How we build an AI employee: I believe that today's organizations are built around human limitations. Humans have small context windows. We cannot understand the entire company at once, so we divide work into functions, teams, and roles. We give each person a narrow scope, a manager, a set of permissions, and a small number of systems. Then we build meetings, reports, and hierarchies to move context between people. When you hire a human, giving them a role is necessary. But it is not obvious that agents need to work this way. An agent can potentially understand the customer, the product, the code, the support history, the financial data, and the current priorities at the same time. In an agent-native company, broad context creates leverage. That creates two very different worlds to build for. 1. Meet the world as it is. Existing enterprises were designed for humans. They have roles, permissions, reporting lines, and strict boundaries between teams. The support team can't access the data of the finance team. To enter them, Viktor needs to resemble a human hire – Viktor for Finance, Viktor for Support, Viktor for Marketing – each with its own role and access. It might be the only practical way to bring agents into today's organizations. 2. Build for the world that's coming. The companies of the future might not be divided into departments in the same way. Small companies growing with agents from day one may never need to create the boundaries that large companies now consider obvious. Shared memory will be an advantage. Context will not have to be repeatedly compressed into dashboards. So yes, it makes sense to build for today's organizations because that is where almost all the work, money, and pain currently exist. But it would be short-sighted to let their structure define our product.