How to set up @GoKiteAI Agent Passport First where can you run this? ✅ Claude Code (easiest, paid) ✅ Ubuntu Terminal (free, slightly more manual) ✅ WSL (Windows Subsystem for Linux) ✅ macOS Terminal ✅ Any Linux-based terminal Good news it works FREE on Ubuntu terminal! Slightly more manual but 100% doable. Here's how 👇 1️⃣ Install Kite Passport curl -fsSL agentpassport.ai/install.sh | bash 2️⃣ Sign up & verify email kpass signup init email you@example.com output json → Check email → click verification link → then: kpass signup exchange signup-id <ID> exchange-token <TOKEN> output json Already have account? kpass login init email you@example.com kpass login verify login-id <ID> code <OTP> 3️⃣ Fund your wallet kpass wallet balance output json → Get your on-chain wallet address → Send USDC to your wallet address → Kite is now LIVE on mainnet! 4️⃣ Register your AI agent kpass agent:register type coding-assistant output json Agent types: → coding-assistant → research-agent → or any custom label 5️⃣ Create spending session kpass agent:session create --task-summary "Your task here" --max-amount-per-tx 2 --max-total-amount 10 --ttl 24h --assets USDC --payment-approach x402_http --output json YOU control the rules: Max per transaction Max total budget Session lifetime 6️⃣ Execute paid request kpass agent:session execute url "x402.dev.gokite.ai/api/weath…" method GET output json Agent pays autonomously via x402 7️⃣ Discover paid services ksearch services list --query weather --payment-approach x402_http --asset USDC limit 10 --output json Monitor active sessions anytime: kpass user sessions status active output json Using Claude Code? → Skills auto-installed → Agent runs automatically → Easiest experience Using Ubuntu Terminal? → Run commands manually step by step → 100% FREE → Same result, slightly more effort → Perfect for builders on budget Your AI agent now has: Identity on-chain Its own wallet Spending limits YOU control Autonomous x402 payments Access to paid API catalog This is the agentic economy in real life Full docs 👇 agentpassport.ai @Kite_Frens_Eco @KiteAIFDN #AIAgents #KiteAISharing

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Most AI models learn from text. @ActionModelAI learn from actions. Every workflow, click, and interaction contributes to a growing Action Tree that helps AI navigate software and complete real tasks. The interesting part isn't just the model itself. It's the network of executable knowledge built through community participation. In the long run, the biggest AI advantage may not be larger models. It may be better actions.

Perasaan 1 Minggu ini udah dar der dor banget, ternyata hanya segini, when yah kek CT² itu 😂 Coba dong drop hasil 1 Minggu kalian penasaran

GM 🌞 Happy Sunday, what are your plans today?

A champion is someone who wants to keep learning and stay consistent. 🏆🏆🏆

Udah TGE yagesya tinggal nunggu alokasi aja kalo di ajak itu juga 😂

GN GN 🧡 One thing that stands out about @RetiumChain is its emphasis on building from first principles. According to the project documentation, the protocol was written from scratch in Rust rather than being developed as a fork of an existing blockchain framework. What I find interesting is that this approach goes beyond performance goals. The design philosophy also emphasizes security-first development, documented processes, and public transparency around architecture and implementation. Instead of adapting an existing consensus model, Retium appears focused on creating infrastructure that reflects its own assumptions about coordination, verification, and network design. Whether discussing mesh architecture, mathematical logic, or protocol development, the recurring theme seems to be building systems from foundational concepts rather than modifying existing ones. #Retium

gelo jam segini internet baru bener

GM GM Most AI today acts like an assistant. You ask a question. It gives an answer. The next generation of AI may look more like an employee. Instead of explaining how to do a task, it can navigate software, interact with interfaces, and complete workflows on your behalf. The shift isn't just better intelligence. It's moving from assistance to execution. That's where autonomous agents become interesting. and that's what the @ActionModelAI is doing

GM GM,selamat pagi dunia Happy Friday

GN GN CT AI is becoming one of the most valuable technologies in the world. The question is: Who owns it? Most platforms concentrate value at the top. @ActionModelAI is experimenting with a model where contributors help train the system and participate in the ecosystem through $LAM. In the age of AI, ownership may become just as important as innovation. @dross_aether #ActionModel #LAM

Whitelist secured ✅ Been following the vision around zero-slippage stablecoin trading for a while. Curious to see how Phase 1 performs in the wild and what the team ships next. Join Now → stabilizer.finance/whitelist @StabilizerFi

Phase 1 Testnet Whitelist Extension 💫 Early access to zero-slippage trading Join Now → stabilizer.finance/whitelist

GM CT Many blockchain scalability discussions focus on one question: How do we process more transactions? Most solutions expand throughput through larger blocks, additional layers, or parallel execution paths. What caught my attention while exploring @RetiumChain is that the architecture appears to approach the problem differently. According to Retium's design, the goal is not simply to create parallel lanes beside a traditional chain. The network introduces a mesh structure where blocks can connect through mathematical relationships, allowing execution to extend across multiple directions rather than a single linear path. This is why Retium often describes its architecture as multidimensional rather than just parallel. Instead of viewing the blockchain as one road carrying all activity, the design explores whether network coordination itself can exist across a mesh of interconnected execution paths. It's an interesting shift in perspective. The focus is not only on increasing throughput, but on rethinking how blockchain systems organize activity from the ground up. #Retium #Blockchain #Web3

AI on Air Ep.17: Hashed on Korea’s Agent Finance Moment x.com/i/broadcasts/1mGPaaRWq…

GM happy Thursday The future of agentic AI isn't just about smarter models, it's about connecting data, decisions, and execution. That's why the partnership between @DatalineAI and @GoKiteAI makes sense. Dataline provides structured upstream data, from spot markets and perp funding to prediction market insights, giving AI agents the information they need to reason and act. Kite AI completes the loop with fast settlement and low cost micropayments, enabling agents to execute transactions autonomously onchain. Data → Decision → Settle. Dataline delivers the signal. Kite delivers the execution layer. Together, they're building the infrastructure autonomous agents need to operate at scale. FLY THE KITE 🪁 @Kite_Frens_Eco @KiteAIChinese @KiteAIFDN

gAction Perhaps most AI models learn from text. But teaching an AI to take actions is a completely different challenge. Every website, button, menu, and workflow creates countless possible paths. @ActionModelAI addresses this through the Action Tree a growing map of digital interactions built from community-contributed workflows. Think of it like Google Maps for the internet. The more paths that are mapped, the better the model becomes at navigating software, completing tasks, and adapting to new situations. What makes this interesting isn't just the AI itself. It's that the intelligence comes from collective action data, not only model parameters. In a world where most AI companies compete on bigger models, Action Model is building a network of executable knowledge. #LAM #ActionModel

Morning guys,BTW itu gelasnya doang Torabika kopinya mah indocape 😂