Nick Rotenberg

Primus zkTLS × Kaito Pulse & Aura! Your online reputation should reflect what you actually do, not just how much attention you get. I think the collaboration between @primus_labs and @KaitoAI is a good example of how Web3 reputation systems could become more useful. A lot of people spend their time trading, building products, contributing to communities, and using different platforms. But proving those activities to people outside those platforms isn't always easy. -> This is where @primus_labs comes in... Primus uses zkTLS technology to help users verify specific information from websites and online services without sharing unnecessary private data. For example, imagine you've been trading on an exchange for several months. You want to prove that you've reached a certain trading volume, but you don't want to share your password or give another application full access to your account. With Primus zkTLS, you can generate cryptographic proof of a supported claim using information from the original platform. The receiving application can verify that information without needing your login credentials or complete account history. Now, this is where the Kaito integration becomes interesting. @KaitoAI Pulse can use @primus_labs zkTLS to bring verified off-platform activity into the X experience. And Kaito Aura can consider verified activities as part of a broader approach to measuring online reputation. Of course, verifying an activity doesn't automatically mean someone is trustworthy or guarantee a higher reputation score. But it gives reputation systems more useful information to work with. I think this matters for creators, traders, and community contributors. Someone might spend months supporting an ecosystem, testing products, or building something valuable without having a massive following. If those contributions can be verified, their experience becomes easier to recognize beyond their own community. -> And the potential goes beyond reputation. The same technology could support digital identity, access verification, financial applications, and other services that need reliable information from existing online platforms. What I like about this collaboration is that it's not just about adding another feature to Web3. It's about connecting real online activity with information that other applications can verify. A large audience can show how much attention someone receives, but it doesn't always reflect their actual experience or contributions. That's why I think bringing verifiable activity into reputation systems is a direction worth exploring. -> Explore primus: s.kaito.ai/iS3At9q !!

Can we really trust what AI agents tell Us ? imagine asking an AI agent to check $BTC market data before making a trade. within seconds, it gives you the price, some analysis, and a suggestion on what to do next. sounds pretty useful. but what if the agent never actually checked the exchange it claims to have used? that's a question that came to mind while i was exploring @primus_labs and its work around verifiable AI agents. AI is already changing how we research tokens, track wallets, and understand the market. but when real money is involved, knowing where the information comes from matters just as much as getting an answer. and this is where @primus_labs caught my attention. its zkTLS technology helps verify information coming from websites and APIs through cryptographic proofs. in simple terms, an AI agent could show evidence that certain data actually came from an exchange, rather than just claiming it did. what made this even more interesting was something i found on their @github. Primus has developed @binance Verifiable Skills and @okx OnchainOS Verifiable Skills. these tools help developers connect exchange APIs with zkTLS verification. the Binance examples cover services like Spot and Futures, while the OKX tools explore market data, token information, and other API interactions. i like that there's actual developer work behind the idea, not just a discussion about what AI might do someday. imagine a trading agent checking an exchange, getting the latest available market response, and attaching proof of where that information came from. you could verify the source data without having to take the agent's word for it. of course, there's one thing worth remembering. real data doesn't always lead to the right decision. even with verified information, an AI agent can still make mistakes or suggest a bad trade. zkTLS helps with checking the data source, not guaranteeing the quality of an AI's decisions. personally, i think that's an important distinction. as AI agents become more involved in crypto, i'd like to see more tools that help people understand what happened behind the scenes. not just faster answers, but better ways to check the information those answers are built on. i also made a 30-second motion video to show how this works, from an AI agent requesting market data to Primus helping create a verifiable proof. tried to keep it simple so anyone curious about the technology can follow along. the more i explore @primus_labs the more i see why verifiable data could matter for the next generation of AI agents. because at the end of the day, a confident AI answer is useful, but knowing where its information came from is even better. -> explore primus: !!