Markdown vs JSON for LLMs

Markdown and JSON serve different parts of an LLM workflow: readable documents for people and explicit structures for software. This paper compares their roles in prompting, retrieval, extraction, validation, and application integration.

It proposes a hybrid architecture with Markdown upstream and JSON downstream, alongside an evaluation framework covering accuracy, latency, editing effort, schema validity, and downstream task success.