Markdown is widely used for documentation, but it has significant limitations, especially for technical content. While it’s user-friendly and makes documents visually appealing, Markdown lacks the semantic structure needed for effective machine consumption. Search engines and AI tools rely on well-formed HTML with specific semantic tags. Markdown's simplistic syntax can lead to ambiguities that hinder accurate indexing and parsing. Developers often find themselves constrained by Markdown's inconsistencies, as different flavors of Markdown yield varying results depending on the platform. The article compares Markdown to programming languages with implicit typing, where flexibility comes at the cost of structure and guarantees. Without strict rules, headings and other elements can become misclassified. This inconsistency becomes especially problematic when reusing or syndicating content across different systems. Tools like MDX try to extend Markdown's capabilities but introduce their own issues with portability and compatibility. For those seeking more robust documentation formats, the article highlights alternatives like reStructuredText, AsciiDoc, and DocBook. reStructuredText supports structural semantics and is used in Sphinx documentation. AsciiDoc combines human readability with semantic expression, allowing for attributes and cross-references. DocBook, an XML-based format, provides a clear hierarchical structure with meaningful tags, enabling complex transformations. Each of these options offers greater control over content structure, ensuring better machine understanding and easier content reuse across various formats.