In this podcast, Jason Zhou discusses the importance of prompt engineering for reasoning models like Google's Gemini 3, highlighting how concise and well-crafted prompts can significantly improve model performance. He references Anthropic's blog post on enhancing front-end design through skills and introduces a three-step process for crafting effective prompts: identifying convergent defaults, understanding the root cause of undesired behaviors, and structuring guidance with concrete alternatives. Zhou also mentions HubSpot's library of cloud-skilled prompts and shares a practical example of tuning a model for high-quality Excalibur Y-frame designs, emphasizing the iterative nature of prompt improvement and the integration of these techniques into superdesign.dev for UI generation.
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