Common Mistakes With Vibe Coded Websites
In a Nutshell
AI-assisted website coding produces ubiquitous "slop" like purple gradients, distracting scroll-following lines, dumb hover effects that hide navigation, scroll jacking, and low-contrast text, eroding originality and user trust across YC startups. These trends arise because LLMs replicate popular designs easily, but founders must QA rigorously, prioritize inviting hovers that enhance clickability, ensure visual consistency, and craft opinionated hierarchies to stand out. Use AI to accelerate unique, conversion-focused designs—start with a deliberate color palette and brand system, not accept raw outputs.
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Common Mistakes With Vibe Coded Websites
It's easier than ever to design with AI tools, but that doesn't mean you should always accept all changes. Today, joined by Raphael Shad, one of the newest visiting partners at YC, co-founder of Kron (modern calendar tool sold to Notion), to look at the good, the bad, and the ugly of AI-assisted design and how to use these superpowers to stand out.
Raphael is thrilled to be back at YC helping the next generation of founders build iconic companies.
Topic is AI design trends: on the negative end, AI design slop; on the positive end, easier to build for anyone even if not a designer.
Common trends Raphael has seen:
- Dumb hover effects on startup landing pages, presumably AI-coded.
- Purple gradients everywhere on startup websites.
- Sections that fade in and fade out as you scroll.
These aren't inherently bad, but they're now ubiquitous, losing meaning, specialness, and originality.
In the old world, good websites established trends slowly; now LLMs train on popular examples (e.g., good site with purple gradient gets linked a lot), so next week all startups look the same.
This power is both good and bad if used right. Reviewing YC companies' websites built with AI coding tools to see what's used well and what to do differently.
new.ai: Solve your game testing with AI agents. Save countless hours of manual game QA by using AI agents performing end-to-end tests at scale.
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