PROACTIVE MEMORY FOR LONG-HORIZON AGENTS

Summary from the TLDR AI newsletter

A separate memory agent tracked important state and selectively reminded an action agent when relevant information risked being lost. This approach improves pass rates on Terminal-Bench 2.0 and τ2-Bench without modifying the underlying action model.