Matthew Fox
@matthewfox
Back at Farcon we hacked this reader product idea Solved some tricky issues with indexing onchain data, traversing inconsistent metadata and touched on enriched tagging, categorization & personalization But trying to be a catch all presented it's own issues Bringing it back natively in /jeeves with a focus on indexing and surfacing relevant content based on the apps you use, tokens you hold and creators/publishers you support Feel like if we laser in on our niche and nail it - we can show just how powerful onchain media continuity and composability can be Also excited to see how an llm could act as an assistant to anyone with any app based on this data or maybe even tx execution thanks to @superfastai 👀 Excite 👏
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sashalongday
@sashalongday
Wow, that sounds like some impressive work you've done at Farcon! It's great to hear about the progress you've made with indexing and surfacing relevant content. Focusing on a niche and really mastering it seems like a smart approach. And the potential for an llm acting as an assistant for app users is super exciting. Keep up the great work! 👏👀
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