Barbera opens a window onto Palermo today ☕️ Espresso, cream, cocoa and cinnamon meet in the legend of “caffè del parrinu.” A cup of #Coffee becomes a little letter Sicily sends from the past to the present 💌 Some stories are read, others are sipped.

A hotel doesn’t need its own taxi fleet to offer guests an airport transfer. 🏨 It can connect an outside service to its booking workflow. ​ No need to send the receptionist to driving school just to get a guest from the airport. 🙂 ​ That’s how I read @termix_ai’s latest SDK announcement: An app doesn’t need to become an AI agent to buy services from one. ​ The SDK gives developers software tools to connect the TermiX marketplace to their existing applications. ​ With TypeScript, Python and Go support, an app can work within its own workflow to: ​ 🔎 Discover agent services. ​ 🧾 Place orders. ​ 📦 Receive deliverables. ​ 💳 Settle payments onchain. ​ AACP is the core protocol behind TermiX’s commerce and settlement infrastructure. agent.family is the marketplace built on it. The SDK helps applications connect to that marketplace. ​ My earlier post explored how Agent Skills gives agents access to the market. This time, the door opens from the other side: Existing software can become a customer of those services. ​ Imagine a content app. A user enters their brand details. The app buys a service from a suitable video agent and adds the delivered video to the user’s project. ​ That’s a possible integration, rather than a feature I’m claiming every app already has. ​ But the important choice is this: An app doesn’t need to produce every capability in-house. ​ Like a hotel arranging an outside transfer, software can hire a specialist agent for a particular job. ​ 🔐 Transaction authority still matters. The SDK can return unsigned transaction data for the app’s own signer to handle. With a connected signer, it can also manage signing and broadcasting. ​ Making integration easier doesn’t remove the need for transaction authorization. ​ For me, that’s where the economic angle gets interesting. Listing more agents expands the supply of services. Opening a purchasing path inside existing apps could expand the customer side. ​ A need could become a service order while the user is already working in their familiar app. ​ Of course, an SDK alone doesn’t prove those orders are arriving or that customers are satisfied. But it opens another route for demand to reach the marketplace. ​ The agent economy’s next customer might be someone trying to finish a task in an app they already use. ​ The hotel stays a hotel. It just doesn’t need a new department in the basement for every service. 😄

You can’t bring a truckload of parts to a factory and say, “What you need is probably in there. Good luck.” 📦 If you do, you’ve delivered a treasure hunt along with the shipment. 🙂 When delivering data for robot training, the customer’s first question is reasonable: “𝗦𝗼 𝘄𝗵𝗮𝘁 𝗷𝗼𝗯 𝘄𝗶𝗹𝗹 𝘁𝗵𝗶𝘀 𝘁𝗲𝗮𝗰𝗵 𝗺𝘆 𝗿𝗼𝗯𝗼𝘁?” What catches my attention about @axisrobotics’ commercial approach is how it structures delivery 𝗮𝗿𝗼𝘂𝗻𝗱 𝘁𝗵𝗲 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿’𝘀 𝘁𝗮𝘀𝗸. 🔧 The 𝗧𝗮𝘀𝗸 𝗣𝗮𝗰𝗸𝗮𝗴𝗲 is defined as its core commercial unit. Four elements define the package’s scope: 🏭 𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼: Where will the robot operate, and what job will it do? 🦾 𝗦𝗸𝗶𝗹𝗹𝘀: Which movements are needed, such as grasping, placing, or rotating? 🔀 𝗜𝗻-𝘁𝗮𝘀𝗸 𝘃𝗮𝗿𝗶𝗮𝘁𝗶𝗼𝗻: What variations in objects and layouts will it encounter? 📚 𝗧𝗿𝗮𝗷𝗲𝗰𝘁𝗼𝗿𝗶𝗲𝘀: How much usable training data will be delivered? This lets the customer assess which operating conditions and behaviors the package covers. “𝗛𝗼𝘄 𝗺𝗮𝗻𝘆 𝗚𝗕?” 𝗶𝘀 𝗷𝗼𝗶𝗻𝗲𝗱 𝗯𝘆 “𝗪𝗵𝗮𝘁 𝗷𝗼𝗯 𝘄𝗶𝗹𝗹 𝗶𝘁 𝗵𝗲𝗹𝗽 𝘄𝗶𝘁𝗵?” We can’t assume the robot has learned a trade just because the hard drive is full. 😄 And every customer doesn’t want the same delivery. 🧩 🧠 For a 𝗺𝗼𝗱𝗲𝗹 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝘁𝗲𝗮𝗺, the product could be training data, structured task bundles, or joint model training. 🦾 For a 𝗿𝗼𝗯𝗼𝘁 𝗺𝗮𝗻𝘂𝗳𝗮𝗰𝘁𝘂𝗿𝗲𝗿, the process could include integrating its hardware into simulation, generating tailored data, and validating the trained model on the physical robot. 🏭 For an 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿, the offering extends to an automation solution for a specific production workflow. 𝗪𝗵𝗮𝘁 𝗴𝗲𝘁𝘀 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝗲𝗱 𝗱𝗲𝗽𝗲𝗻𝗱𝘀 𝗼𝗻 𝘄𝗵𝗲𝗿𝗲 𝘁𝗵𝗲 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗻𝗲𝗲𝗱𝘀 𝘀𝘂𝗽𝗽𝗼𝗿𝘁. One wants training material. Another wants a workflow that works with its own robot. The factory cares about how the job gets done during the shift. You can’t send the sales presentation to work in the robot’s place. 🙂 Axis also reports 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝗶𝗻𝗴 𝗮 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗱𝗮𝘁𝗮𝘀𝗲𝘁 𝗰𝗼𝘃𝗲𝗿𝗶𝗻𝗴 𝟯𝟱 𝘁𝗮𝘀𝗸 𝗽𝗮𝗰𝗸𝗮𝗴𝗲𝘀 to a model company. 📦 To illustrate the contents of that delivery, it examines the robot’s workspace, the distribution of movements, and the precision different tasks require. A short movement toward a target and aligning a part for insertion into a hole don’t have the same training needs. 𝗧𝗵𝗲 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆’𝘀 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗺𝗮𝗸𝗲𝘀 𝘁𝗵𝗲𝘀𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲𝘀 𝗮𝘀𝘀𝗲𝘀𝘀𝗮𝗯𝗹𝗲 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿. Of course, delivering a data package doesn’t guarantee success across every production condition. 🔧 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗼𝗻 𝘁𝗵𝗲 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿’𝘀 𝗿𝗼𝗯𝗼𝘁 𝗮𝗻𝗱 𝗶𝗻 𝗶𝘁𝘀 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁 𝗿𝗲𝗺𝗮𝗶𝗻𝘀 𝗽𝗮𝗿𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗷𝗼𝗯. My second takeaway is this: 💡 𝗔 𝘁𝗮𝘀𝗸-𝗱𝗲𝗳𝗶𝗻𝗲𝗱 𝗱𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗰𝗼𝘂𝗹𝗱 𝗺𝗮𝗸𝗲 𝗶𝘁 𝗰𝗹𝗲𝗮𝗿𝗲𝗿 𝘄𝗵𝗮𝘁 𝘁𝗵𝗲 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝗶𝘀 𝗯𝘂𝘆𝗶𝗻𝗴 𝗮𝗻𝗱 𝗵𝗼𝘄 𝘁𝗼 𝘁𝗲𝘀𝘁 𝗶𝘁. Which behaviors are covered? Which conditions are represented? What needs to be validated in the target environment? As these questions become clearer, customers can compare offers by 𝗵𝗼𝘄 𝘄𝗲𝗹𝗹 𝘁𝗵𝗲𝘆 𝗳𝗶𝘁 𝘁𝗵𝗲𝗶𝗿 𝗷𝗼𝗯, alongside data volume. A full truck is good. A load that helps the customer do the job is better. Writing “a bunch of stuff” on the delivery note rarely amuses the purchasing department. 🧾

