Handshake AI CSO @Sbhaiwala03 reveals how they build simulated white-collar work environments to train frontier AI agents: "An environment consists of a few elements. The first is the software tools the agent needs access to. If I'm an investment banker, I have access to Excel, SEC EDGAR where all the financial reports are, and PowerPoint. Agents need the same access." "We build simulated versions because of infrastructure and access constraints. Labs are querying that tool thousands of times in a given second." "The second thing you need is data that populates the environment. If I'm building a financial model, I need the data room with the messy files from the company I'm evaluating." "The final piece is tasks and verifiers. What are the requests of the agent that would reflect what a real investment banker might ask. We try to find tasks complex and realistic enough that the models fail. If the model can't perform, we know it needs more training data." "What we send to labs is essentially a Docker file, a full containerized task. It has the tools the model has access to, the full data that populates the world, and the task and verifier. We'll send tens of thousands of these to a given lab for just one domain." @joinHandshake @GarrettLord