We faced a recurring issue in our content generation pipeline: the LLM frequently outputted malformed Markdown. Unclosed code blocks, broken list levels—you name it. Relying solely on Prompt engineering became a game of whack-a-mole that we couldn't win.
The core problem? Asking an LLM to generate Markdown is a probabilistic process. A Prompt is a "soft constraint." No matter how well you phrase it, a slight token fluctuation can break the syntax, causing frontend crashes.
The Shift: Data vs. Presentation
We realized we were violating the Single Responsibility Principle. We were asking the model to do two jobs:
Understand the content and generate data.