A chef liking their own food is a good start. But if they’re also the restaurant’s only customer, we’re still testing the kitchen. 🍽️ Changing hats and sitting at three different tables doesn’t make you three customers. 🎩 One requirement in BNB Chain’s Set and Earn campaign brings this distinction into focus for @termix_ai: 🧾 The agent you build must receive at least three completed hires from three distinct wallets that you neither own nor fund. This is 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗰𝗼𝗻𝗱𝗶𝘁𝗶𝗼𝗻𝘀 for a qualifying agent in the campaign. TermiX is among its nine shortlisted marketplaces. The important detail isn’t just the transaction count. It’s the relationship between the wallets placing orders and the builder. 🔗 𝗧𝗵𝗿𝗲𝗲 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 𝗮𝗱𝗱𝗿𝗲𝘀𝘀𝗲𝘀 𝗱𝗼𝗻’𝘁 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗰𝗮𝗹𝗹𝘆 𝗺𝗲𝗮𝗻 𝘁𝗵𝗿𝗲𝗲 𝗶𝗻𝗱𝗲𝗽𝗲𝗻𝗱𝗲𝗻𝘁 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀. This condition excludes hires from wallets the builder owns or funds from that eligibility requirement. My previous post explored the value of a second order. This time, I’m taking the question one step back: 𝗪𝗵𝗼 𝗽𝗹𝗮𝗰𝗲𝗱 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗼𝗿𝗱𝗲𝗿? 🤔 🧩 TermiX’s AACP infrastructure connects agent identity, service discovery, offers, escrow, delivery and payment settlement into a commerce workflow. agent.family is the marketplace built on that infrastructure. In restaurant terms: 📋 The menu describes the service. The order specifies what’s wanted. Delivery is the plate arriving at the table. 🔐 Escrow is the till where money reserved for the order is managed under defined transaction rules. But a transaction in the till doesn’t explain why the customer came. One boundary matters here: Set and Earn counts testnet hires too, and the campaign offers rewards. 🎁 So an agent meeting this requirement hasn’t automatically proven 𝗹𝗮𝘀𝘁𝗶𝗻𝗴 𝗱𝗲𝗺𝗮𝗻𝗱 𝘄𝗶𝘁𝗵𝗼𝘂𝘁 𝗶𝗻𝗰𝗲𝗻𝘁𝗶𝘃𝗲𝘀. Still, it’s a more meaningful threshold than simply registering an agent: Completed hires from other wallets are required. ✅ Building an agent is like opening the kitchen. Someone else choosing it is the menu starting to find an audience. The chef saying “this turned out great” doesn’t earn the restaurant a star. ⭐ When a customer asks for a second plate, the conversation gets more serious. 🙂

Coffee teaches us to slow down. The marketplace has other ideas ⏱️ Getting lost in @Barbera_1870’s roasting legacy sounds lovely… until someone races past in three seconds, taking your sleep and your pride with them 😄 The #coffee isn’t the only thing brewed strong here. So is the competition ☕