explain the mechanism, technical stack and optimizations that make a difference.