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Soo… good afternoon guys 👋 Over the past 3 days, I’ve been working on setting up the @GoKiteAI Agent Passport. And I can finally say… I’m done 😭 It honestly wasn’t easy fr. What I thought would be a quick setup turned into a full learning experience. From getting everything running properly in Termux, configuring the agent environment, setting up the passport, understanding permissions, execution flow, and fixing random issues along the way… it took way more patience than I expected. There were moments I got stuck badly 😭 Moments I had to restart processes. Moments I kept rechecking the docs just to make sure I didn’t miss something small. But eventually everything started clicking together. And once the setup was finally complete, I decided not to stop at “setup successful.” I wanted to test something real. So I used the agent to order a book from @amazon using the @crossmint payment system. And honestly… this was the moment the whole idea of AI agents started feeling real to me. The process was actually crazy to watch. First, I defined the task clearly for the agent and configured the permissions inside the Agent Passport so it had controlled access to execute actions safely. Then I launched the workflow through Termux and let the agent handle the execution flow. From there, the agent: •searched for the book using the query system inside the agent workspace •identified a valid Amazon listing •prepared the checkout flow •and completed payment through Crossmint What stood out to me most was that I wasn’t manually controlling every step. Once the boundaries and permissions were defined, the agent simply operated within those limits and completed the task. That balance between: •autonomy •permissions •and real-world execution is what makes this whole system interesting. Crossmint acted as the payment bridge connecting the agent’s workflow to an actual real-world purchase, and seeing the order go through successfully honestly changed how I look at AI agents. It stopped feeling like “AI tools.” And started feeling more like delegating tasks to a digital operator that can actually execute actions on your behalf. This is where things start getting really interesting for me 🪁⚡ When running yours, if you run into issues or have questions, feel free to ask me or @0xLaughing. Shout out to people who helped me @KingTowdah @danielnwabuisi0 @marurlemo @david_grammy @Kite_Frens_Eco

GDAY KITERS 🪁 One important part of building an agent economy is figuring out how AI agents will handle money. Think about it. An AI agent may need to purchase data, access paid APIs, use computing resources, or pay another service to complete a task. But what kind of money should it use? This is where stablecoins become important. @GoKiteAI uses stablecoin-based payments to help agents interact with digital services without relying entirely on traditional payment systems. Here's how it works: 1. Stablecoin payments Stablecoins such as USDC provide a dollar-denominated payment option for agents. This makes it easier to price services and process transactions without the same price fluctuations associated with volatile crypto assets. 2. Automated payments Through Kite Agent Passport, users can authorize spending sessions with specific budgets and permissions. Agents can then make eligible payments within those approved boundaries. 3. Cross-chain support Kite is working toward making agent payments possible across multiple blockchain networks. This matters because agents shouldn't be restricted to services operating on just one network. 4. USDG support Kite has also introduced support for holding and sending USDG on Robinhood Chain, including gas-sponsored transfers and automatic USDC-to-USDG routing. This is particularly interesting because it reduces some of the friction involved in moving between supported stablecoin payment options. Why does all this matter? The agent economy will require more than intelligent software. Agents need a practical way to pay for the services they use, receive value, and interact with other applications. Stablecoins provide a useful payment medium, while Kite provides infrastructure designed to connect those payments to AI agent workflows. The bigger picture is simple: As AI agents become more independent, stablecoins could become one of the financial tools powering their everyday activities. Kite is building toward that future. HIGHER 🪁 @Kite_Frens_Eco @0xLaughing

GN KITERS 🪁 One interesting question about the future of AI is this: What happens when AI agents become active participants in the digital economy? Think beyond agents answering questions or automating simple tasks. Imagine an agent that can access financial services, interact with DeFi applications, move digital assets, and execute transactions across different networks to complete a task. For this to work, agents need more than a wallet. They need identity, authorization, and infrastructure that allows them to move value securely. This is the direction @GoKiteAI is exploring with what it calls Agentic Value Movement. Through Kite Agent Passport, users can define what their agents are allowed to do, which services they can access, and the conditions under which they can transact. The bigger idea is to connect AI agents to the existing digital asset ecosystem rather than build an entirely separate financial system for them. Why does this matter? Because as agents become more capable, they will need access to the same financial tools humans and businesses already use. Kite wants to help make that possible across applications, assets, and blockchain networks. We're moving toward an economy where AI agents won't just process information. They'll also participate in moving value. And that's a development worth watching. The next evolution of DeFi might not just be more users. It could be AI agents becoming participants in the ecosystem. @Kite_Frens_Eco @0xLaughing

