I spent the first few months of the AI boom treating prompts like magic spells. I would tweak a word here, add 'think step by step' there, and hope for the best. When it worked, I felt like a wizard. When it broke in production, I had no idea why.
If you are building features that rely on Large Language Models (LLMs), you need to stop guessing. Prompting is not a mystical art. It is a configuration problem.
The Problem With 'Vibe-Based' Development
Most developers start with a single long string in a variable. They send it to the API, look at the output, and manually edit the string until the output looks right. This is vibe-based development.
The issue is that LLMs are non-deterministic. A prompt that works for one edge case might fail for another. If your prompt is a 500-word block of text, changing one sentence to fix a bug in the 'user profile' logic might accidentally break the 'password reset' logic.
