Current AI products are too good at impressing users for ten minutes—but it’s hard to earn their trust for ten months. This is especially true for trading agents. Asking an AI to analyze market conditions once is easy, but once personal asset data, research files, and continuous monitoring tasks are involved, user expectations change completely. I just discovered that Minara has recently launched Web V2 and opened Early Access. They’ve set up individual, isolated cloud sandboxes for every user, ensuring data and tasks run in separate, secure environments. I’ve always believed finance is one of the most critical use cases for this kind of architecture. After all, trading involves real money. Users need to know where their data is stored, where their tasks are running, and how much control they truly have. Model capabilities may determine whether you try the product—but security and trust determine whether you dare to use it long-term. Additionally, Minara has now brought the same UI and codebase from their desktop app to the web. The original Chat has been upgraded to an Agent, and features like file previews and functionality recommendations have been fully integrated. Workflows are also evolving toward automation, aiming to let Agents execute tasks continuously in the background—though some monitoring functions still rely primarily on the desktop app. I think this reflects a noteworthy product trend worth paying attention to. In the past, AI trading tools competed by seeing who could analyze more assets or generate more complex strategies. But as models improve, these capabilities will likely narrow in difference. The next battleground will be who can make Agents truly integrate into users’ daily workflows—protecting data, consistently performing tasks, and seamlessly continuing across devices.