GM KITERS 🪁 AI agents are getting smarter, but intelligence alone isn't enough. Imagine an AI agent that can research markets, pay for data, access different services, and complete tasks on your behalf without you having to manage every step manually. Sounds like the future, right? But for this to work, agents need more than intelligence. They need identity, payment infrastructure, and clear permissions that determine what they can do and how much they can spend. This is where @GoKiteAI comes in. Through Kite Agent Passport and its agent-focused infrastructure, Kite is working toward a future where AI agents can pay for digital services, interact with other systems, and execute tasks within limits defined by their users. Think about businesses using agents to gather information, analyze data, and access paid tools automatically. Instead of humans handling every transaction, agents could manage eligible payments as part of their workflow. That's what makes the agent economy interesting. We're moving from AI that simply answers questions to AI that can actually get things done. Kite is building toward that future, and I'm interested to see how far this ecosystem can go as adoption grows. What industry do you think will benefit the most from the agent economy: finance, e-commerce, or digital services? #KiteBBW Binace square post link: app.binance.com/uni-qr/cpos/…

GM KITERS 🪁🪁 For a while now, I haven’t been very active here because school has been keeping me busy. But while I was away, @GoKiteAI kept building, and there’s quite a lot to catch up on. So today, let’s talk about Kite AI, its recent developments, and why I think the direction it’s taking is worth paying attention to. First, what problem is Kite trying to solve? Think about how we use AI today. You can ask an AI to research a product, analyze data, write code, or plan a business campaign. But what happens when that AI needs to pay for a premium API, purchase a service, or complete a transaction to finish the task? That’s where things get complicated. AI agents need more than intelligence to perform useful work independently. They need an identity, clear permissions, access to payments, and a way to prove what they have done. This is the problem Kite AI is working to solve. Its goal is to build infrastructure that allows AI agents to transact and coordinate while remaining within boundaries defined by their users. And some of its latest developments show how this vision is taking shape. 1. Kite Agent Passport is becoming more practical One of the most important parts of the ecosystem is Kite Agent Passport. It allows an AI agent to make payments on behalf of a user without giving it unrestricted control over the user's funds. Instead, the user can approve a spending session with specific limits, such as a budget, an expiry time, and the services or assets permitted. Imagine asking an AI agent to research a topic using paid services. You could authorize a specific budget for that task. The agent can then make eligible payments within the approved limits, while its activity remains available for review. The important distinction is that the agent receives controlled authority, not unlimited freedom. That’s a meaningful step toward making AI agents useful beyond conversations. 2. The Passport dashboard and service discovery have improved Kite’s October 9 update introduced a redesigned Passport dashboard, support for Arc mainnet in the wallet, and a public Explore page where people can browse services and recipes without signing in. Why does this matter? Because infrastructure is only useful when people can understand and use it. A developer building an AI agent needs to discover available services. A user needs to understand payment activity and spending sessions. And both need a clearer way to interact with the system. Kite is working on these practical parts of the experience, not just the big idea of an agent economy. The same update also introduced an Aave auto-repay feature for eligible USDC loans on Base, allowing users to set a health-factor threshold and approve the action in advance. It’s an example of how agent infrastructure could support specific financial workflows rather than simply answering questions. 3. Kite is exploring more advanced agent payments Another important development is the continued work around x402 payments. In simple terms, x402 enables a service to request payment when an agent tries to access paid content or an API. The agent can then handle the payment process and receive the service response. Think of an AI research agent that needs information from several paid data providers. Instead of relying on a traditional subscription for every service, the agent could pay for eligible resources as needed, subject to the permissions and payment rules in place. This opens the door to a different way of delivering digital services: machine-to-machine payments, where software can pay other software to get work done. Kite Passport has also been developing multi-offer payment flows, helping agents handle situations where a service offers different payment options. The bigger idea is to make payments a natural part of an agent’s workflow. 4. Cross-chain payments and network support are expanding @Kite_Frens_Eco @0xLaughing

GN KITERS 🪁 One question I keep coming back to when thinking about @GoKiteAI is: What happens when AI agents stop waiting for humans to make every decision? Today, an AI agent can find information, analyze it, and recommend what you should do. But recommendation is only one part of the journey. The bigger opportunity is execution. Imagine telling an agent: “Find the best data source for this task, pay for access within my budget, process the information, and give me the result.” The agent would need more than intelligence. It would need an identity to operate with, permissions to act, a wallet to transact, and infrastructure to communicate with other services. That is where Kite AI becomes interesting to me. Its focus is not simply on creating smarter agents, but on building the infrastructure that allows agents to actually participate in a digital economy. The more I learn about this, the more I believe the next phase of AI won't be about humans doing everything through AI. It will be about humans setting the objective and AI agents handling the execution. And the infrastructure enabling that transition could become just as important as the AI models themselves. @Kite_Frens_Eco @0xLaughing