When More Context Makes LLM Agents Worse

The article argues that providing LLM agents with excessively long context windows can degrade performance by introducing noise, distracting the model, and increasing latency, rather than improving reasoning. It challenges the assumption that unlimited context is always beneficial, showing that agents often perform better with carefully filtered, concise information.