Recently, everyone should have noticed a trend: major CEX players, including OKX, are crazily promoting Agenticization strategies. Why does CEX need to make every effort to break away from the traditional trading methods of "human flesh monitoring the market" and "manual ordering" in the past? The core reason is that the pure service "human" trading scenario has encountered a growth bottleneck, and now everyone is running into the AI trading track to grab a foothold. @ derivio-xyz has also launched a new trading paradigm of full chain AI native trading terminals in this context. How to do it specifically? It did not focus on the graphical user interface (GUI), but instead developed a hardcore Agenetic Terminal CLI (Command Line Terminal). At first glance, it may seem like an interactive form of "atavism", returning to the era of programmer preferences in Linux. However, assuming your users have all become agents, this may not necessarily be the case. Because in the past GUI mode, it was designed for the human eye (traders), requiring you to cut web pages, look at charts, click buttons, and the process was lengthy and full of uncertainty. And CLI is designed for code and AI agents, it is purely intent and execution. In this CLI terminal, you don't need to cross multiple web pages to collect information, analyze fund flows, or manually calculate slippage. You only need to input a trading intention, and the AI agent integrated in the Derivio backend will automatically decompose the task, completing the entire process from information capture, signal extraction to final execution. This is what is known as' one person is a quantitative team ', which separates the tedious execution layer from AI, and people are only responsible for the decision-making layer. But whether the agent can run smoothly or not, relying solely on innovative and eye-catching interactive forms is obviously not enough. The key still depends on whether the trading experience can withstand the test? Derivio is well aware of this, so they put in a lot of effort to independently develop a high-performance Data Engine. The function of this engine is to clean the unstructured data and exclusive on chain anomalies of the entire network into signals that agents can understand in real time, as well as quantify market sentiment in real time. The ability of "millisecond level data cleaning+fast execution" is the true moat of AI Trading. Think about it, when faced with drastic market fluctuations, others are still waiting for the front-end UI to refresh, and they are still pulling the network cable from the trading platform. Your agent has already analyzed a wave of data and quietly completed the position building. On this basis, Derivio has also solved a funding efficiency issue that Smart Money is most concerned about: to establish a closed loop between high volatility spot and high stability wealth management funds within the same terminal. For example, when Agent traders capture profits from Alpha, they can deposit funds into interest bearing assets such as tokenized US bonds with just one click. This seamless asset rotation eliminates the friction costs of cross chain and authorization, which is very in line with the fund management logic of professional traders. Derivio's use of Agentic terminals to reconstruct transaction paradigms is in line with current infrastructure trends. In the current environment of cold liquidity in the primary market, it was recently announced that it had won a strategic financing of $6 million against the trend, indicating that this is also a new trend favored by top capital. Finally, just wait for the "wow" confirmation from a professional human trader at some point one day, after all, any trading tool must serve the goal of making money, even if the subject is changed to an agent. Note: By the way, if the agentialization of transactions is also a new narrative, the process of experiencing, criticizing, and roast about new products can also be air dropped. You can participate in the experience appropriately.