New paper from Microsoft on compressing agent context at test time. If your agent gets worse as its interaction history grows, this method i…

New paper from Microsoft on compressing agent context at test time. If your agent gets worse as its interaction history grows, this method is worth a look. FOCUS asks which past interactions the agent's next decisions actually depend on. It keeps those units of the history and drops the others. It needs no training data or fine-tuning, so it works as a separate layer in front of closed-API models. On tool-calling, QA, web and multi-turn dialogue benchmarks, it cuts peak context by up to 48% and raises task success by up to 8.9 points compared with running on the full history. Paper: https://academy.dair.ai/papers/focus-training-free-decision-preserving-context-compression-for-llm-agents-2609.37590

Source: DAIR.AI (X) | 2026-10-02