The decision framework I wish I'd had before studying AI-103

Short summary

A personal account of passing Microsoft AI-103 after failing the first attempt, emphasizing that the exam tests architectural decision-making over service memorization. Key decision frameworks include RAG vs fine-tuning, MCP vs A2A, and workflow vs multi-agent orchestration. The author strongly recommends hands-on lab experience over documentation reading.

• •AI-103 tests architectural decisions, not service memorization
• •Key frameworks: RAG vs fine-tuning, MCP vs A2A, workflow vs multi-agent
• •Hands-on labs are more valuable than documentation for exam prep

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