Rethinking AI Search: Building Rixx for Research, Exploration, and Creation
The article discusses the limitations of current AI search tools and the vision behind building Rixx, an AI-powered search engine that goes beyond just answering queries to support deeper research, verification, visual exploration, and turning insights into useful outputs.
Why it matters
The article highlights the need to rethink AI search beyond just providing quick answers, and outlines a vision for a more comprehensive research and exploration tool that can drive deeper understanding and meaningful outputs.
Key Points
- 1Current AI search tools focus too much on just providing quick answers, missing the need for deeper verification, exploration, and turning research into something useful
- 2Rixx aims to provide better AI-generated answers, the ability to choose different models, deep verification workflows, personalized memory, exports, shareable chats, visual exploration, and the ability to turn search sessions into blog posts
- 3Improving answer quality is a key priority, as speed is less important than providing nuanced, well-reasoned responses that users can verify and build upon
- 4Allowing users to choose the most appropriate AI model for their task is important, as different models excel at different things
- 5Verification and helping users feel confident about the information they're consuming is crucial, not just generating responses
Details
The article argues that current AI search tools, while impressive, often feel incomplete. While quickly answering queries is useful, the real value comes from helping people search better, verify information more deeply, explore visually, and turn research into something actionable. The author started building Rixx, an AI-powered search and research engine, to address these needs. Rixx aims to go beyond just providing answers to support deeper verification workflows, personalized memory, exports, shareable chats, visual exploration, and the ability to turn search sessions into blog posts or other useful outputs. Improving answer quality is a key priority, as speed is less important than providing nuanced, well-reasoned responses that users can verify and build upon. Allowing users to choose the most appropriate AI model for their task is also important, as different models excel at different things. Verification and helping users feel confident about the information they're consuming is crucial, not just generating responses. The article also discusses the importance of making search more visual, as charts, graphs, and interactive visuals can often explain things faster than plain text.
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