AI4 min read
Long-horizon reasoning
The one framework that lets AI agents remember what they did 47 steps ago
PRO-LONG is a minimal framework that helps LLM agents retain and retrieve information across long sequences of actions. On the ARC-AGI-3 benchmark, it improved average pass rates by 18 percentage points across frontier models while using 4.2 to 5.8 times fewer tokens than existing harnesses. With Fable 5, it hit 97.4% best@2 at a total inference cost of $1,750.
2026-07-24