Comment by hkbuilds

This matches my experience building AI-powered analysis tools. Structured output from LLMs is dramatically more reliable when you give the model clear delimiters to work with.

One thing I've found: even with XML tags, you still need to validate and parse defensively. Models will occasionally nest tags wrong, omit closing tags, or hallucinate new tag names. Having a fallback parser that extracts content even from malformed XML has saved me more than once.

The real win is that XML tags give you a natural way to do few-shot prompting with structure. You can show the model exactly what shape the output should take, and it follows remarkably well.