The artificial intelligence market is witnessing the emergence of a new category of models designed specifically for making fast, inexpensive decisions rather than generating text. Jev, a model built to excel at judgment tasks, represents this shift toward decision-optimized AI that could reshape how businesses automate workflows and coordinate across teams. Rather than relying on large language models for every decision point, judgment models offer a more efficient alternative for validation, approval, and routing tasks. The implications extend beyond standalone decision-making. These models enable AI agents to check their own work and coordinate complex decisions across distributed teams, potentially streamlining bottlenecks in business automation pipelines. Salesforce is moving into this space with new model releases and tools designed to support third-party agents, signaling that enterprise software vendors see genuine commercial potential in judgment-optimized AI. Meanwhile, the broader AI policy landscape is shifting. Mark Zuckerberg has pushed back against proposals for collective AI slowdowns, while an unexpected consensus is emerging: Bernie Sanders and Steve Bannon have found common ground on AI regulation, suggesting bipartisan momentum for governance frameworks even as industry figures resist development constraints.