Technical articles on the Claude Certified Architect exam, Claude Code architecture, MCP integration patterns, and agent design — written for developers building with Claude.
Prepare for CCDV-F: $125, 53 items, 120 min, pass 720. Study the 8 domains by weight, with 2-week and 4-week schedules and free prep links.
Prepare for CCAO-F: $99, 60 items, 120 min, pass 720. Seven domains by weight, 2-week and 4-week plans, and links to the Associate hub and prep course.
Prepare for CCAR-P: $175, 63 items, 120 min, pass 720. Seven domains by weight, how it differs from CCA-F, and 2-week plus 4-week study plans.
Pass CCA-F (CCAR-F): $125, 60 items, 120 min, pass 720. Domain-weighted 2-week and 4-week study plans, scenario technique, and free resources on this site.
CLAUDE.md files, slash commands, and Skills are Claude Code's three configuration layers — each with different scope, trigger mechanism, and best use case. A precise comparison with real examples.
Everything you need to know about Anthropic's Claude Certified Architect Foundations certification — what it certifies, who it is for, exam format, how to register, difficulty, and whether it is worth taking in 2025.
What each CCA-F (CCAR-F) domain tests: weights, format ($125, 60 items, 120 min, pass 720) and how this article differs from the interactive exam guide.
Claude Code applies two complementary OS-level isolation layers — filesystem containment and network proxying — to prevent prompt injection attacks from affecting the broader system, while cutting permission prompts by 84%.
Loading all MCP tool definitions upfront costs 150,000 tokens before any work begins. A filesystem-discovery pattern combined with local code execution cuts that to 2,000 tokens — here is how it works.
Tool search, programmatic tool calling, and usage examples are three beta Claude API features that independently address token bloat, inference latency, and parameter errors in production agents.
Multi-session AI agents fail in four predictable patterns: over-ambition, false completion, environmental chaos, and testing gaps. The harness architecture — initializer agents, JSON feature lists, git checkpoints — addresses each one.
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