PRO-LONG: Programmatic Memory Enables Long-Horizon Reasoning

TL;DR - PRO-LONG is a programmatic-memory framework that stores an agent’s complete interaction history in a structured log and uses coding-agent search to retrieve relevant details. It improves long-horizon ARC-AGI-3 performance while substantially reducing token usage versus specialized harnesses.

• Improves over base coding agents by an average of 18.0 percentage points across frontier models.
• Reaches up to 76.1% pass@1 while using 4.2–5.8× fewer tokens.
• Achieves 97.4% best@2 with Fable 5 at a reported total cost of $1,750.
• Addresses context-management tradeoffs by separating comprehensive storage from efficient, programmatic retrieval.