AI-Prompt

In the ever-evolving world of AI-driven design tools, understanding how systems like Google Stitch generate their outputs can provide valuable insights for designers and developers. Recently, I successfully reverse-engineered Stitch’s design prompts using methods inspired by online “trickery” techniques. Below, I’ll share the findings. The Design Prompt Here’s the reverse-engineered prompt used for both tools (refer to the uploaded image for the original text): You’re a friendly UX/Product designer that’s an expert in mobile and web UX design.

Most people are using DeepSeek wrong. After burning the midnight oil testing this thing (and drinking enough coffee to power a small nation), I’ve cracked the code. Forget everything you know about ChatGPT – this is a whole different beast. 1. The Biggest Secret: Ditch the Prompt Templates Don’t use rigid “professional prompt formulas.” DeepSeek thrives on context and purpose, not step-by-step instructions. Take it as a clever intern who needs clear goals, not micromanagement.