The next step after Jev: A decision model like Jev bills and computes the full context on every call, so a 40-message chat checked after each message processes the early messages 40 times. Devs just built Sage2, a streaming decision model that computes each token of a conversation once. The setup is closer to a database cursor than an API call. A session holds the context on the server, and new messages are appended to it, not re-sent. The cached computation over the earlier context is reused. Each new message adds only its own tokens to the cost, and every registered question is re-evaluated against the full history. Each question returns a typed answer with a calibrated probability, so thresholds and routing stay in plain application code. On progressive context, this makes decisions 3x faster, with responses in tens of ms. Sage2 is built by @levantolabs, the team behind the first decision model, launched before Jev. The video below depicts the model in action on a car dealership chat, and I partnered with the team to put this together. More details below.