Researchers have successfully transformed an off-the-shelf large language model (LLM), GLM-5.3-Flash, into a decision model similar to Jev, achieving comparable accuracy and speed. By leveraging a single forward pass, the LLM can make typed decisions with probability estimates for each option, addressing common software queries that require formatted responses. This approach not only matches Jev's performance but also enables typed decisions on images, a capability not available with Jev, making it a promising solution for various applications that rely on LLMs for decision-making.