Lost in the Long Game: What UltraHorizon Reveals About Agent Failure at Scale
TL;DR UltraHorizon is a new benchmark that finally tests what real enterprise projects require: months‑long reasoning crammed into a single run—35k–200k tokens, 60–400+ tool calls, partially observable rules, and hard commitments at the end. Agents underperform badly versus humans. The pattern isn’t “not enough IQ”; it’s entropy collapse over time (the paper calls it in‑context locking) and foundational capability gaps (planning, memory, calibrated exploration). Simple scaling fails; a lightweight strategy—Context Refresh with Notes Recall (CRNR)—partially restores performance. Below we translate these findings into a deployer’s playbook. ...