Long-Horizon-Agents

TL;DR for operators A capable agent can identify the right problem and still fail to finish the job. In the clinical simulation studied here, the stronger baseline framework averaged 4.39/5 on diagnosis, but only 2.94/5 on critical actions and 3.34/5 on timeliness. Asclepius attacks that gap without changing the underlying model weights. It combines three forms of scaffolding: an operating manual refined from prior simulated shifts, an external library of clinical skills, and specialized subagents for triage, diagnosis, and treatment completion. ...

TL;DR for operators A multi-step agent workflow eventually faces a problem that a larger context window does not solve. One model makes a decision, another step runs later with new evidence, and the system must know which earlier facts and decisions still count as official. Replaying the transcript gives the next executor more text; it does not necessarily tell it what has been accepted, superseded, or rejected. ...