Major UX shifts as Perplexity introduces multi-model comparisons, OpenAI tests ads in ChatGPT, and Vercel tackles AI search optimization for developers.
Today in AI Products
 Perplexity |
Feb 9 |
Model Council compares answers across three AI models
Perplexity launched Model Council, a new feature that shows responses from three different AI models side by side for the same query. Users can now compare how different models interpret and answer their questions, getting multiple perspectives in a single interface. Source →
Designer's Takeaway: Consider how comparative interfaces can reduce user uncertainty when AI outputs vary. Apply this pattern by showing confidence levels or alternative approaches when your AI might have multiple valid responses.
Pattern: Explainable AI (XAI)
 ChatGPT |
Feb 9 |
Testing ads in ChatGPT with user controls and privacy focus
OpenAI announced they're testing ads in ChatGPT to support free access. The ads will be clearly labeled, won't influence answer quality, and include strong privacy protections with user control options. This marks a significant shift in how AI chat interfaces might monetize. Source →
Designer's Takeaway: Notice how OpenAI emphasizes transparency and user control in their ad integration. Apply this by designing clear visual distinctions between AI responses and sponsored content, ensuring users always understand what they're seeing.
Pattern: Responsible AI Design
 Vercel |
Feb 9 |
AEO tracking system monitors how AI models discover web content
Vercel built an AI Engine Optimization (AEO) system to track how large language models search for, interpret, and reference their web content. The system expanded beyond standard chat models to include coding agents, recognizing that AI discovery patterns differ significantly from traditional SEO. Source →
Designer's Takeaway: Consider how AI agents interact with your product's content differently than human users. Design content structures and documentation that work well for both human comprehension and AI parsing, especially for developer-facing products.
Pattern: Ambient Intelligence
| Vercel |
Feb 9 |
Platform approach needed for AI agent deployment at scale
Vercel highlighted how AI democratizes agent building but not deployment. While anyone can prototype sophisticated agents quickly, production deployment often results in unnecessarily expensive infrastructure when simple, cost-effective solutions would suffice. The build vs. buy equation has fundamentally shifted. Source →
Designer's Takeaway: Apply this insight by designing onboarding flows that help users understand deployment costs early. Consider progressive disclosure patterns that surface infrastructure complexity only when users need more advanced features.
Pattern: Progressive Disclosure
Today's Takeaway
Transparency becomes the new competitive advantage
As AI products mature, companies are competing on trust and clarity rather than just capability. From Perplexity's model comparisons to OpenAI's transparent ad approach and Vercel's infrastructure honesty, the winners are those helping users understand what's happening behind the interface. Design for transparency, not just functionality.
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