Shuzhi Huang

👋 Hi everyone, David here, co-founder of SuperIntern.AI We’re a team of ex-Google, Meta builders tired of company bureaucracies and passionate in building something fun, unique, and close to our heart. Why? Most AI products nowadays are “singleplayer mode”, it's yourself and AI. But humans are social animals, many of our magic moments happen in groups: where to eat, what to buy, how to proceed....

Sorry maybe a stupid question: why hosting on AgentSea’s own servers making it more privacy friendly?

The "27+ AI models" caught my attention - are these fine-tuned for specific use cases or more general purpose? And how does the Thinking Budget System actually work in practice? Is it token-based pricing or more like compute resource allocation across different models?

Gosh I love it, so addictive

Hi just curious, is this from DeepSeek? Seems I can't see any difference in the website, is it because of the region (i'm based in UK)?

Is there a way to deploy it to my enterprise setup? E.g. integrating with my team data and Microsoft teams?

Thanks team! May I ask that during the mock, are you testing with real humans or via simulations?

Trying this for my Spanish! Duolingo was a bit too prescriptive to me

The "self-healing tests" feature is intriguing - mobile UI changes break our test suites constantly, especially across different device sizes. How does it handle dynamic elements and screen responsiveness in React Native apps? Also curious about the session replay granularity for debugging failures

The LLM-powered discovery caught my attention - how does your natural language processing handle nuanced brand alignment beyond basic demographic matching? Most platforms still rely on keyword tags, but finding creators who actually "get" a brand's voice seems like the real challenge here.

The AI synthesis aspect is intriguing - how does the system handle conflicts when different personality frameworks contradict each other? Like if MBTI suggests one trait but Human Design points elsewhere? Does it weight certain systems more heavily or create some kind of meta-analysis?

This is incredibly helpful! My notion was a nightmare to navigate before and this seems very promising.

Just realized Macaron could be a game-changer for small businesses—imagine it whipping up custom CRM tools or inventory trackers on the fly based on casual chats. Does it support integrations with existing platforms, or is it more standalone? lowkey excited to test this out.

The idea of an AI agent handling 100k+ lines of code without errors is impressive. How does it handle edge cases or niche requirements—like integrating with obscure APIs or custom logic? Also, does it provide any debugging logs for transparency? Lowkey excited to try this for a side project.

Love the focus on realistic persona modeling—definitely a game-changer for testing. Curious if you've explored multilingual persona generation yet? For teams building global chatbots, that could be a killer feature to catch cultural nuances early. Also, how customizable are the personas—can we tweak things like verbosity or slang?

This is super cool! Is it easy to integrate?

Dumb question: is the data locally stored? Or how does it work en ensuring data privacy? :)

Hi team, if you could support crypto payment and handling cases like subscription which wasn't possible, that is a huge pain point. I believe for agent companies and with the current regulation trend, the lines between fiat and crypto will fast blur.

Seems there are quite many players here over the past 10 years, just curious how does it differentiate with those early players such as kajabi, circle.so, mighty network, bettermode, etc.? Sorry probably a super dumb question.