Günaydınlar tostlarım ♥️ Çok yoğun bir haftaya başladık , 4. etkinliğimizde yaklaşık 8. saatimiz. Türkiyeye mükemmel bir talep var çok fazla proje Türkiye’nin büyüklüğünün farkında ve etkinlikler planlıyorlar. @Cointelegraph’ın daveti üzerine VC yatırımları ve KOLs yatırımlarının farklılıklarını ve iki tarafında bakış açısı hakkında konuştuk. Davetleri için teşekkürler Hepinize güzel bir hafta dilerim ♥️

we're not giving these away to bots and farmers. if you've been here early, playing, posting, bringing friends, this one's for you.

This isn’t a trailer. This is the game. Shared galaxy. Raid bosses. PvP in the Dark Zone. Robinhood Chain has never seen anything like this.

I've been building this quietly for months. A space MMO that runs in your browser. No download, no install. Mine, fight, upgrade your fleet, and survive the invasion. @playnexaria coming to Robinhood Chain. The first pilots get in early. 👇

Dostlarım selamlar ♥️ Bir tokenın fiyat grafiğine bakmak yeterli mi? Bence değil. Bugün @nodiens üzerinden $AVAX’ı inceledim. Veriler pek iç açıcı görünmüyor. 📉 Sentiment Intelligence: -35 📉 Market Intelligence: -44 Her iki gösterge de bearish bölgede. Nodiens, X, Reddit ve Telegram’daki konuşmaları analiz ederek topluluğun piyasa duyarlılığını ölçüyor. Burada önemli bir ayrım var: Bir tokenın çok konuşulması, hakkında olumlu düşünüldüğü anlamına gelmiyor. AVAX’ın mevcut verilerini doğrudan satış sinyali olarak görmüyorum. Ancak işlem açmadan önce topluluk duyarlılığını fiyat ve hacimle birlikte değerlendirmeyi tercih ediyorum. Çünkü bazen piyasa duyarlılığı, fiyat hareketlerinden önce değişebiliyor. Siz AVAX hakkında ne düşünüyorsunuz? 🔗 app.nodiens.com/invite?refer…

If a service computes on encrypted financial data, how do you check that it performed the calculation correctly? That’s a different question from whether it could read your inputs. It’s the part of @primus_labs zkFHE approach I’m exploring next. FHE enables computation on encrypted data. But when that work is outsourced, the recipient also needs confidence that the agreed calculation was actually followed. Primus describes zkFHE as combining encrypted computation with proofs of correct execution. Consider a hypothetical institution calculating an exposure metric from confidential positions. It needs to protect the positions and check that the specified calculation was applied correctly. An encrypted result alone doesn’t answer both questions. A proof of execution still has a defined scope, though. It can establish that a particular computation was performed correctly without establishing that the chosen risk model captures every relevant risk. That distinction matters in institutional finance, where the inputs, calculation rules and interpretation of the result each need attention. What interests me here is the possibility of outsourcing useful computation while retaining a way to check the work and protect sensitive inputs. I’d watch the practical trade-offs too: proving time, computation cost and which workloads the system can support. Explore Primus and its XP tasks through my referral link: s.kaito.ai/fo3EOj9

I’m excited for 2027 We’re doing amazing work with amazing people. I’m happy to be with you guys! @surgence_io

You’ve built an AI agent that does something useful. How does someone find it, understand what they can buy, and hire it? That’s the developer side of @termix_ai I’m interested in. TermiX is building commerce and settlement infrastructure for the agent economy through AACP. agent.family is the marketplace built on that protocol, connecting agent services with potential buyers. Imagine a developer who builds an agent that turns messy spreadsheets into structured datasets. The underlying capability is useful, but a buyer needs a clear service offering: • What inputs does it accept? • What output will it deliver? • What are its limits? • What does it cost? Packaging the capability well makes it easier for someone to decide whether it fits their workflow. The campaign materials describe integration options including MCP, REST APIs, smart contracts and event streams. Those connections matter for developers who want their agents to participate in commerce from the tools they already use. For me, an interesting adoption signal would be developers offering narrow, understandable services that customers purchase repeatedly. “AI research assistant” is broad. “Turn these documents into a source-linked comparison table” gives a buyer something concrete to hire. That’s the opportunity I see in agent.family: helping developers connect a useful capability to a discoverable service and a payment workflow. Explore: agent.family

Finding new opportunities in crypto shouldn't require jumping between dozens of websites. 👀 My friends are building @LegosXIO , a platform that brings multiple Web3 tools together in one place. 🔹 NFT mints & potential airdrops 🔹 Ambassador programs & campaigns 🔹 Token unlocks, funding rates & mindshare 🔹 Watchlists, alerts & market analytics It's still in V1, with more features and improvements on the way. Definitely worth checking out, especially if you're an airdrop hunter or Web3 content creator. 🔗 legosx.io

A reserve figure needs context. Which assets does it cover? Where are they held? When was the information verified? What liabilities sit against them? That’s the angle I’m exploring next with @primus_labs Primus includes a Proof-of-Reserve service for onchain and offchain portfolio verification, bringing its data-verification infrastructure into a concrete financial use case. Onchain holdings can be inspected directly. Assets recorded in offchain systems introduce another question: how does someone verify information coming from those systems? zkTLS can help establish the authenticity of data obtained from an HTTPS source. That gives a reserve claim evidence tied to its source. The scope still matters, though. Verified assets alone don’t establish solvency. You also need to understand liabilities, ownership, restrictions and whether the information is current. For example, a verified balance at one moment doesn’t tell you whether those funds are pledged elsewhere or sufficient to cover every obligation. What interests me about Primus here is the potential to make reserve reporting more checkable and easier to update. For institutional onchain finance, the useful outcome would be a clearer view of what has been verified, when it was checked and what remains outside the proof. Explore Primus and its XP tasks through my referral link: s.kaito.ai/fo3EOj9

I think @KaitoAI is back. I wasn’t even in the top 100. I’ll be active in the new projects ❤️

An agent profile tells you what it claims it can do. Before hiring it, I’d also want to know: has it delivered this kind of work before? That’s another part of @termix_ai AACP design worth exploring: connecting agent identity with a record of job outcomes. The whitepaper describes reputation built around completion, on-time delivery, evaluation results and disputes. Those signals answer different questions. An agent might deliver quickly but struggle to meet requirements. Another might handle a narrow category of tasks consistently well. Imagine choosing an agent to analyze a dataset. A history of successful data-processing jobs would tell me more than a broad “research expert” description. Even then, reputation needs context. Completing straightforward jobs doesn’t establish that an agent can handle a complex security audit. I’d look at the work behind the score: • What tasks were completed? • How were the results evaluated? • Were there disputes, and how were they resolved? TermiX is building commerce and settlement infrastructure for agents, with agent.family as the marketplace built on AACP. For developers turning agents into services, a useful delivery history could become a reason customers choose them again. That’s what interests me here: giving buyers evidence they can inspect when deciding who to hire. Explore: agent.family