Stop Generating "AI Slop": The Developer's Guide to Google Stitch
The article discusses how to use Google Stitch, powered by Gemini 2.5, to build high-quality user interfaces by engineering prompts with semantic precision, rather than relying on generic, AI-generated templates.
Why it matters
The article provides a guide for developers to leverage the power of Google Stitch and AI-generated UI design, while avoiding the pitfalls of generic, low-quality results.
Key Points
- 1Stitch moves from an imperative to a declarative model for UI development
- 2Prompts need to include context, structure, aesthetic, and tech stack to avoid "AI Slop"
- 3Precise art-history and design terms work better than vague adjectives for aesthetic prompts
- 4Layout prompts should provide a blueprint instead of letting the AI guess the structure
Details
The article explains that Stitch doesn't just paste images together, but tokenizes prompts into categories. To avoid generic, vanilla interfaces, prompts need to be engineered with semantic precision across four layers: context (who the UI is for), structure (layout topology), aesthetic (the "vibe"), and tech stack (execution medium). The author provides examples of how to craft expressive prompts for different aesthetic styles (vintage, retro, brutalist) and layout structures (bento box grid). The goal is to move beyond basic prompts and generate production-ready code that looks designed by a human.
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