Source: The Next Web
As AI applications stack multiple models and data sources, Markdown has become the pragmatic middle layer—standardizing how search results, documents, and knowledge bases pass information to language models without losing formatting, structure, or retrievability. It sidesteps the fragmentation problem: instead of every AI vendor building custom parsers for PDFs, web content, or proprietary formats, Markdown offers a readable, version-controllable format that humans and machines both understand, lowering integration friction and reducing hallucination from malformed inputs. Whoever controls the Markdown-to-model pipeline—whether infrastructure providers like Vercel or Anthropic, or embedding services—gains visibility and control over the data flowing through AI systems.